Observed Signal · Jun 5, 2026 · Research Report · Source: https://martech.org/feed/ · Impact: 3/5 · Sentiment: Negative
Report: Marketing Measurement Fails Amid Fragmentation
Bitly’s "The Marketing Visibility Report" (surveying more than 250 marketing professionals) finds that marketing measurement is increasingly fragmented: the average team uses six measurement tools but only 18% have a clear view of what works. Organic social is the most-used channel (72%) yet is also where visibility gaps are largest, followed by landing pages, paid social, search, and email. The report highlights that channel-specific metrics and disconnected tools prevent marketers from tying activity to business outcomes. Emerging phenomena — AI-generated answers, zero-click behavior, private sharing and "dark-funnel" activity — are creating more untracked interactions, while AI-driven campaign acceleration increases the volume of signals that teams must reconcile.
The report highlights persistent cross-channel measurement and attribution gaps that affect marketers' ability to prove ROI, which has medium industry impact for MarTech vendors, measurement platforms, and data/identity initiatives.
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Key Takeaways & Evidence Grounding
- Bitly published "The Marketing Visibility Report" based on a survey of more than 250 marketing professionals.
- The average marketing team uses six different tools to measure performance.
- Only 18% of marketers say they have a clear view of what is actually working.
- 72% of marketers report using organic social media, the most common channel.
- Marketers identify the biggest visibility gaps in organic social, dedicated campaign landing pages, paid social, search, and email.
Connected Companies & Entities
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Related Market Signals & Shifts
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Marketers Lose Trust in Measurement Amid Conflicting Signals
Industry figures Zach Epstein (founder of Haus) and Jon Humphrey (GM of Rokt Ads) tell The Drum that marketing measurement is failing because multiple platforms send overlapping data and claim credit for the same conversions. They argue that more data has produced conflicting signals, outdated budget inputs, and attribution that often reflects correlation rather than causation. The pair promote focusing on higher-quality, intent-confirmed environments (the 'Transaction Moment'), continuous incrementality testing and counterfactuals, and independent, causal data as prerequisites for trustworthy AI-driven marketing decisions. Haus claims its platform provides real-time signatures of incremental events to reduce insight-to-action lag.
B2B Marketers Lack Trust in Measurement Data
A new 10Fold study of 400 marketing and communications professionals across the U.S., U.K., France and Germany finds less than half (49%) are very confident in the accuracy and completeness of the data that informs B2B marketing budgets. Measurement still heavily influences budgeting across channels (e.g., paid social, paid media, owned content), but teams struggle to integrate data: only 35% have fully integrated reporting and 37% still use manual spreadsheets. The study also finds growing executive attention to downstream business outcomes and emerging AI-related metrics such as AI visibility and LLM citation tracking, though connecting those signals to revenue remains difficult.
Marketers Are Media Measurement's Biggest Problem
The article argues that marketers themselves are the primary obstacle to reliable media measurement, not just walled gardens. It claims agencies, brands, and platforms each configure measurement around their own goals, leading to fragmented data that fails to reconcile. The author recommends three changes: structuring campaigns from the outset to support multi-touch attribution (MTA), marketing mix modeling (MMM), and incrementality testing; adopting common industry taxonomies and standards such as those from IAB and IAB Tech Lab; and requiring independent certification or accreditation from bodies like the Media Rating Council. The piece warns that without a common language, AI will confidently scale flawed data. Marketers are urged to enforce standards in partner selection and funding decisions, making transparency and independent review routine requirements.
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