How to find a gap in the app market: read the 1-star reviews for the assumption the leader lives on

The short answer

The pages that rank for this query are a Reddit thread, a 2019 blog post and general business guides. They tell you to talk to users and look at competitors. None counts anything. This one does.

Why the gap matters more now

Cedlom, a creator, posted a short video (a sponsored ChatGPT partner post) on building a shared habit tracker and an interactive waitlist with no coding experience. The takeaway for anyone with an app idea is plain: building is cheap and getting cheaper.

That moves the hard part. The founder in the top Google result for this query, a Reddit post in r/AppIdeas, says the same thing from the other side: with vibe coding, “everyone and their mum can build an app,” and every idea seems to be taken by a company that can outspend them. The first reply is the useful one.

“Look at negative reviews on apps that already exist.”r/AppIdeas

Another commenter reframed the problem as the number of “uniquely problematic experiences” growing, not ideas running out. Both are right. The rest of this page shows how to do it with numbers instead of hunches. (If you would rather buy an app that already has users, see how to buy a SaaS business. Once yours ships, see when to ask for App Store reviews.)

What is a hidden assumption?

Designer Tim Gabe makes the cleanest version of this idea in his video The Secret Behind Apps Big Players Can’t Copy. Every category runs on a belief about the user that nobody says out loud, and the leader usually built its business on it. Meeting apps assumed you wanted to browse profiles first. Language apps leaned on quick tap games. Health trackers assumed serious tracking meant buying a ring or band. In his telling, the companies that won built the opposite.

The reason it works is not cleverness. The leader cannot copy the opposite without hurting the product that pays its bills. Gabe’s homework is simple: write down what the big apps in your category all assume, and circle the one their business depends on.

That is a good exercise. It has one weak spot. Most people do it from their own head, so they circle the assumption they personally dislike. Reviews let you circle the one thousands of users dislike.

Why 1-2 star reviews show it

A 1-star review is written by someone who paid for, or at least installed, the app and cared enough to complain. It names the exact thing that broke the deal: the paywall, the ads, the missing feature, the crash. People who are happy rarely explain why. People who are annoyed do.

Reviews also come from both stores. Of the 7,700+ apps in our data, about 3,600+ are on the Apple App Store and about 4,100+ on Google Play. A complaint that shows up on both is harder to dismiss as a platform quirk.

Where users push back, by category

We took 12 broad categories (60 apps each, 58 to 60 analyzed) and counted two things. First, the share of apps whose AI analysis found a paywall or an ad complaint. Second, the share of 1-2 star reviews whose text mentions subscriptions, paywalls, premium or pricing (money) or ads.

Three patterns stand out. Subscription categories sit at the top. News is the only category where ads, not subscriptions, lead. And shopping and food delivery barely complain about money at all. Each pattern is a different kind of gap, or no gap.

Gap 1: the core action is behind a subscription

In meditation, fitness, photo editing, language learning and dating combined, 1,073 of 3,798 1-2 star reviews (28.3%) mention money. In shopping and food delivery it is 135 of 1,811 (7.5%). Between 73% and 88% of the analyzed apps in the first group draw paywall complaints.

The hidden assumption is that the core action sits behind a subscription and renewals are automatic. Users say so in plain terms:

“No free functionality at all (you cannot even save), and no option to buy outright.”App Store review, photo editing app, 2 stars

“I am not fond of apps that automatically renew even if you only used them once or twice.”App Store review, meditation app, 1 star

“Predatory auto renew.”App Store review, language learning app, 1 star

Why a leader cannot copy the opposite: its revenue model runs on recurring subscriptions. A pay-once photo editor or a meditation app that renews only on a manual yes would shrink the revenue of anyone who switched. A small team does not carry that cost.

What the data cannot say is that users would pay once. A complaint is demand for a different deal, not proof of a price. Check it with the pre-sell step below, and size the revenue with our free App Store revenue calculator.

Gap 2: ads pay for the free tier

News is different. 63% of the 59 analyzed news apps draw ad complaints, and 207 of 1,229 low-star news reviews (16.8%) mention ads. The next highest category, music streaming, is 9.5%.

The assumption here is that readers accept ads, in the page and over the page, in exchange for free content. The most upvoted ad complaint in our news sample has 855 thumbs up:

“Still too forcing ads on us.”App Store review, news app, 1 star, 855 thumbs up

Publishers cannot easily give this up because the ads are the business. An ad-light or paid reader that curates a narrow beat works because the leader’s reader apps are built to hold ads, not readers. The real constraint is distribution: you need a niche audience you can reach, which is why the step list below starts with picking a category you can reach directly.

