A new study from the Affinity Solutions Outcomes Marketing Council suggests that many brands and agencies are still optimizing campaigns without verified purchase data, exposing a widening measurement gap across modern advertising. The findings arrive as marketers increase investment in AI-powered optimization, retail media, and performance advertising while struggling to connect media spend to actual business outcomes.
A growing number of marketers are making campaign optimization decisions without access to verified purchase data, according to new research released by the Affinity Solutions Outcomes Marketing Council. The report found that 80% of brand and agency marketers primarily optimize campaigns using signals other than real-time verified sales data, while 35% said those optimization decisions ultimately “don’t hold up” when reconciled against actual purchase outcomes.
The study highlights a broader measurement crisis emerging across digital advertising, retail media, and AI-driven marketing ecosystems as brands face mounting pressure to prove return on ad spend (ROAS) and customer acquisition efficiency.
According to the research, marketers continue relying heavily on proxy signals such as attributed conversions, modeled performance outputs, engagement metrics, and platform-reported analytics because verified transaction data often arrives too slowly for real-time optimization.
That lag is becoming increasingly problematic as advertising platforms accelerate automation and AI-powered campaign management.
Modern marketing systems across Google, Meta, Amazon Ads, The Trade Desk, Adobe, and Salesforce increasingly depend on machine learning models to automate bidding, targeting, audience segmentation, and media allocation decisions. However, many of those systems still optimize against incomplete or delayed performance signals.
The report suggests the disconnect is creating significant operational inefficiencies across the advertising ecosystem.
“Marketing is still optimizing against signals that are too slow, fragmented, and disconnected from actual sales,” Affinity Solutions Chief Commercial & Marketing Officer Damian Garbaccio said in the study announcement.
The findings reinforce a growing industry concern that marketing attribution systems built for earlier digital advertising environments are struggling to keep pace with fragmented customer journeys, privacy changes, and AI-driven media buying systems.
According to MarTech.org’s 2026 State of Data analysis, 75% of marketers say their current measurement systems are failing to deliver the speed, trust, or accuracy needed to connect media investments to business outcomes.
The pressure is especially acute in retail media and performance advertising.
Brands are increasingly shifting budgets toward commerce media networks, connected TV, influencer campaigns, and omnichannel customer engagement strategies. Yet many attribution systems remain heavily dependent on legacy tracking models that were not designed for today’s fragmented media landscape.
The Affinity study also found that nearly two-thirds of marketers reported three or more operational steps between a customer transaction and a campaign optimization decision, increasing latency and reducing data quality.
Industry analysts say those delays can significantly affect campaign performance in fast-moving advertising environments where bidding, audience targeting, and creative optimization increasingly happen in near real time.
The rise of AI-generated search experiences and automated recommendation engines is adding further complexity.
Brands are now competing for visibility not only across traditional search engines and social platforms, but also inside AI-driven discovery environments such as ChatGPT, Google Gemini, Claude, and Perplexity. Those systems rely heavily on structured data quality, verified outcomes, contextual relevance, and authoritative signals when surfacing recommendations.
At the same time, marketers are under pressure to reduce wasted advertising spend.
According to additional findings cited in the report, 91% of marketers believe platform-reported advertising results are overstated to some degree, reinforcing concerns around attribution inflation and unreliable optimization metrics.
The broader challenge reflects a structural shift happening across modern marketing infrastructure.
Third-party cookie deprecation, privacy regulations, signal loss from mobile platforms, and fragmented customer journeys are forcing brands to rethink how advertising effectiveness is measured. Many organizations are now investing in first-party data infrastructure, retail media analytics, AI-driven measurement platforms, and marketing mix modeling (MMM) to rebuild more reliable attribution systems.
Industry conversations around incrementality testing and verified outcome measurement are also accelerating.
Major advertisers increasingly want direct proof that campaigns generated measurable business impact rather than simply correlating with engagement metrics or modeled attribution outputs.
That trend is reshaping enterprise martech stacks.
Platforms capable of integrating verified transaction data, customer identity systems, AI optimization tools, and real-time analytics are becoming increasingly valuable as brands seek more reliable campaign intelligence.
Research from Supermetrics similarly found that campaign optimization remains one of the least mature AI adoption categories despite widespread enterprise investment in artificial intelligence across marketing operations.
The Affinity Solutions report ultimately underscores a growing reality for enterprise marketers: AI-powered advertising systems are only as effective as the quality and accuracy of the underlying data feeding them.
As marketing automation becomes more autonomous, verified purchase intelligence may increasingly become the competitive differentiator separating efficient advertising systems from expensive optimization guesswork.
