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Google Ads AI does not invent your business objective. You choose the campaign goal, conversion actions and, when appropriate, a target CPA or ROAS. Google’s systems then combine those instructions with campaign settings, account information, supplied creative, optional feeds, audience signals and auction context to predict which opportunities are most likely to produce the outcome you defined.
The exact data depends on the campaign and feature. Performance Max uses goal, asset, audience and feed inputs across Google inventory, while AI Max for Search uses existing search ads, landing-page content, assets and search-matching controls to tailor text and reach.
What Google Ads AI is actually trying to do
Google Ads AI is an optimization system, not an autonomous marketing planner. The advertiser selects the outcome that represents success, such as sales, leads or another conversion objective. In Performance Max, Google lets you choose conversion actions and optionally provide a target cost per action (CPA) or target return on ad spend (ROAS). Those settings define what the system should optimize toward. Google describes the AI as finding opportunities likely to achieve the selected outcome, not as deciding what the business goal should be.
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Consequently, “what data does the AI use?” has two answers: the information you provide to define and describe the campaign, and the contextual and performance signals Google uses to estimate results. Google’s help pages document examples of both, but they do not publish a complete inventory of every model input.
The main data categories Google documents
| Input category | Examples | How it is used |
|---|---|---|
| Goals and measurement | Campaign objective, conversion actions, conversion values, optional target CPA or ROAS | Sets the outcome and supplies the learning signal for automated bidding |
| Campaign and account information | Campaign settings, business name, URL, linked services and account-level assets | Provides context, recommendations, prefilled content and campaign configuration |
| Creative and destination material | Text, images, videos, landing-page copy, URLs and optional data feeds | Supplies material for ads, asset combinations and, in some features, generated text, images or videos |
| Audience guidance | Customer, visitor, app-user, video-viewer and Firebase lists; custom segments | Guides discovery of people who may be valuable; it is not necessarily a reach boundary |
| Auction and performance context | Query, device, location, time, language, browser, operating system, network partner, audiences and ad creative | Helps predict conversion probability and value for an individual opportunity |
These categories overlap. For example, an ad’s creative can be both an asset you supplied and a contextual signal used when a bid is calculated.
Goals, conversion actions and value data
You choose the objective
During setup, the advertiser selects the campaign goal and the conversion actions that count as success. For Performance Max, Google’s setup guide describes conversion goals and optional target CPA or ROAS settings. If a purchase, qualified lead or phone call is the action you mark as valuable, the system learns from those recorded actions rather than guessing a different definition of success.
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Google says Smart Bidding uses conversion data at query level across ad groups and campaigns. Where conversion values exist, the model can optimize for expected value instead of treating every conversion as identical. With cross-account conversion tracking, Google also says manager-account query-level data may contribute to learning. This does not mean every account automatically shares data; it describes a documented case in which the tracking configuration permits that learning.
Targets are instructions, not guarantees. A target CPA tells the system the cost level you want to pursue; a target ROAS expresses the return you want relative to ad spend. The AI still estimates which auctions are likely to meet the selected goal and adjusts bids as evidence accumulates.
Business and account information
Google’s getting-started flow can request a business name and URL and may offer connections to a Google Business Profile, YouTube channel, mobile app or Merchant Center account. The Performance Max setup documentation describes these business-information fields and account links as optional. Google says the information can help it understand the business, make recommendations and prefill content.
An optional link is not proof that every item in the linked service is always used as a model feature. Treat it as an available campaign input or source of assets and context when the selected feature calls for it. The fields and links shown in an account can also vary by campaign type, account state and current Google Ads interface.
Creative assets, landing pages and feeds
Performance Max asset inputs
Performance Max can use advertiser-supplied text, images and videos, along with campaign and account settings, bidding goals, audience signals and optional data feeds. Google’s Performance Max overview says its generative tools can combine supplied creative assets and generate images and videos. The generated material is therefore grounded in the assets and settings available to that campaign; it is not a replacement for defining the objective or supplying accurate business information.
AI Max for Search text customization
AI Max for Search is a Search-campaign feature set rather than a separate all-channel campaign. Its documentation says text customization can use existing ad text, landing-page copy and assets with generative AI to create ad copy tailored to a search. The source material matters: inaccurate or outdated landing-page language can give the system poor material to adapt.
Final URL expansion
When enabled in the relevant feature, Final URL expansion can select a relevant page from your domain based on the query and ad-group theme. This is a feature-specific behavior, not a claim that every Google Ads campaign automatically scans every page on a site. Review URL controls and the resulting destinations in the campaign interface before relying on the setting.
