How is AI impacting market research? Customers don’t understand what AI can do, so what questions are you asking them?

I want to challenge the statement "Customers don't understand what AI can do." Sure, some don't, but many in the automation space do and in fact, we are learning quite a lot from the initial use cases we see happening across our accounts. Our CS team is always feeding us new ideas so we can integrate them into our product roadmap and capture them in our messaging.

There is certainly a lot of opportunity being left on the table as the bounds of AI are relatively limitless (and the limits keep getting pushed out!) In those cases, instead of asking for the answer, we ask for the approach to getting to the answer. For example, instead of asking "What are you using generative AI for?" we ask "What are the problems you are trying to solve?" Here is a set of sample questions to include in your customer research.

General Research Questions

• What are the problems you are trying to solve today?

• What are the biggest barriers to solving those problems?

• What approaches have you tried - why have they failed/succeeded?

• How do you view our platform/product as being able to solve your problems or meet your needs?

• Where do we fall short?

• Where do we exceed expectations?

• What functionality or solutions would you love to see built into our product in the near future?

Once you have a baseline without any assumptions, you can follow up with more specifics on generative AI usage.

Generative AI Usage Questions

• How are you using generative AI to solve your problems today? (can you get specific on use cases?)

• How is it helping/what are the outcomes?

• What are the limitations you are seeing?

• What innovation or training would help overcome the limitations?

• How is it being adopted? What are the barriers to adoption?

• What is the sentiment around the use of this tech?

• How do you see it helping you do your job better? Your team? Your company?

• How much are you spending on the tech? How much do you wish you could spend? Who manages this?

The list could go on, but my point is to never dive right into the tech. Always start with the problem/opportunity and better understand how to solve it for your customer.

AI is going to change market research in some big ways. It will enhance data analysis, allowing PMMs to process vast amounts of information from diverse sources and uncover deeper insights. AI-powered tools will offer continuous, real-time market intelligence and more automated reporting and analytics, so teams can make quicker and more informed decisions.

However, one thing I’ve run into in my own market research focused on AI products is that customers still don’t fully understand what AI can do. Here are some ways to address that:

• Ask about current challenges: Dig into time-consuming tasks and inefficiencies, for example: "What are the most tedious parts of your job?"

• Focus on outcomes: Frame discussions around business goals and pain points rather than the specifics of the AI technology.

• Use analogies: Compare AI capabilities to familiar concepts to make them more relatable. For example, AI that can automatically parse through customer service requests is like having an extra agent on hand to do triage.

• Let customers get hands-on: Allow customers to experiment with AI tools firsthand to grasp their potential, maybe via a targeted pilot. The key is to support customers as they’re trying these tools out and to provide regular check-ins to understand their experience.