By Sean Clarke, Founder of Pacific IQ and EcomIQ

I just wrapped a Q&A with Jennifer Courtney, our head of strategy at Pacific IQ, and one thing she said has been living rent-free in my head ever since.

Negative reviewers are your most engaged customers. Not your five-star fans. Your one-stars.

Here's why that matters, and why most DTC operators are looking at their customer data completely backwards.

Why five-star reviews are a trap

Most founders I talk to, myself included at times, have a bad habit. We read our five-star reviews to feel good about what we've built. It's a dopamine hit. Sales are up, the reviews are glowing, we're crushing it.

Except the five-stars don't tell you anything useful. They tell you the product is working for the people it was obviously designed for. Fine. That's table stakes.

The one-stars are where the real business is.

Negative reviewers aren’t haters. They’re engaged.

Jen made this point on our last call and it's worth repeating.

Someone who takes the time to leave a one-star review isn't indifferent. They're fired up. They cared enough about your product to buy it, had an experience that frustrated them, and then cared enough to sit down and tell you about it.

That's not a hater. That's a customer with energy.

I've seen brands where the customer service team is incentivized to convert one-star reviewers into VIPs. They call them. They say, “Hey, I’m the founder (even if they’re not, the customer doesn’t know), I saw your review, I want to make this right.” They send a replacement, offer a refund, whatever it takes.

The conversion rate from brand-hater to brand-advocate is absurd when you put in the effort. Way better than acquiring a new customer from cold. And it makes sense. You already paid to acquire them once. They're already in your CRM. You're just fixing the experience, not starting from zero.

Where the gold actually is

If you want to find what's broken in your business, and where the biggest unlocks are, you need to look at four places:

1. Your one and two-star reviews (Judge.me, Junip, Yotpo, Okendo, Google, Trustpilot, Amazon, anywhere)

2. Your customer service tickets, specifically the repeat questons and complaints

3. Reddit threads about your brand or your category

4. Social media comments and DMs

Every single one of these is free data. And most brands I work with don't touch any of it systematically. They read a bad review when it lands, get defensive, move on. That's not a system. That's a reaction.

Competitor one-stars are a positioning roadmap

Here's a second angle Jen raised that I love.

If you want to differentiate, go read your competitors' one-star reviews.

If you're in skincare and your biggest competitor has 400 negative reviews complaining about shipping times, packaging damage, or customer service response times, that's a gift. That's exactly where you win. You don't beat them on their strengths. You win at the things they can't or won't fix because they're too big, or moving too fast, or too spread across too many products.

That's not copycat strategy. That's precision positioning.

The 15-minute AI workflow

Right. Here's the actual process. Block 15 minutes. Do this today.

Step 1: Export your one-star reviews.

Most review platforms (Judge.me, Junip, Yotpo, Okendo) let you export to CSV in about two clicks. Pull the last 12 months of one and two-star reviews. If you don't have a review platform, pull what you can from Amazon, Google, Trustpilot, Reddit, wherever customers leave public feedback on your brand.

Step 2: Drop the CSV into AI.

Upload it. Prompt it with something like: “Here are my one and two-star reviews from the last 12 months. Identify the top 5 recurring themes, rank them by frequency, and pull 2-3 representative quotes for each theme.”

You'll have a ranked issue list in about 30 seconds.

Step 3: Cross-reference with Reddit.

Next prompt: “Search Reddit for recent discussions about [your brand name] and [your product category]. Summarize what people are saying, positive and negative, and flag anything that overlaps with the themes from the reviews.”

Step 4: Consolidate.

Next prompt: “Combine the review themes and the Reddit findings into a single prioritized list of the top 5 issues affecting my customers, ranked by how often they show up across both sources.”

Step 5: Get the fix list.

This is the step most people skip, and it's the most important one. Give Ai context about your business and ask for the plan.

Prompt: “Here’s my brand [one sentence]. Here’s my product [two sentences]. Here’s my website [URL]. Given the top 5 issues above, what are the 3 to 5 highest-leverage fixes I can implement this week? For each one, tell me the expected impact and the difficulty to ship.”

That's it. Fifteen minutes. You now have a prioritized action list built on actual customer behaviour, not your gut, not your last board meeting, and not whatever the loudest person in your inbox said this morning.

Do this this week

None of this is theoretical. I'm telling you the exact prompt chain I've used and that I recommend to operators we coach.

Every brand I've shown this to finds at least one thing they can ship this week that moves the needle. Sometimes it's a product page FAQ. Sometimes it's a shipping policy rewrite. Sometimes it's a packaging change, or a customer service script update, or a product page photo.

Doesn't matter what it is. The point is it's a change grounded in what your customers are actually telling you, not what you assume is the problem.

If you haven't touched your one-star reviews in the last 90 days, you're leaving money on the table. Probably a lot of it.

Go do it.

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