I’ve worked with hundreds of companies to combine myriad analytical techniques with meaningful strategy and practical tactics. There are dozens of analytical techniques worth knowing, but there are 3 simple ones that every XM professional should know for making simpler and more effective decisions.


Overview of Three XM Analytical Techniques

Analytics are not a buzzword; they really do work. But only when you match the best analytical tool to the problem you’re trying to solve. Here are things to consider to select the best technique for some of the common challenges XM practitioners face.

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Driver Analysis Simplifies Where to Pay the Most Attention

Driver analysis aides in understanding where to put resources and in what order of priority in order to induce the outcome you seek.

Overall experience (represented by your KPI) is influenced by experience levers (represented by other x- and o-data variables you collect). If we’ve done a good job linking our experience management metrics to financial outcomes, changing the performance of experience levers produces a predictable ROI. Driver analysis clarifies where to focus XM efforts for the best return because it:

  1. Assigns Priority. You can easily see which parts of your experience are more critical than others and stack rank them for order of address.
  2. Maintains Relativity. The weights are scalar; a weight 2x that of another is 2x more effective at explaining variance in the outcome.
  3. Acts Simply. Regression-based drivers automatically remove variables that are highly correlated, keeping only the strongest among them. The result is you can confidently focus on 1 thing instead of 10!

With a blueprint of where to focus efforts and a predictable ROI, driver analysis enables leaders to guide change with confidence.


Factor Analysis Distills Program Complexity into Powerful Themes

Factor analysis converts lots of metrics into fewer, managerially-relevant ideas and workstreams.

The myriad experience and behavior metrics we collect can be aggregated into representative themes; these themes can then be used to conceive, communicate, and manage our experiences more effectively. Themes developed through factor analysis enable:

  1. Message Simplification. No complicated message ever wins hearts, minds, or attention. If we can’t explain data simply, we don’t know our data well enough.
  2. Metric Simplification. In cases where certain metrics load similarly on a factor and are highly correlated, this is a chance to reduce the length of surveys.
  3. Analysis Simplification. Factor analysis can be coupled with driver analysis, i.e. running analysis against factors instead of unique metrics.

Factor analysis forces teams to communicate in broader themes while maintaining visibility to critical metrics. Mature XM organizations almost unanimously lead with rhetoric and execute in specifics. This analysis connects them.


Cluster Analysis Enables Scaling of XM Activities

Cluster analysis enables the scaling of service- and product-related efforts by parsing employee, customer, and prospect populations.

Classifying individuals – whether customers, prospects, employees – into similar groups based on some identifiable characteristics helps us personalize experiences easily. Cluster analysis provides:

  1. Deeper Understanding. This analysis leverages both x- and o-data so you can use everything you know about a customer to effectively understand that customer.
  2. Easier Management. Many firms manage customer and prospect segments separately. Improved clustering also improves market sizing and segment management.
  3. Better Opportunities. With a cleaner understanding of a product or service target, firms using cluster analysis design better products and service routines more effectively.

Cluster analysis is a way of reimagining your customer and prospect base through an experiential lens. Using it will almost certainly reveal a different way of thinking about how to compete on experiences uniquely for the customers you have and the ones you want.


Bottom Line: Driver, Factor, and Cluster analysis enable XM Leaders to invest in efforts with the highest ROI, keep the organization focused on the most important outcomes, and deliver personalized experiences effectively.


Luke Williams is an XM Catalyst with the Qualtrics XM Institute.