Category: Blogs

Leveraging Machine Learning to Predict Employee Attrition Risks and Guide Retention Interventions  

How Machine Learning Can Help You Reduce Employee Turnover is a free webinar available on demand, presented by iQor’s Vice President of Operations Terri Robertson, Senior Vice President of IT Joe Przybylowski, and Data Scientist Andrew Reilly. Here’s an overview of what they discussed.  

Why Retention Strategies Are Critical to Your Business Success 

Employee attrition is a more pressing concern for organizations than ever, as evidenced by cultural dialogue like “The Great Resignation” and “quiet quitting.” Attrition is even more significant for BPOs like iQor whose business is to deliver outsourced customer service to the brands that entrust us. 

The cost of employee attrition is significant in both direct and indirect ways. For example: 

• The average cost to hire and train a replacement employee can be up to 200% of that employee’s salary. 
• Replacing an experienced employee with a new hire can lead to a decrease in productivity and efficiency, which can affect revenue. 
• A high turnover rate can lead to discontinuity in customer service, which can result in loss of business. 
• High turnover can impact morale among other employees and cause a snowball effect of attrition, incurring further costs.  

The value of investing in employees speaks for itself. At iQor, employee experience is a cornerstone of our business model. Creating a work environment that promotes job satisfaction, recognition, and growth opportunities is critical to retaining valuable tenured employees.

Using Predictive Analytics to Help Prevent Attrition With Proactive Retention Strategies at iQor 

For over 15 years, iQor has used cutting-edge technology to provide an irresistible employee and customer experience (CX). Our team of expert data scientists has developed models for predictive analytics to guide our strategies for revenue recovery, customer satisfaction (CSAT), net promoter scores (NPS), and more. So, why not leverage our data analytics expertise to predict attrition before it has a chance to materialize?

Using the power of predictive analytics, we asked the fundamental question of attrition: How do you know when an employee is thinking about leaving?

To answer this question, our team of expert data scientists developed a machine learning model to identify variables that correlate with attrition and predict which employees might be at risk of leaving the company. Our goal was to play offense rather than defense to the problem of employee attrition by developing proactive retention strategies for at-risk employees. The model successfully:  

• Analyzes which variables influence employee attrition. 
• Identifies employees at risk of attrition. 
• Guides our operations team’s retention strategies. 
• Contributes to the retention of thousands of at-risk employees. 
• Informs an improved employee experience through a culture of empathy and professional development opportunities. 

Using the power of predictive analytics, we asked the fundamental question of attrition: How do you know when an employee is thinking about leaving?

Customized Employee Retention Processes Guided by Predictive Analytics 

Predictive analytics placed the ball in our court to proactively shape a positive employee experience that improves retention. The foundation of machine learning and predictive analytics is data. To begin, iQor’s data scientists needed to know what data they required to build their “crystal ball” for proactive employee attrition prediction. 

Their approach to data modeling consists of three stages: 

1. What data is available?  

The existing body of structured data could include tenure, compensation and benefits, workforce management data, interaction analytics, coaching outcomes, performance reviews, bonus history, training data, and other information that iQor already gathered about our employees.  

2. What are we missing?  

After conducting an inventory of existing data, we could identify data gaps. Gaps often include unstructured data, which is more difficult to gather and too subjective to easily evaluate, such as employee feedback.  

3. What can we create?  

Identification of data gaps can then drive strategies for gathering that data. For example, annual surveys for employee feedback are an option, but that doesn’t provide enough data for accurate analytics. Filling in this gap requires a high-frequency method of employee surveying for gathering reliable and timely feedback regarding their outlook on the job.  

The answers to these questions create a broader data pool of structured and unstructured data to begin identifying which data points correlate to attrition risks. 

Transforming Raw Data Into Usable Variables  

Data is just raw material; it needs to be refined to be useful, as described by Gartner’s Four Phase Data Maturity Model. iQor’s data scientists had to decide how to categorize the data into variables that could be computed by their algorithms. They then validated each data feature using a process called variable importance testing to determine what to include and exclude from the production model. This process assesses how much influence a particular variable or feature has historically impacted our attrition. Those that rank high are selected while those that rank low are rejected. 

Using these variables and a combination of five main algorithms, our data scientists deployed a five-fold cross-validated Stacked Ensemble Meta learner with auto-tuned hyperparameters—or, in layman’s terms, they created a customized employee retention model that could assess the probability of employee attrition within the next 60 days. 

From Data Science to Pragmatic Action: The Plan for Proactive Frontline Employee Retention 

At iQor, we place a high value on providing exceptional employee experiences. As our data scientists and operations teams collaborated to develop a practical, specific, repeatable process for proactive retention, they kept the employee experience top of mind. The process needed to be simple for employees and managers in terms of time and effort expended; it needed to be standardized yet flexible; and it needed to be embeddable into our feedback culture. The result was a Measurable Skip-Level Meeting, also known as “The Touch Base.” 

“The Touch Base” Strategy for Employee Retention  

Every week, iQor runs our machine learning model for all 40,000 employees company-wide. We analyze each individual’s probability of attrition between 0% and 100%. At-risk employees are identified at a threshold of 65%. Employees who meet or exceed this threshold for attrition risks will automatically engage the company’s proactive retention strategy enacted by the operations teams. 

As a result of these analytics, our operations teams are informed of at-risk employees every week. They receive the employees’ names, the names of their direct supervisors, and the skip-level managers responsible for scheduling the Touch Base. These managers have a structured guide with clear, consistent guidelines, a system of record, and a method for feeding results back into the analytics model. 

The Touch Base is standardized enough to provide data points that can guide improvements to the machine learning model but also conversational and customized to each employee’s needs.  

It’s important to note that the Touch Base is not focused on the employee’s performance. Rather, it is about encouraging open communication to identify and support the employee’s needs. The anatomy of the Touch Base is as follows:  

• Before the Touch Base 
  • The manager reviews the employee’s information to approach the conversation with an informed and empathetic mindset. 
  • The manager schedules the 30-minute session with the employee through our workforce management system.  

• During the Touch Base 
  • The manager asks open-ended questions in an effort to identify what the employee may be experiencing that makes them at risk.  
  • The manager lets the employee guide the conversation to help the employee feel listened to, valued, and supported.  
  • The manager thanks the employee for their time and willingness to share. 

• After the Touch Base 
  • We use the same module that guides our coaching to measure the effectiveness of each Touch Base. The Touch Base checklist includes a summary with the following priorities: 
    • Clarify timelines, deliverables, and expected outcomes. 
    • Agree on next steps. 
    • Schedule a follow-up meeting with the employee. 
    • Escalate to the next level of management, if needed. 
  • Lastly, the manager documents the meeting in the system with as many details as possible. 

The manager also rates the Touch Base for their impression of the employee’s overall state of being. In some cases, just having the conversation with the manager can make the employee feel valued and clear up the risk of attrition. In other cases, the situation is not something the manager can easily address, and escalation may be necessary.  

Combining Clinical Trial Methodology and Human Storytelling to Gauge the Effectiveness of the Touch Base Process and Guide Next Steps 

For iQor’s machine learning model to be effective, it has to be able to measure the effectiveness of our interventions and the results of these Touch Base meetings. We performed a controlled study, much like a clinical trial, to go beyond the manager ratings to use a scientific approach to our evaluations.  

Comparing Retention Outcomes Between Control and Experimental Groups Showed a 2.6x Increase in Retention for Touch Base Employees 

Out of 100 at-risk agents, we withheld a small sample of at-risk agents to serve as a control group. They received no Touch Base interventions. The other 95% served as the experimental group and proceeded through our Touch Base intervention process. The results were clear. After 60 days, the control group experienced 18.3% attrition while the experimental group experienced 7% attrition.  

This led to two main findings:  

1. The model appropriately identifies employees at risk of attrition. 

2. The intervention is meaningful.  

At-risk employees who go through the Touch Base process are 2.6 times more likely to stay with the company than employees who do not receive proactive retention strategies. We refer to this as our Attrition Mitigation Factor. The takeaway? Our Touch Base strategy worked to effectively retain at-risk employees and embody our commitment to providing an outstanding employee experience.

Stories Shared by Agents and Managers Through a Culture of Feedback Relate Positive Outcomes Beyond the Science 

What steps actually work to retain at-risk employees? The answer to this can help us implement a repeatable process and create a culture of feedback. Feedback and storylines from our operations teams about their experiences with the Touch Base process guides continuous improvement to the model.  

Using the Touch Base process, managers now get to talk directly to frontline employees instead of just hearing from their direct managers. This makes it much easier to find resolutions and improve relationships to encourage retention. When managers listen, they can facilitate adjustments that lead to employee retention. Sometimes, preventing employee attrition is as simple as adjusting schedules. 

Putting the “Active” in “Proactive:” How the Machine Learning Model Constantly Self-Improves 

iQor’s machine learning model is dynamic. Future improvements are guided by the data science team, the operations team, and stakeholders, who have the opportunity to provide feedback and ask questions during quarterly reviews. The key is data. Each time the machine learning model processes new information, it improves its own ability to fulfill its intended purpose.  

Best Practices for a Machine Learning Approach to a Proactive Retention Strategy 

iQor’s machine learning model is successful because our data science, operations, and frontline teams collaborated to define, implement, and improve the process. Embodying our iQorian Value of open communication helped our teams develop an effective machine learning model that kept the human experience at the forefront of the process. 

Here are some best practices our teams followed: 

• Define the problem in as much detail as possible through collaboration, data discovery, and analysis.  
• Acquire high-quality data by asking three main questions: what data do we have, what data can we create, and what data can we enrich by joining it to another data source? 
• Name the project to give it its own brand. Our Touch Base system makes the project memorable to stakeholders and builds value.  
• Create a control group like a clinical trial to evaluate results for an accurate indication of effectiveness.  
• List all KPIs to specifically define the model’s parameters.  
• Start with a quick win to motivate involvement and maximize collaboration potential.  
• Fail small and fast to allow the data science methodology to break the project into bite-sized pieces that are not overwhelming.  
• Communicate between teams so they can seek support across the organization. Establishing a regular cadence for communication keeps channels open that we can use as potential input sources for continually improving the model. 

Investing in Employees to Retain Tenured, High-Performing Teams 

Employee attrition can be a significant issue for any company. Our proactive retention strategies help us stay ahead of the curve through processes that incentivize valuable employees to stay on board. iQor’s machine learning model successfully predicts attrition and guides effective intervention strategies, empowering us to transform at-risk employees into tenured career professionals that provide irresistible customer service.  

Experience the Best in CX  

iQor offers analytics as a service to enhance employee, customer, and client outcomes. Our proprietary speech analytics platform, cloud computing, machine learning, artificial intelligence, and data analysis enable us to provide effective workforce management solutions, flexible work environments, and improved coaching processes. We prioritize our employee experience and aim to cultivate a culture of success that fosters loyalty and high performance. 

As a managed services provider of customer engagement and technology-enabled business process outsourcing (BPO) solutions, iQor provides a comprehensive suite of full-service and self-service scalable offerings that are purpose-built to deliver enterprise-quality CX.  

Our award-winning CX services include:  

• A global presence with 40+ contact centers across 10 countries.  
• A CX private cloud that maximizes performance and scales rapidly across multiple geographies on short notice.  
• A partnership approach where we deploy agents and C-level executives to help maximize your ROI.  
• The perfect blend of intelligent automation for scale and performance coupled with an irresistible culture comprised of people who love to delight your customers.  
• Virtual and hybrid customer support options to connect with customers seamlessly, when and where they want.  
• The ability to launch a customer support program quickly, even when you need thousands of agents ready to support your customers.  
• A best-in-class workforce management team and supporting technology to create a centralized organization that can better serve your entire business.  

iQor helps brands deliver the world’s most sought-after customer experiences. Interested in learning more about the iQor difference? If you’re ready to start a conversation with a customer experience expert, contact us to learn about how we can help you create more smiles. 

Joe Przybylowski is senior vice president of IT at iQor. Connect with him on LinkedIn.
Andrew Reilly is a data scientist at iQor. Connect with him on LinkedIn.
Terri Robertson is vice president of operations at iQor. Connect with her on LinkedIn.

