Most Adobe Marketo Engage instances do not fail all at once. They slowly drift out of alignment with how enterprise buyers actually behave. The symptoms usually show up in familiar ways: MQL volume looks fine, but pipeline quality is flat; scoring rules are still based on old assumptions; data hygiene keeps slipping; and email performance […]
In 2026, enterprise B2B teams with Marketo-heavy stacks are removing outdated rule-based lead scoring in favor of AI-powered predictive models. These AI-driven models analyze historical outcomes and multiple signals (behavioral, firmographic, intent, etc.) to identify the leads and accounts that are most likely to convert. This shift is critical because, as Gartner cautions, “demand generation […]
AI-generated demand is becoming a new layer in enterprise vendor discovery. Buyers are no longer starting only with search engines, peer recommendations, or vendor websites. They are increasingly asking LLMs like ChatGPT, Claude, and Gemini for vendor recommendations, category comparisons, implementation guidance, and shortlists. That changes how demand is created, how trust is built, and […]
B2B revenue teams are moving beyond individual lead scoring to focus on the full buying group. If you want to make that shift without rebuilding everything from scratch, this guide is for you. What This Guide Covers B2B marketing and sales teams have spent years chasing MQL volume. The logic was simple: more Marketing Qualified […]
Executive Summary Marketing technology investment is entering a new phase in 2026. Adoption is accelerating, but so is failure. Enterprise teams are no longer struggling with access to tools — they are struggling with selection, integration, and measurable impact. Key market signals shaping this shift: Over 70% of enterprise MarTech stacks are underutilized or redundant, […]
Executive Summary Marketing leaders are entering 2026 with a clear constraint: budgets are not growing, but expectations are. Enterprise benchmarks show that marketing budgets have stalled at around 7.7% of company revenue, while many CMOs still report that available budget is not enough to execute their strategy. At the same time, boards and CEOs continue […]
Generative AI is now part of how enterprise marketing works. Most teams already use it for content, campaigns, and analysis. But very few can clearly show how it improves pipeline, revenue, or forecasting. The problem is not adoption. It is control. AI creates value when it is used inside clear workflows, clean data systems, and […]
Marketing Mix Modeling (MMM) vs attribution is a revenue decision. In 2026, marketing leaders are evaluating what drives incremental revenue, improves efficiency, and strengthens forecast reliability. Attribution models can still report performance, but they often fall short in explaining revenue outcomes with the level of confidence required for budget allocation and executive alignment. MMM is […]
Artificial intelligence is rapidly moving from experimental marketing technology to operational infrastructure inside enterprise marketing organizations. Most teams now use AI for segmentation, content production, analytics, or campaign automation, yet relatively few can connect AI adoption to measurable improvements in pipeline quality, revenue growth, or forecasting reliability. The difference is rarely the technology itself. It […]
Why Attribution Is No Longer a Reporting Problem In 2025, attribution stopped being a downstream reporting exercise and became a decision dependency. Boards, CFOs, and revenue leaders began using attribution outputs to justify budget allocation, headcount, channel investment, and GTM strategy. When attribution failed, it slowed decisions, weakened confidence in forecasts, and forced leaders to […]
