Pruning Slow Movers: An Assortment Discipline for Quick Commerce SKUs

Most brands treat their quick commerce catalogue the way they treat their Amazon catalogue. Add more. List every variant, every pack size, every flavour, every gift box. The logic feels safe. More SKUs, more surface area, more chances to be the thing a shopper buys. On a dark store that logic is not just wrong. It is actively expensive. A dark store does not have an infinite back room. It has a few hundred slots of real estate, and every slot you spend on a slow mover is a slot you did not spend keeping a hero in stock.

So we run assortment on quick commerce as a subtraction exercise. The question is never what else can we list. It is what can we remove so the things that work never run out. That reframe is uncomfortable for founders who measure progress by catalogue size. It is also the single highest-leverage move most brands are not making.

A dark store is a constraint, not a warehouse

The mental error starts with the word inventory. On a marketplace fulfilment centre, breadth is close to free. Storage is deep, the long tail can sit there for months, and an obscure SKU costs you a little holding fee and nothing else. A dark store inverts every one of those assumptions. It is small by design, stocked for speed, and refilled on a tight cycle. Space is the binding constraint, and space is shared across your whole range.

How binding that constraint really is became impossible to ignore in the 2025 festive run. During the rush, Blinkit halted new product onboarding through the end of October because its fulfilment centres were running at full capacity, per Inc42. When the platform itself runs out of room and stops taking new listings, the message to brands is blunt. Shelf is finite, it gets rationed under load, and the SKUs that earn their slot are the only ones that stay.

That means your SKUs are not additive. They compete with each other for the same finite shelf. List a slow variant and it does not sit harmlessly in a corner. It takes a facing, a replenishment slot, and a slice of the buffer stock that should have gone to your bestseller. The cost of a bad SKU is not the SKU. It is the availability it steals from a good one.

Bloat shows up as a fill rate problem

Here is the chain most brands miss. Too many SKUs spread your replenishment thin. Thin replenishment means more frequent stockouts. Stockouts on quick commerce are not a soft miss. They are a hard one, because the shopper wanted it in ten minutes and a competitor is one tap away. And the platforms watch this. A weak in-stock record drags down the availability signal that decides whether you even appear, which is exactly the dynamic we lay out in why your Blinkit dark-store availability score matters more than your ad spend.

So a bloated catalogue does not fail loudly. It fails as a slow leak in fill rate. Your hero SKU goes dark for a few hours a week in your best stores, and you never connect it to the nine vanity variants quietly eating its replenishment. The catalogue looks healthy. The availability is bleeding.

Every slow mover you keep on a dark store is paid for by a stockout on a product that actually sells. Assortment is not a list of what you offer. It is a budget you are spending.

Slow movers dilute hero velocity

The deeper cost is velocity. Quick commerce rewards momentum. A SKU that sells fast and steadily earns better placement, more replenishment priority, and a stronger availability score, which compounds into still more sales. Velocity is the flywheel. Slow movers do not just sit out of the flywheel. They drag on it.

When you split demand across too many variants, no single SKU builds the concentrated velocity that triggers the reward loop. Five mediocre sellers each doing modest numbers will lose to one hero doing the combined volume, because the platform algorithm and the replenishment cycle both favour concentration. Spreading demand thin is how brands end up with a full catalogue and not one product the algorithm treats as a default. Your hero products need that concentration to win, and slow movers steal it one order at a time.

How we decide what gets cut

Pruning is only ruthless if the rule is clear, because every slow SKU has an internal champion with a reason to keep it. We make the cut on evidence, not affection. The working filters we apply with our Catalog & Assortment Operations team look like this.

