THE ASO PROFESSIONAL FIELD GUIDE / ASO keyword research process
LESS KEYWORD SOUP. MORE INTENT.
Keyword research is a way to understand what people want and whether your app can deliver it. A list becomes useful only when it helps you make a decision.
ASO keyword research turns product capabilities and audience language into prioritised search-intent groups. The deliverable is a decision map: what fits, what needs validation, what is excluded and how the selected intent should shape the listing.
Your deliverable: Build a defensible keyword map from product evidence, search intent and prioritisation.
A related business topic is not automatically a product fit.
Illustrative intent groups. No search volume or difficulty data is implied.
01
Define the market and product boundaries.
Specify the store, language and country you are researching. List the app’s strongest use cases and the audiences it does not serve. This prevents broad category terms from dominating simply because they appear popular.
For a fictional receipt app, capturing expenses, creating invoices and managing payroll are different jobs. If the product only handles receipts, the other concepts are not automatically good targets.
02
Build a candidate set from several inputs.
Start with product language, questions from users, review themes and relevant alternatives. Search suggestions and research tools can add candidate terms. Record where an idea came from so it can be reviewed later rather than inheriting authority from a spreadsheet row.
Do not interpret a suggestion as a verified search count. Public discovery cues are useful inputs, but they do not reveal every part of the store’s demand or ranking systems.
03
Group by the job behind the words.
Put terms together when they imply a similar user need. Keep adjacent needs separate where the product or message would differ. A group about scanning receipts may need different evidence from a group about submitting an expense report.
The intent map is illustrative, not measured keyword demand. It shows how one product can support a primary use case while leaving other topics outside the brief.
04
Evaluate relevance before estimates.
Ask whether the product satisfies the implied need, whether the listing can explain that fit and whether the audience is commercially appropriate. Only then weigh demand estimates, competitive context and existing visibility. Label estimates as estimates.
Avoid treating scores from different tools as interchangeable measurements. Their definitions and scales can differ. Explain why the chosen group deserves priority instead of allowing the largest number to make the decision.
05
Map priorities into a readable listing.
The handoff should connect each priority group to a message and the relevant store fields. It should also identify exclusions, unresolved questions and assumptions. Read the proposed copy as a person, not just as a collection of terms.
Implementation belongs in the iOS workflow or the Google Play workflow. A shared positioning decision does not mean copying the same field structure between stores.
06
Refresh when the context warrants it.
Revisit the map when the product, audience, market or evidence changes. Keep earlier versions so a later reviewer can understand why a term was selected or removed. Constantly changing language without a reason makes interpretation harder.
SlipKeep is a fictional receipt organiser for self-employed people. It scans receipts and exports records, but it does not calculate tax or run payroll. A research tool returns attractive ideas for all three jobs. The team is tempted to include every business-related term because the category feels close enough.
How to reason through it
Begin with the supported workflow and collect the language customers use to describe it. Group candidates by the job behind the query, then annotate product fit, locale, source and uncertainty. Research estimates can help compare candidates within a consistent context; they cannot make an unsupported intent relevant. Preserve rejected terms with reasons so the next stakeholder does not reintroduce them without new evidence.
The next practical move
Create clusters for receipt scanning, receipt storage and expense records. Hold broader expense-management terms for product verification. Reject payroll and tax-filing promises unless the app genuinely supports them. Draft metadata from the selected clusters, then review whether the visible listing explains the same job. A technically neat keyword map is incomplete if the creative tells a different story.
Swipe horizontally to compare the decision map →
Receipt scanning is not the same as accounting: illustrative decision map
Decision area
What to inspect
What it means for the work
Receipt scanner
Directly supported capture workflow
Investigate as a core cluster
Expense manager
May imply approval or reimbursement features
Verify intent and product fit
Payroll software
Product does not perform the job
Exclude and record the reason
The trap to avoid
Do not deliver a spreadsheet of phrases without decisions. The team needs to know which terms are relevant, which require validation, which were rejected and how the selected clusters should influence copy. Export size is not research quality.
When the situation gets more complicated
Use versioned research snapshots. A later reviewer should be able to reconstruct why a term was selected even if tool estimates change. When results are disappointing, review the original intent and product-fit assumptions before swapping in another high-volume phrase. Search behaviour, discoverability and listing choice are different questions; a ranking report cannot answer all three.
FROM METHOD TO DELIVERABLE
A populated keyword map you can reproduce
The entries below continue the fictional SlipKeep example. They are editorial candidates, not observed search demand. No search-volume or difficulty scores have been invented. Each row states what the researcher should verify before handing it to a writer.
Swipe horizontally to read the complete example →
Fictional candidate map. Product assumptions are illustrative; demand is not measured.
