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RevOps

For sales ops and revenue operations teams managing pipeline, forecasts, and sales performance.

Try These First​

Open the agent and ask:

Show me pipeline by stage with week-over-week change
What's our win rate by segment and sales rep?
Compare forecasted vs actual closed revenue by month

Key Tables​

TableWhat's in it
opportunitiesPipeline with stage, amount, owner
pipeline_snapshotsHistorical pipeline by stage and date
accountsCustomer data with segment and ARR
revenueMRR movements: new, expansion, churn

Common Workflows​

Pipeline analysis​

Ask the agent:

  • "Show me pipeline coverage ratio for next quarter"
  • "Which deals have been in negotiation for more than 30 days?"
  • "Break down pipeline by segment and expected close month"

Win rate analysis​

Understand what's working:

Show me win rate trends by quarter for the last year
Compare win rates: Enterprise vs Mid-Market vs SMB

Forecast accuracy​

Track forecast reliability:

Show me forecast vs actual by rep for the last 6 months
What's our average deal slippage rate by stage?

Defining RevOps Metrics​

Save your key metrics to the semantic layer:

measures:
  - name: pipeline_value
    type: sum
    sql: amount
    filters:
      - sql: "stage NOT IN ('closed_won', 'closed_lost')"
    description: "Total open pipeline value"

  - name: win_rate
    type: number
    sql: "COUNT(CASE WHEN stage = 'closed_won' THEN 1 END)::float / NULLIF(COUNT(CASE WHEN stage IN ('closed_won', 'closed_lost') THEN 1 END), 0)"
    description: "Won deals / Total closed deals"

  - name: weighted_pipeline
    type: sum
    sql: "amount * (probability / 100.0)"
    description: "Pipeline weighted by stage probability"

  - name: average_deal_size
    type: average
    sql: amount
    filters:
      - sql: "stage = 'closed_won'"
    description: "Average won deal value"

Next Steps​