Why BPOs Need to Continuously Invest in Zero Trust

The threat landscape is constantly changing, and a static security model is not an option. Zero trust is a dynamic approach to security that enables BPOs to stay ahead of the curve. By continuously investing in zero trust, BPOs can protect their data and systems from the latest threats and ensure a secure environment for the mountains of client data they store, handle, and analyze. 

What Is Zero Trust? 

Zero trust is a security concept created by cybersecurity expert John Kindervag. The phrase he coined, “Never trust, always verify,” has become the watchword of zero trust advocates and practitioners. 

Kindervag broke new ground when he recognized that every instance of trust in a network represented a vulnerability. As he saw it, every user and every device needed to be authenticated and authorized before it could access any part of a network. With zero trust, no activity on the network, no matter where it originates, is presumed to be trustworthy. 

Zero trust was a major departure from the status quo, which built security on the idea that a secure perimeter around a network would keep the network safe—much like a moat around a castle. Security experts presumed activities inside the perimeter to be trustworthy because an actor had to pass through perimeter security to get inside. But as with a castle, once a bad actor penetrated the perimeter and was inside, they could wreak havoc. 

The Castle-and-Moat Approach No Longer Provides Enough Protection

The castle-and-moat approach was fine when everyone worked from the office and the network server was on premises. Today, businesses have data in data centers, in the cloud, in branch locations, and on endpoint devices. Employees work at home, a hotel, or their neighborhood coffee shop.  

This is the era of the distributed network, and cybercriminals have more ways than ever to penetrate a network.  

How much havoc are bad actors causing? Every 11 seconds a business is hit by a cyberattack. According to Cybercrime Magazine, if Cybercrime were a country, it would have the third largest economy in the world, behind only the U.S. and China.  

Fortunately, zero trust is catching on.  

Standards Help Business Process Outsourcers (BPOs) Transition to Zero Trust 

Zero trust is a concept, not a product. You can’t set it and forget it. For years, zero trust experts often described it in different ways, which could be confusing for BPOs that wanted to implement zero trust and build a zero trust architecture (ZTA).  

That changed when, after a series of data breaches in various agencies, the U.S. government made a strong commitment to zero trust. The National Institute of Science and Technology (NIST) published NIST 800–207, “Zero Trust Architecture,” to help organizations transition from legacy security systems to zero trust. In 2021 and 2022, the president issued executive orders requiring all U.S. federal agencies to adhere to NIST 800–207 and to ensure the responsible development of digital assets. 

Now vetted and validated by many commercial customers, vendors, and government agency stakeholders, private organizations and enterprises widely recognize NIST 800–207 as the reigning zero trust standard. By providing helpful guidance—especially for organizations with no experience in zero trust—NIST 800–207 has provided clarity for BPOs and all organizations that want to phase in zero trust.  

3 Principles of Zero Trust 

CrowdStrike cites the three principles of zero trust as: 

• Continuous verification. Verify all users and their permitted level of access before granting access to any resources. Only “least-privileged access” should be granted to any user, meaning users have access to only the resources they need. 
• Limit the “blast radius.” In case a breach does occur, minimize the damage it could cause. 
• Automate context collection and response. Automatically analyze behavioral data against the entire IT stack to develop the most accurate response to an access request or perceived threat. 

Zero Trust Needs of BPOs 

When a BPO manages an omnichannel customer experience (CX) program, massive amounts of data (Big Data) are collected. Every customer interaction—phone, text, chat, email—is recorded and analyzed. Various applications are used to analyze the data produced from these interactions. Automation makes processes more efficient.  

Hundreds or thousands of customer service agents and supervisors, many of whom work at home (WAH), have access to the data. Agents providing back office services handle thousands of personally identifiable records.  

These activities are repeated for every client, every day.  

And these 5 pillars of zero trust protect them from bad actors. 

5 Pillars of Zero Trust for BPOs 

Regardless of the scope of a dynamic zero trust implementation, these five pillars are must-haves for BPOs. 

1. Multifactor Authentication

Multifactor authentication hardens security access to networks by requiring users to confirm their identity through two or more factors. Authentication factors are things you… 

• Know: username/password, PIN, security questions. 
• Have: RSA key, fast identity online (FIDO) key, phone, registered endpoint, certificate. 
• Are: biometric scan – fingerprint, palm, eye, voice, facial. 
• Locate: source IP, known device location, GPS. 

Organizations can use multifactor authentication in numerous ways, including: 

• OTP: After entering your user ID and password, the system asks you how you’d like to receive a one-time password (OTP), via SMS, chat, or email. After you select your preferred method, the system sends you the OTP and provides a form field for you to fill in after you’ve received it. 
• Third-Party Sync: At the login screen, the system asks for your password and an OTP provided by a third-party application that syncs the OTP it sends to your smartphone with the login page. 
• Biometric Scan: Login includes a user ID, an OTP, and a fingerprint scan. 
• Hardware Token: To log in, press the button on your hardware token device to generate a new passcode and enter it into the first or second password field on the login screen. 
• FIDO2: Open-standard FIDO2 delivers hardware-based authentication through your existing FIDO2-enabled device such as a smartphone, security key, or hardware token enabling you to simply enter your biometric or pin-based authentication to log in. 

Multifactor authentication emerged as an important line of defense against bad actors as they became more adept at stealing user IDs and passwords through brute force (trial and error) and social engineering (convincing people to divulge their login credentials) attacks, such as: 

• Phishing: Using fraudulent emails and websites to deceive users into revealing personal information or inadvertently installing malware. 
• Smishing: Using text messages or messaging apps to obtain sensitive information from unsuspecting individuals. 
• Spear Phishing: More personalized than phishing, spear phishing targets a specific person or group with a personalized message seemingly coming from a known sender. 
• Keyloggers: Often installed through vulnerable browsers that fall prey to bad actors, a keylogger records every keystroke made by the user to gain access to confidential information. 
• Credential Stuffing: Attackers use lists of credentials obtained through a data breach in one system to gain access to another system. 
• Brute Force and Reverse Brute Force Attacks: Bad actors obtain the username or account number (brute force) or password (reverse brute force) and use automation tools to determine the missing key to gain access. 
• Man-in-the-Middle (MitM) Attacks: Bad actors intercept messages between two parties to obtain and/or alter data with malicious intent. 

While multifactor authentication may add a minute to the login time, it adds an important layer of protection to the network by making it much harder for bad actors to get in. 

2. Network Security and Microsegmentation 

Multifactor authentication provides protection against bad actors trying to breach the network’s perimeter. 

Microsegmentation protects the network from bad actors who somehow make it into the network and then attempt to cause damage throughout the network. 

Microsegmentation employs software to virtually isolate parts of the network where applications can run—known as a workload—from each other.  

With each workload isolated and every attempt to move from one workload to another requiring authentication and approval, microsegmentation limits any damage done in one workload from reaching another. It also ensures that any user in one workload who attempts to access sensitive data in another workload has the appropriate permissions. This is an area of continued investment for iQor into 2024 and beyond.  

3. Data Security 

Multifactor authentication and microsegmentation protect areas and resources of the network from bad actors. Zero trust data protection (ZTDP) protects the data itself by applying the principles of zero trust (detailed above) to data. In other words, ZTDP is an extension of zero trust. Instead of being network and resource centric, ZTDP is data centric. 

Even with data, never trust, always verify.  

With ZTDP, both structured and unstructured data—whether in a database, in a protected file store, or on the move (in use)—are protected by requiring that users be authenticated and granted only least-privileged access. This necessitates access policies at the most granular levels. 

In granting access, the context of the access request is considered. Contexts to be considered might include: 

• Is the request coming from a user or an application?  
• Is it known how the requestor will use the data? 

Automation is used to evaluate and enforce access policies. All data requests are logged, regardless of the outcome of the request. 

4. Device Authentication and Authorization

Authentication and authorization are two steps that sound similar but have different meanings. 

Authentication is the process by which a user or device is confirmed to be who they claim to be. Typically, the network authenticates users by their user ID, password, and another required authentication factor.  

Devices are often authenticated by IP address. If the authenticated user’s IP address is what’s expected, the device is authenticated for that user. If the authenticated user’s IP address isn’t what’s expected, the network may ask for further proof that they are who they claim to be. Also, a notification may be sent to the user that someone has logged in with their credentials from an unrecognized device, instructing them to contact the network administrator if it wasn’t them. 

Much of the communication in complex networks is between devices that work autonomously, such as routers and switches. To make sure bad actors don’t mimic these devices, security teams use encryption to protect and send data between devices.  

Authorization is the process of providing least-privileged access to the authenticated device for areas and resources requested.  

This principle of least privilege (PoLP) is a foundational aspect of zero trust to help improve an organization’s security posture by reducing their attack surface. The process of authorization involves verifying the user’s or device’s identity and then assigning access privileges that correspond to the user’s role, responsibilities, and need-to-know. This is typically done by assigning the user or device a set of permissions that dictate the applications, data, and resources they can and cannot access. 

5. Continuous Monitoring of All Actors 

The transition from traditional unified networks with castle-and-moat security models to zero trust raises three important topics for IT: visibility, automation, and analytics. 

Visibility 

IT maintains a high level of resource visibility in a traditional network. With zero trust and network microsegmentation, resources are segmented into small pieces. Traditional monitoring and network management were developed to provide visibility to one network, not to many small segments that comprise a network.  

Lack of visibility can lead to a network with unpatched devices, unmonitored systems, and shadow IT, where IT-related hardware and software are used without the knowledge and consent of IT or security. 

Meanwhile, zero trust depends on continuous monitoring of all actors. Automation and analytics make up for the visibility deficit. 

Automation and Analytics 

Zero trust relies on software that automatically and consistently monitors all network segments, data correlations (how strongly sets of data are linked together), and logs to form a baseline of user behavior.  

When analysis of the monitored data indicates there are anomalies in user behavior, they are reported to IT and security stakeholders as potential threats in real time. Real-time notification gives stakeholders their best chance to mitigate a threat before it does any damage. 

Benefits to BPO Clients 

When BPOs implement the five pillars of zero trust to protect their networks, their clients can feel confident that the BPO is taking every step to limit access to their data to users with the proper access privileges.  

They can also feel confident that their BPO takes strong measures to protect their own operations against bad actors, so the business processes the client outsources to them have less chance of being compromised by cyberattacks. 

These practices offer BPO clients peace of mind that their outsourced business processes are protected so they can focus on achieving desired KPIs.

Zero Trust Is the Future of Security for BPOs 

Brands in all sectors are evaluating and in some stage of their planning a zero-trust security implementation.  

BPOs use Big Data to find new agent-coaching opportunities to predict employee attrition and much more. They save, manage, and analyze massive amounts of data and can’t afford to have that data breached, stolen, or corrupted. Zero trust is the standard that provides maximum cyber protection for BPOs and their clients. 

Zero trust requires considerable know-how and time to implement. There’s no such thing as a “finished” zero trust program. Technology keeps changing, and cybercriminals keep finding more ways to breach systems to deny service, steal secrets, or demand ransom. As circumstances change, organizations that employ zero trust need to change with them. 

As more BPOs implement zero trust, brands in search of a BPO may well start asking, “How are you coming along on your zero trust security roadmap?” 

As BPOs continue to invest in and implement zero trust practices, brands in search of a BPO partner can discuss current and planned zero trust initiatives.  

Experience the iQor Difference 

At iQor, we partner with clients to design the optimal mix of CX automation and people where security is always top of mind. As a managed services provider of customer engagement and technology-enabled business process outsourcing (BPO) solutions, iQor provides a comprehensive suite of full-service and self-service scalable offerings that are purpose-built to deliver amazing customer experiences. 

