Most SaaS products answer “what's the ROI” with a big, confident, unsourced number — “save $10,000 a year!” — pasted next to a stock photo of someone celebrating at a laptop. This post is our actual attempt at figuring out how much app market research is worth, in three pieces, labeled by how sure we actually are of each one. If a number here doesn't have a reason behind it, that's a bug, not a feature — tell us and we'll fix it.
- Time saved doing the research yourself: roughly $60–$900 per report.
- Subscription avoided vs. an enterprise ASO tool: $0–$700+/month, but only if you'd have actually paid for one.
- Avoiding a wrong build or a mis-scoped client project: potentially $6,000–$45,000+, and the least provable number on this page.
- We don't collapse these into one headline figure, and you shouldn't trust anyone who does.
The time you don't spend doing app market research yourself
A thorough manual pass — checking the store listing, reading the positioning, guessing at keywords, sizing the market, checking Google's opinion of the app, pulling trend data, and actually reading through a few dozen reviews — realistically takes an experienced person 2 to 6 hours per app studied. Value that time at $30–50/hour for a solo indie developer, or $75–150/hour for an agency professional's billable time, and you land at roughly $60 to $900 saved per report, with a typical case closer to $150–300.
This is the number we'd defend most confidently on this page — it's just time not spent, not a claim about what you'll do with the time you got back.
All eight modules run in parallel from a single search — the same ground a manual pass covers, compressed into seconds instead of hours.
The market research subscription you might not need
Enterprise ASO and market-intelligence tools commonly run $150–$800+ a month for a usable tier. If you'd have genuinely paid for one of those instead, the delta versus Appifacts' Free or Starter plan is real savings, potentially $80–$730+ a month.
But be honest with yourself about the counterfactual: plenty of indie developers were never going to subscribe to an enterprise tool in the first place. If that's you, this line item is worth exactly $0 — and a vendor telling you otherwise is counting savings against a purchase you were never going to make.
The cost of the mistake you might not make
This is the number that actually matters, and the one we trust least. A typical scrappy MVP build runs 200–600 hours. Valued at just $30–75/hour, that's $6,000–$45,000 of effort avoided if a report correctly talks you out of building the wrong thing — or a similar or larger figure for an agency that avoids scoping a client project on a false premise.
The catch: this value only exists if two things are both true — the verdict has to actually be right, and you have to have been about to build the wrong thing anyway without it. Neither is something a tool can prove about itself after the fact. Anyone who puts a specific dollar figure on this without asking real users what they would have done otherwise is guessing, us included.
The Build Recommendations module is the one place this shows up directly — a verdict, a difficulty rating, and the gaps and evidence behind it, so the call is at least grounded in real signal instead of a hunch. Grounded isn't the same as guaranteed, which is exactly why this module is labeled estimated, not measured.
Why there's no single ROI number for market research
We could add up the high end of all three ranges and put “$46,000 ROI” on the homepage. It would be technically defensible in the same way a horoscope is technically defensible — vague enough that it's never quite wrong. We'd rather you see the actual reasoning and disagree with a piece of it than accept a single number you can't take apart.
It's the same principle behind every module in an Appifacts report: real data and AI estimates are labeled differently on purpose, because collapsing them into one confident-looking number is exactly how a market-size estimate or a difficulty score stops being useful and starts being marketing.