See where sales dropped on WB and Ozon
The month closed below plan and the reason won't surface: fewer orders, or lower prices? Ozon and Wildberries get read separately, factor by factor.
Medium · 25 min · once a week
What you get
a breakdown in the reply · once a week
Revenue drop, March: −18% (−1,240,000 ₽) Ozon −6% price down, orders flat −310,000 ₽ WB −27% 2,100 fewer orders −930,000 ₽ Top 3 items behind the drop: ART-4471 −340,000 ₽ 14 days out of stock ART-2210 −210,000 ₽ priced 12% below last month ART-9008 −155,000 ₽ returns 9% → 21% Excluded: 240,000 ₽ from SKUs you marked clearance
A sample on made-up data; your numbers will be your own.
Who it fits
- Revenue fell, but in each dashboard on its own everything looks "roughly as usual".
- You need to separate a general demand dip from problems with specific listings, since the fixes differ.
When it won't work
The operating model changed mid-period: FBS to FBO, or a new legal entity. Before and after aren't comparable.
How the agent does it
Pick the comparison period
The agent reads both dashboards itself. Say what we compare against (last month, or the same month a year ago), since the conclusions differ.
Run the breakdown
Each marketplace is counted on its own, and the drop is split into price, quantity and returns. Not one combined number, but what made it.
Check the conclusions
Ask the agent to review its own work: where a conclusion rests on five orders, and where an item was simply out of stock and that got read as weak demand.
What you set
Connect Ozon and Wildberries. From you: the period, what to compare against and the items to leave out (clearance stock, discontinued lines).
What you'll need
Starter prompt
Copy the prompt or open it straight in a chat with the agent.
Merge Wildberries and Ozon sales for [period] and compare with [the previous period / the same period last year]. For each marketplace, category and SKU show revenue, orders, average order value and returns. Break every decline down into factors (order count fell, selling price fell or returns grew) and show each factor's contribution in rubles. Don't explain a decline by "falling demand" or "seasonality" until you show a figure that confirms it. If an item didn't sell because it was out of stock, say exactly that: that isn't a demand decline. Output a SKU table sorted by lost revenue, and the ten items that account for half of the decline.
Open in chatReview the analysis. List: - SKUs where the decline was calculated on fewer than [30] orders in one of the periods; - items that were out of stock, and this got confused with a demand decline; - comparisons where the periods have a different number of days or a different number of marketplace promos; - cases where revenue fell but margin grew (that isn't a problem); - which explanations of the decline you confirmed with a figure and which remain hypotheses.
A second prompt: the agent uses it to review its own work and show what's left for you.