The pricing lesson that cost me 3 months of wrong customers
Charged £5/month for the first three months of Genie 007 (genie007.com).
Thought it was smart. Low barrier to entry, easy to try, get users in the door. The kind of thinking that sounds reasonable until you look at what actually happens.
Here's what happened:
The £5 customers churned at 3x the rate of everything else. Tried it for a week, didn't form the habit, left without much thought. The unit economics looked fine on paper. In practice I was spending time on support and onboarding for customers who were never going to stick around.
The customers who came in during a brief period where I tested £19/month? Almost all still here.
This wasn't a coincidence. Cheap pricing attracts people who don't value the problem yet. They haven't committed to solving it. The lower the price, the easier it is to not bother figuring out how to use something properly.
The fix seems counterintuitive: raise the price.
Not because you're greedy. Because higher prices attract people who've already decided the problem needs solving. And those people do the work to get value out of the tool.
Here's a useful reframe: you're not pricing the product. You're selecting the customer.
£5 selects people who want to "try it."
£19 selects people who want to "fix the problem."
The person who wants to fix the problem does the onboarding. Reaches out when they're stuck. Sticks around long enough to get value. Becomes the testimonial.
The person who wants to "try it" doesn't.
Three things I changed after figuring this out:
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Removed the monthly option entirely for new customers. Annual only. Forces commitment, selects for intent, improves cash flow.
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Ran the pricing page conversation backward: instead of showing the price and then what you get, show the problem first and let the price be the last thing they see.
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Added an optional onboarding call for annual customers who want it. Long-term retention from those users is significantly higher than unassisted.
None of this is a huge revelation. But it took me 3 months of actual churn data to see it clearly.
If you're getting users who try it and leave, your pricing might be doing the wrong selection job. Worth checking before you blame the product.
Did going up on price hurt your acquisition more than it helped retention? Curious what people have found on that tradeoff.
The "you're selecting the customer, not pricing the product" reframe is one of those things that seems obvious in retrospect but takes real churn data to internalise. I've seen the same pattern from the other direction — I'm building a code audit tool aimed at non-technical founders, and the temptation is to price it low because "they don't know what code quality costs yet." But that logic is exactly what you're describing: low price attracts people who haven't committed to the problem yet.
The annual-only move is interesting. Did you see any signal on whether it was the commitment period or the onboarding call doing the real retention work? I ask because those two changes landed at roughly the same time, and I'd expect the onboarding call to be the stronger predictor for a tool like yours where the habit-formation gap is probably the main churn driver.
One thing I'm wrestling with: for a product where the buyer isn't the user (e.g. a founder buying a code audit they won't read themselves), the selection dynamic might work differently. The price signals "this is serious" to the buyer, but the retention depends on whether the output is actionable enough that they keep coming back. Still figuring out whether that breaks your model or just extends it.
The "you're selecting the customer, not pricing the product" reframe is one of those things that seems obvious in retrospect but takes real churn data to internalise. I've seen the same pattern from the other direction — I'm building a code audit tool aimed at non-technical founders, and the temptation is to price it low because "they don't know what code quality costs yet." But that logic is exactly what you're describing: low price attracts people who haven't committed to the problem yet.
The annual-only move is interesting. Did you see any signal on whether it was the commitment period or the onboarding call doing the real retention work? I ask because those two changes landed at roughly the same time, and I'd expect the onboarding call to be the stronger predictor for a tool like yours where the habit-formation gap is probably the main churn driver.
One thing I'm wrestling with: for a product where the buyer isn't the user (e.g. a founder buying a code audit they won't read themselves), the selection dynamic might work differently. The price signals "this is serious" to the buyer, but the retention depends on whether the output is actionable enough that they keep coming back. Still figuring out whether that breaks your model or just extends it.