Discovery Campaigns + Search-Term Harvesting in Apple Search Ads (Without Wasting Spend)

Discovery in Apple Search Ads is less about “guessing keywords” and more about letting Apple’s matching surface what real users type—then using that signal to build tighter campaigns. The core challenge for indies is doing it fast without turning discovery into a spend sink. Here’s a workflow you can run every week.

Why Discovery (Search Match) helps

On the Search Results placements, Apple Search Ads matches your ad to user searches using the ad group’s keyword settings. When you use Search Match (often called Discovery/Search Match), Apple decides which searches are eligible based on relevance. You don’t set a keyword-to-search-term mapping ahead of time.

That’s useful because:

• You get exposure to queries you wouldn’t think to target manually.
• You can identify which searches lead to taps and then installs (and ideally purchases).
• You can harvest the actual search terms shown in Apple’s reports and turn them into controllable keywords.

But: Search Match can also generate irrelevant traffic. Your job is to (1) structure the campaign so learning is clean and (2) harvest quickly.

Set up Discovery so harvesting is actionable

Before you launch anything, decide how you’ll separate “learning” from “scaling.” A simple setup works well.

1) Use one Search Match campaign per country/region

Remember: one campaign targets one country/region. If you mix regions, you make reporting harder and your harvested insights less reliable.

2) Keep the product relevance tight

Discovery is still constrained by what Apple considers relevant to your metadata/product page. Make sure:

• Your app name, subtitle, and description clearly reflect your app’s category and primary value (within Apple’s rules).
• If you use custom product pages, ensure the Discovery traffic can land on the right page (more on that later).

3) Create dedicated ad groups for your discovery intent

Even though Search Match lives at the ad group level, treat ad groups like “themes.” Example themes:

• Primary use case (e.g., “meal planner”)
• Audience intent (e.g., “for busy parents”)
• Problem/solution (e.g., “track expenses”)

Why this matters: when you harvest search terms, you’ll want to map them back to a theme so your Exact/Broad keywords go into the right ad group.

What to harvest (and where)

After your Discovery campaign has collected data, you’ll use the Search Term report to see the actual queries that triggered your ads.

Apple’s search term reporting will typically show (at minimum):

• Search term (the query)
• Impressions and taps
• TTR (taps ÷ impressions)
• Installs (via AdServices attribution token resolved within ~24h)
• Conversion rate (installs ÷ taps)

Revenue is not directly “per keyword” inside Apple; attribution happens through the install → purchase chain (often mapped with RevenueCat or similar). Practically, you should base decisions on install efficiency first, then validate ROAS/CPA downstream using your revenue mapping.

The harvesting workflow (a weekly loop)

Here’s a repeatable routine that stays practical for small budgets.

Step 1) Pick a learning window

You’re looking for enough taps that TTR and conversion rate aren’t pure noise.

A good rule of thumb:

• Don’t harvest until you have a meaningful number of taps across the search terms you’ll evaluate.
• If your budget is small, aggregate multiple days into a weekly batch.

(Exact thresholds depend on your traffic volume; the principle is: avoid building keywords from one-off visits.)

Step 2) Filter for “promising” terms using efficiency metrics

Sort harvested search terms by:

• High conversion rate (installs/taps)
• Reasonable CPA/CPI once you map installs to revenue/attribution
• ROAS where available through your revenue mapping

Also track negative signals:

• Very low TTR (users don’t click)
• Taps with near-zero conversion rate (users click but don’t install)

What to do with them:

• High conversion + acceptable CPI/ROAS → promote to Exact (and sometimes Broad)
• Good clicks but low installs → usually indicates mismatch (creative/landing/product page relevance), so treat carefully
• Low clicks → often just irrelevant; consider excluding if you see repeated spend waste

Step 3) Promote winners into controllable keywords

When you find a converting search term, you want to move from “Apple decides” to “you decide.”