Velocity per slot, not total sales. Rank SKUs by units sold against the shelf and replenishment cost they consume. A SKU can have respectable total sales and still be a poor tenant if it ties up stock that a faster product would turn over twice.
Stockout contribution. Trace which SKUs are absorbing replenishment during the hours your heroes go dark. If a slow variant is in stock while your bestseller is not, that variant is the problem, not the bad luck.
Cannibalisation, not addition. Check whether a variant brings new buyers or just splits the same demand. A third pack size that mostly steals from the first two adds catalogue and subtracts focus.
Margin after the real cost of carry. A slow mover rarely survives once you load it with the platform economics it actually carries. We size that against the picture in the real unit economics of quick commerce after platform fees and returns, because a SKU that looks fine on gross margin can be underwater once the shelf it occupies is priced in.
City and store fit. A SKU that earns its slot in dense metro clusters may be dead weight elsewhere. Pruning is often local. Cut a variant in the stores where it drags and keep it where it earns.

Pruning is a routine, not a project

The mistake after the first cleanup is to call it done. Assortment bloat is not a one-time mess. It accrues. New launches, seasonal lines, a sales team that wants more options, and a founder who hates retiring anything all push the count back up. So we treat pruning as a standing cadence, reviewed on a fixed cycle, not a heroic annual purge.

That cadence is where discipline lives. Every cycle, a fresh velocity-per-slot ranking. Every cycle, a short list of candidates to demote, regionalise, or delist. Every cycle, the freed-up replenishment reassigned to the heroes that can absorb it. Run as part of Operations & Logistics Management, it keeps the catalogue lean without anyone having to fight the same battle twice. The brands that win on quick commerce are not the ones with the widest range. They are the ones whose narrow range is never out of stock.

Pruning is not the same as never launching

To be clear, this is not an argument against new SKUs. It is an argument for paying for them honestly. A new variant should have to earn its slot by displacing a weaker one, not by quietly expanding the footprint until availability slips. Launch with intent, give the SKU a fair window to prove velocity, and if it does not, cut it cleanly. The same discipline applies when you are recovering visibility on other channels, which is its own playbook in the Amazon India listing suppression recovery playbook. Across every channel the principle holds. Concentration beats sprawl.

What changed recently

Two shifts in the last year make this discipline more urgent, not less. The first is structural. In September 2025 Blinkit moved to an inventory-led model, buying stock directly from brands rather than running a pure marketplace, a transition Inc42 reported alongside the festive warehouse strain. When the platform owns the buy decision, it has every reason to back proven velocity and quietly drop the long tail. A slow variant that survived on a marketplace by sheer listing inertia has nowhere to hide once a buyer is deciding what to stock.

The second shift is the fee load. Platform commissions, mandatory ad spend, storage and return charges have climbed to the point where they can swallow a third or more of revenue, and Inc42 documents founders ending strong-revenue quarters in a loss once those fees clear. That economics punishes breadth directly. Every slow SKU now carries a heavier real cost of carry, so the margin-after-carry test does more work than it did a year ago. The brands holding up are the ones running a tight, high-velocity range, not the ones still measuring health by catalogue size.

The honest way to think about it

Quick commerce did not reward brands for being comprehensive. It rewarded them for being available and fast on the few things people actually want right now. A bloated SKU count works directly against that. It thins your replenishment, drags your fill rate, and dilutes the velocity your hero products need to win the shelf. The fix is not clever. It is just disciplined. Cut the slow movers, concentrate the stock, and let your best products run.

We build that discipline into Catalog & Assortment Operations and Marketplace Account Management, because on a dark store the catalogue is a budget, not a brochure. Spend it on what sells. Subtract the rest.

Scaling From One Crore to Ten on Marketplaces Without Breaking Ops

Getting a marketplace brand to one crore in annual revenue is a demand problem. You find a category with room, get the listings right, fund ads behind the SKUs that convert, and ride the platform’s traffic. Most of the work sits at the top of the funnel, and the constraint that holds you back is almost always whether enough people are finding and buying the product. So that is where founders point their attention, their budget, and their hiring. It works. It gets them to a crore.

