customer-experience Case Study

Understanding True Brand Position with Competitive Customer Experience (CCX)

The Situation

Woman pays for something with a credit card

The Study

Women happily walk down the street carrying shopping bags

Approach + Solution

A drivers analysis was conducted to see which aspects (products, touchpoints, or brand perceptions) most impact the likelihood to recommend a brand.

We used a combination of brand attributes plus open-end responses to find this out.

For this study, we created a model to autocode the open-ended data. A drivers analysis was then conducted across open-end and scaled data to see which factors had the biggest influence on whether a brand was recommended or not. By using regression analysis and looking at the data holistically, we were able to see how different aspects affect recommendation – is brand a stronger predictor, or do transactional experiences matter more?


We discovered the importance of Brand and Touchpoint Experiences differ by category.

We found that Brand & Touchpoint Experiences are both very important, even in a more functionally driven category such as Auto Insurance. In a category with more limited customer touchpoints, like OTT, Brand impression drives levels of Recommendation. Across both categories, the products themselves (in the case of Auto Insurance, the policy and in the case of the OTT providers, the shows offered and the user interface) played a much smaller role in predicting the likelihood to Recommend. It was the clear difference in Brand impression and individual touchpoints to drive the likelihood to Recommend that highlighted the importance of understanding customer expectations and experiences cross-category.

The strongest relationships can be found when incorporating both brand and open-end responses regarding specific touchpoints on whether a customer will recommend a brand to others or not. Contact us today to find out what drives your customers to recommend your brand.


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Final Word

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