Methodology

How scores on the Decision Friction Index are produced.

How scores are produced

Every piece of content on the Index is evaluated against the same 7-point structural framework. Scoring is performed by an AI diagnostic engine (Claude, Anthropic) applying the Strategic Flow framework consistently across every company — the same checks, in the same order, every time.

• 1. Subject line / headline construction — Does the subject or headline lead with an outcome the reader cares about, rather than a feature name or internal label?
• 2. Lead construction — Does the opening line hook the reader with a concrete stake or benefit before any setup or preamble?
• 3. Feature-to-outcome translation — Are features explained in terms of what the reader can now do or achieve, not just what was shipped?
• 4. Visual hierarchy — Does formatting (headings, spacing, emphasis) guide the eye to the most important information first?
• 5. Before/after contrast or concreteness — Does the content use specific, concrete before/after framing rather than vague or abstract claims?
• 6. Social proof — Is there evidence — numbers, quotes, customer names — that others have used or validated this?
• 7. CTA language — Does the call to action use ownership language ("Get your X") rather than guest language ("Learn more", "Submit")?

Scores range from 1 to 10, where 10 represents excellent structural quality (low decision friction) and 1 represents severe structural failure (high decision friction).

What we score

Only publicly available content: changelogs, product update blog posts, landing pages, newsletters, and blog articles. Each company page on the Index shows the content type scored, the excerpt that was evaluated, and the date it was scored.

What the score is NOT

The score is not a judgment of the product, the company, or the team behind it. It measures the structural conversion quality of one specific piece of communication, at one point in time — nothing more.

Limitations

Companies are scored on one or more representative content samples. Scores shown are the average across all samples analyzed for that company. Each sample's individual breakdown is visible on the company page. If you believe a score is out of date or based on the wrong sample, companies can request a re-score or a correction by contacting strategicflow@proton.me.

The pattern library

When content is scored, it may be tagged with one or more of these six canonical failure patterns:

• Filing Label Subject — A subject line that names an internal category or feature instead of the outcome for the reader.
• Feature-First Bias — Leading with what was built rather than what the reader can now do.
• Guest Language CTA — A call to action phrased as a favor to the sender ("Learn more", "Submit") instead of a benefit to the reader.
• Consequence-After-Caveat — Burying the real stakes or impact after qualifiers, caveats, or disclaimers.
• Missing Visual Hierarchy — No formatting cues to guide the reader to what matters most.
• Zero/Buried Social Proof — No evidence of validation from other users, or proof buried far from the point it should support.

Index scores vs WHY.™ Friction Scores

The Decision Friction Index and the WHY.™ diagnostic tool are built on the same underlying framework but serve different purposes. Index scores are produced with the fixed 7-point structural evaluation so companies can be compared consistently. WHY.™ delivers a deeper diagnosis of a single piece of content — friction points, predicted reader questions, and a rebuilt version — rather than a comparative ranking. The two scores are not directly interchangeable.