01
Account & contact research
Claude reads the sources a rep would and writes a brief into the CRM: what the company does, why now, who to talk to, what to open with.
Claude for GTM
Claude, wired into the revenue stack
Most GTM teams use Claude as a chat window. The value is in the layer underneath: research that runs on every new account, qualification that reads the whole context rather than a form field, and agents that do the work between the tools. We build that layer with prompts, evaluations and guardrails you can audit.
Plain English
Why Claude for revenue work
Claude handles long context and structured output well, which is what GTM work needs: read a website, a CRM record, three call transcripts and a pricing page, then return a scored, formatted answer a workflow can act on. Via MCP it can also reach your systems directly (CRM, data warehouse, docs) so answers are grounded in your data instead of the open web.
What we build
How we work with Claude
Built in your environment, under your account, documented as it ships.
02
Qualification & scoring
Inbound and outbound leads scored against your real ICP definition, with the reasoning attached so a manager can check the call rather than trust it.
03
Message generation
Sequence copy and one-to-one messaging generated from the signal that triggered it, inside your voice guidelines. Reviewed, tested and measured, not sprayed.
04
MCP & tool access
Claude connected to your CRM, warehouse and internal docs through MCP so it answers from your systems, with permissions and logging in place.
05
Internal agents
Agents for the work between the tools: cleaning records, drafting handoff notes, summarising accounts before a QBR, watching for churn signals.
06
Evaluations & guardrails
Test sets, output validation, human-in-the-loop checkpoints and cost controls, so quality is measured rather than assumed.
How we implement it
From audit to a system that keeps running
01
Use-case selection
We pick the two or three jobs where AI actually pays: usually research, qualification and first-draft messaging. Everything else waits.
02
Prompt & context design
Your ICP, objections, positioning and history turned into structured context Claude can use consistently: the company brain, not a clever prompt.
03
Build & integrate
Wired into Clay, the CRM and the sequencer, with output validation and a human checkpoint wherever a customer sees the result.
04
Evaluate & tune
Scored against a held-out test set each cycle. Model choice, prompt and cost per run tuned as the tooling changes.
Questions
Claude, answered
RevenueHoop builds Claude into the revenue stack as an engineering layer: account and contact research written into the CRM, inbound and outbound lead qualification with the reasoning attached, signal-based message generation within your voice guidelines, internal agents for work between tools, and MCP connections to your CRM, warehouse and docs. Each comes with prompts, evaluations and guardrails you can audit.
Also from us
The rest of the stack
Clay engineering
Clay
Clay workflows, intent signals, CRM enrichment and the outbound campaigns that run on top of them. Built and maintained inside your stack.
ZoomInfo GTM Studio
ZoomInfo GTM Studio
For CROs who are already paying for ZoomInfo: turn Copilot, intent and GTM Studio into routed pipeline instead of another dashboard.