Then they try to do it ten times over, with the same playbook, and the brand starts to crack in places that have nothing to do with demand. Stockouts on the hero SKU during the exact week ads are scaled. Cash locked in inventory the brand cannot reorder. A returns pile that quietly eats the margin the topline was celebrating. The demand was there. The brand could not carry it. That is the whole story of scaling on marketplaces in India, and the brands that survive it are the ones who planned for the constraint they had not hit yet.

The bottleneck moves, and most founders chase the old one

At one crore your binding constraint is demand. At ten crore it is almost never demand. It is some combination of inventory, cash, and process. The danger is not that the bottleneck is hard to fix. It is that it moves silently, and a founder trained by the first crore keeps optimising the thing that is no longer the problem.

You see it in the ad account. The brand that cracked acquisition keeps pushing spend because spending is the lever they know, and the orders arrive faster than the supply chain can serve them. Now you are paying to acquire demand you cannot fulfil, your account health drops on late shipments, and the platform throttles the listings you just paid to promote. The ads were never the problem. The ceiling was downstream the whole time.

Scaling does not break where you are looking. It breaks where you stopped looking once the first crore came in.

So the first discipline of scaling is unglamorous. Before you push more demand, find out what would fail if the demand doubled tomorrow. Usually it is not the funnel. It is the warehouse, the reorder cycle, or the bank balance.

Operations is the first wall you hit

The operational load of a marketplace brand does not rise in line with revenue. It rises faster. Ten times the orders is more than ten times the support tickets, returns, reconciliation lines, and SKU-location combinations to keep in stock. Process that ran on a founder’s memory and a shared spreadsheet at one crore becomes the single point of failure at five.

The brands that scale cleanly tend to have built the boring parts before they needed them. Inbound and labelling that does not depend on one person. A returns process that inspects, grades, and restocks instead of writing everything off. Reconciliation that catches the fees and deductions the platform quietly applies. None of this is exciting, and all of it is the difference between growth that compounds and growth that collapses under its own order volume. We made the full argument for front-loading this in the operations setup checklist before you list a single SKU, and at scale the cost of having skipped it is simply larger.

The signal that operations has become your bottleneck is specific. Your account health metrics start sliding even though nothing changed in the product. Late dispatch rate creeps up. Cancellation rate ticks. Negative feedback clusters around delivery, not the item. Those are not customer-service problems. They are capacity problems wearing a customer-service mask, and no amount of ad spend fixes them.

Capital is the constraint nobody plans for

This is the one that catches good brands by surprise, because it is invisible on the topline. Marketplace growth eats cash. You pay for inventory now and collect from the platform later, on a settlement cycle that can run a week or more. The faster you grow, the bigger that gap, because every rupee of new revenue requires inventory funded before the cash from the last batch has landed. Profitable brands run out of money mid-scale all the time, and the P&L gives no warning because the problem is not profit, it is timing.

Working capital, not demand, is what actually rations how fast you can grow once the funnel works. A brand that can fund three inventory cycles can scale three times faster than an identical brand that can fund one, regardless of how good either one’s ads are. That single fact reorders the priority list for most founders, and we devoted a whole piece to why in working capital is the real constraint on marketplace growth. The math is unforgiving and it does not care how strong your conversion rate is.

The practical moves at this stage are about widening the gap you can survive.

Forecast inventory against the growth you are funding, not the growth you hope for. Order to a demand plan you can actually pay for, because an out-of-stock hero SKU costs you rank that takes weeks to rebuild.
Negotiate supplier terms before you need them. Thirty days of credit from a manufacturer is cheaper working capital than anything a lender will offer, and it scales with the relationship.
Treat the platform settlement cycle as a financing cost. Reconcile it, claim back every wrongful deduction, and know to the day when cash lands so you can time reorders against it. Faster settlement tiers are a real working-capital lever, and they are earned through fulfilment reliability, not negotiated.
Hold a cash buffer sized to one full inventory cycle. The brands that die mid-scale are usually the ones who ran the buffer to zero to fund one more batch.

