Generic, Brand, Competitor, and Discovery Apple Search Ads: what each campaign type is for

If you’re running Apple Search Ads as an indie studio, the biggest win isn’t “better bidding”—it’s sending the right user intent to the right campaign. Generic, Brand, Competitor, and Discovery campaigns overlap in placement, but they don’t overlap in intent. Treat them like separate jobs, each with its own KPIs and bidding rules.

Below is a clear “what it’s for” guide, plus what to check so you don’t accidentally bid your way into the wrong kind of installs.

Generic campaigns: demand capture (high intent, broad discovery)

What Generic is for: capturing users who are searching for what your app does—by category, feature, or problem. This is where most new spend should live, because it’s your main path to scalable, non-brand demand.

What typically lives inside Generic:

• Keywords describing the app outcome (e.g., “habit tracker”, “PDF editor”, “meal planner”).
• Category-like terms that match how users phrase their problem.
• If you use Search Results targeting, you’ll usually run exact and broad keyword variants (or you’ll let Search Match/Discovery handle some discovery separately—more on that later).

How to think about match types (Search Results keywords):

• Exact: you’re buying a narrower slice of intent; CPT and conversion rates tend to be steadier.
• Broad: you’re buying volume; you may see lower conversion or more irrelevant taps, so you need tighter monitoring.
• Discovery/Search Match is not the same as broad. Discovery is automatic matching inside its own ad group/campaign setup (depending on your account structure).

Metrics that matter most:

• TTR (taps ÷ impressions): are the ad placements/keyword pairings getting the right attention?
• Conversion rate (installs ÷ taps): are the product page and offer aligning with what the keyword promises?
• CPA/CPI and ROAS: only after you confirm you’re getting signal-worthy traffic.

Common failure mode:

• Generic campaigns become “junk drawers” (too many broad terms, no negative keywords where applicable, and bids set high because something got installs once). Generic should be measured demand capture, not a “try everything” bucket.

Practical setup checklist for Generic

• Keep one campaign per country/region (Apple’s structure expects that), then organize ad groups by intent type (feature terms vs category terms vs problem terms).
• If you split exact vs broad, compare their conversion rate rather than only CPT. A higher CPT with better conversion can be cheaper per install.
• Use product page alignment: the keyword theme should match the first visible screenshots and the top portion of your App Store description.

Brand campaigns: defend your name (and reduce wasted spend)

What Brand is for: capturing users who already know your app (or are searching closely for it). This often produces the best efficiency—because intent is already baked in.

What typically lives inside Brand:

• Your app name (and common misspellings).
• Your developer name / exact brand terms.
• Any obvious branded phrases.

Why Brand matters even if it’s “cheap”:

• If you don’t bid Brand, competitors (and your own other campaigns) can pay to win clicks from people who were already going to install.
• Brand campaigns also act as a sanity check: if your branded terms are getting weaker conversion, your product page, creatives (App Store product page), or tracking mapping could be off.

Metrics that matter most:

• TTR and conversion rate (you want stable performance).
• CPA/CPI and ROAS (brand should often be your baseline).

Common failure mode:

• Letting Brand keywords bleed into other campaigns and then making bidding decisions based on mixed attribution performance.

Practical setup checklist for Brand

• Put Brand keywords into their own campaign so you can separate “intent-ready” traffic from discovery/interest traffic.
• Don’t overreact to short-term CPI swings; branded searches can show consistent patterns, so treat sudden drops as a “check the product page + attribution mapping” moment.

Competitor campaigns: capture substitute intent (with guardrails)

What Competitor is for: targeting users who search for another app that competes with you—people actively looking for alternatives.

What typically lives inside Competitor:

• Exact competitor app names.
• Close substitutes where users might swap (e.g., “X workouts app”, “Y budget planner”).

Important expectation:

• Competitor intent is real, but it’s not “native” to your brand. Some searches yield curious clicks that don’t convert.
• Your job is to earn the install through differentiation: the product page needs to explain why your app is better or different within seconds.