Our award-winning CX services include: 

• A global presence with 40+ contact centers across 10 countries. 
• A CX private cloud that maximizes performance and scales rapidly across multiple geographies on short notice. 
• A partnership approach where we deploy agents and C-level executives to help maximize your ROI. 
• The perfect blend of intelligent automation for scale and performance coupled with an irresistible culture comprised of people who love to delight your customers. 
• Virtual and hybrid customer support options to connect with customers seamlessly, when and where they want. 
• The ability to launch a customer support program quickly, even when you need thousands of agents ready to support your customers. 
• A best-in-class workforce management team and supporting technology to create a centralized organization that can better serve your entire business. 

iQor helps brands deliver the world’s most sought-after customer experiences. Interested in learning more about the iQor difference? If you’re ready to start a conversation with a customer experience expert, contact us to learn about how we can help you create more smiles.

John O’Malley is SVP, Chief Information Security Officer at iQor. Connect with John on LinkedIn. 

Improve the Employee Experience for Customer Service Agents and Supervisors Through Conversations Informed by Predictive Analytics   

Creating rewarding employee experiences and retaining employees is key to running any business. Using machine learning as a retention enabler is the focus of this blog post. 

While appearing on CNBC in 2019 to announce a new tool IBM had created—with AI, machine learning, and predictive analytics—to identify employee flight risk candidates, former IBM CEO Ginni Rometty said, “The best time to get to an employee is before they go.”  

By harnessing digital technology innovation, forward-thinking business process outsourcers (BPOs) can take action to reduce employee churn—especially among frontline workers.  

In this blog post, we’ll explore how BPOs can use machine learning and predictive analytics to retain more contact center employees by assessing frontline employee attrition risk and leveraging that knowledge to create an employee experience that often addresses their unique needs.  

We’ll cover: 

• Employee retention in the 2020s. 
• Costs of replacing contact center employees who leave. 
• Modeling data to identify employee attrition risk patterns. 
• Predicting and reporting employee attrition risks. 
• Intervening to retain employees. 
• Measuring intervention outcomes. 
• Calculating the impact of intervention on P&L. 
• A real-world example.

Employee Retention in the 2020s  

Since the onset of the pandemic, employee retention has become an even greater challenge than it was when Ginni Rometty appeared on CNBC in 2019.  

A global survey by PwC revealed that, across all lines of work, one in five employees expected to find a new opportunity in 2022.  

Digitally savvy BPOs use every tool at their disposal in an attempt to retain their frontline customer experience team members. 

Costs of Replacing Contact Center Employees Who Leave  

Direct and indirect costs add up quickly when replacing contact center employees who leave voluntarily. 

Direct costs include recruiting, onboarding, and training each new employee. It can take months to hire a new employee and train them to become fully versed in a new customer experience position. 

Indirect costs become factors the moment an employee departs. That’s when the employer loses the employee’s skillset, everything the employee learned about the company and the CX program they supported, as well as internal processes when working with their team and stakeholders.  

Moreover, teams have to cover the gap left by the departing employee until a new employee is onboarded and up to speed.  

When a team member departs, their loss can also lower morale. When an experienced worker leaves—especially one in a supervisory role—indirect costs rise even higher.

Watch Our Webinar

iQor SVP IT Joe Przybylowski, Data Scientist Andrew Reilly, and VP Operations Terri Robertson explain how iQor uses machine learning to help reduce employee turnover.  

Modeling Data to Identify Employee Attrition Risk Patterns

Organizations have long used annual surveys to measure employee sentiment. Surveys can provide a limited sense of how employees feel about working for an organization to help guide general improvements. Annual surveys are limited in their ability to identify individual employee sentiment and predict which specific employees are likely to leave, for several reasons: 

• Many workers don’t complete the survey. 
• Some workers might respond with what they think is the “right” answer instead of how they really feel. 
• Some organizations only use anonymous surveys, so the organization doesn’t know which employees fit the profile of a flight risk. 

For a more accurate snapshot of individual employee sentiment, quick surveys conducted at regular intervals that identify employees are often more effective.  

Training the Machine Learning Model 

Data Scientists can use machine learning to analyze harvested data from former employees’ surveys and create profiles of employee sentiment that suggest when a worker is likely to voluntarily separate from the BPO. With these profiles, data scientists can create an employee attrition risk training model for a machine learning algorithm. As new data is compiled from existing workers and as more workers depart, machine learning automatically updates the algorithm to make it more accurate. 

Adding More Data Sources for Modeling Accuracy 

While using a single source of data may provide some guidance, there’s always a risk that the model is biased in some way, or that the sample size is too small. Using multiple data sources makes the model more accurate.  

Data scientists follow a formal process to identify and validate potential data sources based on elements of a worker’s environment, including how they interact with coworkers and supervisors. 

Environmental data sources might include: 

• Schedule. 
• Login and logout times. 
• Frequency of breaks. 
• Compensation. 
• Complexity of the tasks assigned. 
• Coaching interactions. 

Data scientists diligently explore other data sources through cross-functional analysis of processes.  

Predicting and Reporting Employee Attrition Risks 

Using multiple data sources minimizes bias built into a single data source. With enough data, predictive analytics (a subset of machine learning) can forecast which employees are the most likely flight risks and why they are at risk of leaving. 

Once data analysts have an accurate view of which employees are likely to voluntarily separate—and the probable causes for their separations—they share their findings with the employees’ managers. These reports get to the heart of who’s at risk and why, and spare managers the tedious task of having to decipher the data.  

The manager then determines the next step to take with each employee. Knowing the likely reasons an employee is an attrition risk gives managers a relevant starting point when they intervene proactively in their attempt to retain the employee. 

Intervening to Retain Employees 

Knowing why an employee is considering leaving can enable a manager to determine the best approach to resolve the employee’s concern, create a better experience for them, and help them remain on the team. 

When the manager is empowered to take an empathetic approach to intervening with the employee, they help the employee understand their commitment to resolving the concern. 

For example, if predictive analytics identifies an employee encountering scheduling concerns that make their job logistically challenging, the manager can work with the employee to design a more flexible schedule that better meets the employee’s needs. 

If, for instance, predictive analytics identifies an employee seeking additional career growth opportunities, the manager and employee can develop a plan to support the employee’s aspirations to learn and grow within the organization. 

With these and many other examples, when a manager knows the likely reasons an employee might voluntarily separate, they can tailor their approach to address the employee’s individual needs and create a better employee experience that recognizes their value to the organization and keeps them on the team.

More Real-World Examples

Learn How Machine Learning Can Help You Reduce Employee Turnover
Check out our webinar featuring iQor SVP IT Joe Przybylowski, iQor Data Scientist Andrew Reilly, and iQor VP Operations Terri Roberts to discover how to harness technology to engage employees and reduce turnover. Get the details directly from the experts responsible for this program. 
Watch Now

Measuring Intervention Effectiveness 

To determine the efficacy of interventions, companies run tests. Among a group of employee churn candidates, a portion is placed in a control group to measure the differences in outcomes between those who receive interventions and those who don’t.   

Calculations over time have proven how much more effective intervening is than not intervening to retain employees predicted to be at risk of voluntarily separating through the intelligent model explained in this blog post. This can result in significant boosts in contact center employee retention as well as improved overall employee experiences, including career advancement for retained employees.  

Bottom Line: Retaining Customer Experience Agents Improves CX 

Experienced customer service agents build relationships with their teammates, serve as mentors to newer agents, treat their customers with the care and respect they deserve, and champion the brand they represent. 

With machine learning and predictive analytics, BPOs can positively affect frontline employee retention and keep their employees and customers smiling. 

Experience the Best in Data Analytics   

iQor’s analytics as a service offering uses a combination of iQor’s proprietary speech analytics platform, cloud computing, machine learning, artificial intelligence, and data analysis to develop custom interventions for identified areas in need of improvement along the customer journey. The results produce targeted improvements for the employee, customer, and client. 

iQor is a business process outsourcing company ideally suited to help brands create amazing customer experiences. iQor provides a comprehensive suite of full-service and self-service scalable offerings that are purpose-built to deliver enterprise-quality CX. 

Our award-winning CX services include:   

• A global presence with 40+ contact centers across 10 countries.   
• A CX private cloud that maximizes performance and scales rapidly across multiple geographies on short notice.   
• A partnership approach where we deploy agents and C-level executives to help maximize your ROI.   
• The perfect blend of intelligent automation for scale and performance coupled with an irresistible culture comprised of people who love to delight your customers.   
• Virtual and hybrid customer support options to connect with customers seamlessly, when and where they want.   
• The ability to launch a customer support program quickly, even when you need thousands of agents ready to support your customers.   
• A best-in-class workforce management team and supporting technology to create a centralized organization that can better serve your entire business. 

iQor helps brands deliver the world’s most sought-after customer experiences. Interested in learning more about the iQor difference? If you’re ready to start a conversation with a customer experience expert, contact us to learn about how we can help you create more smiles.   

Joe Przybylowski is SVP of IT at iQor. Connect with Joe on LinkedIn.
Andrew Reilly is a data scientist on the AI & Data Science Team at iQor. Connect with Andrew on LinkedIn.

How BPOs Can Use Predictive Analytics to Improve Employee Retention 

Predictive analytics answers “what if” questions, as in, “If we do X, what’s most likely to happen?” It’s not the same as having a crystal ball that shows you the company’s future, but it’s the closest thing we have right now. Big data makes it possible. 

Modern computing and cloud storage systems have enabled businesses to collect, retain, analyze, and use massive amounts of data. Data analysis, machine learning, and predictive analytics all use lots of data, and for different reasons.  

Data analysis creates a current state picture of any operation, machine, department, or line of business. Dashboards can be created to visualize the data for stakeholders in real or near-real time.  

Machine learning (ML), a subset of artificial intelligence (AI), uses data to improve digital system outcomes. For example, your email client uses AI to identify spam messages and put them in your junk folder. Some spam messages may still come through. As you move those messages to your junk folder, ML teaches your email client that it should automatically put these spam messages in your junk mail, so you don’t have to see them again. 

Unlike ML, which works in the present state, predictive analytics points to future outcomes by studying past events, generating models of future events, and predicting the likelihood of each model to deliver desired outcomes.  

People can manually perform predictive analytics, one model at a time. Computers, on the other hand, generate dozens of predictive models for any scenario and show the most likely result for each model in a tiny fraction of the time it would take a person. 

Predictive analytics uses historical data—the more data, the better—to show businesses the opportunities and challenges they’re likely to face moving forward. The results present stakeholders with a view of which options are most likely to succeed, without having to invest the time and money to test each option in the real world.

The Link Between Predictive Analytics, Employee Experience, and Great CX 

Predictive analytics offers myriad business benefits for predicting future trends and events. This, combined with lower costs of data collection and storage, has made predictive analytics an attractive option for more companies than ever. Markets and Markets forecasts the predictive analytics market will grow from $10.5 billion in 2021 to $28.1 billion in 2026. 

According to a 2022 SkyQuest Technology survey, companies that use workforce analytics better understand their employees’ needs than those that don’t and enjoy higher employee retention rates (64% vs. 40%). 

This is further supported by a recent Gallup survey that highlights the importance of regular coaching, support, and career development between managers and their employees, finding that employees who receive meaningful feedback on a weekly basis are 50% less likely to seek new employment. Predictive analytics can improve how companies manage talent and help managers target their conversations to further increase employee retention. 

In this blog post, we explore how BPOs can use predictive analytics to manage frontline employees and improve the employee experience, resulting in better employee retention and excellent CX outcomes. 

How BPOs Can Use Predictive Analytics to Improve Customer Service 

BPOs can use predictive analytics in support of strategic outsourcing for their clients. In this blog post you’ll get an overview of six predictive analytics use cases BPOs can employ.

1. Improving Employee Retention and Productivity

Retaining frontline employees is a challenge in any sector. Replacing workers—including recruiting, hiring, onboarding, and training—comes with substantial cost. Experienced employees take with them extensive knowledge that takes time for new employees to replace. 

A decline in productivity is one of the first signs a frontline employee is at risk of voluntarily separating from the company. The key to retaining the employee is to intervene before they consider leaving.  

A decline in productivity is one of the first signs a frontline employee is at risk of voluntarily separating from the company. The key to retaining the employee is to intervene before they consider leaving.  

Using productivity data and other signals of employee sentiment, predictive analytics can identify workers who are more likely to voluntarily separate from the company and suggest the reasons why. Supervisors can then reach out to their at-risk employees and help put them on course to regain their positive sentiment for the company and desire to be more productive.  

