Prove that it worked — instead of believing it
Set a goal, watch progress run along from real records — and test a measure against a control group.
Screens from a demo workspace. Companies, people and figures are fictitious.
OutcomeOS at work
Four capabilities people actually open OutcomeOS for. Everything else it can do is listed in full in section 04 — this is only what stands on its own.
An A/B test on real records
Test two approaches against each other — directly on leads, deals or candidates. Newly created records are assigned to a variant automatically and by weight the moment they are created: per record, once, and unchangeable afterwards. The same record never ends up in two variants.
the same record never lands in two variants
The holdout group that makes proof possible in the first place
Alongside control and variant you can deliberately leave one group untreated. Only that comparison separates “it got better” from “it would have got better anyway” — the difference between an observation and a proof.
only the comparison with the untreated group turns it into proof
Significance instead of pretty bars
For every variant you see the difference in absolute and relative terms, the p-value, the confidence interval and the clear statement of whether the result is dependable. A minimum sample per variant stops three lucky hits passing as a success.
stops three lucky hits from passing as a success
Your next step, not only your numbers
or waiting, blocked, unusual, or deliberately in the holdout — kept apart cleanly
The outcome inbox says where something is needed from you right now — and distinguishes cleanly: action needed, waiting on somebody else, blocked, unusual, or deliberately in the holdout and therefore intentionally untreated.
Paths that run through here
An experiment runs on REAL records, not on a copy. That is why the result is the same pipeline people work in — not a simulation next to it.
From a customer to a repeat customer
What OutcomeOS receives and passes on
OutcomeOS proves whether a measure achieved anything. Where the day stands is shown by the dashboard — proof is a different question from status.
Everything that is in it
20 capabilities in 3 groups — complete, not curated.
What it does not do
Every limit names the place where it happens instead.
- No language model.
The computation is statistics you can read. A model that guesses at an effect would be cheaper and worthless.
- No control group, no proof.
Leave out the holdout group and you get a trend, not a cause. And it says so, instead of claiming success.
- Thresholds are fixed in advance.
Significance level and duration are locked to the experiment. Moving them afterwards is not possible — otherwise every experiment wins.
What teams want to know beforehand
How long does an experiment take?
As long as it takes to be meaningful, decided up front — the duration is locked when you create it and not adjusted once you like the result.
Do my people notice anything?
Only the measure itself. Assignment runs in the background, and the records look exactly as they always do.
What if nothing comes out of it?
Then it says nothing came out of it. An experiment without an effect is a result — and cheaper than a measure you keep running for years.
OutcomeOS is one of 21. You get all of them.
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