Metrics that matter most:

• Conversion rate (this is the main truth serum here).
• ROAS once you’re confident attribution is working.
• TTR is useful too—low TTR suggests the ad isn’t matching what people expect from that competitor query.

Common failure modes:

• Bidding aggressively on competitor terms without confirming your product page answers the obvious question: “Why should I switch?”
• Using the same bid/strategy as Brand campaigns.

Practical setup checklist for Competitor

• Start by selecting a small set of your closest competitors rather than targeting everything in the category.
• Segment ad groups by competitor cluster (direct substitutes vs adjacent tools).
• Review taps vs installs: if you have taps but low conversion, focus on product page clarity (screenshots, app description structure, and any custom product page if you use them).

Discovery campaigns: automatic matching for incremental users

What Discovery is for: finding pockets of users you didn’t explicitly keyword-target. In Apple Search Ads, this is typically handled via Search Match / Discovery, where the system uses automatic matching to show your ad for relevant searches.

Where Discovery fits in the funnel:

• It’s not “Brand replacement” and it’s not “Generic substitute.” It’s best treated as an expansion engine around what’s already working.
• Discovery often generates new keyword-like demand signals—but you don’t get to micromanage every query.

What to expect:

• Discovery can be great for incremental installs, but you’ll still need to control budget and review efficiency.

Metrics that matter most:

• CPA/CPI and ROAS (because discovery can mix intent levels).
• TTR can indicate whether the system is showing you to the right type of searchers.

Common failure mode:

• Running Discovery at a high max CPT bid with no guardrails because “it’s automated so it’ll optimize.” Automation optimizes within your constraints—you still set the max CPT and overall campaign structure.

Practical setup checklist for Discovery

• Run Discovery in its own campaign/ad group so you can compare its performance directly against Generic.
• Use Discovery to complement your best-performing keyword sets—if Generic exact is converting well, Discovery often finds adjacent queries that behave similarly.
• If Discovery performance is erratic, reduce max CPT and/or narrow your targeting context via how you structure campaigns by country and ad groups.

How to choose where your budget goes (a simple decision rule)

When you review performance, don’t compare these campaign types on a single headline metric. Instead:

• Brand: use as baseline + defensive efficiency check.
• Generic: main scale lever; optimize keywords, match type mix, and product page alignment.
• Competitor: use as “switcher” intent; optimize differentiation and conversion rate.
• Discovery: use as incremental coverage; optimize max CPT and watch efficiency closely.

A concrete way to decide:

1. If Brand ROAS/CPA is strong, make sure you’re not stealing that audience from yourself (separate campaigns).
2. If Generic broad has lots of taps but poor installs, tighten with more exact terms and improve product page alignment for those keyword themes.
3. If Competitor has decent taps but weak conversion, focus on the “why switch” message first.
4. If Discovery is expanding volume but dragging ROAS, lower max CPT and let it run long enough to see stable attribution (~24h resolution via Apple’s AdServices).

One more practical note: attribution and “what revenue means”

Apple Ads attribution is based on the install→purchase chain (via AdServices’ attribution token), and mapping to revenue typically happens in your analytics layer (e.g., RevenueCat). There isn’t per-keyword revenue in Apple Ads itself—so treat ROI/ROAS comparisons as “revenue attributed to installs from those campaigns,” not “revenue from a specific search query.”

Quick takeaway

• Generic captures search intent for what you do (your scaling engine).
• Brand defends and validates conversion (your baseline).
• Competitor targets switchers (your differentiation test).
• Discovery expands beyond your explicit keywords (your incremental coverage).

If you want, tell me your app category and what you currently run (exact/broad, Discovery or Search Match yes/no, and your last-week ROAS/CPI split by campaign). I can suggest a prioritized plan for which campaign type to adjust first and what to change in the account structure.