How to Conduct Customer Research and Competitor SWOT Analysis with AI

Adam McQueen

The product marketing community has been consistently told to ‘do more with less’ this year.

Cue the clichéd eyeroll…

Which is why we tagged in Jess Petrella, Director of Product Marketing at Unbounce and queen of AI in product marketing.

Jess joined Klue to lead a tactical workshop for the community on using AI to speed up two of the most time-consuming PMM tasks: customer research and competitor SWOT analysis.

We’ve boiled this session down to some of the biggest highlights, but if you want to get a whole lot smarter and more efficient in your role, I highly recommend tuning in to the full workshop below 👇

(Psst, looking to learn and connect with other PMMs and competitive intelligence professionals? The Compete Network has you covered. Check out our latest shows, events, and job openings here.)

1. Leveraging AI for an efficient customer interview process

“AI can help you fast track a lot of what I call busy work. Writing multiple emails that are required to invite customers to your interviews and writing your interview scripts.”

One of Jess’ favourite things to do is to minimize ‘busy work’. And there are a whole lot of repeatable tasks that can be streamlined with AI when taking on customer interviews.

She showed off a few of the workflows she’s using with tools like Notion AI to quickly generate customer interview invitations, reminder emails, thank-you emails, and interview scripts. 

This automation saves significant time, reducing busy work and allowing product marketers to focus on the actual interviews… you know the fun strategic work where product marketers shine. 

“We get to the heart of what we really want to do, which is talk to our customers, communicate with them, and learn from them,” said Jess.

(AI is new around here. So we wanted to learn from our Compete community on how they’re working with AI in competitive intelligence today and their predictions for the future. Check out what they had to say in our AI in Competitive Intelligence Report)

2. Summarizing lengthy interview transcripts

“I’m able to bring insights into my reporting without having to do the tedious piece.”

So you’ve conducted 10 customer interviews and had some insightful conversations. Great!

Now, how do you sift through thousands of words of transcripts to find trends and the good stuff? 

If you’re into diving through haystacks looking for needles, then you’re in for a time. But I’m guessing most of you would rather get to the more strategic work.

That’s why Jess shared some of the prompts and workflows she uses post-interview to distill long transcripts into concise summaries that highlight key customer insights. 

She themed prompts and learning objectives into categories — such as customer description, pain points, product likes/dislikes, and reasons for choosing the product — to organize and categorize the findings quickly.

Over at Klue, we’ve been working on tackling this exact problem for product marketers running win-loss interviews with Klue Win-Loss.

Learn how to summarize hundreds of win-loss interviews into important trends in seconds with Klue Win-Loss

3. Know the risks of using ChatGPT for competitor SWOT analysis

“I would share a slight caution to not overshare on your own business information because AI reads that and learns from it and can use it anywhere else.”

If you’re in competitive intelligence, you’ve likely tossed your competitor’s name into ChatGPT and asked for their strengths and weaknesses. Then you’ve asked for it to deliver results in a competitor SWOT analysis.

But Jess explained taking those results as gospel is a major risk. 

First, the data that ChatGPT scrapes aren’t up-to-date, with some versions ending in 2022. Plus, the results provided also have a high chance of not being fully accurate given ChatGPT’s reliance on only scraping public information.

Now, if you’re strapped and want to do a high-level SWOT analysis with ChatGPT, one critical prompt is to ask it to provide the URL sources that it refers to when coming up with answers.

This sourcing allows you to then go in and verify the outputs it provides.

However, to get in-depth SWOT analysis answers from ChatGPT it requires meaningful inputs… like those customer or win-loss interviews you conducted earlier! Proprietary data like win-loss, call transcripts, and internal CRM data is the trove of golden competitive insights to start working with AI.

Now… this is also where things get dicey when working with an open LLM. The moment you start sharing a churn call into ChatGPT, you may as well hand over your documents to your competitors.

(In fact, many community members shared during the session that their businesses have restricted access to open LLMs for this exact reason.)

It’s why one in three competitive intelligence teams mentioned legal and privacy concerns being a major concern when working with AI in our latest report. 

At Klue, one of the ways we’re supporting our customers to safely identify their competitor’s strengths and weaknesses is with an AI-generated SWOT analysis of competitors’ online reviews.

Learn more about working with AI in competitive intelligence

Let’s acknowledge a harsh truth.

Product marketers and competitive intelligence teams have to look for ways to increase productivity in their roles. We’re being asked to do more with less.

At Klue, we believe that understanding how to work with AI is the answer to unlocking this productivity.

We’ve got plenty coming in 2024, but if you want to get a look at some of the ways we’re 10X’ing your competitive intelligence productivity, check out some of the ways Klue AI will help you do exactly that.

And if you want to connect and learn from others who are working with AI — like Jess — then check out all of the events and on-demand content in the Compete Network community.

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