Ad Analytics

Ad Analytics measures sponsored placements in AI shopping answers: your ad appearances, share of voice, competing advertisers, and the creatives that actually get surfaced across ChatGPT, Google AI Mode, and Copilot.

Sponsored placements you can measure like organic visibility

The Ad placements tab aggregates shopping items and sponsored ads detected across ChatGPT, Google AI Mode, and Copilot. Track Your Ad Appearances, Runs with Ads, Own Share of Voice, advertisers observed, and which queries produce ads — then open listings and advertiser drill-downs for proof.

Sponsored ads in AI shopping answers

ChatGPT, Google AI Mode, and Copilot surface sponsored advertiser placements alongside organic picks. Rankscale captures those ad cards for your tracked queries so paid placements are no longer a blind spot.

Own share of voice vs advertisers

See Your Ad Appearances, Runs with Ads, and Own Share of Voice next to an advertiser leaderboard ranked by observed appearances — keyed by destination domain.

Query breakdown and trends

Know which search terms produce ads, how many advertisers show up, and how appearance rates move over time when you drill into an advertiser or query.

Creatives and run evidence

Inspect sample listings and recurring ad items (title, creative, destination, average position), then open recent runs to QA what was actually shown.

Three views teams use every week

Brand-level Ad placements, advertiser detail, and per-search-term Ads Analysis — the same surfaces captured in the screenshots below.

Ad placements overview

Brand-level Ad placements tab with KPIs, advertiser rankings, sample listings, and a query breakdown for ChatGPT, Google AI Mode, and Copilot.

Advertiser detail

Drill into a competitor advertiser for appearances over time, engine distribution, query distribution, and query-level appearance rates.

Search-term Ads Analysis

Per-query Ads Analysis with ads captured, detection rate, providers, destinations, and recurring ad items ranked by repeat appearances and average position.

Key capabilities

Own share of voice for ads

See Your Ad Appearances, Runs with Ads, Own Share of Voice, Advertisers observed, and Queries with Ads in one KPI row so paid AI visibility is measurable, not anecdotal.

Advertiser leaderboard + drill-down

Rank advertisers by observed appearances, then open any domain for appearance trends, engine mix, query distribution, and per-query rates.

Listings, creatives, and run evidence

Inspect sponsored listings with branding and destination, then jump to recent runs or a search-term Ads Analysis view for recurring items, average position, and provider overview.

Why use Ad Analytics?

Turn sponsored AI placements into the same class of reporting you already expect from organic shopping visibility: KPIs, competitor drill-downs, and creative-level evidence.

Count what was actually shown

Served-but-not-shown placements are noted for information and never counted toward appearance KPIs, so share of voice stays tied to ads that surfaced.

Same Shopping & Ads workflow

Ad placements lives next to Overview, Merchant Cockpit, and Product Cockpit with the same engines, topics, tags, queries, and date-range filters.

Evidence for paid and brand teams

Exportable listings, provider overviews, and run links give SEM, brand, and GEO stakeholders proof of who won the sponsored slot.

Frequently Asked Questions

01 What is Ad Analytics in Rankscale?

Ad Analytics measures sponsored placements surfaced by AI shopping and GUI engines for your tracked queries. You get brand-level KPIs (your ad appearances, runs with ads, own share of voice, advertisers, queries with ads), an advertiser leaderboard, sample ad listings with creatives, and a query breakdown that links back to original executions.

02 Which engines does Ad Analytics cover?

The Shopping & Ads Ad placements view aggregates sponsored placements detected across ChatGPT, Google AI Mode, and Copilot for your monitored queries and date ranges.

03 What does Own Share of Voice mean for ads?

Own Share of Voice is your brand’s share of all observed ad appearances in the selected window (for example, 1 of 1,048 appearances). It sits alongside Your Ad Appearances, Runs with Ads, Advertisers observed, and Queries with Ads so paid AI visibility is comparable over time.

04 Can I inspect a single advertiser or search term?

Yes. Click an advertiser for appearance trends, engine distribution, query distribution, and per-query rates. Open a search term’s Ads Analysis view for ads captured, detection rate, unique ads, providers/stores, destinations, a provider overview, and recurring ad items ranked by repeat appearances and average position.

05 What are “not rendered” or non-rendered listings?

Some engines serve ad placements that are hidden or not shown in the final answer. Rankscale notes served-but-not-shown placements for information and never counts them toward appearance KPIs, so leaderboards and share of voice stay based on ads that were actually surfaced.

06 How is Ad Analytics different from Shopping Analysis?

Shopping Analysis measures organic product, brand, and merchant visibility in AI commerce answers. Ad Analytics focuses on paid placements inside the same Shopping & Ads workflow: who runs sponsored ads, whether your ads appear, share of voice, and creative-level evidence.

07 Is there a free trial?

Yes. You can try the Pro plan free for 7 days with a limited credit allowance, so you can explore Ad Analytics alongside Shopping Analysis and the rest of Rankscale before committing. The trial converts to a paid Pro subscription only if you choose to continue, and you can cancel anytime from your account settings.