Campaign to Cash

Tableau Next links leads, journeys, and opportunities end-to-end. With Agentforce, query to see the desired visualizations/metrics, so executives double down on campaigns that drive revenue.

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Inspiration

In a tight, scrutiny-heavy economy, every rupee must defend itself. Marketing is under pressure to prove payback fast, and spendthrift habits of “spray and pray” campaigns just don’t fly anymore. Leaders ask: “Which journeys and campaigns truly move the needle from lead to revenue—and how quickly?” We set out to make that line auditable, conversational, and executive-ready so anyone can ask in plain English and see the story end-to-end: leads → journeys → opportunities → revenue—with efficiency signals that stand up in budget reviews.

What it does

  • Conversational analytics: natural-language queries like “first-touch revenue by channel in Q3” or “funnel Lead→MQL→SQO→Won for Enterprise.”
  • A clean semantic layer in Tableau: canonical metrics (Leads, MQLs, SQOs, Wins, Pipeline, Revenue), conversion rates, Spend, CPL/CPMQL/CPSQO.
  • Attribution views: First-Touch and Last-Touch revenue.
  • Exec dashboard: KPI ribbon, pipeline/revenue trend, attribution split, funnel by campaign, and an efficiency scatter (CPSQO vs SQOs).

How we built it

  • With time pressure considered, used pre-seeded CSV files and uploaded it as data lake objects.
  • Data model (CSV-first): leads, journey_events, lead_touchpoints, mql, sqo_map, opportunities, campaigns, costs_daily.
  • Created a semantic layer where these objects are then related to each other through campaign_id, lead_id and shared tables to enable cross fact trees.
  • Attribution logic: Built a joined touch–opportunity helper so Tableau can compute “First/Last-Touch Campaign (per Opp)”. Measures for First-Touch Revenue and Last-Touch Revenue that roll up by campaign/channel.
  • Natural language mapping: Synonyms (“pipeline”, “won revenue”, “SQO rate”) and default viz rules (trend/rank/funnel).
  • Dashboard viz: Targets, YoY/QoQ deltas.

Challenges we ran into

Skilling up on Tableau Next terminology, analysis of what possible outcomes could be achieved and landing on a suitable idea took its sweet time.

Accomplishments that we're proud of

  • End-to-end visibility (lead → journey → opp → revenue). Stitched Marketing Cloud and Sales Cloud signals into one auditable flow with clean keys and single-grain tables.
  • Executive-ready semantic layer. Implemented canonical metrics (Leads, MQLs, SQOs, Wins, Pipeline, Revenue), step conversion rates, Spend, and CPL/CPMQL/CPSQO—with friendly names, synonyms, and hover defs.
  • Conversational analytics that actually work. Natural-language prompts like “funnel Lead→MQL→SQO→Won for Enterprise in Q3” return the right viz by default (trend/rank/funnel).

What we learned

Start with a good enough idea and then work towards the challenge. Start early to have enough time to skill up on Tableau Next.

What's next for Campaign to Cash

Add more metrics with suitable data that give more insights especially on these metrics - Cost to Acquire a New Customer, Payback (months), Revenue per Sales rep etc

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