Kayla is one of the best in the Voice of the Customer game and she nails it in this post. Say it with us: EVERY interaction is valuable feedback. 👏👏👏 If you don't know where to start when it comes to figuring out how to listen to customers and translate that into better products check out the Notion Voice of Customer template crafted by Kayla: https://lnkd.in/e2NC-w_K We can't wait for the rest of the series, Kayla!
Recently I’ve had the joy of nerding out in several conversations about Voice of the Customer. Shockingly, listening to our customers en masse is still an emerging field, despite it’s potential to shape better products and services. In these recent conversations I’ve found myself describing my approach to VoC work as four sequential components: collecting data, analyzing data, doing something with your data, and closing the loop. There’s so much to dive into in each step, so get ready for a series! Part 1: Collecting data Every interaction with a user is a feature request. Sometimes these are obvious (“I want you to build X, Y, and Z”), other times, they’re less explicit (“Where’s the button for that?” “How did this person edit my page?” “I want my money back”), but every question and every request is feedback on the products we have built, and the policies and pricing packages we’re implementing around them. When we think of every interaction as a feature request, we are met with a plethora of sources. Every tweet, app store review, sales inquiry, Reddit post, question to a CSM, question to a chatbot, and (my bread and butter) every support ticket, is a sneak peak into what customers want when they use our products. So… what do we do with it all? First, take a breath. If you work with customers, start with just your team; if you don’t work directly with customers, pick 1-2 teams to work with. In either case, begin to collect data in a way that you will be able to analyze. As you collect data, try to do so in a single place that can be shared across teams. This may begin as a Notion database, Google sheet, or Asana project, and may scale to a tool like Enterpret or Monterey AI. Keeping everything in a centralized place will help avoid the need to switch tools later (spoiler: you’re probably going to switch tools later). Tag your insights in a way that would make sense to your customers. This way, tags will also make sense to your customer-facing teams, including vendors (you’ll be able to translate for engineers and PMs later). Take early steps to make sure that the same tags, or categories of tags (likely features), are being used across sources. Automate where you can. The more automated the process, the more likely it will be to get done (especially when your teams are busy). If you are using macros for your email or chat support, you can likely automate the application of tags, just set the expectation with your agents that they double check, especially if you have a complex product. What key steps and tricks have you found most helpful in collecting user feedback? Comment to let me know! Next step: Understanding the quality of your feedback. #VoiceOfTheCustomer #VoC #CustomerFeedback #CustomerExperience #CustomerInsights #DataDriven #QuantitativeData #QualitativeData #CustomerSuccess #UserFeedback