Find what users want- Leveraging AI in Product Management Discovery
Product teams need to process & reflect scaled user input
In every company, there’s a battle of who knows best what to develop next- executives, R&D, marketing, sales etc. Successful companies work hand-in-hand with users to innovate and find ways to solve critical problems they are willing to pay for. Users are central to the ideation and delivery phases. To me, the most important product management value is reflection of the users’ perspective in the product lifecycle.
With that said, there is one fundamental truth about the product management team: it does not scale with the growth of users or customers. Their job is to create scalable products and processes that do not necessitate growth of the product team. The mantra is- create great products and documentation that can support user growth.
This dynamic becomes somewhat challenging when a product company creates a vibrant community of users, who actively provide input and feedback (Congratulations, that’s great news! many companies wish they had a live community of users). The question becomes how to extract insight and action from a community of tens, hundreds, maybe thousands of users. Hint- AI.
Side note- About AI
I’ve been asked several times about my thoughts on AI, considering the proliferation of applications and the ease in which it can be applied to many fields.
I’m joining Prof G (Scott Gallaway) in thinking that AI can manipulate {large, diverse, dispersed} information and data into content. This content can aid humans in educating themselves about certain topics that, otherwise, would be hard to assemble into a consumable format. It can also aid humans in making better decisions, such as a doctor analyzing medical imagery to determine the best course of treatment. What AI cannot do, IMO, is be creative. It fully relies on previously created content to generate manipulations of that content, which is something that is complex for humans to accomplish in a scaled, real time and high-quality manner.
AI to summarize and process scales user input
One can see how product companies with access to users’ voice would apply AI to identify commonalities of themes, so that the product team can leverage those for backlog management, feature adjustment and roadmap prioritization.
ProductBoard AI (beta) enables product managers to manipulate users input into theme summary, feature specs, pain points etc. coming from all of the integrations supported such as Slack, Email, direct user input in the portal, Zendesk support tickets, web etc. This doesn’t only accelerate the product managers’ ability to sift through all the input and identify themes, but also author the feature(s) without missing key points. The interface also allows maintaining the volume of users discussing this feature as a prioritization element. These are early days, but one can imagine the efficiencies that come with that.
Aha! also started dabbling with AI, so far more focused on drafting and improving product communications with their AI writing assistant. No doubt they too will apply AI technology as means to manage scaled user input efficiently.
A few emerging vendors are looking at the same opportunity.
Orbit enables product managers to integrate their repository of insights, and from there auto-detect the themes, turn those into Opportunity-solution trees, Objectives, opportunities, solutions and roadmaps. Orbit also supports chat AI to answer questions such as “what are the pain
points our customers are facing?” (without sending 3 product managers frantically going back into user input and their notebooks), or, “which customers asked for feature X”.
Next enables product managers to upload user interviews, (transcribed through tools like Zoom and Gong, and video-recorded). It will automatically detect the main insights in the interview and even slice the video to point to the right moment when the user referred to the point highlighted.
It is essential for any product company to establish continuous dialog with their users. The alternative ensures missing the mark and not leveraging the investment. Leveraging AI to summarize user input and later point to specific users and details can make the product managers’ life easier, the roadmap relevant, and provide users to validate features as those get delivered.
Some of the tools above come from well established product-tooling vendors, integrated with user portals, strategy planning, roadmap prioritization and other aspects of a product manager day. Others come from emerging vendors, and therefore rely on integrations more.
