ASO Share of Voice: How to Measure and Grow It

October 20, 2026

ASO share of voice (SOV) is the percentage of the available visibility across a chosen set of keywords that your app captures, compared with the competing apps on those same keywords. If you track 50 keywords and your app owns 20% of the visibility on them, your share of voice is 20%. It tells you something rank tracking alone cannot: whether you are winning or losing the market, not just your own position.

This guide covers the formula, a worked example, what counts as a good number, and the levers that move it, both organic and paid.

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TL;DR

ASO share of voice is your weighted visibility across a keyword set divided by the total visibility of all apps on that set. It is a relative metric, so it moves when competitors move.
Weight each keyword by search demand and each ranking by position. Counting top-10 appearances without weights overstates your strength on low-volume terms.
There is no universal good percentage. Compare your trend against your category and your closest rivals, not against a fixed number.
Organic and paid visibility compound. Apple’s own reporting gives you an impression share figure for paid search, which you can read next to your organic SOV.
Defend branded terms first, then expand into category and competitor keywords.

What share of voice means in app store optimization
How to calculate ASO share of voice
What is a good share of voice percentage?
Why share of voice matters for installs
Organic and paid share of voice
How to increase your ASO share of voice
Our perspective: treat SOV as a trend, not a score
Track your share of voice with Apptenium
Common mistakes when measuring SOV
FAQ
Sources

Share of voice began as a marketing measure of how much of the conversation or advertising space a brand owns compared with rivals. In ASO the “space” is the search results page of the App Store or Google Play for a given query. There are only so many slots above the fold, and every slot your competitor holds is one you do not.

That is why SOV is more useful than a single rank number. Ranking #4 for a keyword with 100 searches a day and #4 for one with 10,000 are very different situations. Ranking #4 in a category where the top three results are one dominant publisher’s apps is different again. Share of voice folds demand, position and competition into one figure you can trend over time.

It is also different from the SEO use of the term. In web search, SOV usually estimates the share of organic traffic across a keyword set. The app store version has two quirks:

Store search returns few results above the fold. Position weighting needs to be steep.
Rankings are limited by what stores expose. According to a guide on ASO metrics, keyword rank is read from the store’s own results, with iOS visible to roughly the top 200 and Google Play to roughly the top 30. Anything beyond those depths is invisible to a tracker, so your calculation should treat it as zero.

The formula is simple. The discipline is in the inputs.

SOV = (your visibility score ÷ total visibility score of all apps in the set) × 100

Where visibility for one app is the sum, across all keywords, of search demand × position weight.

Step 1: Build a keyword set that reflects your real market

Pick 30 to 100 keywords and group them into clusters:

Brand terms: your app name and obvious misspellings.
Category terms: the generic phrases a new user types, such as “habit tracker” or “expense manager”.
Feature terms: specific jobs your app does.
Competitor terms: the names of rival apps.

Keep clusters separate. A blended SOV hides the fact that you may own 95% of brand terms and 2% of category terms.

Step 2: Assign demand to each keyword

Use a popularity or search-volume estimate per storefront. Note that these are estimates. As the ASO metrics guide above points out, store autocomplete-based demand data tells you a term is searched, not exactly how often, so treat it as relative weight rather than a literal count.

Step 3: Choose a position weight

Pick a curve and keep it fixed so your trend stays comparable. A practical example:

Rank	Position weight
1	1.00
2	0.60
3	0.40
4-5	0.25
6-10	0.10
11-30	0.02
Beyond 30	0

These weights are an illustration, not an industry standard. What matters is that the curve drops fast and that you never change it mid-analysis.

Step 4: Compute and compare

Here is a worked example with three keywords and three apps (your app, Rival A, Rival B). Demand is on a relative 1 to 100 scale.

Keyword	Demand	You (rank)	Rival A (rank)	Rival B (rank)
budget planner	80	3	1	2
expense tracker	60	2	1	6
bill reminder	20	1	4	8

Your visibility: (80 × 0.40) + (60 × 0.60) + (20 × 1.00) = 32 + 36 + 20 = 88. Rival A: (80 × 1.00) + (60 × 1.00) + (20 × 0.25) = 80 + 60 + 5 = 145. Rival B: (80 × 0.60) + (60 × 0.10) + (20 × 0.10) = 48 + 6 + 2 = 56.

Total: 289. Your SOV is 88 ÷ 289 = 30.4%. Rival A holds 50.2%, Rival B 19.4%.

Notice what the table reveals. You win the smallest keyword, “bill reminder”, but the weight of demand sits on “budget planner”, where you are third. Moving that one keyword from #3 to #2 adds 16 points of visibility (80 × 0.20) and lifts your SOV by roughly four points.

There is no single answer. Analysts who write about this metric stress that a good figure depends on category: a 50% share in a crowded finance category is far harder to earn, and worth more, than 70% in a niche utility category, according to MWM’s organic installs glossary. The sensible benchmark is your own history and your closest competitors.

Use these rules of thumb instead of a magic number:

Brand cluster: aim for near-total ownership. If a competitor appears above you on your own name, fix that first.
Category cluster: measure month-over-month change. A steady upward trend matters more than the absolute level.
Competitor cluster: it is normal to be low here. Rising is a bonus.
Relative to the leader: the gap between you and the top app in the set is often more actionable than your raw percentage.

As for what 50% means: it means that, on your chosen keyword set, you capture half of all weighted visibility. It says nothing about conversion, so pair it with install conversion rate before celebrating.

Search is where a large part of app discovery happens. According to MWM’s analysis of US iOS apps as of April 2026, the median iOS app receives 61.6% of its installs from organic channels, and App Store keyword search contributes a median of 52.3% of total installs. Dependence varies by category: utility apps lean heavily organic, while hyper-casual games rely far more on paid acquisition.