The long tail gets heavier as you grow

At one crore, a sprawling catalogue is survivable. A few slow SKUs hide inside the topline and nobody notices the cash they are holding hostage. At ten crore the same long tail is a serious drag, because every dead SKU is inventory you funded, warehouse space you rented, and reconciliation lines you process, all returning nothing. The catalogue that felt like optionality at the start becomes ballast.

Scaling is partly an act of subtraction. The brands that grow cleanly are usually narrower than they were, concentrating cash and attention on the SKUs that actually compound and cutting the ones that only consume. That decision gets harder emotionally as the catalogue grows, which is exactly why it needs a method rather than a feeling. We laid one out in killing the long tail that is bleeding you, and at scale the discipline pays back in freed capital faster than almost anything else you can do.

What changed recently, and what it means for your scaling math

Two shifts in the last year move the numbers in this article, and both cut in the brand’s favour if you are paying attention.

The first is fees. Amazon India has been cutting seller economics aggressively. Effective March 2026, it expanded zero referral fees to over 12.5 crore products priced under one thousand rupees across more than 1,800 categories, alongside lower Easy Ship and weight handling charges, and says the combined changes can save sellers up to 70 percent in total selling fees on qualifying items, per Amazon India. That is not a reason to relax. It is a reason to rerun the contribution margin on every sub-thousand-rupee SKU, because a SKU that was marginal at the old take rate may now be worth funding, and the brands that re-cut the math first will redeploy that freed margin into rank before slower competitors notice.

The second is that the demand surface itself is shifting toward quick commerce, and the platform economics there are tightening in the other direction. Quick-commerce players have spent the last two years layering on handling, platform, and surge fees to fix their own unit economics, as Storyboard18 documented, and the leaders are now turning structurally profitable on the back of it. Blinkit posted its first positive adjusted quarterly EBITDA, around four crore rupees, in the December 2025 quarter while running past two thousand dark stores on an increasingly inventory-led model, per Storyboard18. For a brand, an inventory-led quick-commerce platform means the platform, not you, increasingly decides what gets stocked in each dark store, which makes availability and trade terms the new battleground. We work through what that does to your margin in quick-commerce unit economics after platform fees. The headline for scaling is simple. The channel that grows your demand fastest is also the one that compresses your control hardest, so the operations and capital discipline this whole piece argues for matters more there, not less.

Plan the constraint, do not just react to it

The mistake is to scale until something breaks, fix it, and scale again until the next thing breaks. That works, badly, and it costs you a cracked listing rank or a cash crunch each time. The better operators do something different. They look one stage ahead and ask what the binding constraint will be at the revenue they are aiming for, then build for that constraint before they arrive at it.

That is why the order of operations matters more than the speed. Before you double ad spend, confirm the supply chain can serve the orders. Before you broaden the catalogue, confirm the cash can fund it. Before you enter a second marketplace, confirm operations can carry two account structures without the first one slipping. Sequencing the constraints is the actual skill, and it is the spine of a twelve-month marketplace growth roadmap that survives contact with reality. A roadmap that plans demand without planning the operations and capital to carry it is a wish, not a plan.

What changes in how you spend your own time

The founder who scales well usually stops being the best media buyer in the building and becomes the person who watches where the next wall is. Less time in the ad account, more time on the reorder calendar, the cash position, and the account-health dashboard. The leverage moves from acquisition to throughput, and so should your attention. The demand that got you to one crore is rarely what stops you from reaching ten. The thing carrying that demand is.

The short version

One crore is a demand problem and ten crore is an operations and capital problem, and the failure mode is bringing the first playbook to the second fight. The bottleneck moves from the funnel to the warehouse to the bank, quietly, while you are still optimising acquisition. Fee cuts on platforms like Amazon and the rise of inventory-led quick commerce change the numbers but not the lesson. Plan the constraint you will hit next, build for it before you arrive, and sequence growth around what the brand can carry rather than what the funnel can produce.

This is the work our D2C & Marketplace Strategy Consulting exists to do, mapping which constraint binds next and building for it ahead of time. Our Marketplace Performance teams keep the demand engine running while our Analytics & Reporting work makes the moving bottleneck visible before it breaks something. Demand gets you started. Operations and cash decide how far you go.

