Keyword Research Methodology

Step-by-step process for identifying, scoring, and maintaining the keyword field for App Store search optimization.

Contents

• How Apple Indexes Metadata
• Research Process
• Keyword Scoring Framework
• Slot Allocation Strategy
• Seasonal Keyword Rotation
• Before and After Examples

How Apple Indexes Metadata

Apple documents the main App Store search signals as text relevance, including matches for the app title, subtitle, keywords, and primary category, plus user behavior such as downloads, ratings, and reviews. Use this table as a practical planning map, not as a precise ranking-weight model:

Indexing behavior details

• Avoid plurals of words already included in singular form; Apple treats them as duplicates.
• Do not repeat words from the app name, subtitle, or category in the keyword field.
• Use spaces only inside real keyword phrases; do not add spaces after commas.
• Include separate related terms when both are genuine search terms, such as "photo" and "photography".

Research Process

Step 1: Competitor audit

Identify the top 5-10 apps ranking for the primary category terms. For each competitor, note:

• Title and subtitle keywords
• Visible positioning patterns (terms that appear frequently across top-ranking titles, subtitles, and screenshots)
• Gaps -- relevant terms that competitors are not targeting

Use App Store search autocomplete to discover what users actually type. Start typing a category term and note the suggested completions.

Step 2: Category analysis

List every term a user might associate with the app's functionality:

• Primary function terms (what the app does)
• Use case terms (why a user would want it)
• Audience terms (who the user is)
• Adjacent terms (related activities or workflows)

Filter this list against competitor findings. Terms that appear in many competitor titles are high-volume but high-competition. Terms that appear in autocomplete but not in competitor metadata represent opportunities.

Step 3: Search Ads discovery

Run Apple Search Ads discovery campaigns with broad-match keywords matching the primary function. After 2-4 weeks of data:

• Export the search term report to see actual queries that triggered impressions.
• Sort by tap-through rate (TTR) to identify high-intent terms.
• Sort by conversion rate to identify terms where users who find the app actually download it.
• Add high-performing discovered terms to the keyword field.

Step 4: Iteration cycle

With each app update:

1. Review App Analytics for keyword impressions, tap-through rates, and conversion rates.
2. Identify underperforming keywords (low impressions or low TTR) and replace them.
3. Test new terms discovered through Search Ads or category changes.
4. Check if competitor metadata has shifted -- new competitors or renamed apps can change the keyword landscape.

Keyword Scoring Framework

Score each candidate keyword on three dimensions:

Decision rule: Include a keyword only if Relevance >= 3. Among qualifying keywords, prioritize by (Relevance x 2) + Volume + Difficulty. This weights relevance heavily while still favoring discoverable, winnable terms.

Disqualify keywords that:

• Do not describe the app's actual functionality (Relevance < 3)
• Are competitor brand names (violates App Store guidelines)
• Duplicate a word already in the title or subtitle
• Are the app's primary category name (Apple adds it automatically)

Slot Allocation Strategy

The 100-character keyword field requires careful allocation. Here are allocation patterns for different app types:

Example: Fitness tracking app

Title: FitTrack -- Workout Log (23 chars used) Subtitle: Exercise & Activity Stats (25 chars used)

Keyword field strategy -- do not repeat: fittrack, workout, log, exercise, activity, stats

gym,training,health,run,step,calorie,weight,strength,cardio,hiit,yoga,plank,squat,routine,progress

(96 characters -- 4 remaining, all unique against title/subtitle)

Example: Photo editing app

Title: PixelPop -- Photo Editor (24 chars used) Subtitle: Filters & Retouch Tools (23 chars used)

Keyword field -- do not repeat: pixelpop, photo, editor, filter, retouch, tool

selfie,portrait,collage,crop,blur,preset,enhance,adjust,brightness,contrast,saturation,beauty,skin

(99 characters -- all unique against title/subtitle)

Allocation principles

• Each comma costs 1 character. Fewer, longer keywords are not inherently better than more, shorter ones -- Apple matches individual words, not phrases.
• If two terms are searched as a phrase (e.g., "meal prep"), use the phrase when it matches real query behavior; use separate terms when each word is independently valuable.
• Reserve 5-10 characters for experimental keywords that rotate each release based on performance data.

Seasonal Keyword Rotation

Some keywords have seasonal search volume spikes. Plan rotation around predictable events:

Rotate 2-3 keyword slots per seasonal cycle. Keep the core 70-80 characters stable and use the remaining 20-30 characters for seasonal experimentation.

Before and After Examples

Problem: Wasted characters

Before:

fitness tracker, workout app, best exercise, health and wellness, gym

Issues: spaces after commas (-5 chars wasted), "fitness" and "tracker" may duplicate title, "best" and "app" have no search value, "and" is a stop word.

After:

gym,health,run,step,calorie,weight,strength,cardio,hiit,yoga,plank,squat,routine,progress,streak

Fixes: no spaces, no duplicates of title/subtitle, no filler words, all terms are genuine search queries.

Problem: Duplicate keywords

Before (title is "RunMate -- Running Tracker"):

running,tracker,run,jog,marathon,5k,pace,distance,route,gps,heart,rate,training,fitness,health

Issues: "running", "tracker", and "run" duplicate the title -- 17 characters wasted.

After:

jog,marathon,5k,pace,distance,route,gps,heart,rate,training,fitness,health,stride,tempo,interval

Fixes: removed title duplicates, added 3 new high-value terms with the recovered space.