Observed Signal · Aug 27, 2026 · Analysis · Source: The Drum · Impact: 2/5 · Sentiment: Positive
B2B measurement: Five areas to fix GTM data
The article argues that B2B go-to-market (GTM) measurement often creates an "illusion of certainty": precise dashboards and platform-attributed conversions can mislead decision-makers because they favor easy-to-capture signals over long-term drivers. Andy Hasselwander, chief analytics officer at Marketbridge, recommends assessing measurement maturity across five areas — Data, Systems, Methods, Reporting, and Organization & Communication — and adopting multiple causal and counterfactual methods (e.g., MMM, incrementality) to provide more accurate answers when CFOs demand evidence of marketing contribution. Marketbridge offers a measurement maturity workshop to help firms identify foundational gaps.
Addresses B2B measurement practices and encourages adoption of causal methods and integrated data systems, which affect budget accountability and marketing investment decisions but is not a platform-level policy or major industry shift.
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Key Takeaways & Evidence Grounding
- The article identifies five measurement maturity areas: Data, Systems, Methods, Reporting, and Organization & Communication.
- Andy Hasselwander is quoted as chief analytics officer at B2B growth company Marketbridge.
- The piece recommends moving beyond proximity-based metrics (MQLs, platform-attributed conversions) toward causal and counterfactual methods such as marketing mix modeling and incrementality testing.
- Marketbridge is offering a B2B Performance Measurement Maturity Workshop (linked in the article).
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Long B2B Sales Cycles Hinder Measurement
Long B2B sales cycles — sometimes months, years, or longer — create major challenges for marketing attribution, optimization, and proving ROI. The author argues that tracking microjourneys (website visits, downloads, webinars) provides faster measurement but has limits because those signals often do not measure quality or purchase likelihood. He recommends eliminating vanity metrics and building better models that assess fit, likely purchase value, and customer quality rather than simply counting raw events. The piece is authored by Mike Maynard, Managing Director of Napier, and published on MarTech (owned by Semrush).
Bad Data Breaks B2B Go-To-Market Engine
The article explains how poor data quality in B2B marketing creates misleading ‘high-intent’ signals that distort pipelines, damage sales execution, and erode cross-functional trust. Outdated records, failed lead-to-account mapping, inflated intent spikes from bots/crawlers, and buyers moving to hard-to-track channels (LLMs, Slack, private groups, events, dark social) contribute to missed opportunities and inaccurate forecasts. The piece argues incremental fixes to legacy intent systems are insufficient and advocates redesigning the go-to-market (GTM) architecture around "agentic" intelligence: autonomous AI layers that synthesize buyer-level, cross-platform signals to deliver validated, actionable outreach for marketing and sales. The article frames agentic marketing as a path to restore trust and alignment across GTM functions and signals a follow-up installment on implementation details.
Attribution Limits B2B Growth, Urges Broader Investment
Chris Bagnall, CEO & Founder of Transmission, argues that an overreliance on tidy attribution metrics (especially last-click) constrains B2B marketing growth by diverting budget toward immediately measurable touchpoints and away from brand, community, and creator work that drives future demand. The piece cites research from Gartner, Forrester, McKinsey and Brand Finance to show most of the B2B buying journey occurs out of view of dashboards and involves multiple decision-influencers. Bagnall recommends broader measurement — including account-based attribution platforms (e.g., Dreamdata), incrementality/holdout tests, marketing-mix modelling, brand tracking, and self-reported attribution — and argues businesses should fund activities they cannot fully trace.
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