If search drives half your installs, your share of the results is, in practice, your share of a large slice of demand. SOV is the leading indicator: it usually moves before downloads do, which makes it a good early warning that a competitor has launched a metadata update or a campaign.

In the App Store, visibility has two sources: organic results and Apple Ads placements. They are measured differently, and it helps to know both.

For paid search, Apple reports impression share. Apple’s reporting documentation defines it as the number of times your ad was shown for a search term out of the total searches on that term in the same storefront. Apple shows exact percentages up to 90% and a 91 to 100% range above that. This is a measure of paid presence on a keyword, so you can drop it directly beside your organic SOV for the same cluster.

Why look at both?

Gaps: if you rank #12 organically on a high-demand keyword, paid placement can cover the gap while you work on metadata.
Cannibalization checks: if you already rank #1 organically on a keyword, heavy paid spend there may add less than it appears to.
Compounding: MWM’s research reports that each $1 of paid acquisition often drives $0.20 to $0.50 of additional organic installs, as brand awareness lifts organic rankings. Treat that as an observed range from one catalog, not a promise for your app.

Defending your brand terms

Branded search is high intent and cheap to hold. Fetch’s marketing team describes keeping brand share of voice consistently above 90% as an always-on defensive strategy that stops competitors from poaching users who searched for them by name, according to Apple’s success story. The same case reports a 90% increase in share of brand impressions in search results.

The logic carries beyond the app stores. If you also run branded search campaigns on the web, the same discipline applies: a guide on dynamic versus responsive search ads is a useful read on how automation can affect tracking of those high-intent campaigns.

Presence beyond search

Visibility is not only keyword search. The CEO of HabitFactory describes using the Today tab for top-of-funnel discovery and search results for high-intent traffic, so users meet the app repeatedly during their journey, as described in Apple’s Signal Planner case study. Keyword SOV will not capture those placements, so keep a note of them next to your numbers.

Share of voice grows when you rank higher on more valuable keywords, or when competitors fall. You control the first. Here is a sequence that works for most teams.

1. Fix the basics of your metadata

Title, subtitle (iOS) or short description (Google Play), and the keyword field give the store its clearest relevance signals. Remove repeated words, add high-demand terms you do not yet rank for, and keep the title readable for humans.

2. Target keywords you can realistically win

Sort your keyword set by demand and by how far you are from the top 5. Terms where you rank 6 to 15 with solid demand are the best candidates: a small push moves you into a heavily weighted position. Do not spend your limited characters on keywords where the top ten is held by far larger apps.

3. Improve conversion, not only ranking

Stores reward apps that turn impressions into installs. Test icons, screenshots and short descriptions. Google Play offers store listing experiments to A/B test graphics and localized text, which makes it a good place to start on Android.

4. Localize

SOV is calculated per storefront. An app that is #1 in the US can have almost no visibility in Canada, the UK or Germany. Localized metadata opens keyword sets that your English listing never reaches.

5. Watch competitor movements

Because SOV is relative, a rival’s metadata change can cost you share without any change on your side. Review competitor listings regularly, note which terms they add, and check whether their gains came from keywords or from paid placement.

6. Use paid to defend and to test

Bid on your brand terms. Use paid campaigns on category keywords to learn which terms convert before you commit metadata space to them.

Our perspective: treat SOV as a trend, not a score

We see teams fall into two traps with this metric. The first is using one blended number across every keyword, which lets strong brand rankings mask weak category performance. The second is comparing the number to a fixed target found in a blog post, including this one. Neither tells you what to do next.

Our perspective: treat SOV as a trend, not a score — overview diagram

What works is a small set of clusters, a fixed weighting model, and a monthly review of three things: your SOV per cluster, the gap to the leader, and which competitor gained the most. Pair that with downloads, revenue and subscription data, because visibility that does not turn into installs or revenue is vanity. That is why we built Apptenium around ASO scanning, keyword tracking and competitor intelligence in one place, with performance reporting from sources such as Firebase and Google Analytics beside it. When a scan produces a copy-ready fix, you can ship it the same day and see in the next review whether share moved.

If you remember one thing: pick a few clusters, fix the method, and let the trend tell you the story.

— Mike

You can start with the free tools, including the listing scanner and word frequency analysis, to see how your current metadata uses its keyword space. To follow keywords and rivals continuously, Apptenium’s competitor intelligence shows how your market is moving. The Free plan includes a limited number of scans per month, and Pro is $9.99 per month with unlimited scans and premium features. See both on the pricing page.

Common mistakes when measuring SOV

Changing the keyword set between periods. Add keywords as a new cluster and keep the old series intact.
Ignoring the depth limit. Because trackers see only the top of the results, a position beyond that range is unknown, not zero demand.
Mixing storefronts. Calculate each country and store separately.
Treating demand estimates as exact. They are relative weights.
Forgetting conversion. High SOV with weak icon and screenshots wastes the visibility you won.

FAQ

It depends on category and keyword cluster. A 50% share in a crowded category is harder to earn than 70% in a niche one, so compare your trend with competitors and your own history. For branded terms, aim for near-total ownership.

In SEO, it usually estimates the share of organic search traffic that goes to your site across a keyword set. In ASO the idea is the same, but it applies to app store search results, where fewer results are visible and position matters even more.

It means your app captures half of the total weighted visibility across your chosen keywords. It does not say whether those impressions become installs, so read it alongside conversion rate and downloads.

Weekly tracking with a monthly review works for most teams. Rankings fluctuate daily, so a single day’s reading is noisy, while a monthly trend shows whether your metadata and campaign changes are working.