Every retained at-risk employee contributes to sustained productivity.  

Watch Our Webinar
iQor SVP IT Joe Przybylowski, Data Scientist Andrew Reilly, and VP Operations Terri Robertson explain how iQor uses machine learning to help reduce employee turnover.  

2. Developing More Efficient Operational Processes 

Robotic process automation (RPA) automates repetitive processes formerly performed by workers. In its most basic form, RPA records all the actions performed by an individual in performing a task and then performs them with a software robot, or bot.  

Beyond the basics, AI can be built into the RPA, making it a form of intelligent automation. With intelligent automation, RPA not only performs a task, but also collects all data generated throughout the process, making it available for ML and predictive analytics.  

With that data, data scientists can use predictive analytics to develop models that predict how changes to the automation will improve its efficiency.  

In cases where machinery is involved, predictive analytics enables businesses to perform maintenance before it becomes an emergency (predictive maintenance). Plus, they can schedule a time when performing that maintenance will have the least effect on other processes. 

3. Analyzing Customer Support Interactions  

Customers receive net promoter score (NPS) surveys after they’ve interacted with customer support. They measure customer sentiment about the recent interaction to determine if that customer is a promoter, passive customer, or detractor of the brand. Many companies experience a low percentage of survey returns, which makes it difficult to rely on survey results. 

Predictive NPS picks up where a small sample size leaves off, modeling a customer’s structured and unstructured data to build a view of their sentiment and determine how that customer can best be served. 

Additional benefits include: 

Immediate Benefits 

• Increased customer feedback without increased customer effort. 
• Increased sense of fairness and buy-in from agents. 
• Identifying customers with high or low loyalty levels to receive special care. 

Long-Term Benefits 

• Drive more accurate insights. 
• Identify trends related to brands, products, offerings, services, or branches. 
• Increased revenue and reduced customer churn. 

4. Predicting Revenue 

Predictive analytics can generate models of a customer’s lifetime value (CLTV) and where they are in their customer lifecycle. That gives a sense of how much revenue they can expect to earn from each customer over the short and long term. 

Predictive analytics can also help marketers determine which channels and offers would be most effective for different customers. It can also predict which campaign models would produce the most (and least) revenue with a given budget.  

Predictive analytics can identify the best day, time, channel, and number of times to contact a customer to optimize revenue.

Predictive analytics can identify the best day, time, channel, and number of times to contact a customer to optimize revenue.     

5. Measuring Employee Satisfaction    

Satisfied employees engage with company initiatives, satisfy customers, and strive to be productive. Employee surveys are just one datapoint that measures employee satisfaction. Depending on the employee’s role, other datapoints might include customer feedback, employee productivity, attendance, and more. Analyzed together, these datapoints create employee satisfaction profiles. 

When analyzing a group of employee satisfaction profiles, data scientists can segment the group into clusters of individuals with similar profiles. For each cluster, predictive analytics can generate models of other (and former) employees with similar satisfaction profiles. These profiles enable data scientists to predict how each cluster would likely perform in various scenarios.  

Further analysis can help identify which employees are less engaged than others, why they are less engaged, and what steps to take to increase employee engagement. 

6. Monitoring Performance and Continuous Improvement 

Predictive analytics can be an effective tool for helping employees reach their goals. When data indicate an employee is on track to hit their goals, supervisors can provide positive reinforcement to encourage them. Predictive analytics can also recommend recorded classes that will help the employee fill any knowledge gaps to keep them moving forward. Additionally, predictive analytics can recommend and push relevant content tailored to each employee’s needs to fill knowledge gaps and keep them moving forward.  

Performance monitoring can also identify employees who could benefit from help staying on track. In those cases, predictive analytics can identify opportunities to improve their productivity and recommend specific coaching supervisors can provide, based on past coaching successes. 

In some cases, predictive analytics might reveal that the employee’s supervisor has a history of workers with similar challenges. That’s often an indication that the supervisor needs coaching on how best to help their workers. 

Is employee retention one of your priorities? 

Have these six predictive analytics use cases piqued your interest? 

Learn How Machine Learning Can Help You Reduce Employee Turnover 
Check out our webinar featuring iQor SVP IT Joe Przybylowski, iQor Data Scientist Andrew Reilly, and iQor VP Operations Terri Roberts to discover how to harness technology to engage employees and reduce turnover.

Get the details directly from the people responsible for the program.

Watch Now

Experience the Best in Data Analytics  

iQor’s analytics as a service offering uses a combination of iQor’s proprietary speech analytics platform, cloud computing, machine learning, artificial intelligence, and data analysis to develop custom interventions for identified areas in need of improvement along the customer journey. The results produce targeted improvements for the employee, customer, and client.  

iQor is a business process outsourcing company ideally suited to help brands create amazing customer experiences. iQor provides a comprehensive suite of full-service and self-service scalable offerings that are purpose-built to deliver enterprise-quality CX. 

Our award-winning CX services include:  

• A global presence with 40+ contact centers across 10 countries.  
• A CX private cloud that maximizes performance and scales rapidly across multiple geographies on short notice.  
• A partnership approach where we deploy agents and C-level executives to help maximize your ROI.  
• The perfect blend of intelligent automation for scale and performance coupled with an irresistible culture comprised of people who love to delight your customers.  
• Virtual and hybrid customer support options to connect with customers seamlessly, when and where they want.  
• The ability to launch a customer support program quickly, even when you need thousands of agents ready to support your customers.  
• A best-in-class workforce management team and supporting technology to create a centralized organization that can better serve your entire business.  

iQor helps brands deliver the world’s most sought-after customer experiences. Interested in learning more about the iQor difference? If you’re ready to start a conversation with a customer experience expert, contact us to learn about how we can help you create more smiles.  

Joe Przybylowski is SVP of IT at iQor. Connect with Joe on LinkedIn.
Andrew Reilly is a data scientist on the AI & Data Science Team at iQor. Connect with Andrew on LinkedIn.

Delivering Effective Coaching That Strengthens Performance in an Increasingly Complex CX Ecosystem 

5 Steps to Improve Coaching Effectiveness for Frontline Supervisors is a free webinar available on demand, presented by iQor and AmplifAI. David Arellano, head of product at AmplifAI, joined the authors of this blog post: Saurabh Bhaskar, iQor’s senior vice president of operations, and Anthony Paige, director of training and quality for iQor. Here’s an overview of what they discussed.

Measuring and Improving Frontline Coaching Effectiveness Is Critical 

Eighty percent of agents who leave contact centers do so because of their frontline supervisor. And the biggest challenge these supervisors face is usually their own interpersonal coaching skills. Effective frontline coaching is the best way to sustain and improve agent performance. This means measuring and improving frontline coaching effectiveness is critical to achieving desired outcomes. 

iQor invests heavily in recruiting, training, and coaching frontline employees. We want everyone we hire to enjoy a long and successful career with us. That’s why we provide professional learning opportunities and pathways to advancement. Coaching has always been a priority. 

Automation Has Changed Agents’ Roles 

In recent years, automation has taken on many of the more mundane tasks that agents used to perform, leaving them to handle more high-skill and high-value tasks.  

The growth of multi-channel and omnichannel customer experience—and all the digital CX technologies that make them possible—has enabled that complexity. Every CX interaction is recorded. Proprietary data analytics technologies scour recordings in search of opportunities for improvement through coaching and examples of best practices in action.  

Contact Center Complexity and Data Overload Create New Coaching Challenges 

Several years ago, the increasing complexity of the agent ecosystem began to leave supervisors wondering what their next coaching step should be. There was so much data and no efficient, effective, and accurate way to make sure coaching aligned with business priorities or measured coaching effectiveness. 

Fifty-six percent of contact center employees say job complexity is a top challenge. 

One Solution to Reduce Complexity, Identify Business-Critical Coaching Opportunities, and Measure Coaching Effectiveness 

We wanted to allow our supervisors to spend less time with data and more time coaching, so we researched numerous potential solutions.  

We invested in: AmplifAI, an AI-driven performance enablement platform that:  

• Facilitates coaching events by surfacing the most impactful coaching opportunities. 
• Reduces complexity by telling supervisors what they need to do next (based on specific coaching goals). 
• Reports on agent performance in key areas. 
• Identifies the type of coaching that agents and coaches need.  
• Measures coaching effectiveness. 

How Webinar Attendees Rate Their Coaching Effectiveness of Frontline Employees 

14%	43%	14%	4%	25%
Excellent	Good	Fair	Poor	Not Measuring

Three years later, results from our strong partnership with AmplifAI—and the solution’s sophisticated AI and machine learning—have proved that investing in AmplifAI was the right decision.  

iQor employs AmplifAI to help coaches coach and measure coaching effectiveness. The five steps to improve coaching effectiveness show you how we work together. 

1. Create and Communicate Your Coaching System 

Your coaching system—the technology that facilitates the coaching process and measures coaching effectiveness—can only be as good as the coaching itself. 

iQor and AmplifAI align on what good coaching looks like: 

• Proactive coaching with a specific goal in mind that enables the agent to perform their job better. 
• Frontline leaders customize coaching to the individual agent’s learning style, whether that’s visual, audio, kinetic, or digital. 
• Even in flexible work environments where agents can work at home or on premise, all agents are trained equally well.  
• Supervisors need to be able to focus on their team, not the data, and provide specific actions the agent can deliver. 
• Quick onboarding, consistent training, and effective coaching contribute to improved retention. 
• Better employee experience translates to improved customer experience. 

To create your coaching system, you’ll also need clear expectations about:  

• What the system can and will do for you. 
• How much you’ll use the system for coaching. 
• Methods you’ll use to facilitate coaching events. 
• KPIs that are most important to the business. 
• What constitutes coaching success. 

For iQor, the system provides easy-to-review performance data that show where everyone stands in relation to their goals, their team, and their program. 

2. Train Coaches How to Communicate and Develop Others 

In contact centers, supervisors are often former agents who were promoted from within.  

All agents need to be able to communicate effectively. Those who become supervisors (and coach others) also need to have the right underlying skillset, which includes the ability to help others change their behavior.  

At iQor, developing a new leader includes providing best practices for follow-through and leadership skills training. Plus, new leaders are trained to leverage technology that will help them be effective coaches. 

3. Provide Visibility Into Performance and Testing 

With AmplifAI, the system’s AI can be trained to identify coaching opportunities with the greatest potential impact and direct coaching activities to the right metrics, individuals, and tactics to add the greatest lift to performance.  

The AI cuts right through the complexity to show supervisors what they need to do next, offering coaching suggestions unique to each agent’s individual needs. This enables supervisors to save time they once spent determining which potential coaching opportunities to pursue—up to 40% of their time—and devote that time to coaching.

The AI cuts right through the complexity to show supervisors what they need to do next, offering coaching suggestions unique to each agent’s individual needs. This enables supervisors to save time they once spent determining which potential coaching opportunities to pursue—up to 40% of their time—and devote that time to coaching.  

Should KPIs change—along with the behaviors required to achieve success with those KPIs—the system can be tuned to reflect which coaching opportunities are important. iQor’s close working relationship with AmplifAI makes those kinds of changes easy to make. 

4. Measure Coaching Effectiveness 

Measuring coaching effectiveness is critical to understanding which coaches are doing exceptionally well and deserve recognition, and those who could benefit from coaching. 

5. Learn From Successful Coaches 

Many coaches are good at walking their agents through processes and expectations. Some are good at helping agents buy into and become a part of the learning and development process. Others are great at helping the agent understand how this change will benefit them. 

By measuring coaching effectiveness, you can identify where individual coaches could benefit most from coaching. 

AmplifAI points to the most successful coaching lessons in a given area. That enables other coaches to learn how to modify their own behavior based on how the most successful coaches teach those lessons. Also, coaches can use those lessons when coaching agents. 

The best coaching helps improve outcomes for agents, keeps agents more engaged, and contributes to their long-term success. 

