How Apple Search Ads Popularity Score Actually Works

What Is Search Popularity?

If you've ever looked at keyword data in Apple Search Ads, you've seen the Search Popularity (SP) score. It's a number from 5 to 100 that represents the relative search volume of a keyword on the App Store.

Apple doesn't publish raw search counts. Instead, they normalize everything into this 5-100 scale, where 100 represents the highest-volume keywords (think "facebook" or "instagram") and lower numbers represent progressively less searched terms.

The key word here is relative. An SP of 50 doesn't mean a keyword gets half the searches of an SP 100 keyword. The scale is exponential, which means the difference between SP 50 and SP 60 is much larger than the difference between SP 20 and SP 30.

How It's Calculated

Apple hasn't published the exact methodology, but through extensive testing and research from companies like SplitMetrics, we know the following:

Search Popularity is a 7-day moving average of search impressions, normalized against all other keywords on the App Store. This means:

1. The score reflects the trailing 7 days of search activity, not real-time data
2. It's smoothed to reduce noise from daily fluctuations (weekday vs weekend patterns, for example)
3. It's relative to all other keywords, so if overall App Store search volume increases, individual SP scores can drop even without losing actual searches

Because of the 7-day averaging window, SP scores lag real-time search behavior by roughly 4 days. If a keyword suddenly goes viral on Monday, you might not see the full SP increase reflected until Thursday or Friday. This is important to understand when tracking trending keywords or seasonal terms.

The October 2025 Change

In October 2025, Apple made a significant change to how SP data is returned through the Search Ads API. Previously, you could get SP scores for virtually any keyword, even very low-volume ones that scored in the single digits.

After the change, Apple only returns SP scores for keywords with SP >= 35. Keywords below this threshold now return no popularity data at all. This effectively makes lower-volume keywords invisible to tools that rely solely on the Search Ads API.

For indie developers, this is actually a meaningful problem. Many of the best keyword opportunities for small apps exist in the SP 20-35 range — keywords with enough search volume to drive downloads but not enough competition to be unreachable. With this data now hidden, you need alternative signals like autocomplete priority scores to estimate volume for these keywords.

What This Means in Practice

The SP 35 cutoff didn't just remove a few obscure keywords. It wiped out visibility into a large portion of the long-tail that indie developers depend on. Before the change, you could confidently compare a keyword at SP 22 against one at SP 28 and make an informed decision. Now, both return nothing — you're flying blind.

If you built keyword lists or tracking dashboards before October 2025, you'll notice that many previously tracked keywords now show no SP data. This doesn't mean those keywords lost all their search volume overnight. They're still being searched; Apple just stopped reporting on them.

The practical response is to treat the SP 35 threshold as a data boundary, not a quality boundary. Keywords below it can still drive meaningful downloads, especially in niche categories where even 500 daily impressions can put you on the first page of results. You just need different tools to evaluate them — autocomplete priority, rank tracking for apps already targeting those terms, and competitive analysis of what's actually ranking.

Converting SP to Real Search Numbers

The most widely cited research on mapping SP scores to actual impressions comes from SplitMetrics, who published an exponential formula based on their analysis of Search Ads campaign data:

Max Daily Impressions = 254.4443 exp(0.0615 SP)

This gives us a concrete reference for what different SP scores actually mean in terms of daily search volume. For the full breakdown including every SP increment, see our real search volume reference table:

A few important caveats:

• These are maximum daily impressions, meaning the upper bound of what you could see if your app appeared for every search
• Actual impressions depend on your app's rank for that keyword — position 1 gets dramatically more impressions than position 10
• The formula is based on data from a specific time period and may drift as overall App Store search volume changes
• These numbers represent searches on the US App Store; other countries will have proportionally lower volumes

SP Varies Wildly Across Categories

One of the most common mistakes in interpreting SP scores is treating them as universal benchmarks. An SP of 40 means very different things depending on the app category you're in.

In categories like Games, Social, and Photo & Video, SP 40 is relatively low. The top keywords in these categories regularly hit SP 80-100, and even mid-tier terms sit at SP 55-65. If you're building a photo editing app, you need keywords with SP 50+ to get meaningful traction because the entire category is high-volume.

In categories like Utilities, Productivity, and Health & Fitness, the distribution shifts downward. Many excellent keyword opportunities sit in the SP 35-50 range. A utility app targeting "unit converter" at SP 42 can do very well because the competition density is lower and conversion rates tend to be higher for intent-driven searches.

For niche categories like Weather, Navigation, or Developer Tools, even SP 35-40 keywords can represent the top of the volume curve. The entire addressable search space is smaller, so the SP scores compress accordingly. Don't dismiss a keyword at SP 37 in a niche category — it might be one of the best opportunities available.

The takeaway: always evaluate SP relative to your category's typical range, not against some absolute standard.

Combining SP with Difficulty for Keyword Prioritization

SP alone is only half the equation. A keyword with SP 60 sounds great until you discover that the top 10 results are all apps with 500K+ reviews and perfect title matches. That's where keyword difficulty comes in.

