MQL Is Dead: What Replaces It in 2026

MQL failed despite marketers believing in it. It failed because the number stopped predicting revenue, with Forrester research showing fewer than 1 percent of leads ever close. This piece lays out the three capabilities replacing the MQL in 2026, AI propensity scoring, account-level attribution, and pipeline contribution, and shows why each one measures buying behavior instead of form-fill activity. Grounded in anonymized customer evidence and RevSure's own State of B2B Attribution data, it positions the Full Funnel Data Graph as the layer that makes the new measurement system hold up in a board meeting.

RevSure TeamJun 23, 202612 min read

Product Features

RevSure Marketing Attribution Trends Widget: Understanding How Channel Contribution Shifts Over Time

RevSure's Attribution Trends Widget introduces a time-based layer to marketing attribution analysis, allowing teams to track how channel and campaign contributions to pipeline and revenue shift across periods. By surfacing attribution patterns over time rather than as static snapshots, organizations gain the ability to identify high-performing channels earlier, detect emerging shifts before they affect outcomes, and make budget allocation decisions grounded in longitudinal performance data rather than point-in-time reporting.

RevSure TeamMay 20, 20268 min read

Pipeline

Measuring Agentic ROI: How to Attribute Pipeline Impact to Specific Actions

This blog explores why traditional attribution models fail in modern, system-driven GTM environments. It introduces a new approach to measuring ROI based on contribution, state changes, and execution flows rather than isolated touchpoints. The article explains how pipeline is shaped by coordinated actions across the funnel and how RevSure enables visibility into these relationships through its AI Engine and full-funnel AI agents. It helps revenue teams understand what actually drives pipeline efficiency and how to improve it.

RevSure TeamMay 4, 20267 min read

Marketing

RevSure Brings Data Science to Marketing with Difference-in-Differences (DiD)

RevSure applies Difference-in-Differences (DiD) to help marketing teams measure true incremental impact. By comparing treatment and control groups over time, DiD isolates causal lift and removes bias from seasonality and market-wide trends. This enables revenue teams to move beyond attribution dashboards and prove real pipeline and revenue contribution.

Harry HawkMar 4, 20264 min read

Marketing

Email Marketing in 2025: From Inbox Tactics to Boardroom Outcomes

Email marketing in 2025 is no longer judged by opens and clicks; it’s judged by its impact on CAC, LTV, pipeline velocity, and forecast accuracy. AI personalization, privacy-first compliance, and interactive mobile-first formats are transforming it from a tactical channel into a strategic driver of predictable revenue. The blog shows how leaders can tie email directly to boardroom KPIs and how RevSure helps measure its real contribution to the pipeline and forecasting.

RevSure TeamSep 12, 20257 min read

Pipeline

Pipeline Projection Made Predictable with RevSure

Struggling to predict marketing’s pipeline contribution? This blog breaks down how to replace guesswork with data, tracking conversion rates, velocity, and leakage, while layering in AI-driven insights. Discover how RevSure turns unpredictable pipeline into confident, revenue-backed forecasts.

RevSure TeamFeb 23, 20234 min read