The responder snapshot, on one screen.
It fills in as your customers set baselines and check in, and keeps refreshing as new buyers move through. The read you open in March reflects the customers you had in March.
Who responds best
ExampleThe response split, with the best-responding phenotype.
When they respond
ExampleThe week responders first noticed a change.
Median first noticed: week 7. Peaks across weeks 6 to 8.
Dose & adherence
ExampleStrong response by how consistently they took it.
A non-taker and a non-responder look identical without adherence. Part of apparent non-response is really under-dosing.
Cofactor map
ExampleNon-responders more often had low estimated intake. Points = the gap vs responders.
Observational and intake-based. A pattern worth looking into, not a deficiency finding.
Would they recommend
ExampleThe honest split between everyone and those who responded.
Lead with the responder rate, never the blended one.
Retention & recoverable churn
Exampleday-60 retention as it would read on your cohort. Illustrative.
The median quitter left at day 22, a month before the change usually lands. The biggest lever is carrying people past week 6.
Illustrative, not a real client result.
Eight reads, each with a job.
The share reporting a meaningful change against their own starting point. A measured observation of your base, not a promise about the next buyer.
The shape of the response curve over the weeks, so your messaging and follow-up land when customers are most likely to feel something.
The subgroups reporting the strongest response, so you can speak to the customers your product already fits.
The conditions alongside the strongest responses: worth teaching your customers about, in your own voice.
How time of day, with food or without, and routine consistency line up with reported response. Observed behavior, never a dosing instruction.
Where reported response concentrates across the dose levels customers actually use. Measured, not assumed.
Advocacy tied to measured response, not a detached star rating, so you find the customers most likely to speak for you.
Who slows down or stops early, and when. The retention leak your order data hides, an early warning you can act on.
No figure arrives bare.
Each read is reported with a stated confidence level, so you always know whether a number is ready to build on or still forming. How confidence is assigned →
A private picture, and a careful public one.
The dashboard is your private intelligence: the full distribution, including the customers who did not respond. On top of it sits the shareable layer, written in observed, not promised, language. Your product claims stay in your voice. The measurement stays in ours. See the two voices side by side →
Logged, dated, and traceable.
Every read is logged and dated, so what you say in public traces back to something measured. That record supports experience and perception claims. For the strongest, study-grade claims, the Claims-Ready tier adds the rigor that level requires.
An instrument, not a study.
You are not buying a study. You are buying an instrument that keeps measuring, so the next question you have about your product has an answer waiting, drawn from the customers you had this week.