SKU Rationalization: Killing the Long Tail That Is Bleeding You

Open your listing count and feel the pride. Two thousand SKUs. Four thousand. A catalogue that looks like a serious operation. Now ask a harder question. How many of those SKUs sold more than a handful of units last quarter, and of the ones that did, how many made money after fees, returns, and the ad spend it took to move them. The honest answer, in almost every catalogue we have audited, is that a small head carries the business and a vast tail just sits there. The tail does not feel expensive because each dead SKU costs almost nothing on its own. Added up, it is one of the most expensive things you own.

SKU rationalization is the unglamorous discipline of cutting that tail on purpose. Not because pruning is virtuous, but because every dead listing is consuming something the winners need. Aggregate revenue hides this. Roll everything into one GMV number and the tail disappears into the average. You have to break the catalogue apart to see what it is actually doing to you.

The long tail is not free inventory, it is a tax

The seductive lie about a long tail is that it costs nothing to keep. The listing is already live. The photos are already shot. Why not leave it up in case someone wants it. The problem is that a SKU is never just a listing. It is a slice of working capital tied up in stock that turns once a year. It is a forecasting line nobody can predict. It is a row in every report that makes the real signal harder to read. It is operational attention every time it stocks out, gets a return, or throws a pricing error.

Multiply that across a thousand near-dead SKUs and you are running a second, invisible business whose only product is drag. The capital frozen in slow tail stock is capital you cannot put behind the SKUs that actually compound, which is the whole argument we make about working capital being the real constraint on marketplace growth. The tail does not lose money loudly. It loses it by denial of resources.

A dead SKU rarely shows up as a loss. It shows up as a winner you could not afford to stock deeper. The cost is the order you never placed.

Why aggregate revenue protects the tail

The reason most teams never cut is that the number they watch is built to hide the problem. Total revenue, total GMV, total units. At that altitude the tail and the head are blended into one comforting line that only ever goes up. Nobody looks at a rising top line and thinks half the catalogue should be deleted.

The tail only becomes visible when you change the unit of analysis from the catalogue to the SKU. The moment you rank every SKU by contribution rather than revenue, the bimodal shape appears. A steep head of SKUs that make real money, a long flat tail that makes almost nothing or actively loses. That ranking is exactly the output of measuring profitability per SKU, the number that reorders your whole catalogue. Rationalization is not a separate project. It is what you do with that list once you have it.

How to decide what dies

Cutting on gut feel is how good SKUs die and sentimental ones survive. The decision has to run on data, and the inputs are not exotic. For each SKU, you want a small set of honest signals over a trailing window:

Contribution, not revenue. Net of referral fees, fulfilment, returns, and ad spend. A SKU with healthy GMV and negative contribution is the first to go.
Velocity. Units per week. Slow-but-profitable is a different decision from slow-and-loss-making.
Inventory held. A dead SKU sitting on deep stock is freezing capital right now, not in theory.
Return rate. A high-return tail SKU costs far more than its refund line suggests once reverse logistics and write-offs are counted.
Strategic role. Some low-contribution SKUs earn their place as range fillers, search-coverage plays, or deliberate loss leaders. Name that reason explicitly, or cut.

Put those side by side and the catalogue sorts itself into keep, fix, and cut. The cut bucket is rarely small, and that is the point. You are not trimming a handful of mistakes. You are removing a structural drag the aggregate number was built to conceal.

Cut, merge, or fix

Killing is not the only move. A long tail often hides duplication. Six near-identical variants that split demand six ways, each looking weak alone, strong if consolidated into one or two. Merge those and velocity per SKU jumps without losing a single sale. Other tail SKUs are not dead, they are neglected. A broken title, missing attributes, or thin imagery suppresses them, and the fix is a listing problem, not a deletion. Telling the genuinely dead from the merely starved is where a catalogue data quality score your whole team can rally around earns its keep. Score the listing before you sentence it.

