Revenue operations juggle forecasting, attribution, pipeline hygiene, and reporting across dozens of tools. Agentic automation helps by assigning AI copilots to watch data quality, generate insights, and kick off workflows instantly.
This cockpit playbook outlines how to stream data into a central layer, assign analyst agents, and publish daily briefings that help GTM leaders act faster. Perfect for teams burned out on manual spreadsheet updates.
Key outcomes from this playbook
Marketing, sales, and success metrics roll into one trusted board with agent-authored commentary.
Agents pull data, explain trends, and flag anomalies before the weekly stand-up.
Every test logs hypothesis, owner, status, and impact automatically.
Agentic blueprint
Phase 1: Build the telemetry layer
Pipe CRM, marketing automation, product analytics, and finance data into a warehouse with a shared key.
- Standardize account and opportunity IDs across tools.
- Model pipeline stages, attribution touchpoints, and product usage in dbt.
- Expose clean datasets to downstream agents via SQL or semantic layer.
Phase 2: Assign cockpit agents
Create analyst-style agents for forecasting, hygiene, and experimentation.
- Forecast Agent: updates scenarios, compares to target, and highlights risk accounts.
- Hygiene Agent: flags duplicate records, stale stages, and missing fields.
- Experiment Agent: records A/B tests, spend, and lifts, pinging owners for updates.
Phase 3: Publish the cockpit
Ship a Looker, Hex, or Retool app that displays top metrics plus agent commentary.
- Add tiles for pipeline, win rate, CAC, payback, and activation.
- Include Slack or email digests summarizing the past 24 hours.
- Log every insight and task so humans can audit recommendations.
Rapid launch checklist
List every system contributing to pipeline or revenue along with owners and refresh SLAs.
Document the five questions leadership asks weekly, then align agents to answer them automatically.
Have agents write short commentaries explaining metric changes before building the UI.
Launch to RevOps first, then extend access to sales, marketing, and finance once accuracy is proven.
Metrics to watch
Percent of agent recommendations actioned by GTM owners.
Number of duplicate or incomplete records remaining after daily sweeps.
Gap between agent forecast and actuals. Target under five percent variance.
Days from test launch to published readout, shrinking as automation improves.
Suggested toolkit
Snowflake or BigQuery paired with dbt for governance.
Looker, Hex, or Retool for cockpit visualization.
OpenAI GPT-4o, Claude 3.5, or Llama 3 with LangGraph orchestration.
Slack, Asana, or ClickUp for task creation and commentary distribution.
Quick answers
Do we need perfect data before launching?
No. Start with the most trusted sources, then let the hygiene agent surface gaps. The cockpit improves data quality as it runs.
How do we secure sensitive fields?
Use row-level security in the warehouse and restrict agent access via service accounts with least privilege.
Can the cockpit trigger automations?
Yes. Connect it to CRM workflows or marketing automation via API so insights create tasks, reassign accounts, or pause budgets automatically.
Need a builder for this playbook?
These playbooks are designed for teams that want clarity fast. If you prefer to skip the trial and error, I can architect the agentic workflow, integrate your tool stack, and train your team on continuous improvement.