The six evidence dimensions
Buyer proximity
Was the signal produced by a real qualified buyer in the relevant situation, or by somebody outside the buying context?
Behavioral commitment
Did the person merely express an opinion, or take a next step that costs attention, time, reputation, or money?
Recency
Recent evidence is usually more useful for a current decision than an old signal from a changed market, audience, or offer.
Repetition
A repeated pattern across qualified observations reduces the risk of treating one anecdote as a market signal.
Source independence
Evidence from independent buyers and channels is harder to explain as one community, one influencer, or one source bias.
Economic signal
Time, workaround cost, incumbent spending, deposits, paid pilots, and purchases reveal more than stated enthusiasm alone.
Scoring
Each dimension receives 0–4 points. The total is normalized from 0–24 to a 0–100 Evidence Strength score.
| Normalized score | 144Creator band | Decision meaning |
|---|---|---|
| 0–24 | Weak evidence | Mostly assumption, opinion, stale data, or low-buyer-fit signals. |
| 25–49 | Early signal | Useful enough to guide the next test, not strong enough to justify major expansion alone. |
| 50–74 | Decision-grade evidence | Multiple relevant signals support a product decision, while important uncertainty remains. |
| 75–100 | Strong evidence | Recent, repeated, buyer-proximate behavior with meaningful commitment. Still not a sales guarantee. |
How to use it
- Score the strongest evidence you actually have, not the evidence you hope to collect.
- Find the lowest dimension.
- Design the next validation experiment to strengthen that dimension.
- Keep the old score. Do not overwrite history; compare how evidence improved.
This makes the score most useful as a before/after decision record, not a badge.
Limitations
- The scoring weights are deliberately equal in v1.0; 144Creator has not claimed empirical weights.
- Different product categories may require different evidence before a sensible investment.
- High-ticket products can produce fewer but stronger commitment events than low-ticket products.
- One strong purchase does not prove repeatable acquisition.
- A high score describes the evidence entered; it does not estimate future revenue or market size.
Versioning
Material changes to dimensions, scoring anchors, or normalization will produce a new version. Historical research snapshots should state which version generated their scores so results are not silently mixed.
Score evidence with the published model
The calculator runs locally in your browser and can create a shareable result link and branded report.