This section is for Ozon sellers: 48 templates arranged the way money moves — from what you earn on a single sold unit under each of the three fulfillment schemes, through cards and search, supply and stock, buyout and returns, advertising and its honest share of revenue, and on to reports, taxes, picking a niche, and competitors. Here are all 48.
Every template is a live walkthrough on one Ozon seller’s demo data: open it in the Templates section of Analytics Agent and press “Use this template” to run it on your own data.
Ozon Unit Economics: FBO vs FBS vs realFBS
Shows: what you earn on every sold unit, computed three times — once for each way of working with the warehouse: storage at an Ozon warehouse (FBO), shipping from your own warehouse (FBS), and handing the goods to a courier service (realFBS) — with every deduction under each scheme. You can see which scheme earns more on each product.
You get: a product that makes money under one scheme but goes negative under another is moved to the right scheme.
The Ozon Price Calculator, Recomputed
Shows: the minimum price at which a product still turns a profit — computed on your own tariffs and adjusted for ad load, plus what-if experiments: what happens if the commission rises or logistics get more expensive.
You get: discounts given by number, not by eye, and a clear view of how much of the price is actually yours.
Buyout and Returns inside Unit Economics
Shows: what a unit really earns when the observed return rate is put under stress — three scenarios from “fixed it” to “returns ballooned,” and the point at which the verdict on the product flips.
You get: a product that is profitable only in the most optimistic scenario doesn’t stay in your assortment by mistake.
Ozon DRR and Ad Load by SKU
Shows: how much of each product’s revenue advertising takes — compared against the norm for its stage and against the product’s own profit; verdicts: turn it off, dial it down, scale it up, leave it alone.
You get: ads on a thin-margin product stop quietly running at a loss.
Ozon Seller Norms Traffic Light
Shows: one product × metric screen — margin, ad share, buyout, returns, stock — each metric against its category norm, and each product gets an overall color from its worst metric; next to it, the focus list for the week.
You get: no need to read five reports to find the sick product — it is named, and you’re told where to start the week.
Ozon Break-Even and the Minimum Allowed Price
Shows: how many units a month you need to sell for the month to stop losing money, and on which day of the month that happens; separately, the price floor for each product.
You get: instead of a vague sense that things are kind of working, a concrete unit count and a date to reach it by.
Ozon Unit Economics in Motion: Scheme Shifts
Shows: how per-unit profit moved week by week under each scheme, with each week computed at the tariffs in force at its start; level shifts from tariff hikes are found and localized, and the “switch scheme” list is priced in money.
You get: a rise in storage or logistics costs shows up right away by its footprint in profit — not in a quarterly report after the fact.
Ozon Seller Funnel: Impression → Buyout
Shows: where buyers are lost — at impression, click, in the cart, at order, or at buyout; the losses are counted in lost orders per month and tied to the step that kills them.
You get: you know what to fix — the photos, the price, the description, or delivery — instead of guessing.
Ozon CTR vs CR: Views but No Orders
Shows: every card’s click-through rate and conversion to order against category norms; four quadrants, and the card nobody picks and the card that disappoints get different fix lists.
You get: cards that collect views for nothing get exactly the fix they need.
Ozon Card SEO: Title, Photos, Video, Infographics
Shows: a completeness checklist for every card — title, photos, video, description, content — with the measured link to click-through rate and an honest note: a complete card buys the click, not the order.
You get: cards that search under-serves stop losing impressions you have already paid for.
Ozon Card Audit: Why It Doesn’t Sell
Shows: for every card — which of the checked obstacles fired (price, rating, reviews, photos, title) and in what order to fix them; the summary table is turned into a repair order.
You get: fixes start where the most impressions are at risk — and in the right order.
Buyout Rate — the 50-Order Window
Shows: an honest buyout rate in three windows side by side — the last 50 Ozon orders, 30 days, and 90 days — for each product, with a low-reliability flag on thin windows and the disagreement between windows ranked.
You get: you can see which products keep buyers and which just ride back and forth — and the windows stop contradicting each other.
Returns and Cancels by Cause
Shows: which products get returned most often and why — size, “didn’t like it,” defects; the return rate against category norms, and cancels separately with their own fix list.
You get: you know what to work on — the size chart, the description, or quality — instead of “somehow, all of it at once.”
Ozon Search Queries: Won and Lost
Shows: which queries the card is found by and which it loses: underperformers (many impressions, almost no clicks) and lost ones (the product doesn’t show for the query at all), each pair with its share of revenue.
You get: queries where the card isn’t picked get a title and photo rework, and lost ones get new keywords in promotion.
Ozon Demand Forecast with Season Scenarios
Shows: how much to order for next month: the forecast for each product comes as a range — pessimistic to optimistic — the winner of four methods is picked by an honest comparison against history, and a seasonal view rides along where a season exists.