Candidate / intent
Product evidence and uncertainty
Disposition and handoff
Receipt scanner / capture a purchase record
Capture workflow exists; verify the audience’s local terminology
Core candidate; connect copy to a real capture screen
Receipt organiser / retrieve stored receipts
Storage and retrieval exist; demand remains unmeasured
Research candidate; inspect search context and user language
Expense report / prepare a submission
Export exists, but approval and reimbursement do not
Hold; clarify the expected workflow before writing
Tax filing / submit a tax return
App does not perform filing
Exclude; retain reason in the research record
Payroll / calculate and pay staff
App does not perform payroll
Exclude regardless of apparent popularity
Collect evidence in an order that reduces waste
Start with a product walkthrough and a short list of supported jobs. Next collect customer language from available interviews, support themes or reviews, noting the source and date. Use search observations and tools to expand the candidate set after establishing those boundaries. This reduces the chance of spending hours scoring phrases for a workflow the app does not offer.
Resolve disagreement without averaging incompatible scores
If sources disagree, check market, date, spelling, scale and methodology before comparing their estimates. Keep the original values and sources in separate columns. Do not average a popularity index with a different tool’s difficulty score. A candidate with uncertain demand may still deserve investigation, but the brief should say exactly which uncertainty remains.
What the writer should receive
Deliver the priority intent group, the customer job, approved product evidence, appropriate store-field destinations, exclusions and unresolved questions. Include a sample message direction rather than forcing the writer to reverse-engineer the research. For receipt capture, a direction might explain capturing and organising receipts; it should not promise a completed tax return. Check the final draft against this map before publication.
Two keyword tools disagree about the demand for “receipt organiser.” Which estimate should you put in the brief?
Reveal the reasoning
Record both sources, dates, markets and scales rather than averaging incompatible scores. Use the disagreement as uncertainty. Inspect relevance and surrounding search context, then choose a defensible priority without pretending the estimates are exact store counts.
Your working brief
Use your own app for this exercise. Fill in the six fields below and attach the evidence behind each answer. If you cannot complete a field, write the missing question and the person who can resolve it. Do not replace unknowns with optimistic assumptions.
Candidate phrase and locale
Underlying job or intent
Product support and screen evidence
Source, collection date and estimate definition
Cluster and priority rationale
Metadata destination and review condition
For each field, distinguish an observation from an interpretation. Add the date and source where available, then identify the decision that follows. A colleague should be able to trace your recommendation back to the evidence without needing you to explain the entire project again.
Map selected iOS candidates into the metadata set after checking current field guidance.
The worked example is an original editorial framework. Its fictional app, decisions and scenarios are not an industry dataset or a claim of measured uplift.
Tools can help expand and compare candidates, but they do not replace product knowledge or relevance checks. Start with a well-defined research question.
Should competitor brand terms be copied?
No. Do not assume a competitor’s brand belongs in your metadata. Relevance, accuracy and the store’s current policies must guide the decision.
How many terms should the final list contain?
Enough to support the agreed decisions. A larger export is not inherently a better research outcome.
Compare audiences, 100 keyword candidates, real screenshots, worked metadata, Apple Ads structure and creative tests across the broader fitness market.
Compare portion controls, photo review, barcode proof, daily budgets and neutral progress language across 100 keyword ideas and five real screenshot sets.
Compare 100 keyword ideas, eight competitors, five real screenshot sets, bells, interval modes, background behavior and a complete acquisition strategy.
Compare 100 keyword ideas, eight cross-store competitors, five real screenshot sets, safety boundaries, worked metadata and an intent-led acquisition strategy.
Compare 100 keyword ideas, eight workplace-wellbeing competitors, five real screenshot sets, employer access, privacy boundaries, worked metadata and Apple Ads structure.
Compare 100 keyword candidates, eight cross-store competitors, five real screenshot sets, medical and data boundaries, worked metadata and Apple Ads structure.
Compare phone, watch, ring, audio and alarm intent across 100 keyword candidates, eight competitors, five real screenshot sets and a complete acquisition strategy.
Compare 100 keyword candidates, eight competitors, 20 real screenshot panels and practical ways to explain schedules, logged doses, stock and family profiles.
A cycle journal and a menopause report answer different searches.
Compare 100 keyword candidates, eight competitors, 20 real screenshot panels and worked strategies for period records, pregnancy and menopause support.
Compare 100 keyword candidates, eight competitors, 20 real screenshot panels and worked strategies for service availability, visit cost, clinician choice and follow-up.
Compare therapy, peer listening, AI conversation and self-guided tools through 100 keyword candidates, eight apps, 20 real screenshot panels and practical copy tests.
A budget, a transfer and a tax return need different stories.
Explore seven finance subcategories through 100 keyword candidates, eight verified apps, 20 real screenshot panels and worked creative and acquisition strategies.
