Methodology
DataEI research is built on a transparent, repeatable, agent-augmented methodology. Every benchmark, briefing, and finding traces back to a documented source, a defined rubric, and analyst review. No black boxes.
The DataEI Research Method
Five phases, from raw data collection to published benchmark. AI agents handle scale; analysts handle judgment.
AI agents continuously collect public vendor data, financial signals, product positioning, and market activity across the $2M–$50M SMB segment. The MCP server orchestrates collection across hundreds of sources. Output: raw research dataset, continuously updated.
Vendors submit to the Research Briefing Program. Analysts run structured briefings to gather inside perspective, validate positioning, and capture market context that public data misses. Output: briefing notes, validated vendor profiles.
Agents cross-reference collected data against briefing notes, public filings, and historical benchmarks. Conflicts are flagged. The MCP server runs the Leverage Index calculator and segment analyzers. Output: draft synthesis, flagged conflicts.
DataEI analysts review every synthesis before publication. We apply 20+ years of technology-market experience to challenge findings, resolve conflicts, and pressure-test conclusions. Agents propose; analysts decide. Output: reviewed findings, editorial decisions.
Validated findings publish as Leverage Index benchmarks, research briefs, and briefing reports. Every published figure links to its source data, methodology step, and analyst reviewer. Output: published benchmark, source-traced.
The Leverage Index — How It's Calculated
The Leverage Index measures how effectively a company converts headcount and spend into output. It's DataEI's signature benchmark — research you can't get from other analysts or sources.
Normalized revenue per full-time employee, benchmarked against segment median.
Depth of automation, AI, and agent deployment across sales, ops, and product.
Ship speed, release cadence, and time-to-value relative to segment peers.
Net or gross margin, adjusted for segment and stage. Leverage that doesn't convert to margin isn't leverage.
Analyst-applied adjustment based on founder/leadership time spent on leverage-building vs. execution tasks.
Score zones: 0–40 red (under-leveraged), 40–70 amber (developing), 70–100 green (leverage-first).
Source Transparency
Every DataEI finding links to its source. We don't publish unsourced claims.
- Public vendor data (sites, filings, product pages)
- Research Briefing Program submissions (vendor-confirmed)
- Analyst interviews and primary research
- MCP-collected market signals (with timestamp)
- Pay-to-play rankings or paid placement
- Publish findings without analyst review
- Use agent output as final word — agents propose, analysts decide
- Hide conflicts — we flag them in the synthesis