Measure Customer Effort to Drive Loyalty and Reduce Churn
Why Customer Effort Matters
Research from Gartner reveals that reducing customer effort is one of the most reliable predictors of customer loyalty, surpassing even traditional satisfaction metrics like Net Promoter Score (NPS). The result is the Gartner Customer Effort Score (CES), a metric that quantifies how easy or difficult it is for a customer to resolve an issue.
Studies show that customers who experience high effort in resolving their problems are 96% more likely to become disloyal, leading to churn and negative word-of-mouth. In contrast, reducing customer effort can increase repurchase intent by up to 94%. In short, the less effort your customers put in, the more likely they will stay loyal, recommend your brand, and return for future purchases.
High effort leads to disloyalty and churn
Low effort boosts repurchase intent and loyalty
Filling in the Gaps with AI-Powered Predictions
Our AI models predict what a customer’s effort score would have been— without the need for a survey. This approach allows businesses to scale their understanding of customer effort across all interactions, not just those from a small sample of survey respondents. By analyzing real-time interaction data from every call or chat, we generate a reliable and comprehensive view of customer effort and incorporate this data into our comprehensive continuous improvement process.
AI is only as good as the data it learns from. That’s why we use an AI / Human-in-the-loop approach to create and tune our predictive models. Our team manually scores customer interactions for effort, creating a robust dataset that enhances the accuracy and effectiveness of our AI models. By continually training and calibrating the models with real-world data, we ensure our predictions reflect true customer experiences, giving your team the confidence to make informed decisions. If your business does choose to implement the CES survey, we also can calibrate models using their responses.
From Containment to Engagement
Building on the company’s vision to make every interaction effortless, Interactions created an automated, AI-powered, systematic way to measure customer effort on every customer contact. We believe that every customer interaction matters. This new capability furthers the ability to empower brands to evolve from an outdated contact-center model that prioritizes internal efficiency metrics over customer experience. The Interactions solution helps brands bring focus to their customers and transform from a containment model that forces customers through layers of automation and prioritizes cost savings over customer effort.
Simplified CX and Improved Loyalty
Undoubtedly, the Customer Effort Score is the best metric for contact centers because it measures the level of effort customers spend to resolve issues. It provides clear insights into improving the customer experience and reducing churns. According to Gartner research, “Reducing customer effort has a proven relationship to higher-level organizational goals, such as maintaining customer loyalty and minimizing service costs. CX leaders can actively manage what customers do and feel during each interaction in order to reduce the perception of effort.” Taking inspiration from the robustness of Gartner’s CES methodology, Interactions AI-powered CES goes beyond traditional customer satisfaction surveys. It leverages the full power of AI to analyze millions of patterns and metrics to predict the effort from a customer’s perspective as if they had completed a survey.
Continuous Improvement
We leverage the CES models to predict the effort a customer would have provided in a post-interaction survey, even if no survey was taken. Our AI-driven approach analyzes a wide range of interaction data— from call transcripts to chat logs— delivering real-time insights into how easy or challenging each customer interaction has been. However, we take it even further with our continuous improvement services as a team of experts analyzes the CES and other attributes to ensure your customers are getting a low effort experience while maximizing automation.
End-to-End Analytics
Although it’s important to measure the IVA or chatbot experience it does not provide the complete picture since many customers pass through the IVA and end up interacting directly with an agent. Interactions provides complete end-to-end analytics so your business can see the contact center experience through the eyes of your customer, from the IVA all the way through to an agent. The end-to-end analytics is critical for not only measuring the overall customer effort, but also for increasing the IVA’s automation rate and improving agent efficiency.
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