Cohort analysis

Analyzing cohorts with declarative data makes it possible to study the impact of experiences on customer lifetime value (LTV) and to analyze groups of users in the context of their past and future behavior. The segmentations shown below are an example of the use of YourCX's advanced tools in experience analysis.

Our innovative approach to experience analytics is based on a combination of two research directions - Customer Experience research and online analytics. Thus, we combine our proprietary tools related to online analytics (path analysis, conversion, technical data, etc.) with declarative context - consumer emotions and experiences. Adding to this experience in the field of research about consumer behavior (in sociological and marketing contexts), we offer our business partners a lot of extremely useful knowledge about their customers.

Purpose of visit vs. deferred purchase

Analyzing conversions over time against visit goals allows us to better understand user behavior. Using the example given, the highest percentage of repeat purchases in the following weeks is recorded for those who declare the purpose of the visit related to a purchase. Getting acquainted with an offer records a much lower conversion rate, but ranks second of all goals. Those who are least likely to purchase are those who are oriented toward a traditional purchase. When analyzing the goals of visits, a further step would be to see if they were completed and, if not, why not. The purchase itself, as you can see, is not a goal in itself for those oriented to buying in the offline channel, the experience associated with such a goal, however, is in no way less important.

Leaving the service vs. returns

An analysis of re-visits by reasons for leaving the site indicates the problems affecting the lack of return. The example given confirms that indeed the most likely to re-visit the site are those who declare a desire to return or a need to reflect. The lowest probability of a repeat visit is noted among those focused on offline shopping. Re-visits are also negatively impacted by the lack of search sizes and products - these can be targeted with appropriate remarketing campaigns in the next step, for example.

Impact of problems on conversion

Analyzing conversions in the context of negative experiences allows us to estimate the magnitude of their impact on CX. As can be seen above, each problem affects deferred purchases to a decisive degree. Only those who did not encounter problems returning in subsequent weeks made purchases. In the right chart, you can see that problems have little impact on repeat visits to the site. The highest deferred conversion (purchases/returns) can be seen for no problems, while the lowest for erroneous search results.

The impact of experience on shopping

Analysis of past and future actions shows the impact of experience on brand trust. Those who now believe there is something to improve were more likely to purchase before completing the survey than those who see nothing to improve. After the site visit in which the survey was filled out, a sequential decrease in purchase frequency is seen. Those who see nothing to improve buy more often. A negative experience during the visit thus has a major impact on conversion.

Assessment of information quality

Quantitative evaluations of the help sections, combined with information about contacting the BOK, provide a full overview. As many as 68.9% of respondents found the topic they were looking for. The highest share of this response is recorded for those who visited the FAQ subpage, and the lowest for the product information page. Those who did not find the topic are 3 times more likely to contact the BOK via Livechat in the following weeks than those who found the topic.

Contacting the Customer Service vs. retention

Analysis of the Customer Service experience in the context of subsequent behavior shows the real impact of CX on actions. As can be seen from the analysis above, the resolution of an issue by a consultant does not affect the frequency of visits, but has an impact on purchase intent. The positive impact of a consultant's resolution of an issue can be seen over the next 4 weeks.

The impact of offline on online

YourCX allows you to study experiences across channels, including their interaction. In the example given, you can see the aggregate percentage of people returning and making a purchase again. People whose package arrived too early or too late are less likely (33% less) to return to the service and make a purchase. Delivery according to a set date has the most positive effect on retention.

NPS (willingness to recommend) indicator vs. conversion

Analysis of the resulting NPS index cohorts (Promoters and Critics) shows the impact of CX on purchases. As you can see, the willingness to recommend the service turns out to be closely related to the willingness to make repeat purchases. One can see a more than twofold difference in repeat purchases between Critics and Promoters. The next step in the analysis should be to examine the factors influencing being a Critic and their impact on repeat purchases.

These are just examples of analyses that can be made using YourCX tools. However, the conclusions presented cannot be directly applied to all consumers. Much depends on the industry, the competitive environment, the overall image of the brand and, of course, the quality of service or maintenance. We therefore approach each project individually, tailoring the segmentation to the client's needs, including its business goals.

YourCX tools allow you to analyze consumer needs at all brand touch points and with full context, experience and emotion!