MarketingBeginnerPreview
Apple Search Ads
A hands-on, beginner-friendly path through Apple Search Ads, teaching you to launch and structure App Store ad campaigns, choose the right match types, set CPT and CPA bids, point ads at Custom Product Pages, and read install attribution so spend turns into profitable downloads.
App developers, indie founders, mobile growth marketers, and agency account managers who want to launch and control Apple Search Ads campaigns that drive profitable installs rather than burn budget.
Course content
Workbook & downloads
Put the course into practice — a printable workbook plus editable templates you can fill in and reuse.
Preview the workbook
This workbook turns the course into reps on your own app. You will audit your placements and listing, design a four-campaign Search Results structure, build keyword and match-type plans, set bids from your real install economics, and stand up a weekly optimization loop. Work through one section per module and finish with a launch-ready account plan, a bidding model tied to your numbers, and a recurring routine you could run on Monday morning.
How Apple Search Ads Actually Works
Decide where to advertise, choose Basic or Advanced, and ground yourself in how the auction prices your taps.
Exercise: Placement and Intent Audit
Open the App Store on your iPhone and run three searches that matter to your app: your app name, a category term, and a close competitor's name. Screenshot each results page and note what ads appear. Then decide which of the four placements your first campaign should use and why.
- For each of the three searches, what app held the top Search Results ad slot, and was it you or a competitor?
- Which single placement (Search Results, Search Tab, Today Tab, Product Pages) will your first campaign use, and why is it the right starting point?
- What is the intent of a person typing each of your three searches, and how does that intent differ from a Today Tab browser?
- Confirm you understand the pay-per-tap model: write in one line what you are charged for versus what you actually want.
Worksheet: Basic vs Advanced Decision
Fill one row per factor to decide which Apple Search Ads product fits you right now. Be honest about how much time you will actually spend managing the account.
- Monthly budget you can commit
- Hours per week you will spend optimizing
- Do you need keyword-level reporting? (Y/N)
- Do you need Custom Product Pages tied to ad groups? (Y/N)
- Your decision: Basic or Advanced
- One-sentence reason for the decision
Checklist: Pre-Launch Readiness
- I have an Apple account and have agreed to the Apple Search Ads terms
- My App Store product page metadata (app name, subtitle, keyword field) is optimized and current
- I can name the single primary goal of this account (for example installs at a target cost)
- I know my app's approximate lifetime value per user, or have a working estimate
- I have viewed my current default product page as a new user would see it from a search ad
- I have decided which placement my first campaign will use
Building Your First Advanced Campaign Structure
Lay out the Brand, Generic, Competitor, and Discovery campaigns and seed each with the right keywords.
Exercise: Map Your Four-Campaign Structure
On one page, sketch your account as four campaigns: Brand, Generic, Competitor, Discovery. For each, list the ad groups it will contain and the kind of keyword that belongs there. Keep ad groups tight enough that one bid suits the whole group.
- Brand: list your exact app name plus two or three misspellings or variants you will defend.
- Generic: name two to four ad groups by theme (for example feature, problem, category) and a sample keyword for each.
- Competitor: list the three to five rival app names you will target.
- Discovery: confirm it will run Search Match plus loose Broad keywords whose only job is to surface new terms.
Worksheet: Keyword Seed List with Intent
Build your starting non-brand keyword list. Pull seeds from your subtitle and keyword field, then expand. For each keyword, record its bucket and whether it is a head term or long-tail so you bid it correctly later.
- Keyword
- Campaign bucket (Generic / Competitor)
- Head term or long-tail?
- Apple popularity score (if known)
- Why this keyword fits your app (one phrase)
- Starting match type intent (Broad for discovery / Exact for proven)
Checklist: Structure Sanity Check
- Each campaign holds only one intent type (brand, generic, competitor, or discovery)
- No single ad group mixes brand, generic, and competitor terms together
- My exact app name is set to Exact match in the Brand campaign
- Competitor terms are kept in their own campaign so I can cap their bids separately
- Discovery is isolated so its wider matching does not pollute performance reporting
- I have planned which Custom Product Page each ad group will eventually use
Match Types, Custom Product Pages, and Bidding
Set match types and negatives, plan a Custom Product Page per theme, and bid from your install economics.
Exercise: Design the Discovery-to-Exact Relay
Write the rules that move a keyword from discovery into a precise performance campaign, and the negatives that keep the two from competing. This is the engine that keeps finding cheap converting terms.
- Which keywords and toggles will live in Discovery (Search Match plus which Broad terms)?
- What is your rule for graduating a query to Exact match (for example: after it produces installs at or below target)?