The Proof Is in the Results 

When a telecom client asked iQor to shift their KPI emphasis from customer satisfaction (CSAT) to net promoter score (NPS), we turned to AmplfAI to identify opportunities to coach the behaviors needed to improve NPS. By focusing on the metrics that matter most, AmplifAI reduced the number of dashboards and reports that coaches were required to review. 

With a significant increase in coaching and more time spent on effective agent development, we produced these results for the client: 

• 6x improvement in customer resolution time. 
• An increase in NPS ranging from 2.5% at the beginning of the test period to an increase of 13% at the end of the test period. 
• 40% more coaching sessions with tracking and accountability. 

Your Next Step 

For the complete case study details, plus charts, graphs, more in-depth discussion of the points referenced here, and an easy-to-understand look at how AmplifAI works, watch the webinar. It’s free and available on demand. 

Experience the Best in CX 

We partner with clients to design the optimal mix of CX automation and people. iQor is ideally suited to help brands create amazing customer experiences. As a managed services provider of customer engagement and technology-enabled business process outsourcing (BPO) solutions, iQor provides a comprehensive suite of full-service and self-service scalable offerings that are purpose-built to deliver enterprise-quality CX. 

Our award-winning CX services include: 

• A global presence with 40+ contact centers across 10 countries. 
• A CX private cloud that maximizes performance and scales rapidly across multiple geographies on short notice. 
• A partnership approach where we deploy agents and C-level executives to help maximize your ROI. 
• The perfect blend of intelligent automation for scale and performance coupled with an irresistible culture comprised of people who love to delight your customers. 
• Virtual and hybrid customer support options to connect with customers seamlessly, when and where they want. 
• The ability to launch a customer support program quickly, even when you need thousands of agents ready to support your customers. 
• A best-in-class workforce management team and supporting technology to create a centralized organization that can better serve your entire business. 

iQor helps brands deliver the world’s most sought-after customer experiences. Interested in learning more about the iQor difference? If you’re ready to start a conversation with a customer experience expert, contact us to learn about how we can help you create more smiles. 

Saurabh Bhaskar is senior vice president of operations at iQor. 

Anthony Paige is director of training and quality at iQor.

Part Two in a Series of Blog Posts About Robotic Process Automation (RPA) 

This content is from a 2022 webinar produced and published by NICE that features iQor VP of Research and Analytics Ada Smith and iQor SVP of Digital Solutions and Optimization Joe Przybylowski. You can watch the full webinar, iQor Empowers Airline Agents to Boost Performance With Attended RPA, on demand. No name or email is required. 

From Ada Smith’s Presentation 

Over the years I have led many RPA projects for iQor and have developed several best practices. These are my keys to successful RPAs that achieve results with measurable ROI. 

1. Consult All Levels 

Talk to as many people as possible. In addition to spending time with the project requestors and managers, also meet and interview the people who do the manual work and are end users of the proposed RPA. Make it a part of the process to ask the same questions in different ways to a variety of people. This will help you come as close as possible to the right answer.   

2. Disregard Traditional Notions of Scope 

Even though we often begin with an idea of what an automation should be, it is important to see all of the processes in addition to the primary one.   

People often say, “Oh, that doesn’t pertain to this project.” My response is that I need to see it anyways because RPA has many abilities and there may be potential solutions that haven’t been considered. We need to retrain our way of thinking to look beyond simple replacement. The goal is to optimize a process and we need to look at anything that might impact the design. 

3. Establish Clear Roles 

Throughout the project, remind everyone of their roles as you move through the different phases of discovery, design, development, and testing. It is important to set expectations for each person and explain their function in each phase. This will ensure you are correctly resourced and will help you stay on schedule. 

4. Keep the Momentum Going 

During long design and development cycles, morale and focus can slip in both the operations team and the development team. You can manage this on the technical side through defined sprints, clear milestones, and by avoiding large breaks between project steps. On the operations side, frequently communicating progress and positive news of milestones will affirm to team members that the project is moving along.    

5. Conduct Postmortems 

Perform a full review of the project after every bot goes into production. Look at the original design notes, compare them to what was created, and assess whether what you envisioned from the beginning ended up as the production RPA or if you landed somewhere completely different.   

This analysis informs future projects so you know what concepts work, how the development cycle progressed, and what may be done differently going forward.  

6. Follow Up  

Maintain communications with the stakeholders and users to keep up with process changes, system changes, and organizational changes that could impact production RPAs.  Everyone has their own tasks to focus on, so you need to proactively ask for updates.   

RPAs must be maintained, developed, and sometimes overhauled, depending on the needs of the business. Keep the lines of communication open and know that change management is a frequent aspect of automation.  

7. Take Time for Maintenance  

Ensure your materials are up to date. Confirm you have everything stored correctly, your templates are current, you have the latest company branding, and anything else that may apply. This improves efficiency, allows you to quickly generate new projects, and makes it easier to access information for presentations. 

By applying these best practices, I am able to identify strong use cases, speed up design and production cycles, and produce value-added bots. 

Bonus

Here’s one more point that was not part of the presentation, but is a best practice for all RPA projects.

Ensure Data Security

With all RPA projects, it’s important to keep data security top of mind. Implement robust security measures to protect sensitive data during RPA processes. Gartner points to four areas of RPA security that require attention: 

1. Ensure accountability for bot actions. 

2. Avoid abuse and fraud. 

3. Protect log integrity. 

4. Enable secure RPA development. 

More on RPA 

This blog post on RPA is the second in a series by Joe Przybylowski and Ada Smith. Check out Part One, The Benefits of RPA: How BPOs Help Organizations Save Time and Money With CX Automation.

Experience the Best in RPA 

iQor is a business process outsourcing company (BPO) ideally suited to help brands optimize their business processes through RPA and digital transformation. Our intelligent automation delivers better customer experiences and helps employees perform at their best.  

iQor’s cognitive RPA software solutions are customized to client needs. We use AI and machine learning to handle high-volume, repetitive, or slow, time-consuming tasks. With streamlined workflows using RPAs, our team completes tasks faster and more accurately to provide amazing customer experiences. 

Moreover, our experience designing, developing, and implementing successful RPA projects for many different businesses enables iQor to identify and recommend the solutions that will deliver to each client their highest return. 

If you’re ready to start a conversation with an RPA expert, contact us to learn about how we can help you create more smiles. 

Ada Smith is vice president of research and analytics at iQor.

Business Process Outsourcing (BPO) Providers Add Strategic RPA Business Benefits to Projects 

As brands continually look to boost efficiency, productivity, and competitiveness in the marketplace, business process outsourcing (BPO) providers with digital transformation expertise offer unique insights and strategic value. This includes helping brands refine processes to achieve more loyalty throughout the customer journey. 

In recent decades, brands and analysts have come to recognize that BPOs understand how to navigate the options and opportunities created by business process optimization technologies. 

In recent decades, brands and analysts have come to recognize that BPOs understand how to navigate the options and opportunities created by business process optimization technologies.

One such technology—robotic process automation (RPA)—offers myriad business benefits, especially when deployed through a BPO with strategic digital transformation experience. 

Recognizing the Unique Business Benefits BPOs Add to Digital Transformation

In an August 2022 article, Gartner highlighted two unique benefits of partnering with a BPO for digital transformation.  

1. Because BPOs consistently add technology to their tech stack, it’s easy for them to demonstrate how a given digital solution can help solve a client’s operational challenges. 

2. By taking on vendor administration responsibilities for you, a BPO can remove two apparent needs: a) to hire more full-time employees and b) to give your IT staff additional work. 

Beyond these two benefits, BPOs bring a third benefit: objectivity. As third parties, BPOs can focus solely on the client’s objectives: to solve operational challenges, boost productivity, improve efficiency, and increase competitiveness while maintaining excellent customer and vendor relationships.  

As BPOs have demonstrated, these benefits apply to automation projects as well.

BPOs and Automation

Many BPOs that excel at digital transformation have also become experts in business process automation (BPA), an umbrella term that covers any type of automation used to streamline business processes and workflows, including robotic process automation.  

Like digital transformation, BPA is an increasingly popular and effective way to make business processes more efficient, workers more productive, and brands more competitive.

Rapid Expansion of RPA

From 2020-2026, global use of business process automation (BPA) is expected to grow at a compound annual growth rate (CAGR) of 12.2%, from $9.8 billion to $19.6 billion. 

The robotic process automation market is consistently the fastest-growing of all types of BPA. Forrester Research expects RPA deployment and support services to reach $12 billion in 2023. 

Forrester Research expects RPA deployment and support services to reach $12 billion in 2023.

Brands prefer robotic process automation to other forms of automation because it: 

1. Requires little support from IT, leaving them to perform their duties uninterrupted.  

2. Has proved its value across industries by automating a wide array of functions with accuracy, including: 

• Manipulating and migrating files and data between different applications.
• Entering and validating massive quantities of data (big data) from multiple systems.
• Reconciling accounts.
• Processing credit cards, mortgages, invoices, and insurance claims.
• Detecting potential threats of bank fraud.
• Planning resource needs and managing inventory.
• Onboarding new employees.

RPA at a Glance 

RPA is a collaborative function of business stakeholders, users, RPA designers, and developers who automate processes on an RPA software platform.  

With RPA, software records a human’s clicks and keystrokes as they perform a high-volume, tedious, and repetitive process—such as data entry—on a digital interface. A virtual robot (bot) then mimics the human’s clicks and keystrokes, but much faster and with no errors.  

Like a human operator, an RPA robot can perform data entry tasks, open and close different applications, and use optical character recognition (OCR) software to digitalize data found on hard copy assets—such as printouts of Excel spreadsheets—and then use that data in the process. 

Today, RPA and digital transformation are often used on the same projects, so a thorough discussion of RPA must include digital transformation. 

In this blog post we’ll cover: 

• Top Benefits of RPA for BPO clients. 
• The RPA-digital transformation connection. 
• Why a BPO with a proven digital transformation track record can multiply the benefits of robotic process automation. 
• Experience the best in RPA 

Top Benefits of RPA for BPO Clients 

When asked, BPO clients cite the following benefits of robotic process automation. 

Boost Efficiency and Reduce Costs 

RPA saves time by assigning repetitive tasks to bots, which allows humans to focus on tasks that require critical thinking. Reducing the human time spent on repetitive processes also reduces the cost to complete each process. Efficiency savings of 25%-50% are common. 

Improve Customer Satisfaction 

Contact centers help brands build relationships with customers, earn high customer satisfaction ratings with excellent personalized service, and help retain customers. To personalize customer service, an agent must access the customer’s history of interactions with the brand in every channel they’ve ever used—including in-store, e-commerce, chatbot, voice, social media, and more.  

Pulling all that information together can take the agents several minutes. In today’s real-time world, several minutes can be enough to make customers wonder what’s taking so long. RPA can pull all the customer information together from every channel in seconds. That makes it easier for the agent to focus on the customer and provide excellent, personalized customer service that makes the customer smile. 

Accelerate Productivity 

Many frontline workers perform repetitive tasks that take time away from the more valuable work they joined the brand to do. RPA removes the need to perform repetitive tasks and allows them to focus on knowledge and skills-based responsibilities. The result is a win-win for both the employees and the brand. It lowers costs for the brand and boosts workers’ morale by making them feel more valuable. 

Increase Accuracy 

When humans perform the same monotonous tasks repeatedly, they make mistakes. A 2% error rate may not seem like much, but over 10,000 repetitions, that’s 200 errors. Fixing those errors takes time, which costs money, and means valuable workers are doing something other than their primary tasks. When RPA bots take over those monotonous tasks, they make no mistakes. RPAs are robots that do a handful of things consistently well.  

Tighten Data Security 

Brands prioritize the security of business data and personally identifiable data. By specifying strict parameters in the RPA security rules, brands can limit the number of people who see confidential data and make it difficult for bad actors to copy or share it. Tightening data security with RPA helps brands comply with government and industry-specific privacy regulations. 

Scale on Demand 

Many business activities change seasonally, and seasonal change often requires temporarily ramping up headcount, onboarding, and training. When RPA handles the repetitive processes, bots do all required work without impacting headcount to meet changes in demand. 

