Can AI Replace Customer Interviews?

Spoiler: Not really, but it can give you a serious head start. See how!

Let’s be honest, understanding our customers is both vitally important and also incredibly difficult. This is particularly true if you are pre-launch, learning a new vertical, or simply don’t have as much customer data as you want. Could AI perhaps provide additional data and research to supplement what you do have?

That's what I set out to test this week, and I'm sharing two concrete use cases that actually worked.

Quick shout out to Michele Nieberding's LinkedIn post that inspired this experiment. Michele posts weekly AI prompts for product marketers, and this particular post got me thinking about new research tactics. Check her out!

The Challenge: Finding Actual Customer Insights

Sure, established B2B SaaS companies have tools like Gong for sales call recordings and dedicated customer success teams. But what about when you're launching into a new vertical? Or when you're a smaller company without those robust internal resources yet? Or your side project podcast about Taylor Swift gives you literally no useful insights into who your listeners are? (a universal experience, right?)

Even with all the right tools, speaking directly with customers (a.k.a. the gold standard) takes time. You need to identify prospects, schedule calls, and talk with enough people to spot meaningful patterns.

So I wondered… can AI maybe help me start generating insights in the meantime?

The Solution: Use AI to Analyze Massive Amounts of Data

Conveniently, this is a question I’ve been pondering both in my role at Interplay Learning and with the AP Taylor Swift podcast, so I had a couple of solutions I wanted to try. Essentially, I wanted to see how AI could help me scrape massive amounts of data for key insights. There are so many incredible, insight-rich resources out there that have an overwhelming amount of information, so I tried to see if AI could speed things up.

Experiment #1: Surfacing Insights from Reddit

In this post from Michele Nieberding, she suggested using AI to brainstorm content ideas based on key terms in specific subreddits. I love this idea because Reddit has an active user base and is a place where people are unfiltered (for better or worse), so you are seeing honest takes.

This was perfect for the podcast where we had almost no information to work of off. I had a bit of back and forth with Gemini on this one, so I’ll break down the steps by the prompts I used.

Prompt #1 - what are the top 10 taylor swift themed subreddits? Ranked by volume and frequency of posts/responses

This helped me focus on the most active communities rather than getting lost in dozens of options (turns out Taylor Swift has a large fan base? Who knew!).

Prompt #2 - In r/TaylorSwift and r/swiftlyneutral, what books/pieces of literature come up most often in conversation regarding Taylor's lyrics?

This prompt gave me insights into the most popular books that Swifties enjoy as well as what conversations are happening around them.

Prompt #3 - The people who are posting about The Great Gatsby, Rebecca, Robert Frost, and Emily Dickinson would be the ideal listener for the AP Taylor Swift Podcast. Based on the profiles of those people and the comments they make, help me put together an ICP outline for our ideal listener.

Please list the following:
1. Things that these individuals tend to be frustrated with in the discourse around Taylor Swift
2. Things that these individuals get excited about in the discourse around Taylor Swift
3.Other than reddit, where do these people probably spend their time on social media?
4.The top 3 "headlines" that AP Taylor Swift could use to market to these individuals

I wanted to focus in on the behavior of our truly ideal listeners, which is why I specifically mentioned a few of the books. That helped guide Gemini on how to narrow down its research and focus on the specifics that matter. Turns out “Swifties” is a pretty big bucket, so giving more guidance to Gemini was a good call.

Experiment #2: Surfacing Insights from Sales Calls

As a product marketer at Interplay Learning, I’ve had the opportunity recently to start expanding my expertise to new verticals, which meant I had a lot to learn (and fast). Gong felt like an untapped resource for me, but I definitely don’t have time to listen to dozens of calls a day.

To resolve this, I targeted a specific customer/prospect type, pulled up their call recordings, and copied/pasted the transcript into one long Google doc. Then I dropped it into Gemini with the following prompt.

Based solely on the information found in the attached document of sales call transcripts, please identify the following:
1. The top three problems that these prospects are facing in regards to their training processes.
2. The top three reasons why these prospects are excited about partnering with Interplay.
3. The top three reasons why these prospects seem hesitant or unlikely to move forward with Interplay.
Please also identify which calls would be the best use of my time to dig into more specifically as I am learning this vertical.

And what do you know? Gemini read through all 100+ pages and popped out those insights for me in minutes.

The Results: What Worked and What Didn’t

Both experiments felt like wins for getting from zero to one quickly. Like using AI for first drafts, this gave me a "quick and dirty" starting point for customer insights.

What worked?

I got access to key insights in minutes, not in the hours (or even days) it would have taken me to go through all of that data manually.

What didn’t work?

Some of the insights felt generic. Maybe that’s because I already had a general instinct on these audiences or AI was defaulting to covering the obvious as well as the insightful. Either way, I would never build messaging off any of these results without validation and editing from a human.

Conclusion

I feel like at some point I need to put together a rating system for these use cases, but for now I’ll just say that this is definitely one I recommend. While some of the results were generic, I had saved so much time going from zero to one that I had much more space to go from one to two. Plus now I knew which subreddits and Gong calls to focus on more for deeper insights.

AI won't replace talking to actual customers, but it can help you ask smarter questions when you do get on those calls. And when you're starting from zero, whether in a new vertical or with limited data, these techniques can give you a solid foundation to build on.

Bonus Prompts

As a little extra bonus too, here are a few other use cases/prompts I would consider using for either sales call transcripts or Reddit:

Based on the sales transcripts/In these subreddits, what are the top 5 frustrations [role] has around [problem your company solves]. Please surface specific quotes that help identify the problem and rank them on how prevalent they seem in the community.

Based on the sales transcripts/In these subreddits, what are the most discussed topics regarding [problem your company solves]. For each topic, identify why it seems to come up so much and the most common thoughts and ideas around each of them.

Based on the sales transcripts/In these subreddits, please create a list of potential pieces of content that the marketing team at [company name] should consider making. Please break down the content suggestions by the buyer’s journey and identify why that content would be relevant to this audience.

Any ideas I missed? Any way I could have approached this better? Let me know in the comments!