Stop Arguing About Roadmap Priority: Discover the Right Product Problems to Solve Using Emotion Detection
Product teams use lots of data to make decisions on launching new products and experiences, and managing them throughout their life cycle. These decisions range from tactical to strategic and require insights into customer needs whether they are consumer or enterprise. A standard process for discovering customer needs is the combination of qualitative user research and quantitative verification.
For example, a product manager may interview people to uncover pain points and hypothesize what they want. With this direction, the hypothesis can then be tested quantitatively through surveys or coding feedback in public reviews or customer service tickets. However, finding the right hypothesis relies heavily on Product Manager intuition in recognizing problems in customer feedback.
Three key problems exist in this type of discovery:
This process is highly labor intensive with an uncertainty of discovering compelling problems with enough frequency and sample size significance.
Not all feedback is useful.
Uncovering a level of intensity of pain points across all the feedback is manual and therefore subjective.
Typical Feedback on Amazon
We believe that understanding what makes people emotional is the key to uncovering the most compelling pain points that lead to amazing new products. If discovery of emotion in feedback can be paired with relevancy and quantitative discipline, product teams can uncover why people buy and create the next big thing.
Summary:
In short, we believe that product teams expend huge efforts to understand the people that buy their products. There are countless internal cycles burned negotiating and arguing over priority and impact. Often either the loudest (or highest paid) voice wins, and even the most advanced teams still rely on vague and lagging indicators to build their case. While these efforts were necessary in the past, product teams can find the most important problems if they use emotion contained within feedback. By pairing emotion with quantitative methods now available with NLP AI, product teams can now bridge the gap between past qualitative and quantitative user research practices to build better products, dramatically faster.
For more information about improving product and R&D success, read our whitepaper: The Future of Product Development here.
[by Michael Choi]