Generate Valuable Data 

An RPA gives brands the opportunity to digitally track processing efficiency. This is especially important when humans and bots work together, with the bot handling the parts of the process that can be automated and the person handling the rest. The RPA can track the time it takes to complete the process from beginning to end, including the part performed by the worker.  

When some instances take longer than normal, these outliers may be signs that the process could benefit from analysis and modifications that will allow the human and robot team to consistently complete the process in the same amount of time. This data enables organizations to fine-tune their RPA and generate additional efficiencies. 

Function Consistently 

People find their own ways to perform processes, even when they are repetitive.  

When the person who usually handles a process is unavailable, someone else must perform the task. The replacement brings their own touch to the task, so you can’t expect them to complete it in the same amount of time or with the same level of accuracy. RPA works the same way every time, as long as the rules and the systems remain the same. 

Extend the Life Cycle of Legacy Systems  

When workers are required to execute repetitive processes that move data from one application to another, it’s usually because a legacy system that doesn’t accommodate API connectivity is involved. Brands can improve efficiency by using an alternative way of connecting the applications. RPA is that alternative.  

RPA bots do everything workers do when transferring data between systems—but in a small fraction of the time and with 100% accuracy. Bridging connectivity gaps is how brands employ RPA in digital transformation projects. 

Each of these benefits of RPA generates significant value for brands that do RPA right. The next two sections clarify the RPA-digital transformation connection and the role business process outsourcing providers play. 

The RPA-Digital Transformation Connection 

In a perfect world, digital transformation would be a straightforward process, with new software replacing old software and data digitalization making all data shareable and actionable across lines of business.  

In reality, there are times when old software can’t be replaced because the hardware that hosts it doesn’t meet the technical requirements of the new software. That’s usually because the hardware was created for an outdated—or legacy—operating system. When that’s the case, there are two options: 

1. Replace the old hardware with new hardware at considerable cost and time-consuming operational disruption. 

2. Find a way to connect the new software in the modern digital system to the old software in the legacy system.  

This is where RPA comes in. Instead of spending a fortune on new hardware and disrupting operations until it performs all functions properly, RPA can bridge the gap between the new hardware and the old by mimicking all the steps required to connect the two applications. 

The need to solve connectivity gaps is a common need in digital transformation projects, and a major reason RPA has become an invaluable component of digital transformation. By incorporating RPA to bridge digital transformation gaps—at a much lower cost than that of buying and installing new hardware—brands can stage their digital transformation strategy over time. 

Why a BPO With a Proven Digital Transformation Track Record Can Help Multiply the Benefits of Robotic Process Automation 

We’ve touched on three unique RPA business benefits that BPOs bring to projects: 

1. Conduct affordable pilot programs to prove the RPA concept.
If your brand wants to see what RPA can do before investing in a large project, a BPO with RPA expertise can run a small pilot project. 

You could run the test yourself, but the BPO’s technical knowledge and RPA expertise allow your brand to focus on your business without having to become RPA experts while the BPO runs the pilot. 

2. Save the brand from having to hire full-time employees.
Creating a successful RPA requires: 

• Project leaders.
• Ongoing communication with all stakeholders.
• Expert RPA developers.
• Post-launch follow-up communication.
• Ongoing maintenance and fine-tuning as systems and rules changes dictate.
• Vendor management.

A BPO with its own center of excellence has the experienced staff and leadership in place for your first project and all ensuing RPA projects, so increasing your headcount won’t be necessary. 

3. Instill confidence that all recommendations have the brand in mind.
Many decisions are made when creating an RPA. When you partner with a BPO that provides objective advice based solely on the goals and needs of your brand, you can feel confident in both the process and your decisions. 

But the most significant benefit a BPO can provide a brand is its unique ability to take a holistic approach to business process optimization. 

When objectively evaluating an organization’s potential RPA projects, a BPO with digital transformation expertise can employ a strategic perspective of the involved system(s) that includes: 

• Brand objectives. 
• IT modernization plans. 
• Hardware lifecycle stages. 
• Pending operating system and application updates. 

All this information must be considered holistically to properly answer these four fundamental questions: 

1. Which form of optimization is the correct choice of optimization for a given process? RPA? Another type of automation? Digital transformation?
2. What resources are required to complete each task? 
3. What steps for preparing the system for optimization should come first? 
4. In what order, and over what time span, should the creation and implementation of business process solutions be staged to generate a return in the least amount of time while minimizing operational disruption?

Getting these answers right the first time can multiply the value of the top RPA business benefits listed earlier. 

The right BPO—one with a track record of success in both RPA and digital transformation—can provide these services without pushing one solution over another for self-serving reasons.

The right BPO—one with a track record of success in both RPA and digital transformation—can provide these services without pushing one solution over another for self-serving reasons.    

Even if it means recommending an alternative solution to RPA, the BPO’s mission is to help the client achieve its goals to refine processes and improve the customer experience. 

Experience the Best in RPA 

iQor is a business process outsourcing company (BPO) ideally suited to help brands optimize their business processes through RPA and digital transformation. Our intelligent automation delivers better customer experiences and helps employees perform at their best.  

iQor’s cognitive RPA software solutions are customized to client needs. We use AI and machine learning to handle high-volume, repetitive, or slow, time-consuming tasks. With streamlined workflows using RPAs, our team completes tasks faster and more accurately to provide amazing customer experiences. 

Moreover, our experience designing, developing, and implementing successful RPA projects for many different businesses enables iQor to identify and recommend the solutions that will deliver to each client their highest return. 

If you’re ready to start a conversation with an RPA expert, contact us to learn about how we can help you create more smiles. 

Joe Przybylowski is vice president of digital solutions and optimization at iQor. 

Ada Smith is vice president of research and analytics at iQor.

Global CX Experts Share Strategies for Delivering Memorable CX With a Smile 

iQor’s Digitally Irresistible podcast offers customer experience professionals content that informs, educates, and inspires the ongoing practice of delivering a consistently great customer experience in any industry. 

As host of the podcast, I look back on the first full calendar year of the podcast with gratitude to each CX expert I had the privilege of showcasing. From Episode 1 in July 2021 to Episode 64 published on December 8, 2022, the common thread is a passionate commitment to delivering great customer experiences.  

The topics covered in the first 64 episodes run the gamut from digital technology to employee wellness to the role of marketing in the customer experience. Each guest featured on the podcast brings their unique experience and expertise to every conversation. They span the globe and share their perspectives on strategies to create smiles throughout the customer journey. They share their personal journeys, lessons learned, advice, and a little about themselves and what they do for fun. 

In this post, we celebrate each guest as a special thank you for sharing their expertise.  

Every episode is published in three formats: audio, video, and a blog post. The audio is available on all the popular podcast listening platforms, e.g., Apple Podcasts, Spotify, Stitcher, Overcast, Amazon, and many others. The video is embedded in each blog post and is also available on iQor’s YouTube channel.  

A Look Behind the Scenes 

Ever wonder what goes into producing a podcast? Before each episode is recorded, the guest and I meet to discuss and finalize the CX topic we will feature on their episode, based on their expertise and the key points we plan to cover on their episode.  

I then outline talking points that we’ve mutually agreed to cover pertaining to their topic. These talking points guide the flow of the conversation during the recording. Additionally, I script an introduction that highlights the guest’s credentials.  

On the day of the recording, we begin a conversation about the topic guided by our agreed-upon talking points. The only scripted part of the podcast episode is my introduction to each guest.  

I end every episode asking each guest what they do for fun when they’re not working. This is my favorite question because we gain a little insight into each guest’s interests outside of their work. I never know in advance how the guest plans to answer this question, so it’s always a fun experience for me to hear their answer for the first time.  

Our graphic design team takes great pride in the video production that follows each recording, going to great lengths to create an engaging experience for the audience and present the story with visually compelling elements such as video clips supplied by the guest. 

With more than 60 episodes of the Digitally Irresistible podcast, we often hear that this body of content is like a masterclass in CX best practices. We are committed to continuing to publish content through the podcast that informs, educates, and inspires CX professionals to deliver digitally irresistible customer experiences. 

A Masterclass in 64 Episodes 

Below is the list of each guest featured from July 2021 through December 2022. I invite you to join in on the masterclass content. It will make you smile! 

Episode 1: PJ Singh: The Role of Digital Technology in the Modern Customer Experience  

Episode 2: Tarisse Grant-Shelton, M.Ed.: Train the Trainer Certification That Creates Irresistible People 

Episode 3: Annette Timmins: A 25-Year Journey in the BPO Industry Motivated by Helping People 

Episode 4: Ada Smith: How Robotic Process Automation Reduces Call Handle Time 

Episode 5: Maria Castro: The Journey From Call Center Agent to Training Manager 

Episode 6: Chris Holt: Leadership Development Through Training and Mentors 

Episode 7: Gail McLaughlin Toti: How Visionary Selling in the BPO Industry Wins  

Episode 8: Gladys Rodinas: How This Call Center Agent Advanced Her Career Through the sQholar Program 

Episode 9: Troy Sanders: The Trust Building Imperative in BPO Industry Sales Success 

Episode 10: Gary Praznik: The Power of Listening in Your Career 

Episode 11: Flo Navarro: Non-Stop Recruiting of Irresistible Contact Center Agents 

Episode 12: David Rickard: Top Trends in the Customer Experience Management Industry 

Episode 13: William Adams: Why the Net Happiness Score Is Simple and It Works 

Episode 14: Andrew Riley: How Attrition Risk Modeling Enables Employee Happiness 

Episode 15: Sekou Alleyne: Three Reasons for iQor’s Nearshore BPO Expansion in Trinidad and Tobago 

Episode 16: Dan Gingiss: How to Create Remarkable Experiences Customers Want to Share 

Episode 17: Tone Holmen: The Impact of Omnichannel Support on Contact Center Agents 

Episode 18: Shep Hyken: How to Get Customers to Come Back Again and Again 

Episode 19: Andrew McNeile: How ThinScale Technology Transforms the Work-at-Home Experience for Call Center Agents 

Episode 20: April Segovia: Rapid BPO Career Success by Embracing iQorian Values 

Episode 21: Stephon Griffin: Becoming a Top Certified Trainer Against All Odds 

Episode 22: David Wasserman: Three Reasons NICE Powers iQor Global Workforce Management Solutions 

Episode 23: Charlene Li: Three Strategies for Creating Stronger Employee Relationships 

Episode 24: Rohan Kulkarni: Patient Engagement Can Create Customer Experience in Healthcare 

Episode 25: Chris West: How Strong Language Can Be Use to Deliver Great Customer Service 

Episode 26: Loren Dennis: How iQorians Give Back Through iQor Qares 

Episode 27: William Huggins DBA: A Purpose-Driven Leadership Customer Experience Strategy in Trinidad

Episode 28: Tarn Shant: The Three Pillars of Digital Transformation in the Customer Experience 

Episode 29: Howard Tiersky: Digital Transformation Starts with Customer Experience 

Episode 30: Maribel DeLeon: How iQor Launches a New Customer Program Implementation 

Episode 31: Ingrid Ceballos: The Power of Coaching in Building Employee Loyalty 

Episode 32: Max Armbruster: How to Achieve High-Volume Talent Recruiting Success 

Episode 33: George Kushner: Crypto Exchange Looks to Differentiate with Client Service 

Episode 34: Cristy Gavino: How a Customer Service Program Grew by a Factor of Ten 

Episode 35: Kevin Anthony Paredes: How Exceeding Client Expectations Creates Career Growth Opportunities 

Episode 36: Adaeze Nwamah: Coaching and Analytics Propels Customer Service Team to Top Performer 

Episode 37: Zion Joy Suvillaga: The Road to Project Manager in HR 

Episode 38: Christian Smalls: How Relationship Building is Good for Employee Retention 

Episode 39: Jim Down: Two Core Pillars of Exceptional Customer Service 

Episode 40: Kristen Kuyatt, Ph.D.: Customer Experience Trends in Silicon Valley 

Episode 41: Sonia Rosario: Achieving Human Connections Through Personalized CX Training 

Episode 42: Mary Drumond: How AI Provides Insight Into Customer Motivations at Scale 

