Google Ads is rolling out two updates for advertisers with brick-and-mortar locations: Local Customer Optimization for Performance Max campaigns and a simplified Store Sales integration via Google Ads Data Manager. Both features aim to close the loop between digital ad spend and in-store customer activity, and both are arriving just ahead of the Q4 holiday shopping season, when the gap between online research and in-store purchasing tends to be at its widest.
What Is Local Customer Optimization in Performance Max?
Local Customer Optimization is a new campaign-level toggle within Performance Max campaigns set to store goals. When enabled, Google’s system prioritizes showing ads to people who are physically near a business or actively searching for nearby services, and who appear ready to act immediately, such as visiting a store, requesting directions, or calling the location.
According to Google’s support documentation, the feature draws on signals from users who are navigating, trip-planning, or searching for locations across Google Maps, Waze, and local formats on Google Search. Advertisers can enable it when creating a new Performance Max campaign optimized only for offline goals, or activate it under the “Budget and bidding optimization” settings of an existing eligible campaign.
Several compatibility limits apply before enabling the setting, per Search Engine Journal and Google’s own support documentation:
- Not compatible with online conversion goals. Turning on Local Customer Optimization disables the ability to add online goals to the same campaign. To restore online goals, the toggle must first be switched off.
- Not compatible with Merchant Center-linked product feeds. Performance Max campaigns that advertise products from a linked Merchant Center account cannot use this setting, even if the toggle is turned on.
- Requires a separate campaign structure. Retailers running feed-based Performance Max campaigns cannot simply enable the feature within those campaigns. A separate campaign focused exclusively on offline store goals is required.
Google says Local Customer Optimization is rolling out globally, per Search Engine Journal citing Ginny Marvin’s LinkedIn announcement.
What Is Changing with Store Sales in Data Manager?
The second update simplifies how eligible advertisers import offline transaction data into Google Ads. Store Sales in Google Ads Data Manager will allow advertisers to connect existing sales records from sources such as a CRM (customer relationship management system) or Google Sheets directly within their Google Ads account, without a separate technical integration.
According to Search Engine Journal, Store Sales measurement links purchases made at physical locations to prior ad interactions, enabling both reporting and Smart Bidding (Google’s automated bid system) optimization. Advertisers can use this data to optimize toward in-store sales or include offline revenue alongside online conversions.
Google already supports several methods for uploading first-party store sales data, including manual and scheduled uploads, the Google Ads API, and approved store sales partners. The new Data Manager path is designed to reduce the technical overhead of maintaining that connection.
Store Sales in Data Manager is expected to begin rolling out at the end of September, per Search Engine Journal.
Who Actually Qualifies for Store Sales?
Not every advertiser with a physical location will gain access automatically. Google limits Store Sales capabilities to eligible or allowlisted advertisers. Depending on eligibility, an advertiser may receive store sales counts, default-based values, or dynamic values tied to uploaded transaction data, according to Google’s Store Sales documentation.
For advertisers who qualify and upload first-party transaction data, Google requires customer information to be hashed (converted into anonymized codes so raw personal data is never shared) before use. Accepted identifiers include email addresses, phone numbers, and physical addresses. Google Ads can apply SHA-256 hashing (a standard one-way anonymization method) to unhashed data during the upload process.
Google recommends uploading transaction data daily or weekly. Transactions from the previous 30 days are required for dynamic conversion value reporting; data from the previous 14 days is specifically recommended for accurate results, per Google’s support documentation.
What This Means for AI-Search Visibility
The practical takeaway is this: businesses that don’t feed Google their offline sales data are working with a partial picture, and Google’s automated systems, including those that increasingly power AI-driven local discovery, are increasingly shaped by how much verifiable real-world activity they can see.
Here is a concrete example. Imagine two coffee shops in the same neighborhood running similar ad budgets. One uploads weekly transaction data showing 400 in-store purchases per week linked back to ad interactions. The other relies solely on online conversion signals. Google’s Smart Bidding algorithm has far more to work with for the first shop, and will likely allocate budget more efficiently toward the moments that actually drive foot traffic. That same behavioral data, over time, also feeds into the local relevance signals that inform how AI assistants and AI-powered local search tools decide which businesses to surface in response to queries like “coffee shop near me open now.”
This is Hingewise’s assessment, not a claim made by either source: the offline data loop is not just a reporting improvement. It is a signal completeness problem. AI-powered search and discovery tools, whether inside Google or third-party AI assistants, increasingly favor businesses whose real-world activity is legible to automated systems. A business that is active offline but invisible in its conversion data is, from the algorithm’s perspective, less active than it actually is.
One structural point worth flagging: Local Customer Optimization cannot coexist with online conversion goals or Merchant Center feeds in the same campaign. For most retailers running integrated online-offline campaigns, this means maintaining separate campaign structures rather than a unified approach, which adds complexity to account management.
The timing ahead of Q4 is deliberate on Google’s part. Holiday season is when online-to-offline conversion paths are densest, making offline signal quality especially consequential for Smart Bidding decisions. Advertisers who have not yet reviewed their Store Sales eligibility or data upload cadence before October may find themselves entering the highest-stakes period of the year with incomplete bidding inputs.
Quick Checklist Before Enabling These Features
- Confirm your Performance Max campaign is set to store goals only, not mixed online/offline goals, before enabling Local Customer Optimization.
- Check whether your campaign is linked to a Merchant Center product feed. If yes, Local Customer Optimization requires a separate campaign.
- Verify your account’s Store Sales eligibility before building reporting or Smart Bidding strategy around offline conversion data.
- Ensure all customer data uploaded for Store Sales is hashed (email, phone, address) or flagged for Google to hash using SHA-256 during upload.
- Set a recurring upload cadence of daily or weekly to keep conversion data current.
- Maintain at least 30 days of transaction history to unlock dynamic conversion value reporting.
- Review existing Smart Bidding conversion goals before adding store sales actions to avoid unintended shifts in how the algorithm allocates budget.
What to Watch Next
Store Sales in Data Manager is expected to begin rolling out at the end of September. Advertisers currently using manual or API-based offline conversion uploads will want to evaluate whether the Data Manager path reduces their operational overhead. Local Customer Optimization is already in global rollout, but its practical impact will be clearest for businesses whose primary objective is immediate foot traffic rather than blended online-offline demand generation. Whether the separated campaign structure proves manageable for advertisers running both goals simultaneously is the operational question most worth monitoring as both features become widely available.
Sources: Search Engine Journal; Google Ads Help: Local customer optimization.
This article was drafted with AI assistance from the sources cited above and checked against them before publishing. The "What this means for AI-search visibility" section is Hingewise's editorial analysis, built on the frameworks and positions we use in our GEO work. How we work: Editorial policy.