The forecasting dividend nobody mentions

Here is a benefit of rationalization that rarely makes the business case. A shorter catalogue is a more forecastable one. Every SKU you carry is a demand line someone has to predict, and tail SKUs are the least predictable lines you own. Spiky, sporadic, statistically hopeless. They add noise to planning and buffer stock you cannot justify.

Cut the tail and your forecasts get sharper, not just smaller, because you are now predicting demand that actually has a pattern. That compounds directly into better buying and fewer stockouts on the head, which is the entire premise of inventory forecasting for marketplaces when demand is spiky. A leaner catalogue is an easier catalogue to plan, and an easier catalogue to plan is a more profitable one.

What changed recently

Two forces in 2025 turned SKU rationalization from a quarterly hygiene task into a survival skill, and both came out of quick commerce.

First, the channel got more expensive to be average on. Through late 2025, FMCG brands reported quick-commerce margins falling three to five percentage points over six months as peak-slot ad rates nearly doubled and platform charges stacked toward forty percent of product price, according to Business Standard. When the channel taxes you that hard, a low-velocity SKU is not break-even, it is a guaranteed loss every time you pay to surface it. The contribution maths the whole article argues for is now the difference between a profitable shelf and a subsidised one.

Second, the platforms themselves are rationalizing. Blinkit ended the September 2025 quarter with 1,816 dark stores and is targeting 3,000 by March 2027 while moving to an inventory-led model, as covered by YourStory. A dark store holds a few thousand SKUs, not a few hundred thousand, and when the platform owns the inventory it has every incentive to stock only what turns. Your long tail does not just cost you. It gets you delisted by a buyer optimising the same shelf you should be. The winning brands on these platforms are running tight, hero-led ranges rather than sprawling portfolios, a shift Inc42 has tracked across the category. The discipline that used to be optional on Amazon is now mandatory on quick commerce, and it works the same way. We go deeper on this in pruning slow movers on quick commerce.

Run it as a standing discipline, not a one-off purge

The classic failure is to do this once, feel virtuous, and watch the tail grow straight back. SKUs accumulate the way clutter does, one reasonable addition at a time. A new variant here, a seasonal experiment there, a launch that never landed but never got removed. Without a recurring review, you are back to a bloated catalogue within a year.

So make rationalization a cadence, not an event. A quarterly pass that re-ranks every SKU by contribution and velocity, flags the bottom of the tail, and forces an explicit keep-fix-cut decision on each one. Pair it with a rule that new SKUs come in on probation. Earn velocity and contribution inside a window or get pruned automatically. That turns the catalogue from a thing that only grows into a thing that is actively curated.

The short version

A long catalogue is not a sign of strength. It is usually a sign that nobody has looked hard enough to cut. Aggregate revenue lets a tail of loss-making, capital-freezing, forecast-wrecking SKUs hide behind the winners, and the longer it hides the more it costs in orders you could not afford to place. With quick-commerce fees climbing and platforms stocking only what turns, the tail is no longer just a drag, it is a liability. Rank by contribution, decide cut, merge, or fix on data, free the working capital, and run it every quarter so the tail never grows back. The discipline is dull. The dividend, in capital and in clarity, is not.

Building the per-SKU view that makes these cuts defensible, and turning it into a standing review leadership trusts, is what our Analytics & Reporting work exists for. Cut the tail to fund the head. The catalogue gets shorter and the business gets stronger at the same time.

Profitability Per SKU: The Number That Reorders Your Whole Catalog

Pull up your marketplace dashboard and sort by revenue. The SKU at the top feels like the hero of the catalogue. Everyone protects it, stocks deep on it, builds campaigns around it. Now do something most teams never do. Take that same SKU and subtract every cost the platform charges to sell one unit. Referral fee, closing fee, weight-based shipping, return handling, the ad spend it took to win the order. What is left is contribution per unit. Run that math across the catalogue and the list almost always reorders. The bestseller drops. A quiet SKU three rows down turns out to be the one paying the rent.