Episode 43: Ron Dull: The Appeal of South Africa in the Customer Experience 

Episode 44: Caity Morder: iQor Qares Charitable Giving Nonprofit Supports Employees and Communities in Times of Need 

Episode 45: Miri Rodriguez: How Brand Storytelling Influences Customer Experience 

Episode 46: Jay Baer: How to Hug Your Haters to Improve Customer Experience 

Episode 47: Andrew Davis: A Six-Step Model to Develop Customer Loyalty 

Episode 48: Bhawna Singh: How to Optimize Customer Service Through Current and Future State Assessment 

Episode 49: Jeannie Walters: The Three Pillars of Good CX 

Episode 50: Karen Hold: How to Use Design Thinking to Optimize Customer Experience 

Episode 51: Kevin Tydlaska-Dziedzic: Experience Marketing Is the Recipe for Sustainable CX 

Episode 52: Jerry Levine: A Winning Digital Transformation Strategy for Inside Legal Teams 

Episode 53: Annette Franz: 4 Steps to Improve the Customer Experience from the Inside Out 

Episode 54: John Kruper, D.A.: Active Learning Boosts Skill Development and Retention for Frontline Employees at Scale 

Episode 55: Emily McGuire: Elements for Creating Exceptional CX Through Email 

Episode 56: Alec Dalton: The Vital Role of Quality Management in Customer Experience 

Episode 57: Sean Minter: How AI Enables BPO Supervisors to Coach Agents and Boost Performance 

Episode 58: Heather R Younger: How Caring Leadership Transforms Customer Experience 

Episode 59: Brian Wagner: 3 Business Functions of a Digital Marketing Ecosystem in Health Care That Improve the Customer Experience 

Episode 60: Stan Phelps: The Differentiated Experience Is the Most Referable Customer Experience 

Episode 61: Laura Putnam: Workplace Wellness That Puts Organizations in Motion 

Episode 62: John O’Malley, Chris Fago, and Kyle Pierrehumbert: How iQor Optimizes Cloud Security with Prisma® Cloud 

Episode 63: Dennis Wakabayashi: How to Create Profitable Customer Experiences  

Episode 64: Jaymee Marquez: How Employee Engagement Creates Smiles in CX

Bernie Borges is vice president of global content marketing at iQor.

As Experts’ Views on Customer Retention Evolve, Customer Care and Revenue Recovery Become More Alike 

Expert views on customer retention have evolved, as the following three very different opinions make clear. 

1. Based on Customer Acquisition Cost 

Long-held beliefs on the importance of customer retention are rooted in data that shows acquiring a new customer costs five times more than retaining a customer. 

A pre-pandemic survey found that:  

• Retaining an existing customer costs 20% as much as acquiring a new customer.  
• Selling to existing customers is successful 60-70% of the time compared to a 5-20% success rate with prospects.  
• A 5% increase in customer loyalty can boost profits by 25-95%.  

Other views consider the customer lifetime value (CLTV) of retention as much as or more than acquisition cost.

2. Based on CLTV 

When asked about those long-held beliefs for an article in Forbes, Wharton School of Business marketing professor Peter Fader said, “Here’s my take on that old belief: who cares? Decisions about customer acquisition, retention and development shouldn’t be driven by cost considerations—they should be based on future value.” 

Fader believes decisions about customer acquisition and retention should be based on future CLTV, not the cost of acquisition. His view is that some prospective customers are worth acquiring and retaining, while others are not.  

3. Expanding Our Understanding of CLTV 

Michael Schrage, visiting fellow at Imperial College Business School, approaches customer lifetime value in monetary and behavioral terms.

Schrage ends his Harvard Business Review article, What Most Companies Miss About Customer Lifetime Value, with the statement, “The best investment you can make in measuring customer lifetime value is to make sure you’re investing in your customers’ lifetime value.” 

He advises brands to move beyond calculating CLTV strictly in monetary terms and also value customers’:  

• Ideas and insights.  
• Ability and readiness to promote the brand on social media.  
• Trust (the key to unlocking their data).  
• Collaboration.  
• Willingness to try new products and services. 

While these three viewpoints pose intriguing and different opinions about customer loyalty and how to measure customer lifetime value, they align with customer experience (CX) programs that strive to retain your most valuable customers and increase their CLTV. 

Valuing positive customer behavior, as Schrage suggests, has been a hallmark of exceptional customer care for years. Now, brands and BPOs recognize that valuing and encouraging positive customer behavior improves outcomes in revenue retention, including boosting CLTV.

In this blog post we’ll cover:  

• The relationship between customer retention and revenue recovery. 
• 6 ways modern revenue recovery mirrors customer care.  
• The role of digital CX technology in both customer care and revenue recovery.  
• The benefits of partnering with one BPO for both revenue recovery and customer care. 

We’ll start with a look at the ways revenue recovery has changed.  

With Customer Retention in Mind, Revenue Recovery Now Prioritizes Getting Relationships Back on Track 

In the past, revenue recovery focused solely on collecting money from customers who were behind on their payments. 

Today, the focus goes well beyond collecting money from the customer.

Customer-driven brands and their revenue recovery agents strive to build and maintain good customer relationships, retain customers, and keep them happy. 

This shift toward prioritizing customer relationships has been driven by changes that include:  

• Increased use of scheduled automated payments, for which failed payments may be caused by circumstances beyond the customer’s control.  
• Recognition that today’s customers are more likely to respond positively when treated with kindness and empathy.  
• Restrictions by the Fair Debt Collection Practices Act and the new Debt Collection Rule of the Consumer Financial Protection Bureau targeting legacy revenue recovery tactics.  
•  The power social media gives customers to applaud brands that prioritize their relationships and help resolve their credit issues. 
• The need to verify debt reporting information from the outset. In 2017, more than half of all consumers who were contacted by revenue recovery agents reported that either the debt was not theirs or the amount was incorrect.  

Approaching revenue recovery with the intent to understand and assist helps build customer loyalty, get relationships back on track, and reduce customer churn. 

Brands that place a high value on customer retention now approach revenue recovery as a strategic opportunity to create loyalty and strengthen long-term customer relationships, with an eye toward growing the customer’s lifetime value. 

Increasingly, revenue recovery is adopting customer care strategies. 

6 Ways Modern Revenue Recovery Mirrors Customer Care   

Exceptional customer care programs use methods proven to satisfy customers and earn their loyalty, thereby increasing customer satisfaction scores (CSAT), net promoter scores (NPS), and CLTV. Successful revenue recovery programs have adapted these methods and made them their own. Consider how much these revenue recovery techniques are like customer care. 

1. Communicate proactively: Keep customers aware of your policies regarding the timing and cost of late fees. When an analysis identifies customers whose payment habits have slipped, notify the customer of the help available to them. Build trust by showing you’re on their side. 

2. Be flexible: If a customer is struggling to make a payment, work with them to find a solution that meets their needs. Every situation is different, so you’ll need more than one solution to offer them. 

3. Show empathy: Understand customers’ feelings and show them the respect you’d want to receive if you were in their shoes. People don’t want to fall behind. Sometimes things happen beyond their control. Build rapport with the customer by listening to what they say and acknowledging their feelings.

4. Keep their satisfaction in mind: Regularly survey customers to make sure they’re satisfied with the revenue recovery process and with the treatment they receive. Solicit their feedback and take their comments seriously, especially if you receive the same feedback from multiple customers.

5. Take a consultative approach: Show customers that you want to help them get through what could be a tough time for them and keep the brand-customer relationship in good order for the long haul. You both have the same goal: to maintain or reset the relationship on a positive path. Demonstrate your commitment to the relationship. Provide guidance that will help them achieve that goal.

6. Look to the future: Assure the customer that they are valued as a customer, now and in the future. Guide them through their current challenges with a vision toward a long brand-customer relationship ahead.

Role of Digital Customer Experience (CX) Technology  

Using digital CX technologies, agents can review every customer interaction with the brand, regardless of the type or number of channels the customer has used. That includes a customer’s history of interactions with all agents and notes from each of those interactions. 

Digital CX technology provides the agent with all available information about the customer so they can personalize their interactions by addressing them by name and communicating with them knowledgeably and with empathy. 

Supervisors use digital contact center call monitoring and speech analytics to pinpoint agent coaching opportunities. Ongoing coaching improves agent performance, helps lift CSAT, NPS, and CLTV, and improves revenue recovery outcomes. 

Confidentiality and security are critical to revenue recovery. The right digital CX technology will keep all interactions secure and ensure that agents always work in compliance with applicable regulations. 

If your organization is managing revenue recovery and customer care internally, you may find that a partnership with the right business process outsourcing (BPO) provider will improve results and reduce potential exposure to security and non-compliance issues. 

Benefits of Partnering With a BPO for Both Revenue Recovery and Customer Care Services 

BPOs view personalizing the customer experience as a holistic customer-driven approach to two distinct yet related goals: 

• Customer care’s goal is to provide customer service and earn customer satisfaction resulting in sustained brand loyalty.    
• Revenue recovery’s goal is to help the customer get back on track with their payments resulting in sustained brand loyalty.    

That’s why BPOs keep their customer care and revenue recovery staff separate. Agents who provide customer care work exclusively in customer care, just as revenue recovery agents work exclusively in revenue recovery. Those teams are in different locations, possibly even different countries.  

Moreover, agents on the customer care team are trained, coached, or supervised by different trainers, coaches, or supervisors than those on the revenue recovery team, and vice versa—they are separate lines of business (LOB). 

Feedback Loops and Flexible Staffing Benefit the Customer Experience 

The CX personalization techniques used in the two operations are virtually the same, however, and there are several benefits to partnering with one BPO for both LOBs, including: 

• The ability to create feedback loops that inform customer care with what revenue recovery learns from the customer about the impacts of policies and procedures on their customer experience. 
• Similarly, the ability to create feedback loops that inform revenue recovery with what customer care learns from the customer. 
• Continuity in customer relationships, including disclosure and execution of policies and procedures that affect the customer. 
• Increased staffing options, so agents can be assigned to roles where they benefit the client’s program the most. 

Here’s a checklist to help you ensure the BPO you’re considering can deliver these benefits for you. 

How to Know Your BPO Can Handle Revenue Recovery and Customer Care 

When a brand considers contracting with a BPO to handle customer care and revenue recovery, its due diligence begins with confirming that their frontline agents work exclusively on a customer care program team or a revenue recovery program team, with no agent overlap between teams.  

Beyond that, the BPO’s culture should be the brand’s primary focus. With a strong customer service culture, the right BPO will: 

• Focus on customer experience and client satisfaction.   
• Have a proven track record of excellent performance.  
• Prioritize technology-aided training and coaching. 
• Provide robust security and protect customer information.   
• Use compliance software that monitors interactions.   
• Reward agents who produce excellent outcomes for customers.   
• Offer proof of performance in revenue retention, including recovery rates and CSAT/NPS trends.   
• Offer proof of performance in customer care, including no talk time (NTT), average handle time (AHT), call avoidance, first contact resolution (FCR), and CSAT/NPS trends.  

iQor operates multiple long-standing client engagements that began in revenue recovery and were quickly extended to customer care. Likewise, we’ve also started client engagements in customer care and were awarded revenue recovery as our relationship progressed. Either way, our culture-driven passion is always to make our clients and their customers smile by building rewarding experiences throughout the customer journey.

Experience the Best in CX 

iQor is a business process outsourcing company (BPO) ideally suited to help brands create amazing customer experiences. iQor provides a comprehensive suite of full-service and self-service scalable offerings that are purpose-built to deliver enterprise-quality CX. 

iQor’s contact center as a service model channels iQor’s digital ecosystem of customer service solutions to produce targeted improvements for the employee, end-customer, and client. 

Our award-winning CX services include:   

• Proven revenue recovery services delivered with the same passion to create smiles as our customer care programs.  
• A global presence with 40+ contact centers across 10 countries.  
• A CX private cloud that maximizes performance and scales rapidly across multiple geographies on short notice. 
• A partnership approach where we deploy agents and C-level executives to help maximize your ROI.   
• The perfect blend of intelligent automation for scale and performance coupled with an irresistible culture comprised of people who love to delight your customers.   
• Virtual and hybrid customer support options to connect with customers seamlessly, when and where they want.   
• The ability to launch a customer support program quickly, even when you need thousands of agents ready to support your customers.  
• A best-in-class workforce management team and supporting technology to create a centralized organization that can better serve your entire business. 

iQor helps brands deliver the world’s most sought-after customer experiences. Interested in learning more about the iQor difference? If you’re ready to start a conversation with a customer experience expert, contact us to learn about how we can help you create more smiles. 

