1.7 Mining Customer Language
Your customers are already writing your best copy. You’re just not reading it.
The words your customers use to describe their pain are almost always better than the words you’d invent. They’re specific, emotional, and they resonate with other people who have the same problem because those people would use the exact same words. Your job isn’t to be clever. Your job is to find those words and repeat them back.
Ben Boz built Tech Lockdown to $15,000 MRR with 1,300 customers selling to people who described themselves as “addicted to their smartphones” with “compulsive internet habits.” Those aren’t Ben’s words. That’s how his customers described themselves in Reddit threads and App Store reviews before he ever wrote a line of copy. When your landing page uses the exact phrase someone used in a 2 AM forum post about their problem, they don’t feel sold to. They feel seen.
The places where customers confess their pain honestly are Reddit, Twitter/X, G2, App Store reviews, and YouTube comments. Not your own customer interviews, where people are polite. The anonymous places where people vent.
Reddit is the most valuable. Search for the problem your product solves, not the solution. If you’re building something for IT admins like Thomas did with Packager, you’re not searching for “application packaging software.” You’re searching for “Intune packaging taking forever” or “why does packaging applications take so long.” Thomas discovered the core pain himself when he realized packaging a single application could take an hour. That exact frustration lives in subreddits like r/sysadmin right now, word for word, from hundreds of people who have never heard of his product.
G2 and App Store reviews are gold because people are reviewing competitors. They’re telling you exactly what the existing solutions get wrong. Ericos saw that Shopify app developers “lacked great user experience and moved pretty slow.” That’s competitor review language. That became his positioning. He built Kaching Bundles to $4.5M ARR partly by solving what frustrated customers were already writing about other tools.
The Language Mining Template
Here’s the process. For each source, run it like this: search location plus search string plus what to capture.
Reddit plus “[problem keyword] + frustrated/hate/takes forever/manual” plus copy the exact complaint verbatim, especially any phrase they repeat more than once across different threads.
G2 or Capterra plus “[competitor name] reviews” plus look for the “what do you wish it did differently” sections and copy the one-star and three-star reviews word for word.
App Store plus your competitor’s app name plus sort by lowest rating and pull phrases describing friction, not just complaints about bugs.
Twitter/X plus “[problem keyword] + anyone else” or “[problem keyword] + ugh” plus copy the posts with high engagement, because engagement means others feel the same way.
What you’re capturing isn’t themes. You’re capturing exact phrases. “I waste 30 minutes on mockups before I even start the real work” is copy. “Mockup creation is time-consuming” is nothing.
Once you have 20 to 30 of these phrases, your landing page hero headline writes itself. Your cold email opener writes itself. Nick at BlockToPin identified that his customers described Pinterest pin creation as “tedious” and happening “over and over again.” Two words. That’s a subject line, a headline, and an opening hook all at once.
Put those words in your cold DMs verbatim. “I saw people talking about how mockup creation in Photoshop takes 30 to 40 minutes for 50 images” hits completely differently than “I built a tool to speed up your workflow.”
Today, pick one competitor. Go find their G2 or App Store reviews. Read every review under four stars. Copy 10 phrases into a doc. That doc is worth more than anything you’d write yourself.