Rear-view attribution is flawed because markets, ICPs, and competitors constantly change. A more effective approach is to identify common traits among your best current customers and actively seek more prospects who fit that evolving profile.
Don't try to prove an event "caused" a deal. Instead, track correlation. Use a simple CRM checkbox to see if deals with event attendees have a higher close rate or velocity. This is a practical, low-stress way to gauge impact.
The battle over attribution isn't a personality conflict but a systemic issue. It's caused by measuring marketing on MQLs and sales on closed revenue. Unifying both teams under a single, shared revenue goal eliminates this friction and fosters collaboration.
As AI makes high-quality digital outreach easy to create, inboxes and call lists are saturated. Small, intimate, in-person events have become a non-scalable but highly effective way to cut through digital noise and build genuine relationships.
Forecasting accuracy fails when based on a seller's checklist of actions like "proposal sent." Instead, define sales stages by concrete buyer actions, like the number of stakeholders involved or if they've reviewed a proposal. This provides a more realistic view of a deal's health.
The market is evolving so rapidly, largely due to AI's influence on buyer behavior and competitive landscapes, that companies can't rely on a static product-market fit. It's now a continuous process of re-evaluation and adaptation every few months.
A deal forecast is weak if the rep can't articulate the champion's personal motivation. Managers should push beyond "they like the product" and ask what's in it for the individual (e.g., a promotion, solving a personal pain point). This uncovers true deal commitment.
Instead of brainstorming, Sales Assembly's CRO Matt Green actively listens to recurring peer-group calls with AEs, BDRs, and sales leaders. He turns their real-world problems, frameworks, and successes into a constant stream of highly relevant social media content.