UK retail Apple Ads: the App Store search wars (whitepaper + key takeaways)
A quick, skimmable summary of ConsultMyApp’s UK retail Apple Ads whitepaper, with the charts, the ‘intent not category’ lesson, and a simple workflow you can steal.
ConsultMyApp published a useful UK retail Apple Ads whitepaper, backed by APPlyzer data, on how generic (non-brand) App Store searches actually behave.
- Read it here: /whitepapers/uk-retail-app-search-wars/
- Download (DOCX): /whitepapers/uk-retail-app-search-wars/uk-retail-app-search-wars-whitepaper.docx
The one-line lesson
UK retail Apple Ads is not one market. It’s a pile of smaller intent fights, and the obvious-sounding keywords are often the most misleading.
The bits worth stealing
- “Retail app” is basically irrelevant demand. The paper cites ~33 estimated daily UK searches for “retail app”, versus ~9,927 for “shop”. Users search for jobs, not category labels.
- Broad shopping intent is the front door. Terms like shop, shopping, online shopping, buy online behave like “mall entrance” queries, and AliExpress is a consistent top-slot presence.
- Very wins on breadth, not just #1s. It shows up across a wide spread of retail-adjacent intent (fashion, footwear, furniture, beauty-adjacent, resale-adjacent).
- Mytheresa is the surprise aggressor. It over-indexes on top-slot wins across the set, not just pure luxury.
- Fashion is fragmented by query. Different “winners” show up depending on what the user actually means (jeans vs dresses vs menswear vs sale-led shopping).
- Resale is a clean battleground now. Intent is clearer, competition is real, and the auctions look more category-consistent.
- Grocery bleeds into delivery. Once queries shift toward fulfilment, delivery apps start to dominate, even when the user thinks they’re “shopping”.
- Home/DIY/electronics can be noisy. Many product words are really “app functionality” searches (eg, a user searching “camera” is often not looking for a retailer).
Why this matters
If you don’t validate intent, you end up paying for the wrong job-to-be-done. In Apple Ads that means:
- wasted spend (auctions polluted by utilities/games/tools)
- creative/CPP mismatch (routing to the wrong promise)
- “learning” that is actually just averaged noise
Tiny win (30 minutes)
Make an intent map for your category:
- list 15 to 25 generic, non-brand queries you think matter
- for each query, check the top organic results and ad slots #1 to #5
- label each query as clean retail vs polluted
Then only scale budgets (or build CPP variants) for the clean clusters.
If you want the visuals and section-by-section breakdown, the full whitepaper page is here: /whitepapers/uk-retail-app-search-wars/
Want help with ASO?
If you want this implemented for your app, check out our services - or run your workflow in APPlyzer.