This is the single most clarifying number in marketplace analytics, and it is the one almost nobody reports. GMV is loud and easy. Profitability per SKU is quiet and hard. So teams optimise the loud number and wonder why scale never turns into money.

GMV ranks attention, not value

Gross merchandise value tells you which SKU moves the most rupees through the platform. That is a measure of attention, not of worth to your business. A high-GMV SKU can be a margin sinkhole. It might carry a heavy referral percentage in its category, ship at a weight that eats the contribution, attract returns that quietly double its cost of sale, or only sell at volume because it is propped up by aggressive ad spend that never appears next to the revenue line.

None of that shows up when you sort by GMV. The number looks magnificent right up until you net it down. And because the platform reports revenue prominently and costs in a dozen scattered statements, the flattering view is the default view. You have to go looking for the truth.

GMV tells you what the platform sold. Contribution per SKU tells you what you got to keep. Only one of those pays salaries.

What actually goes into per-SKU contribution

Contribution per unit is not complicated. It is just tedious, which is why it gets skipped. For a single unit of a SKU, start at the selling price and remove everything the sale costs you to deliver:

Cost of goods. The landed unit cost, including inbound freight and any pre-marketplace handling.
Referral fee. The platform’s category commission. This varies enormously by category and is the silent killer on low-price items.
Fulfilment and weight fees. Pick, pack, and shipping. Heavy or bulky SKUs can lose here even at a healthy headline margin.
Returns cost, amortised. Not just the refund. The reverse logistics, the inspection, the units that come back unsellable. A high return-rate SKU carries this on every unit sold, not only the returned ones.
Ad cost per unit. Total spend on that SKU divided by units sold. If it only sells because you pay for every click, that spend is part of its unit economics, full stop.

What remains is contribution per unit. Multiply by units and you have total contribution. Rank the catalogue by that, and you are finally looking at the business instead of the brochure. The returns line alone reorders fashion and apparel catalogues hard, which is why we treat return rate as a margin problem, not a logistics one.

The ad layer is where the bestseller usually dies

The most common reversal happens once you load ad cost onto the unit. A SKU can look profitable on cost-of-goods and fees alone, then turn negative the moment you account for the spend keeping it visible. This is exactly the trap of judging campaigns on the wrong metric. A pretty advertising cost of sales on a SKU that loses money per unit is not efficiency, it is a faster way to lose. We have argued at length that you cannot read ad efficiency without the total view, which is the whole point of looking at TACoS rather than the number your ad team prefers.

Put profitability per SKU and ad cost per SKU side by side and a pattern appears. Some SKUs earn their organic rank and barely need spend. Some are pure ad annuities, profitable only while you keep feeding them, dead the day you stop. Knowing which is which changes where every marginal rupee of budget goes. You stop subsidising vanity volume and start funding the SKUs that compound.

Quick commerce makes the math unforgiving

If marketplace contribution is tight, quick commerce is tighter. The take rates are steeper, the basket economics are different, and the margin for error is thin to non-existent. A SKU that contributes comfortably on a marketplace can go underwater the instant it enters a ten-minute channel with platform fees and darkstore economics layered on. Running per-SKU profitability is not optional there. It is the only thing standing between you and scaling a loss. We walk through that arithmetic in the quick commerce margin reality check, and the short version is that channel-blind unit economics will bury you.

The fee load on these channels is no longer the quiet part. Reporting in 2025 put Blinkit’s listing charge at around twenty-five thousand rupees per SKU per state, refunded as ad-wallet credit, with Instamart and Zepto quoting listing-cum-ad packages running into several lakh rupees, and one spice brand told Storyboard18 it spends ten to fifteen percent of GMV just to stay visible on the channel. A per-SKU model that ignores those fixed fees and the ad tax on top of them is not a model, it is a wish.