Add that search term to your keyword set using:

• Exact match first for precision (best for ROI control)
• Optionally Broad later if it continues to convert efficiently

Key detail: when you add as Exact/Broad, you’re not changing the search term itself—you’re changing how you bid and control exposure.

Step 4) Decide bid levels based on observed CPT and conversion

Apple runs a CPT auction with a max bid. Your harvested winners will have a sense of what CPT is needed.

A safe approach:

• Don’t instantly match the highest CPT you ever paid.
• Start with a bid that you can defend if conversion stays similar.

Practical control method:

• Set the Exact keyword bid slightly below the average CPT seen for that winning term, then adjust after the next learning cycle.

Step 5) Add exclusions for clear losers

If a search term is consistently:

• Spending but producing poor install conversion, or
• Driving clicks without downstream results,

…use the ASA exclusion mechanisms to prevent wasting money.

Exclusions are most valuable once you can point to repeatable negative patterns.

Keep your learning clean: avoid “double counting” and distorted data

A common indie mistake is mixing Discovery and Exact/Broad targeting in ways that make attribution messy.

Use clear campaign boundaries

• Keep Search Match (Discovery) separate from your Exact/Broad scaling campaign(s).
• Use one country per campaign.

Watch for cannibalization

If your Exact keywords start matching the same queries that Search Match surfaces, you may see the discovery campaign’s performance change. That’s okay—just interpret it correctly:

• Winners are being “learned,” then “claimed” by your Exact/Broad.
• If discovery performance collapses too early, it can mean you’re harvesting and scaling correctly, or it can mean you underbid Exact/Broad so Apple routes traffic unpredictably.

Landing page strategy: where Discovery often leaks performance

Apple doesn’t have a creative auction advantage; it’s still a CPT auction. So when installs don’t follow taps, the issue is often:

• App store page mismatch
• Missing value prop at the top
• Wrong custom product page

Two concrete checks:

• TTR vs conversion: If TTR is strong but conversion is weak, the listing experience is the bottleneck.
• Custom product pages: If the search terms correspond to a specific use case, route them to a custom product page that emphasizes that use case.

This can matter more than tinkering with bids.

Advanced vs Basic account types: keep control where it matters

If you’re on Basic, automation may adjust performance in ways that complicate learning. If you’re on Advanced, you typically have full control over bids at the level you need for harvesting workflows.

If you’re actively harvesting and promoting keywords each week, Advanced is usually easier to reason about.

A simple example workflow (illustrative)

Let’s say your app is a habit tracker.

1. Launch a Search Match discovery campaign with theme-based ad groups (e.g., “habit tracker,” “streaks,” “daily routine”).
2. After a week, open the search term report.
3. You find a term like “morning streak tracker” generated moderate taps and a high conversion rate (installs/taps).
4. Add it as an Exact keyword in your scaling campaign.
5. If you see repeated spend on terms like “free wallpaper app” with low installs, exclude them.
6. If taps are high but installs are low for terms related to “weight tracking,” consider whether your product page headline/features are actually aligned (or whether you need a custom product page).

This is not about chasing every keyword. It’s about promoting only the terms that show real downstream promise.

How AdsBuddy fits (lightly)

If you’re doing this manually, you’ll still miss patterns. Tools like AdsBuddy can read your Apple Search Ads and revenue signals to generate a short, prioritized list of changes to approve—so you’re not staring at spreadsheets all day. The workflow above is still the backbone; the tool helps decide what to do next.

Closing takeaway

Discovery/Search Match is your “query discovery engine.” Search-term harvesting is how you turn that discovery into controllable Exact/Broad keywords, exclusions, and (when needed) better landing/product-page alignment. Run it as a weekly loop: learn → harvest → promote → exclude → validate with install efficiency and downstream revenue.

If you want, tell me your app’s category and whether you’re currently using Search Match. I can outline a concrete harvest-and-promotion cadence (including what to prioritize first) based on your likely traffic volume.