Evaluates whether a company has the right sales technology for its revenue stage and selling motion. Diagnoses gaps, redundancies, and adoption failures across five layers: CRM, engagement, intelligence, CPQ, and enablement. [src1]
What this measures: Whether CRM serves as reliable system of record with clean data and proper integrations.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | No CRM or basic contact list; deals in spreadsheets | <30% deal data in CRM; no integrations |
| 2 | Emerging | CRM deployed but poorly configured; data gaps | 40-60% field completion; 1-2 integrations |
| 3 | Defined | Properly configured; required fields enforced; core integrations | 80%+ completion; auto activity capture; 3-5 integrations |
| 4 | Managed | Data hub with bi-directional integrations; data governance | Single source of truth; automated enrichment |
| 5 | Optimized | Revenue intelligence platform; AI insights; predictive analytics | AI assistant active; self-cleaning data |
What this measures: Multi-channel outreach sequencing, engagement tracking, and prospecting automation.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | Manual email; no sequencing; no tracking | No cadence tool; no call recording |
| 2 | Emerging | Basic sequencing; some call tracking | Single-channel; no engagement scoring |
| 3 | Defined | Dedicated platform; multi-channel sequences | Reply detection; basic engagement scoring; call recording |
| 4 | Managed | AI-powered engagement; intent-based prioritization | AI email drafts; conversation intelligence integrated |
| 5 | Optimized | Autonomous prospecting agents; real-time signals | AI SDR agents; dynamic sequence adjustment |
What this measures: Deal health understanding, outcome prediction, and revenue insights.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | Basic CRM reports only; spreadsheet analysis | No deal scoring; retrospective only |
| 2 | Emerging | BI tool connected; basic pipeline reporting | Standard dashboards; no predictive capability |
| 3 | Defined | Revenue intelligence platform; conversation intelligence | Deal health scoring; call analysis; basic forecast intelligence |
| 4 | Managed | AI forecasting 85%+ accuracy; deal risk alerts | Predictive scoring; AI coaching insights |
| 5 | Optimized | Real-time prescriptive intelligence; autonomous management | 90-95% forecast accuracy; anomaly detection |
What this measures: Pricing, quoting, contracts, and quote-to-close efficiency.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | Spreadsheet pricing; manual quotes; no approval workflows | Custom-built quotes; pricing errors common |
| 2 | Emerging | Basic quoting tool; simple price books | Standardized templates; email-based approvals |
| 3 | Defined | CPQ platform; automated pricing rules; e-signature | Discount guardrails; quote-to-cash <48 hours |
| 4 | Managed | Advanced CPQ with guided selling; billing integration | AI upsell suggestions; automated renewals |
| 5 | Optimized | AI dynamic pricing; competitive intelligence; zero-touch renewals | AI-optimized per-deal pricing; rev rec automated |
[src5]
What this measures: Onboarding, training, content management, and just-in-time rep resources.
| Score | Level | Description | Evidence |
|---|---|---|---|
| 1 | Ad hoc | No enablement platform; informal onboarding | No content repository; reps create own decks |
| 2 | Emerging | Shared drive for content; basic onboarding | Onboarding 3+ months; training is event-based |
| 3 | Defined | Dedicated platform; structured onboarding | Searchable library; 30-60 day onboarding |
| 4 | Managed | AI content recommendations; coaching cadence | Content usage correlated with win rates |
| 5 | Optimized | Adaptive learning; AI coaching from calls | Personalized dev plans; auto-generated battle cards |
[src2]
Formula: Overall Score = (CRM + Engagement + Intelligence + CPQ + Enablement) / 5
| Overall Score | Level | Interpretation | Next Step |
|---|---|---|---|
| 1.0 - 1.9 | Critical | Missing foundational technology; manual processes limit scale | CRM first, then engagement |
| 2.0 - 2.9 | Developing | Basic tools but underutilized; capability gaps | Drive adoption before buying new tools |
| 3.0 - 3.9 | Competent | Solid foundation; ready for intelligence layer | Add revenue intelligence; optimize integrations |
| 4.0 - 4.5 | Advanced | Well-integrated; AI-augmented workflows | Consolidate vendors; advanced analytics |
| 4.6 - 5.0 | Best-in-class | Fully integrated AI-powered platform | Evaluate emerging agentic AI capabilities |
| Segment | Expected Average | "Good" Threshold | "Alarm" Threshold |
|---|---|---|---|
| Seed/Series A | 1.5 | 2.0 | 1.0 |
| Series B ($2M-$15M) | 2.5 | 3.0 | 1.8 |
| Growth ($15M-$100M) | 3.3 | 3.8 | 2.5 |
| Scale/Public ($100M+) | 4.0 | 4.3 | 3.0 |
Fetch when a user asks what sales tools they need, evaluates their current tech stack, plans sales technology budget, or diagnoses why productivity is declining despite tool investment.