The most effective way to prioritize keywords is to plot them on a two-dimensional grid:

• High SP + Low Difficulty (SP 40-60, Difficulty < 40): These are your best opportunities. Enough volume to drive downloads, and realistic competition. Target these first.
• High SP + High Difficulty (SP 50+, Difficulty > 60): Aspirational keywords. Track them, but don't expect to rank without a strong app and hundreds of reviews.
• Low SP + Low Difficulty (SP 35-45, Difficulty < 30): Quick wins. You can often rank top-3 within a few weeks. Individually they won't transform your download numbers, but stacking 10-15 of these in your metadata adds up.
• Low SP + High Difficulty (any SP, Difficulty > 60): Skip these entirely. There's no reward proportional to the effort.

A practical scoring formula that works well for indie apps: Opportunity = SP * (100 - Difficulty) / 100. This gives you a single number that balances volume against achievability. A keyword with SP 45 and Difficulty 25 scores 33.75, while one with SP 65 and Difficulty 70 scores only 19.5 — correctly reflecting that the lower-volume keyword is actually the better opportunity.

Seasonal SP Patterns

SP scores aren't static. Many keywords follow predictable seasonal patterns that you can exploit if you plan your metadata updates around them.

Fitness keywords like "workout tracker" or "calorie counter" spike in January (New Year's resolutions) and again in May-June (summer body season). Travel keywords peak in June-August. Holiday-adjacent terms ("gift list", "recipe organizer") surge in November-December. Back-to-school keywords like "study planner" or "flashcard app" climb in August-September.

The lag matters here. Because SP uses a 7-day moving average, seasonal spikes appear in the data about 4 days after they start and persist about 4 days after they end. If you're trying to ride a seasonal wave, update your metadata before the spike shows up in SP data — ideally 1-2 weeks before the expected surge. Apple's metadata review process takes 24-48 hours on average, so factor that in.

Tracking SP over a full year for your target keywords gives you a significant advantage. You'll know exactly when to shift your subtitle or keyword field to capture seasonal volume, and when to rotate back to your evergreen terms.

Why This Matters for Indie Developers

Understanding the exponential nature of SP is crucial for keyword strategy. Here's the practical takeaway:

SP 30-50 is the sweet spot for indie apps. These keywords get roughly 1,600 to 5,600 daily impressions — enough to meaningfully move the needle on downloads, but not so competitive that you need millions of reviews and a massive brand to rank. For example, keywords like calorie counter or habit tracker sit in this range with very different competitive profiles.

Keywords with SP 70+ are dominated by well-established apps with huge install bases. Keyword difficulty scores help you assess whether you can realistically compete — check the photo editor keyword difficulty page for a real example of what extreme competition looks like. Unless your app directly competes with them (and you have the reviews/ratings to back it up), these keywords are largely unreachable.

Keywords with SP below 25 are generally too low-volume to be worth optimizing for as primary targets, but they can be useful as long-tail additions to your metadata if they're highly relevant.

The Autocomplete Priority Proxy

For keywords below the SP 35 threshold (where Apple no longer provides data), there's an alternative signal: the App Store autocomplete API.

When you type in the App Store search bar, Apple returns autocomplete suggestions. Each suggestion includes a priority score from 0 to 10,000. While this isn't directly comparable to SP, higher autocomplete priority generally correlates with higher search volume. It's not as precise as SP, but it's free, requires no API access, and covers the long-tail keywords that SP now misses.

A rough mapping: autocomplete priority above 5,000 typically corresponds to SP 30+, while priority above 7,000 usually indicates SP 45+. Below 3,000, you're looking at very low-volume terms.

Getting Access to SP Data

To access Search Popularity scores, you need an Apple Search Ads account. Our Apple Search Ads guide covers setup and usage in detail. The good news: it's completely free to create one. You don't need to run any ad campaigns or spend any money. You just need an Apple ID and a few minutes to set up the account.

Once you have an account, you can use the Search Ads API (specifically the keyword recommendations and targeting endpoints) to query SP scores for any keyword in any country where Apple Search Ads operates. Many ASO tools, including ours, let you connect your Apple Search Ads account to automatically pull this data.

The API uses OAuth 2.0 authentication and has generous rate limits for keyword lookups. It's the single most valuable free data source available for iOS ASO.

Key Takeaways

• SP is a relative, logarithmic score — small differences in SP mean large differences in actual volume
• The 7-day moving average introduces a ~4 day lag behind real-time trends
• Since October 2025, SP data is only available for keywords scoring 35+
• The SplitMetrics formula converts SP to estimated daily impressions
• For indie apps, target SP 30-50 keywords for the best effort-to-reward ratio
• Always evaluate SP relative to your app category — SP 40 means different things in Games vs Utilities
• Combine SP with difficulty scores: Opportunity = SP * (100 - Difficulty) / 100
• Track seasonal SP patterns and update metadata 1-2 weeks before expected spikes
• Use autocomplete priority as a free proxy for keywords below the SP threshold
• Creating an Apple Search Ads account is free and unlocks SP data
• Browse real keyword data on our keyword difficulty pages — for example, see how focus timer or meditation app compare in the SP 30-50 sweet spot