Media Brief Template for Financial Services Paid Search Campaigns

Specify the product being advertised and its regulatory category: mortgage/home lending (TILA/Regulation Z, RESPA, Fair Housing Act — triggers Google Special Ad Category: Housing), consumer credit (ECOA, TILA — triggers Google Special Ad Category: Credit), insurance products (state-regulated, varies by state; TCPA consent required for leads), investment/wealth management (SEC/FINRA oversight), retail banking deposits/accounts (FDIC advertising signage rules), or fintech/digital banking (state money transmitter regulation). Product category determines which disclosure requirements apply and whether Google Special Ad Category restrictions will limit targeting.

For mortgage, consumer credit, auto loans, personal loans, and housing-related financial products, explicitly declare that the campaign will be set up under Google's Special Ad Category — which restricts targeting by age (18+ only, no upper age limit targeting), gender (all genders), marital status, parental status, and ZIP code (ZIP targeting restricted for housing ads). These restrictions cannot be bypassed and must be reflected in the audience strategy section of this brief. Any campaign that attempts to use restricted targeting for Special Ad Category products will be disapproved by Google.

Specify which regulatory disclosures must appear in ad copy or on the linked landing page: mortgage ads (APR disclosure required per Regulation Z if any rate or payment is mentioned — 'Representative APR 6.75%' format); personal loan ads (APR range, representative example — '9.99%–35.99% APR based on creditworthiness'); insurance ads (state-specific eligibility disclaimers); investment products ('Past performance does not guarantee future results' required by FINRA). Attach the compliance team's approved disclosure language for each ad type. Ad copy cannot be finalized without compliance sign-off on disclosure adequacy.

For mortgage, savings, and CD campaigns where advertised rates must reflect current market rates accurately, specify whether dynamic ad copy customizers will be used to update rates in real time or whether static rate ads will be refreshed manually. If using ad customizers, document the rate data feed format (XML/CSV from rate management platform), update frequency (minimum daily for mortgage rates), and the approval workflow for rate changes (does a compliance team member need to approve each daily rate update, or is there a pre-approved rate range within which changes can be auto-published?).

Document the keyword campaign architecture across four tiers: (1) Branded defense — brand name, product names, brand + product combinations (exact match, 90%+ impression share target, never pause); (2) Competitor conquest — '[competitor name] rates,' '[competitor name] mortgage,' '[competitor name] alternatives' (phrase and exact match, 50–75% impression share target); (3) Category non-brand — '[product type] rates,' 'best [product],' 'compare [product]' (phrase match, bid to target CPA); (4) Long-tail specific — specific rate queries, location-based, product-specific configuration queries (exact match, high intent, lower volume). Each tier requires separate campaign with distinct bidding and creative.

Attach the initial negative keyword list covering: legally ambiguous terms that could imply guaranteed outcomes or rates not currently offered; terms that attract non-qualifying audiences (students for retirement products; renters for home equity products); competitor brand terms excluded from the campaign tier (unless running conquest campaigns); and terms flagged by sales as consistently generating unqualifiable leads in past campaigns. Financial services companies that maintain compliance-reviewed negative keyword lists achieve 20–35% lower wasted click rates vs. companies relying on automated bid management alone.

Specify geographic targeting including any states where the financial product is not licensed, rate caps apply that affect competitiveness, or specific state consumer protection laws require additional disclosure in ad copy. Common carve-outs: Colorado, New York, New Jersey often require additional APR disclosure in mortgage ads; some states have more restrictive payday/personal loan advertising rules. Document state exclusions before campaign launch and configure state-level negative geotargeting accordingly — serving ads for unavailable financial products in states where you're not licensed is a regulatory violation.

Financial services paid search shows significant device-level conversion rate variations: mortgage and wealth management campaigns convert higher on desktop (complex forms, document upload requirements); consumer credit and digital banking campaigns convert comparably across mobile and desktop; auto loan and personal loan campaigns convert well on mobile (often simpler application forms). Specify device bid adjustments: recommended starting points for mortgage (desktop +30%, mobile -20%); for digital banking apps (mobile +20%); for auto insurance (mobile flat). Adjust based on actual conversion data within 30 days of launch.

Specify RLSA audiences for this campaign: abandoned application (website visitors who started but did not complete an application — bid multiplier +75–100%); product page visitors who did not convert (+40–60%); CRM customers who are cross-sell targets for new products (+30–50%); loyalty customers in renewal windows for insurance (+50–75%); prospects from prior application cycles who did not close (+60–80%). Define the membership duration for each list (90 days for mortgage consideration, 30 days for consumer credit, 180 days for wealth management), and specify exclusion list: current funded customers (suppress from new customer acquisition campaigns).

List Customer Match audience segments to be uploaded from CRM: (1) expired/lapsed customers eligible for winback (bid +50%), (2) current customers with cross-sell eligibility (bid +30%), (3) qualified leads who did not convert in prior cycle (bid +60%), (4) high-value prospect list from direct mail or partner channels (bid +40%). Specify hashed email upload format (SHA256), upload frequency (weekly for active leads, monthly for historical segments), and consent confirmation that all Customer Match contacts were collected with Google Ads-compliant consent for ad targeting.

Financial services paid search must track conversions beyond form completion: specify the full conversion event hierarchy and the value assigned to each. Example for mortgage: (1) Mortgage inquiry form start (micro, $0 value for bidding); (2) Form submission/pre-qualification (primary conversion, $50 value for Smart Bidding); (3) Soft credit pull / qualification (higher-value conversion, $150 value); (4) Application submission (highest on-site conversion, $300 value); (5) CRM offline import — funded loan (ultimate conversion, actual revenue value). Document the Salesforce or LOS (loan origination system) offline conversion import schedule and attribution window (90-day click for mortgage).

Specify the Smart Bidding strategy for each campaign tier: branded defense (Target Impression Share, target top position); competitor conquest (Target CPA, set at 50% of competitor keyword historical CPA); category non-brand (Target ROAS if sufficient conversion data — minimum 50+ conversions/month; otherwise Target CPA using form submit as primary conversion). Document the 30-day historical conversion volume per campaign at brief submission — if volume is below Smart Bidding minimums, specify the manual CPC or enhanced CPC strategy to use during the algorithm learning phase.

Specify primary performance targets: mortgage lead campaigns (cost per funded application target: $800–$2,500 depending on loan size — document this from LTV model); consumer credit (cost per funded account: $150–$400); insurance (cost per bound policy: $80–$250); wealth management (cost per qualified AUM conversation: $500–$2,000 depending on minimum AUM threshold). Branded campaign success metric: impression share (target 90%+), not CPA — branded campaigns are defensive investments measured by share captured, not cost efficiency.