iOS 開發者的 App Store 關鍵字驗證清單

Disclosure: I'm building AppTrendKit, which supplies the example scores. This post was drafted with AI assistance.

Before writing the first screen of an iOS app, write down a search someone might use to find it. Then check whether the product you plan to build actually answers that search.

Here's a small example from the US App Store keyword pages in AppTrendKit, accessed October 27, 2026:

The numbers are 0–100 scores, not search counts or a prediction from Apple. Higher popularity and opportunity are better; lower difficulty means lower estimated organic competition. It says nothing about your future ad costs.

First, split these into different product jobs

A photo identifier needs to identify a plant. A watering reminder needs a reliable schedule and notifications. A search containing “free” may bring a different price expectation.

Don't put all three into the same target list just because they contain “plant.” Choose the job your first version can do well.

Keep the evidence in a small CSV

keyword,storefront,checked_date,popularity,difficulty,next_check
plant identifier,US,2026-10-27,44,75,inspect relevant ranking apps
water plant reminder,US,2026-10-27,17,37,verify missing ranking evidence
plant identifier free,US,2026-10-27,63,53,check fit with product and price

Add columns for the data source, current competitors, the user's job, and the product difference you could test. Leave missing numbers blank. Turning a missing value into zero makes it too easy to convince yourself you've found a gap.

In this example, the reminder keyword page had scores but no observed ranking apps listed. That is missing evidence. You still need to search the target storefront and inspect the actual competition.

Check the product before changing metadata

For each serious candidate:

1. Record relevant organic search results separately from ads.
2. Read the first screenshots and the offer on several competing listings.
3. Check recent reviews for a repeated problem, then inspect the current version.
4. Talk to potential users about the last time they had that problem.
5. Build and test one useful workflow before expanding the feature list.

For a reminder app, the first technical test should include notification permissions, scheduling, and delivery on actual devices. A polished screenshot cannot establish that the reminder works reliably.

Apple says search uses text relevance and user behavior, including downloads, ratings, and reviews. A third-party difficulty score cannot guarantee your position. Apple's guidance also excludes competing app names and unauthorized trademarks from the keyword field. Keep your competitor research separate from the metadata you submit. App Store search documentation

Decide how you'll measure the first release

Track setup completion and whether users finish the core task. Choose a return interval that makes sense for the job. A weekly plant-care workflow shouldn't need daily opens to count as useful.

After launch, compare acquisition and downstream behavior by source and territory. App Store Connect's App Store Search source includes search ads, so don't label its total “organic installs.” Apple's acquisition definitions

I used AppTrendKit's keyword pages for this example. You can use a different research tool and verify the search results in the App Store yourself.

What evidence would make you test the narrower reminder niche: a repeated complaint, interviews with plant owners, or results from a small prototype?

Example screenshots

AppTrendKit, US App Store, accessed October 27, 2026. Monthly searches shown in the screenshot are estimates.

AppTrendKit, US App Store, accessed October 27, 2026. Lower estimated difficulty comes with lower popularity. No observed ranking apps were listed on this keyword page when checked; verify the actual competition in the App Store.