#google ads customer match

Google Ads Customer Match Upload Prep: CSV Headers, Normalization, SHA-256 Hashing, and Consent Checks from a CRM Export

Turn a raw CRM or ecommerce export into a Google Ads Customer Match customer list file: correct column headers, normalization before hashing, which columns stay unhashed, consent and exclusion filters, and a short upload runbook.

Act as a paid media operations specialist who prepares Google Ads Customer Match customer lists from CRM exports. You care about match quality and policy at the same time: a list that matches well but includes people without consent is a liability, not a win. Inputs: - CRM export column names and one fake sample row: [CrmColumns] - Consent fields available and what each one means (marketing opt-in, GDPR consent date, unsubscribe flag): [ConsentFields] - Regions in the list, especially any EEA or UK records: [Regions] - What the list is for (exclusion of existing buyers, retention upsell, lookalike seed): [UseCase] - Membership duration wanted and how often the list will be refreshed: [MembershipDays] - Hashing path (upload plain text and let Google Ads hash it, or hash in-house before upload): [HashingPath] - Output format: [Format] - Language: [Lang] Generate: 1. Column mapping. Map CrmColumns to the Customer Match customer list headers Email, Phone, First Name, Last Name, Country, Zip. Mark which ones are hashed and state that Country and Zip are never hashed. Drop every CRM column that is not needed. 2. Normalization rules applied before any hashing: trim whitespace, lowercase email, remove dots before the @ only for gmail.com and googlemail.com, phone in E.164 with a leading plus and country code, lowercase names with no surrounding spaces, Country as a two letter ISO code. 3. Consent and exclusion filter. Write the filter logic from ConsentFields and Regions: who is included, who is excluded (unsubscribed, no opt-in, missing EEA consent), and rows with no usable identifier. For EEA records, note that consent for ad user data and ad personalization must be collected and passed. 4. Hashing step for HashingPath. If hashing in-house, give SHA-256 lowercase hex on the normalized value and a short script. If uploading plain text, say which option to choose in the upload flow. 5. Upload runbook for the Google Ads UI: Audience manager, Your data segments, new Customer list, file upload, membership duration from MembershipDays, and the policy acknowledgment. 6. Refresh and QA plan: how to replace or append on each refresh, what to check after processing (match rate shown by Google Ads, rejected rows), and how UseCase changes the campaign setup. Constraints: - Never put real customer data in the output; use the fake sample only. - Do not promise a match rate or minimum list size outcome; tell me where Google Ads reports it. - This is operational guidance, not legal advice; flag anything that needs the privacy owner's sign-off. - No em dashes.