You get: buying to a range instead of a single number lowers the risk of both stockouts and a pile of dead stock.
Ozon Cards and Reviews vs Buyout
Shows: whether card completeness and rating actually affect buyout and returns — checked on data, not on faith; if something else is the real driver (say, the size chart), it is shown directly.
You get: effort isn’t wasted on “obvious” edits that don’t move sales — the work goes where the effect is measurable.
Ozon Safety Stock under Service Level
Shows: how much buffer to keep so a product doesn’t run out: for each product, the safety stock for a 95% in-stock level; next to it, the excess products freezing your money and what their storage costs.
You get: stockouts stop happening, and extra money isn’t sitting in product that’s already covered with room to spare.
Ozon Reorder Point and Order Volume
Shows: at what stock level it’s time to order, and how many units, to fit your supply cycle; what’s already in transit is counted too — so you don’t order twice.
You get: orders go out on time and in the right volume: no empty shelf, no double purchase.
Ozon Out-of-Stock Losses
Shows: what an out-of-stock product really costs: every empty-shelf period is priced in missed revenue, episode by episode, for each product.
You get: you can see which is cheaper — holding stock or losing sales — with the price of both options.
Stockout Date Forecast
Shows: the date the product runs out — as an interval, not a single number; from it, the last day to place an order so the delivery arrives on time.
You get: the order is placed before the product runs out, not after.
Warehouse Allocation
Shows: how to split an incoming delivery across warehouse clusters so the regions don’t get skewed: each cluster’s share of demand minus what already sits in its warehouse.
You get: buyers in distant clusters get the product fast, and stock doesn’t pile up in an already-loaded region.
ABC/XYZ and Turnover
Shows: products laid out by their contribution to revenue and by demand predictability; next to them, turnover and a dead-stock flag — products sitting longer than the replenishment cycle.
You get: money stops being frozen in product that sells slowly and earns little.
Service-Level KPIs
Shows: seven operational metrics on one panel — in-stock days, stockout share, first-pass acceptance, turnover, forecast accuracy, dead stock — each against its own norm with a month-over-month arrow.
You get: the store’s operational health is visible in ten seconds, not from a quarterly summary.
Return Cost with Reverse Logistics
Shows: what each return really costs — return shipping, handling, and the margin lost on units unfit for resale, per product; plus a ranking of how much returns eat from margin.
You get: “it’s just a return” stops being true — an expensive return is visible with a price tag on it.
Recovery of Unbought Orders
Shows: how many refused and unbought orders can realistically be won back: a funnel of unfinished orders by cause and time in transit, and three reactivation scenarios labeled as potential, not a promise.
You get: unbought orders aren’t silently written off, and they don’t turn into a giveaway of discounts that eats your margin.
Return Windows and the In-Flight Book
Shows: when a return can still land — each order’s window by buyer level (14, 30, or 60 days), the distribution of delays, and a projection: what will arrive in the next 30 days and how much revenue to reserve for it.
You get: the monthly report stops looking final before it has cooled — money for future returns is reserved in advance.
The Ad Metrics Passport
Shows: every metric from the ad cabinet for each campaign on one screen — spend, clicks, click-through rate, cost per order, ad spend share, return on spend; metrics that must not be mixed are not mixed.
You get: you can see which metric failed where — including the “cheap clicks, no orders” trap.
The DRR Lifecycle Benchmarks
Shows: what ad spend level is normal for a product right now: launch, growth, established phase — each stage has its own band, and a long-standing overload is flagged separately.
You get: ads get trimmed where they eat more than they bring in, and aren’t cut for nothing when they’re within the norm.
DRR in Three Honest Views
Shows: the same ad load computed against three different denominators — total revenue, ad revenue, sales revenue — by campaign and by product; a map of “which view answers which question” is printed next to the numbers.
You get: ads stop looking better than they are because of cancelled and returned orders in the calculation.
Ozon Ad Metric Conflicts Watchdog
Shows: a weekly check of metric pairs — click-through rate rising while conversion falls, spend rising on the same reach — with a diagnosis and an action for each trigger, sorted by the money at stake.
You get: an ad problem is caught in the same week, not a month later in a summary report.
Cheap Traffic and the DRR Strategy Matrix
Shows: products sorted into four fields by the pair “ad load × unit margin” — feed, fix the card, harvest, phase out; budget is moved by a rule computed to the cent.
You get: the ad budget flows to where it earns, not to where it is merely cheap.
A/B Tests of Creatives and Offers
Shows: whether the new photo is really better: two variants are compared in an honest test with confidence intervals, the required impression volume is named, and the cost of peeking at results early is visible.
You get: the creative changes on data, not on the feeling that this seems better.
Ads inside Unit Economics
Shows: the cost of an order next to the profit each order brings — under a clear rule of “advertising no more than such-and-such share”; the rows invisible to a plain ad spend share are caught separately.