Same SKU, different channel, different verdict

Contribution is not a property of a SKU. It is a property of a SKU on a specific channel. The same product can be your best earner on one marketplace, break-even on another, and a loss leader in quick commerce. Averaging across channels hides all of it. The number only means something when it is cut by SKU and by channel together, which is precisely the kind of view a blended report is built to obscure.

What the reordered list tells you to do

Once you rank by contribution instead of GMV, the actions stop being guesswork. The catalogue sorts itself into a handful of honest buckets.

High contribution, high volume. Your real heroes. Protect availability ruthlessly, never let these stock out, and concentrate the budget that compounds here.
High contribution, low volume. Underexposed winners. These deserve more visibility, better listings, and the ad spend you were wasting on vanity SKUs. Fixing the listing often unlocks the volume.
Low contribution, high volume. The dangerous bucket. Loud, busy, and barely profitable or worse. Re-price, renegotiate cost of goods, cut the ad dependency, or accept they are a deliberate loss leader. Never mistake their GMV for health.
Low contribution, low volume. The long tail that quietly bleeds operational attention and working capital. This is the bucket for honest pruning.

That last bucket is where most catalogues are carrying dead weight they have never measured. Cutting it is not failure, it is hygiene, and it is the natural sequel to this analysis. Once profitability per SKU exposes the tail, the next move is rationalising the SKUs that are bleeding you rather than admiring how many listings you have.

What changed recently

Two shifts in the last several months should send every operator back to the per-SKU model to re-run it. The first is good news for low-price catalogues. In November 2025 Flipkart waived seller commission on goods under one thousand rupees, and Amazon India followed by removing referral fees in the same price band, a move Business Standard reported as a direct response to Flipkart. By March 2026 Amazon had expanded zero referral fees to more than twelve crore products under one thousand rupees across some eighteen hundred categories and trimmed Easy Ship fees for sub-three-hundred-rupee items, with YourStory noting sellers could cut fee costs sharply in that bracket. If a chunk of your catalogue sits under one thousand rupees, the referral line on those SKUs may have just gone to zero, and SKUs you had quietly written off as margin-negative can flip back into the black. Re-run the model before you prune them.

The second shift cuts the other way. The visibility tax on quick commerce keeps climbing. Storyboard18 reported that Blinkit, Zepto and Instamart together crossed three thousand crore rupees in advertising revenue in FY25 and are tracking toward roughly four thousand nine hundred crore this year, with advertising now near fifteen percent of Blinkit’s revenue. That money comes out of brand margins one sponsored slot at a time. The lesson is the same one the per-SKU model has always taught. Lower commissions on one channel do not make you profitable, and rising ad costs on another do not have to sink you. Only the contribution number, cut by SKU and by channel and refreshed when the fee structure moves, tells you which way each SKU actually broke.

Make it a number leadership can see

None of this works if the analysis lives in a spreadsheet one analyst opens once a quarter. Profitability per SKU has to be a standing view, refreshed and ranked, sitting where the people who set budgets and stock plans will actually look at it. That is a reporting discipline as much as an analytics one. A contribution-ranked SKU list, cut by channel, beside the GMV list everyone already trusts, is one of the most decision-changing things you can put on a single screen. Getting it there without drowning leadership in tabs is exactly what we mean by a dashboard leadership will actually read.

The short version

GMV ranks your catalogue by how much the platform sold. Profitability per SKU ranks it by how much you kept. Those two lists are rarely the same, and the gap between them is where the money you thought you were making quietly disappears. Net every SKU down to contribution after fees, returns, and ad spend, cut it by channel, and rank by what survives. When a platform zeroes a referral fee or raises an ad rate, the verdict on individual SKUs moves, so the model is not a one-time exercise. The bestseller you have been protecting may be the one you should be re-pricing, and the SKU you have been ignoring may be the one funding the business.

Building that view, channel by channel and unit by unit, is what our Analytics & Reporting work is for, and it is why our Marketplace Performance teams are judged on contribution rather than the GMV slide. Rank by profit, not by attention. The catalogue will tell you the truth the moment you ask it the right question.