A Live Walkthrough of My AI-Assisted GTM Workflow
Deciding where to concentrate GTM resources should be a data problem, but in practice it's a coordination problem: the signals live in systems that don't talk to each other. Account revenue and hierarchy sit in Salesforce, product adoption sits in amplitude, customer context in Backstory, delivery risk in Jira, internal strategy in Slack, and market context—company size, customer-facing headcount, tech-stack maturity—in public sources. Pulling these into one defensible tiering model used to mean weeks of back-and-forth across sales, CS, product, and ops.
I'll walk through how I ran that entire analysis myself, using Claude to pull from and reconcile across those tools, and produced a four-tier account model (A–D) with revenue projections for our exec team in days. This is a working session, not a slide tour: I'll show the real backend, where the automation carried the load and what I scrapped between iterations—so you can rebuild the pattern against your own stack.
Why it mattered: the model let us reprioritize our resources and staffing to align with and concentrate on the small set of accounts with the most headroom that pave the path to our revenue targets. The transferable part is the workflow itself—a single operator with a few connected tools doing what used to need a cross-functional team and a month of calendar time. You'll leave with the specific sequence: which tools, in what order, and where a human still has to make the call.

Sr. Manager, Customer Success
Backstory