How It Works
Revenue AI Strategy is opinionated. Each step exists because skipping it is why most AI initiatives fail. Here's exactly what happens — and what you walk away with.
01
Why · Most AI rollouts start with the tool. Revenue AI Strategy starts with the outcome. One business metric, one timeline, one number to move.
What the platform does · Guided target builder with templates for win rate, churn, pipeline, cycle length, and gross margin. Owner assignment + exec sponsor capture.
Output
→ Single target charter: "Improve win rate 21% → 30% in 12 months"
Pitfall avoided
Avoids vague mandates like 'use more AI'.
02
Why · An outcome doesn't move on its own. 2–3 leading KPIs causally drive it. These — not 'AI usage' — are your accomplishments.
What the platform does · Visual KPI tree builder. Pre-seeded driver libraries per outcome. Baseline + target + data source per KPI.
Output
→ Win Rate → Qual Accuracy · Proposal-Close · Cycle Length
Pitfall avoided
Avoids measuring AI activity instead of business causation.
03
Why · AI is only as strong as the data feeding it. Most failures are diagnosable in 20 minutes, not 6 months.
What the platform does · 5-section diagnostic: Aggregation, Extraction, Inputs, Outputs, Under-the-Hood. Guided fix list for every section that scores low.
Output
→ AEIOU score 68/100 with 3 red blockers flagged
Pitfall avoided
Avoids launching pilots on broken data foundations.
04
Why · AI capabilities are finite (summarization, extraction, generation, orchestration). Match them to ranked workflow pain — never to shiny tools.
What the platform does · Pain → Capability → Tool matrix. Override-able recommendations. Deployment model decision: standalone, integrated, or custom.
Output
→ Capability Roadmap doc, exportable to RevOps backlog
Pitfall avoided
Avoids the 'we have 14 overlapping AI tools' trap.
05
Why · The model worked. The team didn't adopt it. Six Boxes (Gilbert) diagnoses why before the pilot — not after.
What the platform does · Six diagnostic boxes: Expectations, Tools, Incentives, Skills, Capacity, Trust. Scored, flagged, fix list generated.
Output
→ Readiness score with incentive + capacity flags
Pitfall avoided
Avoids deploying to teams whose comp plans punish the new workflow.
06
Why · One use case. One Tiger Team. One pre-pilot eval gate. Controlled scope is the only path to real signal.
What the platform does · Pilot builder with Tiger Team capture, baseline/target/timeline, risk pulled from your readiness scores, and a rubric-driven eval gate.
Output
→ Pilot charter: 8-week timeline, named owners, success criteria
Pitfall avoided
Avoids 'roll out to everyone and see what happens'.
07
Why · ROI for AI is finally provable: value of KPI movement ÷ fully-loaded cost. One number your CFO understands.
What the platform does · Computed score per initiative with KPI movement, fully-loaded cost, and Scale / Fix / Kill recommendation.
Output
→ Qualification AI = 3.2x · Content Writer = 0.4x — Kill
Pitfall avoided
Avoids rewarding adoption when adoption isn't moving the KPI.
10 minutes to a readiness score. 30 days to your first AI Strategy Score.
