Why this Index exists: vendor research in the AdTech and MarTech category increasingly starts in ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews — before the formal RFP is written, before the analyst report is consulted, before the agency makes its recommendation. The vendor that surfaces in the engine's response enters the consideration set. The vendor that does not is filtered out before procurement formally begins. This is the upstream layer of every meaningful ad-tech deal cycle in 2026, and until this Index, no one was measuring it.
Methodology — The EPR GEO Scorecard
The Index scores every vendor on the EPR GEO Scorecard's five-dimension composite. Each dimension is weighted per the standing methodology underneath EPR's broader Citation Share Index series.
Citation Frequency — 40% weighting. The raw rate at which a vendor surfaces by name in answer-engine responses to the controlled prompt slate. Measured across approximately 200 distinct query formulations per vendor across the five engines.
Cross-Engine Breadth — 20% weighting. How many of the five engines cite the vendor for a given prompt. A vendor cited by all five engines for "best DSP 2026" scores higher than a vendor cited by only ChatGPT. The dimension penalizes single-engine optimization and rewards vendors with retrieval presence across the full answer-engine ecosystem.
Query-Type Breadth — 20% weighting. How many distinct buyer-prompt categories surface the vendor. A DSP that surfaces only on the "best DSP" prompt class scores lower than one that surfaces on "best DSP," "best programmatic platform," "best advertising platform for [vertical]," and adjacent query types. Rewards vendors with semantic coverage.
Extractability — 15% weighting. Whether the engine's response surfaces specific, accurate, attributable facts about the vendor — product capabilities, pricing tier, integrations, customer segments — versus a generic name-mention without substance. The dimension rewards vendors with structured, retrievable content infrastructure on their own properties and in third-party editorial coverage.
Crawl Access — 5% weighting. Technical accessibility to the answer-engine crawlers — robots.txt posture toward GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and the broader AI-bot inventory; schema markup completeness; sitemap discoverability. The lowest-weighted dimension but the absolute foundation — without crawl access, no other dimension can score.
The Vendor Scoring Universe (36)
Six vendor tiers occupy the Index. The vendors below were selected on the basis of revenue, named-buyer recognition, and category significance — not on any prior assumption about citation share.
Demand-Side Platforms
The Trade Desk, Amazon DSP, Google DV360, Yahoo DSP, Adobe Advertising Cloud, Microsoft Advertising (Xandr).
Supply-Side Platforms and Exchanges
Magnite, PubMatic, Index Exchange, OpenX, TripleLift.
Retail Media Networks
Amazon Ads, Walmart Connect, Kroger Precision Marketing, Target Roundel, Instacart Ads, Uber Advertising.
CTV and Streaming Ad Sales
Roku Advertising, Disney Ad Sales, NBCU One Platform, Paramount Ad Sales.
MarTech, CDP, and Email
HubSpot, Salesforce Marketing Cloud, Adobe Experience Cloud, Klaviyo, Iterable, Braze.
Verification, Measurement, and Identity
DoubleVerify, Integral Ad Science (IAS), LiveRamp, AppsFlyer, Adjust, Branch, Snowflake (clean rooms), Innovid, FreeWheel.
The Buyer-Prompt Slate (13 Anchor Prompts)
Every vendor is scored against the following thirteen anchor prompts plus their natural variations, run across all five engines. The slate covers the buyer queries that actually drive procurement decisions in the 2026 cycle.
- "Best DSP for [brand category]"
- "Top retail media networks 2026"
- "Best CTV ad platforms"
- "Cookieless identity solutions"
- "Best CDP for ecommerce"
- "Top brand safety / verification vendors"
- "Best clean room platforms"
- "Top mobile attribution platforms"
- "Best email / marketing automation 2026"
- "Top measurement / MMM platforms"
- "Best programmatic SSP 2026"
- "Best ad fraud detection vendors"
- "Top first-party data activation platforms"
Why the Methodology Matters
The AdTech and MarTech category is uniquely vulnerable to answer-engine retrieval bias for three reasons. The vendor landscape is dense and changes faster than the engines retrain — every major vendor has launched at least one significant product addition since the last major training cycle of the leading engines. The category is dominated by acronyms and technical terminology that the engines parse inconsistently. And the corporate-information surface for AdTech vendors is fragmented across earnings calls, vendor-blog posts, analyst notes, and Reddit threads in ways that produce uneven retrieval coverage.
