“Consumer Trust Is Evolving in the Digital Age.”
That’s the headline from this recent article on eMarketer. It makes sense, right? New channels emerge. Consumers find them more or less trustworthy than the old channels. The consumers’ relationships with those old channels continue to evolve, and thus the perceived trustworthiness of those channels changes.
Perhaps unsurprisingly, the perceived trustworthiness of specific channels varies by generation. The article points to a May 2016 survey by Salesforce that shows a 16 point difference in the percentage of millenials and baby boomers who rate online reviews as their most trusted source of product information. (If you don’t want to guess who places more trust in online reviews, you can see the results of the survey here.)
Having been involved in many sentiment and satisfaction projects (particularly around our Customer Satisfaction Index Analytic Solution), this got me thinking. Typically, we start by helping customers join data from multiple channels to understand how customers interact with their companies across those channels. This enables us to build analyses that show how these channels affect satisfaction. We use techniques like general linear modeling, principal component analysis, and collaborative filtering to explore how single- and multi-channel events or sequences of events are associated with positive or negative satisfaction or sentiment.
Adding a scoring impact to a rule in the Customer Satisfaction Index Guided Analytics Interface.
Now, what if we performed those same analyses, but first segmented customers on various factors such as age? It would be interesting to see how the impacts of events in certain channels varied and whether the results lined up similar to Salesforce found in their survey.
It’s often important to take a “crawl, walk, run” approach to analytic projects. For example, in the case of the Customer Satisfaction Index solution, we recommend that you start with a few rules that you know matter, and then apply more analytic techniques to more events with better segmentation over time. But there is certainly plenty of opportunity to expand on such an analysis. Send me an email at email@example.com if you’re interested in how our team can help you better understand how all your customer segments trust and interact with all the channels with which they engage.
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