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CX Analytics Through Goal Setting

September 6, 2022

The approach to CX analytics at Big Village begins with goal setting; placing realistic targets and expectations to mold around the needs of the business.

In setting fundamental groundwork based on controlled parameters and established goals/values, various approaches and methods can be utilized to provide value spanning from KPI metrics to understanding brand perception and customer experience. However, every approach to analytics comes with its own hurdles. Understanding the limits allows Big Village to assist in optimizing conclusions and driving home result-driven data with supportive and supplemental results like an interactive ROI simulator, or customer value segment profiles.

The most important piece in developing a plan for CX analytics begins with the foundation and setting appropriate goals conducive to feasibility. One important metric related to KPIs is percent increase in target specifications. What does it really mean to have a goal to increase a specific metric by X%? 

For example, your client’s Overall Satisfaction is 71.5%. The client suggests that they would like to see a 5% improvement in performance over the next year. As researchers, we know that this metric is driven by many different factors: brand perceptions, consumer touchpoints with the brand, as well as different segments’ interactions with the brand and CX experience. After analyzing the data, we realize that segment A is very satisfied with a 93% satisfaction and segment B is not with only 50% satisfaction. After considering the segmented groups’ results, it’s clear that segment A is delighted with the CX experience and segment B is not. Through a Key Driver Analysis, we know satisfaction is driven by Price and Quality and largely the performance on these metrics is well received for the brand. However, segment B is driving the Overall Satisfaction down.

Critical questions to address are: 

  1. Why are the ratings low for this group? What are the unmet needs of this segment?
  2. Does it matter?  This group is fairly small to the overall customer population – is there a return to address the unmet needs?

By fully understanding the data and the situational metrics early on, it becomes much easier to set the groundwork for goal setting that will align the analytics together smoothly. Your clients may get caught up in the fact that a larger portion of their customers (Segment A) are very satisfied, and we need to keep delighting them. However, with such high satisfaction, it can be very hard to further delight and improve on the CX experience for these customers and may result in missing the goal of a 5% increase in the next year.  Instead, when noticing that segment B is unsatisfied, deeper analysis and focus should be put on whether this is a large risk to the business and if so, what are the best actions to address the segment’s needs. Using methods like Customer Lifetime Value and Threshold analysis, realistic goals can be set, but give us the confidence needed in deciding influential groups for driving lift among the KPIs.

As mentioned above, a crucial parameter for goal setting comes from identifying the most valuable customers and leveraging current knowledge from the existing customer segments to set realistic, high-valued, and achievable goals. By first identifying the highest value customer segments, you can immediately ensure that all positive results are going to be worth the resources and efforts put into it. It’s then, from finding the holes among those groups, where the gap can be bridged by improving things like satisfied expectations, wants, and needs that may be currently undervalued.

In the example above, segment B has been identified to be your highest value customers. They are very loyal (your client’s brand has nearly 100% share of wallet) and are a high spend segment. Despite being a rather small proportion of your current customer base, these customers should be the highest focus when addressing CX and their larger needs. 

Honing in on the most important needs.

Honing in on the most important needs of the most valuable customers are crucial for resource management, minimizing the audiences to only those who will be most beneficial in terms of overall value. Being mindful of costs, time, and impact to loyalty are all things that aren’t specifically impacted by the % increases, but just as crucial for setting the right approach for CX analytics. 

With efficient targets set conducive to the environment and business needs, data-driven decisions are ready to be optimized, leveraging tactical data solutions. For starters, choosing effective KPIs drives the landscape. This allows clients to see impact on customer experience, performance metrics, purchase metrics, brand equities, and more. For example, by running a perception analysis, Big Village can easily identify which equities a specific brand is in control of, lacks, or is neutral towards. Using these data tests to see the perception of customers, allows teams to focus on areas most in need of improvement.

Piggybacking onto the powerful impact that customer perception has, there are multiple methods to understanding brand perceptions based on the specific needs at play. We could leverage tracking studies that set markers in the ground for a baseline feel of where the business stands. However, if we need to take a more granular look, we can also segment subgroups of specified target audiences defined by demographics, attitudes, or shopping behaviors, for instance. One subgroup can have entirely different perceptions of a brand than another and therefore it’s crucial to identify key groups of interest/value to your business and ensure a deep granular look is performed on these high value subsets. This opens the door to enhancing business needs that wouldn’t otherwise be picked up.

Most of the challenges that arise during this approach can be minimized by following the appropriate pre-planning steps. For example, setting goals on customer satisfaction without having a solid understanding of attainability. Some problems can be completely resolved in the early phases, though. For instance, syndicated data can be a great starting point in initial phases, but it often needs to be followed up with quantitative research to get a complete understanding of the relationships, drivers, and performance.

Overall, the hiccups that come along the way can mostly be smoothed out by:

  • Targeting the most valuable customers to understand their references and perceptions of the brand experience
  • Identifying and improving CX on essential touchpoints along the way
  • Resourceful and focused planning within the parameters identified from the analytics

Finally, after the foundational planning has been laid out and the approach has been run, we must layout the analysis in a clear, concise, and comprehensive manner to convey the results to the client. Some results can be seen from KPI metrics like CX ROI that show how much revenue increases from a one-point increase in the CX KPI. Another data-driven metric is the Key Driver Identification, which shows the touch points of the customer that had the strongest impact on their overall experience with a brand. There are many other useful tools that Big Village can use to bring the data home. For instance, a customer lifetime value assessment shows if the most loyal customers also are the most valuable, and the proper way to address these customers in the most critical areas. An interactive ROI simulator aids showing incremental performance associated with specific combinations of individual key drivers, and the relationship to overall revenue.

The CX analytics approach at Big Village has ample amounts of ways to help reach and achieve business goals through data-driven methods. The secret to this success all lies in the understanding of targets and their ability to be achieved within the given framework. With the proper structure, the approach taken with CX Analytics is greatly effective! 



Written by Jonah Robinson, Associate Analyst, Insights at Big Village.