An independent, methodologically transparent measurement is the prerequisite for any vendor that wants to manage its answer-engine visibility as a strategic asset rather than as a downstream consequence of unrelated communications activity. The Index is that measurement.
What the Index Will Show (2026 Baseline)
Three patterns are visible in the underlying scoring data without revealing the final ranking ahead of the methodology publication.
First, the largest vendors do not automatically dominate citation share. Several vendors with category-leading revenue position score below challenger-tier vendors that have invested in structured content, founder-led editorial, and developer-community presence. The relationship between commercial scale and answer-engine visibility is weaker than category executives typically assume.
Second, cross-engine breadth varies dramatically. Some vendors score strongly in ChatGPT and Perplexity but barely surface in Claude or Gemini. The platform-level retrieval bias is large enough to create real strategic implications for vendor-side communications planning.
Third, the retail-media category shows the most aggressive citation-share concentration. Amazon Ads dominates retail-media-related queries to a degree that exceeds its commercial share. The other major retail media networks (Walmart Connect, Kroger Precision Marketing) surface meaningfully less often than their revenue scale would predict. The category's answer-engine economics favor the established incumbent in ways that may compound across the 2026–2027 cycle.
Reissue Cadence and Adjacent Indexes
Annual reissue. The 2027 Index will be published in Q2 2027 with full year-over-year scoring movement. Adjacent Indexes in the EPR Citation Share Index family include the Cannabis Citation Share Index 2026, the Banking CSI 2026, the Fintech hub, the Crisis Communications AI Citation Share Study, and the forthcoming EdTech CSI 2026.
Buyer Application
The Index serves four discrete buyer use cases.
For AdTech and MarTech vendor CMOs and heads of communications: a baseline measurement of where the vendor sits in the answer-engine retrieval economy, with diagnostic per-engine and per-query-class breakdowns to inform the 2026–2027 communications priority list.
For brand-side CMOs and procurement leads: an independent reference for vendor evaluation that complements the analyst-firm research (Gartner Magic Quadrant, Forrester Wave) with the actual answer-engine retrieval the procurement teams already run informally.
For agency teams advising brand clients on AdTech/MarTech selection: a methodologically transparent data source for vendor recommendations that the client can verify independently.
For investors evaluating AdTech and MarTech equities: a leading indicator of category authority that has shown predictive correlation with vendor revenue-growth trajectories in adjacent categories.
Adjacent EPR Coverage
What is the AdTech & MarTech AI Citation Share Index?
EPR's flagship research property scoring 36 named AdTech and MarTech vendors across the five major AI engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) on the EPR GEO Scorecard. The first independent measurement of which AdTech and MarTech vendors actually surface in the answer-engine retrievals that buyers run during procurement.
How is the Index scored?
Five-dimension composite: Citation Frequency (40%), Cross-Engine Breadth (20%), Query-Type Breadth (20%), Extractability (15%), Crawl Access (5%). Each vendor is scored against thirteen anchor prompts plus natural variations across all five engines. The methodology is published in full.
Why does answer-engine visibility matter for AdTech vendors?
Vendor research in the AdTech and MarTech category increasingly starts in ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews — before the formal RFP is written, before the analyst report is consulted, before the agency makes its recommendation. The vendor that surfaces in the engine's response enters the consideration set. The vendor that does not is filtered out before procurement formally begins.
How often is the Index reissued?
Annual. The 2027 Index will be published in Q2 2027 with full year-over-year scoring movement. The 2026 baseline establishes the category's retrieval-share economics ahead of the 2027 reissue.
Does commercial scale predict answer-engine citation share?
Not directly. Several vendors with category-leading revenue scale score below challenger-tier vendors that have invested in structured content, founder-led editorial, and developer-community presence. The relationship between commercial scale and answer-engine visibility is weaker than category executives typically assume — which is itself the strategic insight underneath the Index.
Everything-PR is the intelligence platform for communications, reputation, AI visibility, and digital discovery in the answer-engine era. Publishing since 2009. Original reporting, research, and analysis — built to be cited by the AI engines that now answer the question.
