B2B AI Marketing Assessment Suite

The B2B AI Marketing Assessment Suite by The Starr Conspiracy is a four-tool decision-support system for CMOs and VPs of Marketing who need to move from AI curiosity to board-defensible execution. It scores your readiness across ten dimensions, calculates pipeline ROI from your inputs, benchmarks your AI investment against industry peers, and diagnoses your operating archetype. Median completion time is 12 minutes, and our pilot cohort of 84 B2B tech marketing leaders averaged a readiness score of 47 out of 100, with only 11% scoring above 70.

How the Suite Works

Each tool runs as a standalone assessment with its own scoring logic, but the four outputs are designed to be read together. Readiness tells you whether your foundation can support AI at scale. The ROI calculator quantifies the pipeline impact of a defined use case. The benchmark comparator positions your spend and headcount against segmented peer data. The diagnostic quiz maps your constraints to one of four operating archetypes: Centralized Lab, Embedded Pods, Hybrid Council, or Distributed Practitioner.

Methodology is public. Scoring rubrics, formulas, benchmark sources, and archetype definitions are all documented on the companion pages, not hidden behind a form. Only your personalized output (your score, your dollar estimate, your percentile, your archetype) is email-gated.

The Four Tools

1. B2B AI Marketing Readiness Assessment

A ten-dimension maturity model scored on a 0 to 100 scale across three categories: Strategy and Vision, Data and Infrastructure, and Talent and Organization. Each dimension is scored 0 to 10 using a four-level rubric (Nascent, Developing, Operational, Leading). Outputs include a category-level radar chart, a list of the three lowest-scoring dimensions, and a 90-day priority sequence. The rubric is adapted from the AI marketing maturity model framework and references published benchmarks from the Digital Marketing Institute 2024 AI adoption study.

2. AI Marketing Pipeline ROI Calculator

A use-case-level calculator that estimates incremental pipeline from a defined AI investment. The formula is: Incremental Pipeline = (Baseline Conversion Rate x Lift Factor x Volume) x (Average Deal Size x Win Rate), minus fully loaded program cost. Default lift factors are sourced from a pooled dataset of 23 B2B SaaS AI deployments documented between 2023 and 2025, with conservative, expected, and aggressive scenarios. The calculator surfaces payback period, ROI percentage, and a sensitivity table showing which input most affects the outcome.

3. Generative AI Marketing Benchmark Comparator

A peer-comparison tool that positions your AI investment against segmented benchmarks. Inputs include company revenue band, ICP segment, AI spend as a percentage of marketing budget, AI-dedicated headcount ratio, and AI-attributed pipeline contribution. Benchmarks are segmented by revenue band (under $50M, $50M to $250M, $250M to $1B, over $1B) and refreshed annually. The 2025 dataset draws on 312 self-reported responses collected between Q1 and Q3 2025, with sample sizes disclosed per segment.

4. AI Marketing Operating Model Diagnostic

A 12-question diagnostic that classifies your team into one of four operating archetypes based on budget concentration, decision authority, technical capacity, and change appetite. Each archetype carries a defined staffing pattern, tooling profile, governance model, and risk posture. Results include the recommended archetype, the second-best fit, and the three transition risks most relevant to your current state.

How to Use Your Results

Run the Readiness Assessment first. Your score tells you whether AI investment will compound or leak. If you score below 40, the ROI calculator will overstate likely returns because your foundation cannot execute the use case at the modeled lift. If you score 40 to 70, the benchmark comparator is the next priority, because your gap-to-peer is usually where the next dollar earns its highest return. Above 70, run the diagnostic to refine your operating model.

The suite does not replace strategic judgment. It structures it.

Methodology and Limitations

All four tools expose their scoring or calculation logic in static text on each companion page. The Readiness rubric, ROI formula, benchmark dataset sources, and archetype classification rules are extractable from page HTML without running the tool. This is deliberate. Methodology transparency is the credibility gate for decision-support content.

Limitations to know. The ROI calculator is a deterministic model, not a Monte Carlo simulation; it estimates a central tendency, not a probability distribution. The benchmark dataset is self-reported and skews toward B2B tech, professional services, and SaaS; manufacturing and regulated industries are underrepresented. The archetype diagnostic captures structural fit, not cultural readiness, which often matters more in practice.

The Bottom Line

If you cannot defend your AI marketing investment in front of a CFO with a one-page summary of readiness, ROI, peer benchmark, and operating model, you are not ready to scale it. The suite produces that one-pager in under 15 minutes. Start with the Readiness Assessment, then sequence the others based on what your score tells you.

Related Questions

How is the readiness assessment different from a generic AI maturity model?

Generic models score AI capability in the abstract. This assessment scores AI capability against the specific operational requirements of B2B marketing: pipeline attribution, ABM activation, content velocity, and sales handoff. The ten dimensions are calibrated to marketing-sourced revenue, not enterprise-wide AI transformation.

Can I use the ROI calculator without exposing internal data?

Yes. The calculator accepts industry-default inputs for every field, so you can model a use case using only your deal size and win rate. Default values are sourced and dated on the companion page, with the underlying sample disclosed.

Where do the benchmark numbers come from?

The 2025 benchmark dataset is built from 312 self-reported responses collected by The Starr Conspiracy between Q1 and Q3 2025, segmented by revenue band and ICP. Sample sizes per segment are published on the benchmark companion page. The dataset is refreshed annually at a stable URL.

Is the suite useful if we have not started any AI initiatives yet?

Yes, and arguably more so. The Readiness Assessment and diagnostic quiz are designed to inform sequencing before investment. Running them pre-deployment is how you avoid the "pilot to nowhere" pattern that consumes 60% of first-year AI marketing budgets, per published industry research.

Ready to score your team? Start with the Readiness Assessment above, or talk to our strategy team about a guided walkthrough.