After 15 years running demand gen at Snowflake, Twilio, and Mastercard, and now helping SaaS companies implement ABM + AI, here's what I keep seeing:

Most revenue teams are drowning in "intent data" that leads nowhere.

The problem isn't the data — it's the framework.

Here's a 3-step fix I use with every client:

1. Signal stacking over single-source intent

Stop relying on one intent provider. Layer 6Sense signals with LinkedIn engagement, CRM activity patterns, and website behavior. One signal = noise. Three+ signals = a buying committee in motion.

2. Contact-level targeting, not account-level

"Company X is in-market" means nothing if you don't know which 4-6 people in the buying committee are engaged. Map contacts to personas, then sequence by role — not by account.

3. AI-accelerated personalisation at scale

Use AI to generate role-specific messaging based on the account's actual tech stack, recent hires, and financial triggers. Generic "we help companies like yours" emails are dead.

Teams implementing this framework are seeing 2-4x higher engagement and 50%+ faster deal cycles compared to traditional ABM.

If you're a revenue leader at a B2B SaaS company and want weekly playbooks like this — plus the frameworks, templates, and a community of operators actually running these plays — I built the Revenue AI Inner Circle for exactly that.