How Analytics as a Service Unlocks Insights to Reduce Attrition, Boost Retention, and Elevate CX
Ongoing advances in big data and artificial intelligence (AI) provide countless insights and opportunities to improve the customer experience. One such capability is the use of machine learning to predict employee attrition. By collecting and analyzing data to identify employees at risk of attrition, data scientists can identify opportunities to intervene and reduce employee churn. These insights provided through analytics as a service can empower operations and human resources teams to develop strategies that raise employee engagement and retain key talent, ultimately improving business outcomes and creating a more rewarding employee and customer experience.
In this blog post, we’ll dive into the data sources and processes that make this possible along with the insights and outcomes they produce. But before we do so, let’s revisit what analytics as a service is and why it’s so valuable.
What Is Analytics as a Service?
Data-driven innovation happens when data scientists are integrated into the business culture and processes. Through analytics as a service, data scientists offer guidance and expertise to improve business outcomes that can measurably support our client’s customer support programs. A digital transformation strategy that includes analytics as a service provides access to massive amounts of data which the data scientists and operations teams dissect in order to harness its potential.
As a managed services provider of customer engagement and technology-enabled business process outsourcing (BPO) solutions, iQor offers analytics as a service as part of our comprehensive CX solutions to some of the world’s top brands. Through iQor’s vast digital ecosystem, we harness advances in AI-powered technology along with the expertise of our data scientists and operations teams to perform data analytics that yields measurable outcomes to improve employee and customer experiences at scale.
Data-based digital technology solutions have the power to drive meaningful results specific to the operating environment. iQor’s data scientists interpret the data housed in our private CX cloud to translate technical research and statistics into actionable insights that inform operational decisions and improve business outcomes. The 10-steps of analytics as a service typically start small and gradually expand to incorporate the entire customer service program. One of the many areas in which they provide insight is employee attrition and retention.
The Process of Predicting Attrition
The ability to predict and prevent employee attrition presents opportunities for success in customer service. Retaining qualified, experienced, and high-performing customer-care agents and supervisors can make a world of difference in the quality and consistency of service provided to the end customer.
Data scientists begin by introducing new data sources to the machine learning model to identify agents at risk of leaving the company. In order to do so, they follow a formal process for identifying and validating potential data sources, gathering the data, and cleansing it. This enables them to generate new variables out of the data sources and then run variable-importance testing that compares the predictive power of every potential variable. If the predictive power exceeds the threshold, it’s included in the machine learning model to yield insights into attrition.
This is an ongoing process by which data scientists continue to explore additional data sources to add to the model in order to make it as accurate as possible for the entire company population.
Expanding the Data to Power Predictions
In order for predictive analytics to accurately forecast attrition, the projections must originate from more than one data source. This helps ensure a balanced view of each employee’s experience and accounts for a lack of data points for certain employees.
For example, iQor gathers data from weekly Mood-o-Meter surveys that employees have the option of completing. The survey gauges their job satisfaction and generates a net happiness score that provides helpful insights into their experiences. However, if certain agents never respond to the optional survey it cannot serve as a data source for deciphering whether those agents are at risk of attrition.
To offset this type of feedback-driven source, data scientists cast a wide net and include additional data sources based on each agent’s environment to help assess how they interact with iQor. These environmental data sources include how much time the agent spends logged in to work, participating in trainings, and taking a break. They also include the agent’s total pay, bonus history, and the complexity of the customer support program on which they work. Coaching interactions serve as another source for deriving environmental data. When an agent participates in the iQor Coaching ecosystem, data scientists are able to harvest this critical data from internal systems versus needing to seek a direct response.
Together, these data sources provide a more comprehensive view of the agent experience to determine if they are at risk of churning.
Analytics as a Service Yields Up to 2X Retention Rate for At-Risk Agents
Analytics as a service yields powerful results in reducing employee attrition.
iQor’s Machine Learning algorithm correctly identifies agents at the highest risk of attrition on a weekly basis. This is evidenced by the difference in attrition rates between the control group (a 5% sample of at-risk agents who do not receive an intervention) and the experimental group (those receiving an intervention). The experimental group retention rate is consistently up to 2 times higher than the control group retention rate.
By improving retention, these data-based interventions have increased the overall tenure makeup of the enterprise, ultimately leading to enhanced performance. Indeed, when deployed enterprise-wide, these attrition prevention methods can have a positive impact on employee engagement and improve business outcomes on a large scale. This benefits the client’s customer support program while also instilling confidence in agents and supervisors, which can lead to improved recruiting efforts. Furthermore, the iterative nature of the process allows for ongoing opportunities to add data sources and improve the model to produce increasingly valuable results.
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 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 50 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.
Andrew Reilly is a data scientist on the AI & Data Science Team at iQor.