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JonbarIstanbul (UTC+3)

ENTR

[ Use case 01 ] Promotions

Know which campaign still pays after it ends.

Rehearse the campaign you've planned against other mechanics, the same discount framed as a pack or a smaller discount, on your own sales history, and see the profit each leaves, including the weeks after the campaign.

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Bring one past campaign; we run it blind first.

Gross profit · 20% off vs. pack vs. 10% off · 12 weeksSample scenario · synthetic
Gross profit · 20% off vs. pack vs. 10% off · 12 weeks
WorldValue80% range
A2,028,329baseline
B2,070,6542,009,220 – 2,119,036
C (Leading, not clear)2,084,9622,031,075 – 2,136,867
A
Planned: 20% off
B
20% off as a pack, weeks 5-6
C
10% off, weeks 5-6

In this sample run, the pack sells the most, but on gross profit the three are too close to call.

! Prior-based: the pack effect comes from a published range, not from your history.

[ 01 ] Scope

What Jonbar simulates

Whose problem: Marketplace sellers and DTC brands planning a peak-season campaign. The campaign week looks great in revenue; nobody knows what the following weeks cost.

  • Promo lift for each mechanic you define (percent off, pack framing).
  • Pull-forward and the post-promo dip: sales that were only moved, not created.
  • Cannibalization: units your other SKUs in the same group lose.
  • Gross profit per world after the dip and cannibalization (unit cost and discount included; marketplace commission and shipping not yet).

[ 02 ] Sample output

The same run, week by week.

Each line is one version of the decision, with its range. The shaded weeks are the campaign window; the weeks after show what it cost or kept.

Weekly gross profit by world · sample scenario
Weekly gross profit by world · sample scenario
A
Planned: 20% off
B
20% off as a pack, weeks 5-6
C
10% off, weeks 5-6
Units sold in each world, as shares · sample scenario

ABC

[ 03 ] Limits

What it doesn't do yet.

  • Free-shipping thresholds are not modelled yet.
  • Accuracy is not yet backtested; every run shows its backtest status.
  • Platform-funded discounts are kept apart from your own decision.

[ 04 ] Other use cases

Planning a decision like this?

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