Your customers share their feedback with you via surveys, support requests, chatbot interactions, social media engagement, and app store reviews. You want to find insights hidden in these rich datasets so you can improve your product. You'll be more effective at applying the right user or customer insight if you segment the data; that is, by identifying what types of insights come from which dataset.
For the purpose of surfacing insights and taking action on the findings, customer feedback generally falls into two broad categories:
Support requests - customers requests for immediate help when using the product.
Product feedback - feedback about users’ experience with a product, level of satisfaction, and ideas for improvement.
Below is a list of the most common types of feedback channels for each broad category.
A note on app store and online product reviews: we’ve added them to both categories because it’s commonly used by customers to both report immediate problems and provide deeper product feedback.
Analysis of support requests is most likely to reveal immediate problems that customers are having. As the frontline representatives of a company, customer support agents are responsible for responding to and resolving immediate problems. The desired outcome is to reduce friction between customers and the product. In other words, maintain happy customers.
From what we’ve seen, helpdesk data reveals problems or issues customers are having with a product, via answers to questions such as:
What do customers think about product x?
What do customers like about feature x?
What do users dislike about product line x?
What problems are customers having with order status?
What are the most common issues with shipping?
How do users feel about x feature?
But some problems are more difficult to identify and resolve. Sometimes customer feedback submitted via support channels point to larger trends but don’t necessarily provide sufficient insight for a product manager or customer experience team to come up with a solution.
That’s where product feedback comes in.
Net promoter score (NPS) and customer satisfaction (CSAT) surveys provide not only a numerical rating, but also ample opportunity for customers to submit their written feedback.
NPS survey analysis will reveal customers’ longer term feelings about your product while CSAT survey analysis typically surfaces feedback specific to a transaction or event.
Either way, customers are more likely to share their user experience and make feature requests in surveys than in day-to-day support channels. The desired outcome is to build products that meet customer needs in a better way, attract new customers, and drive business growth.
In our experience, surveys provide insights into how to solve problems surfaced via support channels, specifically by answering questions such as:
How can we improve product x?
How can we improve the sign up process?
Why did users sign up for product x?
What do users like about our product?
Why don’t customers purchase product x?
What integrations do users want next?
What features should we add?
Helpdesk tickets, live chat engagements, NPS surveys, CSAT, app store reviews, online product reviews, etc—these datasets all work in a complementary way. Insights from support requests lead naturally to asking questions—and getting answers—of product feedback. Such insights help product teams deploy product improvements faster and with greater confidence.
At Viable, we encourage our customers to analyze both types of data. We find companies that analyze multiple sources of qualitative feedback are able to create a more complete picture of how their customers experience their products.
If you’re a product manager, customer experience lead, marketer, sales executive, or other type of growth leader, we’d love to hear how you segment and use qualitative customer feedback. Send us a tweet or leave us a comment on LinkedIn.
Last Updated: 04/07/21
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