Audience signals guide discovery, but do not form a hard fence
Performance Max audience signals can include customer lists, website-visitor lists, app-user lists, video-viewer lists and Firebase lists. You can also create custom segments from interests, keywords, URLs or apps. Google’s audience-signal instructions explain how these signals are added, generally at the asset-group level.
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Operational requirements that can affect audience data
Google’s current instructions list several timing and eligibility conditions. New signal integration can take up to two weeks. New or changed lists may need 24–72 hours for audience-size updates. The instructions also list more than 1,000 active and eligible users and refreshing lists every 540 days. These are platform requirements stated by Google Ads Help and can change, so check the live documentation and your account’s eligibility notices before treating them as permanent rules.
Context used for each auction and query
Google’s automated-bidding documentation lists contextual signals that can influence a Smart Bidding decision. Examples include:
- The actual search query and the device used
- Geographic location, local time, day and date
- List-based audience membership
- The ad creative eligible to show
- Interface language
- Browser and operating system
- Search network partner
- App ratings and reviews, where relevant
Google emphasizes that signals can interact. A location by itself may not explain a bid; its effect can depend on the query, device, time, creative and the campaign’s historical conversion pattern. The published list is an example set, not a complete disclosure of every internal model input.
Performance Max and AI Max for Search are different systems
| Axis | Performance Max | AI Max for Search |
|---|---|---|
| Campaign scope | One goal-based campaign that can access Google inventory across channels | Feature set applied to a Search campaign |
| Inputs highlighted by Google | Goals, creative assets, audience signals, optional data feeds and account settings | Existing ads, landing-page copy, assets, URLs and search-term matching controls |
| Creative automation | Combines supplied assets; generative tools can create images and videos | Text customization creates search-tailored ad copy from existing material |
| Reach guidance | Audience signals and optional search themes guide discovery | Search-term matching uses broad-match, asset-based and landing-page-based technology |
| Controls and reporting | Campaign assets, settings and performance reporting | Text customization, Final URL expansion, URL controls, brand controls and asset/search-term reporting |
The distinctions come from Google’s Performance Max overview, Performance Max setup guide and AI Max for Search documentation. Do not transfer a control or behavior from one feature to the other without checking its documentation.
How to control the data Google Ads AI can use
- Define the outcome first. Select the campaign objective and the conversion actions that genuinely represent success. Remove or correct actions that should not drive optimization.
- Decide whether value-based bidding fits. Supply reliable conversion values if different conversions have materially different business value. Add a target CPA or ROAS only when the target reflects what you are prepared to pursue.
- Complete relevant business information. Add the business name and URL when requested, and link services such as YouTube, Google Business Profile, an app or Merchant Center only when they are accurate and useful to the campaign.
- Provide usable creative. Add current text, images and videos in the formats requested by the campaign. Check that claims, prices, branding and destinations match the landing pages.
- Choose feed and URL settings deliberately. Add a data feed when the campaign needs structured product or business information. If Final URL expansion is enabled, review URL controls and the pages it can select.
- Add audience signals as guidance. Use first-party lists and relevant custom segments where available, but plan for the possibility that delivery expands beyond them. Allow for list-processing and integration delays.
- Review generated and served material. Inspect asset combinations, generated images or videos, customized text, selected URLs and search-term or asset reports. Adjust or replace inputs that produce unsuitable results.
What Google does not establish in these documents
- Google does not publish a complete inventory of every internal model input, so the documented signal examples should not be presented as an exhaustive data-collection list.
- An advertiser-selected goal is not something the AI independently discovers. The system estimates how to achieve the goal you configured.
- An audience signal is not a guaranteed reach restriction in Performance Max.
- An optional linked account is not evidence that every record in that service is always used in every campaign.
- Performance Max asset generation and AI Max for Search text customization are feature-specific behaviors, not universal behavior across all Google Ads campaigns.
Google Ads feature names, defaults, controls, list requirements and campaign behavior can change. Before publishing time-sensitive instructions or making a live campaign decision, compare your account’s current controls with the relevant Google Ads Help pages.
Quick Recap
A practical review checklist
- Is the selected conversion action the business outcome you actually want?
- Are conversion values, CPA targets or ROAS targets based on reliable measurement?
- Do the supplied ads, images, videos and landing pages contain current, consistent information?
- Have you checked which optional feeds, linked accounts and URL-expansion settings are active?
- Are audience lists eligible, recently updated and large enough under the current Google requirements?
- Have you allowed time for new audience signals to integrate before judging delivery?
- Have you reviewed generated assets, customized text, selected URLs and search-term reports?
- Are you distinguishing documented examples of signals from Google’s undisclosed internal model details?
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