January 12, 2018

Jiffy Lube: Identifying Key Revenue Drivers in Customer Comment Data

In-depth consumer understanding through text analytics.

Jiffy Lube: Identifying Key Revenue Drivers in Customer Comment Data
Tom H.C.

by Tom H.C.

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CHALLENGE

Like many customer-focused businesses, Jiffy Lube International uses various likert scale rating scale questions in its customer satisfaction tracking. In addition to satisfaction rating questions, Jiffy Lube also asks its customers to explain their reasons for giving the rating.
Unlike other text analytics software, the OdinText advanced analytics platform allows users to leverage not just text comments but any and all contextual structured ‘quantitative data as well, whether they are survey data such as (Purchase Intent, OSAT, NPS etc.) or actual behavior (return behavior, churn or sales).

Jiffy Lube deployed OdinText to identify key drivers in the comment data from more than 100,000 recent Jiffy Lube customers that had significant impact on the ratings those customers gave.

In addition to their annual customer satisfaction data, Jiffy Lube further integrated data from its CRM data base (including actual number of visits for each customer) as well as sales data (revenue by store).

That is when the shock came. While the structured likert scale survey metrics correlated highly with each other, there was no correlation to actual store visit behavior or sales! In other words, the analysis revealed no correlation between an individual’s rating (stated loyalty and satisfaction) and their “number of previous visits” (an actual measure of customer loyalty).

In addition, the relationship between mean ratings per Jiffy Lube store and store revenue across approximately 1600 locations was also investigated. Once again, analysis revealed absolutely no relationship between store rating and store revenue. Locations were also investigated. Once again, analysis revealed absolutely no relationship between store rating and store revenue.

SOLUTION

Using key drivers discovered by OdinText in the customer comment analysis in conjunction with ratings provided the link needed – a strong positive relationship with mean number of visits.

This finding suggested that while the customer satisfaction ratings alone may not be sufficient to predict actual customer visit behavior or sales, looking at the ratings in combination with text provides a meaningful context in which the ratings can be used to understand actual visits and sales.

OdinText revealed 13 key drivers (verbatim concepts) that significantly predict Jiffy Lube store revenue – and the extent to which they do so. For instance, stores in which just 1% more customers make comments related to “ease” generate approximately $14,000 more revenue than stores in which this verbatim concept is mentioned less frequently. Conversely, verbatim concepts that predictably decrease store revenue were also identified.

OUTCOME

Whereas your customer satisfaction rating alone may not be a predictor of repeat purchase or revenue, when used in combination with text analytics it can become a powerful tool for an in-depth understanding of customers’ intentions, perceptions, and behavior. Text analytics can increase the value of your customer satisfaction program as well.

“As a result of these findings we are in the process of rethinking many elements of our customer satisfaction program. The insights delivered really are actionable and management now routinely asks us to ‘OdinText’ various issues.”

– Amy Raihill, Insights Manager, Jiffy Lube International

 

Visit OdinText at www.odintext.com .

OdinText’s New Mixed Data AI Platform: http://odintext.com/predict-what-matters/

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case studycustomer satisfaction researchtext analytics

Disclaimer

The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.

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