Where the gap is not

Shopping and food delivery show the opposite. Only 7% of analyzed shopping apps and 18% of food delivery apps draw paywall complaints. The pain is elsewhere:

“The worst customer service ever! I tried to contact the customer care center for order cancellation.”App Store review, shopping app, 1 star, 147 thumbs up

That is a service and logistics problem. A solo developer cannot fix delivery. Seeing this early saves months: if the complaints in a category are about operations, a pricing-model flip is not your wedge. This is the same logic as a hidden assumption, applied in reverse.

For a wider view of what users complain about across categories, see our state of mobile app pain points and the app ideas ranked by complaints.

How to find the gap, step by step

You can do this by hand for one category. It takes a day or two for 20 apps.

1. Pick one category. Choose a category you can reach directly, such as one profession, hobby or workflow. Broad categories are where leaders outspend you.
2. List what every leader assumes. Write down the pricing model, the ad model, the hardware or data they require and the effort they ask of the user. This is the hidden assumption list.
3. Collect 1-2 star reviews from both stores. Pull the lowest-rated reviews for the top 20 to 60 apps from the Apple App Store and Google Play. One store alone skews the picture.
4. Sort complaints by type. Group them into money, ads, missing features, UX and technical problems. Count each group per app and per category.
5. Circle the assumption the leader earns from. If users attack the subscription, the ads or the hardware, the leader's revenue sits behind that complaint. That is your gap.
6. Check it is not just one app. Look for the same complaint across at least 30 apps. One angry app is a story. Thirty is a category.
7. Pre-sell before you build. Reach 10 people who wrote those reviews or sit in the same communities and ask them to commit to your opposite.

Two notes from the Reddit threads Google ranks for this topic. One commenter in r/AppIdeas put it as “chase problems, not ideas.” In r/AppStoreOptimization, a thread on how founders find ideas, the repeated advice is to start with your own pain point and then check it generalizes to a wider group. Reviews are the check.

For manual methods, see our help guide on how to analyze app store reviews, and the guide to SaaS ideas from negative reviews.

Doing it for 60 apps: App Store Pipelines

Reading reviews for one app is easy. Doing it for 60 apps across two stores is where people stop. That collection and sorting is what App Store Pipelines (BETA, Pro) automates, at /apps-research.

• Create a pipeline at /apps-research/new: up to 10 keywords, with an AI keyword generator, the stores you want (Apple App Store, Google Play or both) and a star-rating filter. Set it to 1 and 2 stars.
• Read each run in tabs: Pain Points (each with root cause and solution), Missing Features, UX Issues, Technical Problems, Monetization, Competitors, Quick Wins and Long-Term.
• Monetization splits into Paywall Friction, Pricing Complaints, Ad Experience Issues and Value Perception Gaps, which are the four views used in the table above.
• Check demand with the free App Store revenue calculator linked in the header.

Across the 7,700+ apps in our data, about 66% have at least one monetization complaint and about 49% have a pricing complaint. That is the reason to start with the Monetization tab: it is where the hidden assumption usually sits. You can also browse the data directly in the App Store database. Compare review tools in best app store review analysis tools.

ChatGPT or Claude are good for summarizing a batch of reviews you paste in. They do not collect the reviews for you, so the 60-app view still needs a pipeline.

What this cannot tell you

• Complaints are not willingness to pay. A pay-once app still has to prove users buy.
• Review samples are small per app. Our reviews are collected by keyword with a star filter, so the 12-category cut is almost entirely low-star by design. It shows what unhappy users say, not how many users are unhappy.
• Regex, not judgment. Money and ad shares count review text matching a term list. A review that says “premium” about something else is counted.
• Category by keyword. Apps are in a category because they surfaced for that search keyword. Top results skew toward large, established apps.
• AI-extracted fields. Paywall and ad complaint shares per app come from GPT analysis of that app’s sampled reviews.
• Distribution is not in this data. A gap you cannot reach customers for is not a gap.

Methodology

All queries ran read-only against the BigIdeasDB App Store database on October 11, 2026: 136,000+ reviews and 7,700+ apps collected from the Apple App Store and Google Play. For the category cut, we used 12 broad search keywords with 58 to 60 analyzed apps each. Low-star means 1 or 2 stars. Review shares count the low-star reviews whose text matches the term lists above. App shares count apps whose AI analysis has at least one item in the paywall friction or ad experience field.

Video claims about companies are Tim Gabe’s and are not verified by us. Reddit quotes are from public threads that Google ranks for the query, anonymized.

Data sources and limitations

Frequently asked questions