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SellZyme

Platform

Scenario Lab & A/B Testing

Scenario Lab lets you model one strategy against another on the same set of products or campaigns — same period, different conditions — grounded in 60 days of history plus category trend, and converts a simulation into a live A/B test when the outcome is too close to call.

Illustrative interface — not customer data.

The problem

“What if we tried X instead?” usually gets answered by trying it with real money and finding out weeks later. And when two options genuinely look similar, most tools still pick a confident winner they can't justify.

How it works

  1. Build a custom set — pick the products and campaigns you want to compare.

  2. Run Scenario A vs B: the same set and period, changed only by the conditions you're testing.

  3. Each scenario is re-modelled from that scope's own run-rate, with the outcome shown as an honest range, not a single number.

  4. When the confidence bands overlap, Zyme refuses to pick a winner — and offers to convert the simulation into a live A/B test with its prediction on record.

What you get

  • Test strategy against modelled outcomes before spending on it
  • An honest “too close to call” instead of false confidence
  • Live A/B tests that start with a prediction to be scored against

FAQ

Scenario Lab & A/B Testing — questions

How does SellZyme's Scenario Lab work?
You build a set of products or campaigns and run two scenarios — the same set and period, differing only in the conditions you're testing. Each is re-modelled from that scope's own 60-day run-rate and category trend, and results are shown as ranges. If the ranges overlap too much to separate, Zyme declines to pick a winner and offers to run it as a live A/B test.
What is the 'too close to call' verdict?
When two scenarios' confidence bands overlap, there's no honest winner to declare. Rather than fake one, Zyme says so and offers to convert the simulation into a live A/B test — recording its prediction up front so the test's result can be scored against it.
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