You get: ad spend is judged by the profit of the orders, not by the clicks that don’t bring them.
The Realization Report, Decoded
Shows: the report’s three headline numbers, separated by the questions they answer: revenue, the settlement transfer, and the tax base; every deduction column is named and computed on your own data.
You get: the report stops being “the platform computed something” — any line can be checked by hand, and a month with a negative accrual stops being scary.
UPD-1 and Extra Services
Shows: what hides inside the UPD (universal transfer document) and extra services: the agency commission and five service lines, each flagged — already subtracted from the payout or billed separately.
You get: services aren’t counted twice, and the real extra costs — storage and advertising — are visible apart from the paperwork lines.
Net Profit: From Accruals to Fact
Shows: the path from transfers to the money that’s left: services billed separately, product purchase, fixed costs; each number from its own source, and the reconciliation “net = accrued minus costs” checks out in every month.
You get: you see how much actually stays from every currency unit the platform pays you — not just how much “landed in the account.”
Tax Regimes: NPD, USN, AUSN, OSNO
Shows: all four regimes computed on the same base — how much tax is paid now and how much would remain under each of the other regimes, with assumptions you can show your accountant.
You get: you can see whether switching tax regimes makes sense, and the difference in money is computed, not guessed.
Points and Compensations: The Margin Error
Shows: each product’s margin computed twice — without the points and compensations log and with it; you can see which products only look profitable because buyer points were forgotten.
You get: products that were counted as profitable by mistake are finally computed honestly.
Accruals by Order Type: Delivered, Cancelled, Returned
Shows: what the platform accrues for delivered, returned, and unbought orders: a return or an unbought order carries almost the full set of deductions at zero revenue, a cancellation before delivery costs nothing; the total is the full price of the “returns wedge.”
You get: you can see how much money leaks to returns and unbought orders — and that an unbought order costs almost as much as a return.
Stock Control FBO/FBS (Assortment Report)
Shows: every “product × scheme × warehouse” pool with days of cover: surpluses, shortages, and even products worth moving between schemes are named one by one.
You get: surplus and shortage are visible in one report, not in two that contradict each other.
Niche Entry: Demand before Launch
Shows: a map of the category before you put money in: how sellers have split the market, the price corridor, and the demand trend — with every third-party number carrying an honest estimate band; the entry verdict is recomputed under different scenarios.
You get: the decision to enter a new niche is made on several estimates at once, not on a single number that can be wrong.
Competitor Cards and Prices
Shows: your price and card against the field of competitors in each segment: price, rating, reviews, photos; a double-barrier flag — price above the median and rating below the bar — marks where the buyer stops.
You get: you can see what’s missing to stand next to the segment leaders, and in what order to fix it.
Category Trends – What to Sell Next
Shows: which categories are growing, where sellers are packed in, and where there’s open space: demand growth over two years, competition, demand per seller, seasonality — every factor on the table, and the result checked for stability.
You get: the new category is picked by the numbers, not by advice from a chat.
Ozon Analytics Services Scorecard — Which Service for Which Task
Shows: analytics services compared by task, with real names and prices, and a total weighted for your tasks (task weights are sliders in the report header: move them and the podium rebuilds); for each task — the best option and a backup within budget.
You get: you pay a service for what it sees outside your own cabinet — not for a big name, and not for numbers you already have in your own realization report.
Own Data + the Service Feed: One Ozon Mart — Facts Beside Estimates
Shows: your own facts from the cabinet stand next to an analytics service’s estimates on one screen, and every column says plainly whether it is a fact or an estimate; join mismatches are shown and explained.
You get: it’s clear where the service sees the market and where it’s wrong — and third-party estimates don’t get mixed up with your own numbers.
Buyer LTV and Repeat Purchases — Cohorts, Observed Horizons, and the OOS Claim That Wouldn’t Confirm
Shows: what a repeat buyer brings: cohorts by first-purchase month, only lived-through periods with no made-up forecasts, customer-value deciles, and an honest check of whether stockouts actually lose you the buyer.
You get: what you invest in keeping a buyer is judged by their real value, not by the platform’s claims.
Reviews — Sentiment and Conversion: the Two-Tier Russian Read and the Complaint That Names Itself
Shows: what reviews say and how it connects to sales: negative reviews are broken down by theme, and the complaint itself names what to fix — size, delivery, or quality; the link between reviews and purchases is tested honestly.
You get: review work targets the complaints that actually hit sales, not every single one.
The Seller’s One-Page Mart — Every Sibling’s Verdict on One Screen, Nothing Recomputed
Shows: the store’s whole money picture in one report: how money travels, adjusted margin, ads, buyout, returns, stockout risk, taxes — every column with its own source, nothing recomputed.
You get: the store’s condition reads from one screen in a minute, and every red product is explained by a specific cause.