 James McClenahan is executive vice president and chief sales officer at iQor.

Why More Contact Centers are Investing in Speech Analytics for Agent Training and Coaching

As consumers, we’re all familiar with the recorded message we hear before speaking with a customer service agent, “This call may be recorded for training purposes,” to name one. Contact centers may get hundreds, thousands, or hundreds of thousands of calls each day.

Before speech analytics, there were only a few ways to mine those calls for agent training and coaching opportunities:

1. Live call monitoring of a limited number of calls.
2. Listening to a limited set of calls chosen randomly.
3. Collecting information directly from agents.

Listening to a limited call sample in its entirety didn’t always reveal the most pressing opportunities for improvement, which could delay coaching interventions and potentially increase legal or financial risk.

Today, advanced contact center speech analytics technology uses artificial intelligence (AI) and machine learning to “listen” to every call. It marks specific agent-customer interactions where attention may be advisable. This attention can take the form of corrective coaching for certain agents as well as global procedural changes. Brands that employ advanced speech analysis tools have seen measurable long-term KPI improvement (e.g., average handle time) resulting in increased customer satisfaction and company growth.

What You’ll Learn  About the Benefits of Speech Analytics

In this blog post, you’ll learn how contact center speech analytics facilitates agent training and coaching, including best practices such as: 

• How every level of a contact center’s structure benefits from coaching insights.
• How speech analytics makes coaching more efficient.
• How coaching powered by speech analytics boosts performance.

Following these best practices, iQor’s speech analytics has yielded powerful results:

• Utilized machine learning to train our analytics algorithm to detect COVID conversations in March 2020 accelerating agent training and coaching.
• Achieved 17.25 times more effective call sampling for an airline client.
• Improved a retail client’s overall efficiency by 52 seconds.

Support Key Stakeholders With Customer Service Speech Analytics to Guide More Effective Training and Coaching

Within each layer of the contact center, every interaction that requires additional coaching matters. The specific insights gained through speech analytics offer opportunities to enhance the employee experience by giving agents the support they need to grow and consistently provide excellent customer service. These insights benefit speech analytics users throughout the organization and strengthen the training and coaching of customer service agents.

Quality Assurance (QA)

The speech analytics technology sends marked interactions to QA specialists who examine the marked areas to determine whether further action should be taken. This significantly reduces the amount of time spent analyzing calls and identifying agents in need of support. For example, out of approximately 100,000 calls, QA might need to review less than 100 interactions.

The QA team can quickly scan the marked interactions and identify those in need of additional attention—often dozens or hundreds—to be addressed by operations and supervisors. This process saves thousands of work hours that would be spent if, in the absence of advanced speech analytics, manual call listening was required to analyze such a volume of calls.

Trainers

Trainers guide new customer service agents on specific skills based on KPIs and client expectations. With speech analytics technology that detects each case in which the trainee agent can benefit from additional support, the trainer is able to assess whether the agent has improved and if more guidance is needed.

Supervisors

Supervisors use automatic reporting and QA-sourced data to learn which agents require more support and what kind of coaching they need.

Coaching designed to improve agent performance in a specific area is often the most frequent use of speech analytics in a contact center. Coaching also forms the basis of a broader analysis to determine if the procedures and guidelines coaches follow benefit agent outcomes and where improvements can be made.

Managers

Managers use the data they receive from QA to create reports. These reports, combined with auto-generated reports from the speech analytics platform, provide insight on opportunities for the program.

With call monitoring tools in a speech analytics platform like iQor’s VALDI—such as the Agent Performance Report—operations teams can easily access, document, and report on performance improvements. This supports open communication with the client to show positive trends in the KPIs or any other metrics of interest.

After iQor implemented agent scoring for a telecommunications client using our proprietary speech analytics platform VALDI—and after supervisors provided the necessary coaching—the operations team discovered a correlation between the net promoter score (NPS) and agent scoring. Consequently, they introduced a single targeted coaching procedure to further improve both metrics.

Clients

A default set of filters and search topics, augmented by the flexibility to customize the solution to the clients’ diverse business needs, allows iQor to quickly put our advanced customer service speech analytics technology to work for clients.

In short order, clients across industries are able to gain valuable insights into the impact of changing environments, new product launches, pandemic-related shipping delays, natural disasters, and more.

50% of all active VALDI speech analytics users perform roles connected (directly or indirectly) to call audits and coaching (e.g., call center supervisors, trainers, QA, and compliance analysts).

The COVID Challenge: iQor’s Speech Analytics in Action

All brands can relate to this example of how speech analytics benefits the training and coaching of customer service agents, which comes from the early days of the COVID-19 pandemic.

When COVID-19 became a factor in conversations with our clients’ end customers, iQor needed to know how often customers raised the topic and what they said to agents about it. With that knowledge, iQor teams could develop training and coaching with speed and accuracy to help agents respond appropriately.

iQor sampled 500 calls that had at least one mention of COVID. Based on information gained from those calls, we immediately added 150 keyword phrases to the search, using COVID and its variations to identify related agent-customer interactions.

Using this insight, VALDI speech analytics detected more than 150,000 COVID keyword phrase instances in one week alone in March 2020.

Machine learning trained the VALDI speech analytics algorithm to detect and mark COVID conversations. Agents received immediate training and coaching on how best to handle different interactions that included COVID-19. This empowered them to respond to customer needs with agility amidst the changing global environment and improved the customer experience.

How Speech Analytics Transforms Your Contact Center

A speech analytics tool transcribes all call center agent and customer conversations. All audio, video, and chats are automatically saved in the CX cloud for security and fast retrieval. Opportunities for corrective action are marked so team members can find them easily.

It’s important to note that advanced customer service speech analytics technology doesn’t just examine the words and phrases used and identify the speaker. It also offers the flexibility to automatically mark interactions where:

• Using text-based sentiment analysis, it understands that a customer’s speech indicates negative emotions and shows escalation patterns.
• Connectivity is below the minimum acceptable standard.
• There are long silences.

Quickly Discover Agent Coaching Opportunities With Speech Analytics

A business process outsourcing provider like iQor uses speech analytics in four ways to identify agents who could gain the most from coaching, determine what that coaching should be, and quantify its impact on the business.

1. Call Auditing

The call audit is one of the most common methods to determine coaching opportunities. Speech analytics technology is a game-changer in the otherwise time- and effort-consuming process.

Speech analytics technology provides QA with the automatic monitoring of KPI metrics, which informs future auditing targets and mitigates the resources needed.

Users can save the selected auditing setup on the speech analytics platform, allowing for quick quality checks after introducing targeted coaching and additional training.

With the help of speech analytics automatic reporting, the QA team can extract information about the agents who made the greatest impact on the given KPIs and focus on them in an audit to provide additional support.

An iQor team improved compliance scorecard KPIs by almost 50% for a client in the banking industry by using script monitoring within the speech analytics solution to detect and verify variations from the compliance script.

2. Referrals From Quality Assurance Teams

Supervisors review the marked interactions they receive from Quality Assurance and determine which ones call for immediate attention through additional training and coaching support.

3. Search With Filters and Topics

When supervisors learn that more calls than expected have extended periods of silence, last longer than usual, or exhibit variations from the agents’ scripts, they can search for calls according to metrics thresholds, interactions where the expected topic was not detected, or both.

The speech analytics system will provide the supervisor with the names of agents in need of additional support and will help design coaching sessions for them.

4. Agent Scorecards and iQor’s VALDI Speech Analytics Scores

iQor’s proprietary VALDI speech analytics agent scores and KPIs defined by the client tell a supervisor how their agents are performing. The supervisor uses this information to coach agents based on specific opportunities for improvement to best meet the agents’ needs and yield better performance outcomes for the client.

A major airline wanted to monitor a particular type of agent-customer interaction. They found that agent scoring through iQor’s VALDI speech analytics was 17.25 times more effective at identifying that interaction than sampling random calls. Thanks to faster and more efficient detectability, the program’s operations team was able to quickly implement effective training and coaching opportunities to improve the interaction score’s result.

Every coaching opportunity is an occasion to help improve agent performance, customer experience, and the agent-coach relationship. Every time an agent improves their performance, it raises customer satisfaction.

With VALDI, speech analytics can be used not only to detect situations requiring special attention, but also those with a maximum quality score. Exemplary agent performance is searchable and can serve as a model for future coaching interactions.

Using Speech Analytics to Coach the Coach

Customer service speech analytics can measure the progress agents make after coaching. That progress indicates the agent’s improvement as well as the effectiveness of the supervisor’s coaching.

Designing and delivering effective coaching sessions creates an opportunity for coaches to continually improve their coaching abilities, even as they learn how to obtain data that has the greatest value for the client and the agents on their program. Accessing and analyzing the data with ease and speed enables operations teams to identify the interventions that yield the most effective long-term improvements and ensure they are prepared to address changing situations.

Call Center Speech Analytics Helps iQor Agents ‘Be More’ Through More Effective Coaching

Each VALDI speech analytics instance is operated and maintained by iQor and customized to the unique needs of each client. Today, iQor runs VALDI programs for outsourced customer service clients across various industries.

The manual call analyses of the past are now supported by innovative technology. Under one platform, coaching is supplemented by:

• Access to all calls within seconds.
• Automatic agent scoring.
• KPI measurement on an individual and global scale.
• Automatic reporting of all essential data.
• Quick information exchange between supervisors and the QA team.

Speech analytics makes day-to-day training and coaching more efficient and insightful. Results apply not only to a single agent but also contribute to the success of the entire client program. An effective and responsive training and monitoring system supports targeted adaptations based on insights gained on changing external conditions and the ongoing development of customer service agents to create smiles throughout the customer journey.

“The VALDI PCA Score* aided us with a targeted approach to improve the speed to competency of low-tenure agents mastering changes within the client program. It helped supervisors adeptly coach agents toward desired call behaviors, improving overall efficiency by 52 seconds.” – Senior Operations Manager for a client in the retail industry

*The PCA Score is a VALDI speech analytics automatic scoring system that assesses the potential for call avoidance.

Experience the Best in Speech Analytics

iQor’s proprietary speech analytics platform uses a combination of cloud computing, machine learning, and artificial intelligence to extract every customer interaction for actionable data insights delivered as a custom solution with outsourced CX services.

iQor is ideally suited to help brands create amazing customer experiences. As a managed services provider of customer engagement and technology-enabled business process outsourcing (BPO) solutions, iQor provides a comprehensive suite of full-service and self-service scalable offerings that are purpose-built to deliver enterprise-quality CX.

Our award-winning CX services include:

• A global presence with 40+ contact centers across 10 countries.
• A CX private cloud that maximizes performance and scales rapidly across multiple geographies on short notice.
• A partnership approach where we deploy agents and C-level executives to help maximize your ROI.
• The perfect blend of intelligent automation for scale and performance coupled with an irresistible culture comprised of people who love to delight your customers.
• Virtual and hybrid customer support options to connect with customers seamlessly, when and where they want.
• The ability to launch a customer support program quickly, even when you need thousands of agents ready to support your customers.
• A best-in-class workforce management team and supporting technology to create a centralized organization that can better serve your entire business.

iQor helps brands deliver the world’s most sought-after customer experiences. Interested in learning more about the iQor difference? If you’re ready to start a conversation with a customer experience expert, contact us to learn about how we can help you create more smiles.

Julia Kopyłowska is business intelligence analyst II at iQor. Connect with Julia on LinkedIn.

Irena Michalewicz is manager of Information Services at iQor. Connect with Irena on LinkedIn.

Monika Starczewska is director of Analytics at iQor. Connect with Monika on LinkedIn.

Joe Przybylowski is senior vice president of IT at iQor. Connect with Joe on LinkedIn.