Why Did My Customer Disappear?

Quick Insights Analytics Helps Clarify Why Customers Do or Do Not Achieve Desired Outcomes

For many large businesses, it’s difficult to have a clear-cut understanding of why every customer is contacting you, and why many of them do not achieve their desired outcome. For those that understand the necessity and inherent value of a positive customer experience, identifying the differences between customers who complete their journeys and those who do not, in any number of scenarios, represents a critical capability.

Luckily, quick insights analytics—as found in NICE’s Scenario Analyzer, which helps customer experience personnel quantify customer journey dynamics—helps such businesses gain those critical insights from multichannel customer journeys.

To demonstrate, one of our clients analyzed a scenario in which there were 46,250 initial customer contacts. 15% of callers were dropping off before the second stage, and another 20% or so were dropping off before reaching a completed process via self-service means. Ultimately, this meant only two out of three callers were getting what they came for. Quick insights analytics helped them to learn that “a potentially confusing IVR menu” was a considerable factor driving customers to drop off.

Quick insights analytics lets users pinpoint a specific stage (node) of their customer interactions, and access visualizations of:

  • All available customer attributes, sorted by their predictive power*.
  • The most common attributes values for those interactions that reached this stage of the process.
  • Those values most common among customers who dropped off.
     

*To illustrate this concept of “predictive power,” and its relevance to your CX program, consider the role of statistics in prognosticating the outcome of sports games. If it were a baseball game, one might suggest any number of KPIs is the most reliable indicator of success: run differential (the team’s season total of runs scored vs. runs allowed), the team’s on-base percentage, slugging percentage (batting average weighted for extra-base hits), batting average with runners in scoring position, pitching staff ERA, etc. In the context of your operations, this technology helps remove the guesswork from the equation, demonstrating which attributes (statistics) are most important for optimizing any given scenario (game).

The benefits of quick insights analytics are substantial:

  • One click to insights. Compare drop-offs relative to your target with ease.
  • Understand customer behavior. Isolate various customer characteristics, and the most important attributes and values for predicting completion or drop-offs.
  • Flexible scenario analysis. Dig deep into any aspect of a complex business scenario, including multichannel scenarios.
  • Agile and better-informed decision-making. Take action quickly to improve customer pain points.
     

As a supplement to IVR optimization and customer journey optimization, quick insights analytics gives organizations a quick, clear view of the disparities between those customers who are completing their desired tasks (and are presumably pleased) and those who are giving up or resorting to other courses of action (and whose customer experiences could likely be improved), and what factors are contributing to that gap. It helps you personalize the customer experience more effectively, prevent their frustrations, eliminate roadblocks in the multichannel journey, and deliver outcomes that yield customer loyalty.

To learn more about quick insights analytics and how it might benefit your customer experience strategy,  drop us a line today, or visit us next week at Forrester’s CXSF 2016 event.

 

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