- When you graduate a query, what negative do you add to Discovery, and is it negative Exact or negative Broad?
- List three brand or off-topic terms you will add as negatives to your Generic campaign right away.
Worksheet: Custom Product Page Plan
Plan one Custom Product Page per major keyword theme so each ad lands on a page that matches the search. Fill one row per page you will build in App Store Connect.
- Custom Product Page name
- Keyword theme it serves
- Ad group it will be assigned to
- First screenshot message (what it must show in one second)
- Promotional text angle
- Default-page conversion rate to beat (if known)
Worksheet: Bid-from-Economics Calculator
Work backward from value to a starting CPT bid for each ad-group type. Enter your inputs and leave the derived cells blank to compute yourself; do not guess the result.
- Estimated lifetime value per user (input)
- Target return on ad spend, e.g. 3 to 1 (input)
- Target cost-per-install = LTV / target ROAS (compute and write here)
- Expected conversion rate for this ad group (input %)
- Starting CPT bid = target CPI x conversion rate (compute and write here)
- CPA goal to set in the interface (usually at or near target CPI)
Checklist: Pre-Spend Bidding Gate
- I derived my target cost-per-install from lifetime value and a return target, not from a comfortable-feeling number
- Each ad-group type has a starting CPT based on its own expected conversion rate
- Brand bids are high enough to reliably win the slot; competitor bids are capped
- Every Broad and Search Match source has at least a starter negative list
- Each ad group is mapped to a Custom Product Page or the default, deliberately
- I will change only one lever at a time so I can read each result
Attribution, Reporting, and Optimization
Wire up attribution, read the five metrics that matter, and run a disciplined weekly loop.
Exercise: Attribution Readiness Check
Confirm how you will know which keyword earned each install, and what you can measure after the install. Write down the mechanism you rely on for each layer rather than assuming a tool does it.
- How will you capture install attribution (AdServices framework token to the Apple Search Ads Attribution API, directly or via a measurement partner)?
- What post-install events will you track through SKAdNetwork or AdAttributionKit (for example onboarding complete, trial start, subscribe)?
- Confirm in one line why a Search Ads install can be attributed without App Tracking Transparency consent.
- Who owns wiring this up (you, an SDK, or a mobile measurement partner), and is it done?
Worksheet: Diagnosis from the Metrics
For three keywords or ad groups, record the five core metrics and use them to name the single fix. Leave any rate or per-unit cost you have not pulled yet blank rather than estimating.
- Keyword / ad group
- TTR (taps / impressions)
- CR (installs / taps)
- CPT (cost per tap)
- CPA / CPI (CPT / CR)
- Diagnosis and one fix (ad problem / page problem / overbidding)
Exercise: Run One Weekly Loop
Do a full pass of the optimization loop on your account (or on paper if not yet live). Make a small number of deliberate changes and record them so next week you can tie any movement in CPA to its cause.
- Which keywords were above target CPA and had enough taps to act on, and what did you do (cut, pause, lower bid)?
- Which keywords beat target and were limited by low impression share, and by how much did you raise the bid?
- Which search terms did you graduate to Exact, and which did you add as negatives?
- What one test (a Custom Product Page or a new ad group) did you start, and what single variable does it isolate?
Checklist: Weekly Loop Discipline
- I waited for enough taps before judging any keyword a winner or loser
- I moved bids in small steps (roughly 10 to 20 percent), not large jumps
- I changed one lever at a time so every result is attributable
- I graduated converting search terms to Exact and negatived them in Discovery
- I scaled proven winners (budget, bid, more Custom Product Pages) before chasing new themes
- I logged every change with its date so I can read cause and effect next week
Your Action Plan
- Audit your three core searches on a real iPhone and confirm whether you or a competitor owns your top slots.
- Decide Basic or Advanced from your budget, time, and need for keyword-level control and Custom Product Pages.
- Optimize your App Store metadata first, since it drives both relevance in the auction and eligible keywords.
- Lay out four campaigns: Brand, Generic, Competitor, and Discovery, with tight ad groups inside each.
- Build your keyword seed list from your subtitle and keyword field, tagging each as head term or long-tail.
- Derive your target cost-per-install from lifetime value, then back into a starting CPT per ad-group type.
- Set up the discovery-to-Exact relay with Search Match and Broad in Discovery and graduation rules to performance.
- Build one Custom Product Page per major keyword theme and assign it to the matching ad group.
- Confirm attribution through the AdServices framework and the Attribution API, plus SKAdNetwork for post-install events.
- Run the weekly optimization loop: sort by CPA, cut waste, scale winners, graduate terms, and log every change.
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