Competitor Keyword Research for Apps: Find the Phrases They Own
How to mine competitor titles, subtitles, and descriptions for keyword roots, separate newcomer phrases from giant-owned terms, and turn the gaps into a listing plan.
**Competitor keyword research** is the fastest way to learn what a category calls itself. You do not need a private database. Competitor titles, subtitles, and descriptions are public, and the phrases they repeat are a strong signal of what the market searches for.
The useful output is not a list of every word a competitor uses. It is a map of which phrases are shared by the category, which are owned by giants, and which are open enough for a smaller app to take.
Key takeaways
- Pick three to five direct competitors, not just the category leaders.
- Repeated two-to-four-word phrases are stronger roots than one-off words.
- Separate phrases owned by giants from phrases where the results are weak.
- Mine reviews and screenshot captions, not only metadata.
- Use competitor phrases as seeds, then validate with store autocomplete.
Choose the right competitors
A competitor is an app that appears for the phrases you want, not necessarily the biggest app in the category. Pick three to five: one or two leaders for category language, two or three mid-sized apps for winnable phrasing, and maybe one adjacent app that serves the same job differently.
If you are pre-launch, search the phrases you think describe your idea and use the results as the competitor set. If the results are all unrelated, the phrase is probably too broad or the product positioning is unclear.
Mine the four visible surfaces
| Surface | What to extract | Why |
|---|---|---|
| Title | Primary phrase and brand structure | Shows what the app wants to be found for |
| Subtitle / short description | Second phrase and benefit | Shows the supporting keyword bet |
| Description | Repeated phrases and section headings | Reveals category vocabulary and use cases |
| Screenshots | Caption text | Often contains plain-language benefits missing from metadata |
| Reviews | How users describe the job | Reveals real phrasing and unmet needs |
Copy the phrases into a table with the competitor name and source. When the same phrase appears across three competitors, it is a category root. When it appears in one, it may be brand language.
Build a phrase frequency list
Tokenise the titles and subtitles into two-to-four-word sequences. Count how many competitors use each sequence. Sort by count. This simple frequency list is often more useful than a giant keyword database because it is grounded in the actual category.
- A phrase used by 3+ competitors: category language, strong root.
- A phrase used by 1 competitor with a strong brand: may be their positioning, not the market's.
- A phrase used in reviews but not metadata: a possible gap.
- A phrase used by everyone in the title: likely crowded and hard to win.
Separate giant-owned phrases from open ones
A phrase can be category language and still be a bad target. If the top results are all apps with millions of installs and complete listings, a new app will struggle. NewASO groups competitor phrases into newcomer keywords and phrases giants own to make this distinction visible.
The open phrases are often more specific: a use case, a constraint, a user type, or a workflow the leaders treat as secondary. Those are the seeds for your long-tail research.
Validate before you write
- Type each root into the target store and capture autocomplete.
- Search the root and note the top results' strength and relevance.
- Keep phrases where the app can deliver the promise and the results leave room.
- Score the shortlist with a consistent method.
- Map each phrase to a field before writing a single line of copy.
What competitor research cannot tell you
It cannot tell you a competitor's installs, revenue, conversion rate, or exact keyword volume. It also cannot tell you whether a phrase is profitable. Those are private or modelled numbers. What it can tell you is what the category says, which phrases are crowded, and where the language is thin.
NewASO reads similar apps, niche search results, and up to five URLs you provide, then extracts repeated phrases and turns them into roots. From there, the same project expands and scores them. See app keyword research for the next step, or the features page for the mining inputs.
Frequently asked questions
How many competitors should I analyze?
Three to five is enough for a first pass. Include at least one mid-sized app so the list is not entirely dominated by category giants.
Can I use competitor brand names as keywords?
No. It risks trademark and review problems, and it is not a durable strategy. Use the category language and the job to be done instead.
What if I cannot find direct competitors?
Look for apps that solve the same job in a different way, or search the phrases your potential users would type. If the results are unrelated, your positioning or phrase choice may be too broad.