Inventory Forecasting for Marketplaces When Demand Is Spiky

Pull up a year of marketplace sales for any brand selling on Amazon or Flipkart in India and the shape is unmistakable. Long flat stretches, then violent vertical walls during sale events, then a hangover dip, then flat again. It is not a trend line. It is a heartbeat monitor. And almost every forecasting method a seller reaches for first is built to smooth that heartbeat into a comfortable average that is wrong on both the quiet days and the loud ones.

The cost of getting it wrong is not symmetric. Overstock ties up cash and racks up storage fees. Understock during a spike does something worse. It hands the sale to a competitor and, on platforms where availability feeds rank, it costs you the organic position you spent months earning. Spiky demand punishes the naive forecast far harder on the downside than the upside, and that asymmetry should change how you plan.

Why steady-state forecasting fails here

Most forecasting defaults to some version of a moving average. Take the last few weeks or months, smooth them, project forward. It is the logic baked into spreadsheets, into basic seller tools, into the gut instinct of anyone who has run a normal business. And on steady demand it works fine.

Indian marketplace demand is not steady. It is dominated by a handful of engineered events. Big Billion Days, the Great Indian Festival, Republic Day and Independence Day sales, Prime Day, end-of-season clearances. On those days a SKU can do a month of volume in seventy-two hours. A moving average treats that spike as either noise to be flattened away or, worse, as a new baseline to project forward from. Both readings are wrong. The spike is not noise and it is not the new normal. It is a known, dated, plannable event.

You are not forecasting demand. You are forecasting a calendar of events, and demand is what happens between them.

This is the mental shift. Stop trying to predict a single smooth curve. Start treating your year as a steady-state baseline with named, dated spikes layered on top, each one planned as its own mini-launch.

Separate baseline demand from event demand

The first practical move is to split your history into two pools. Strip the sale-event weeks out of your data entirely. What remains is your true baseline, the demand that shows up when the platform is not actively manufacturing urgency. Forecast that with whatever simple method you like, because on the quiet days a moving average is genuinely fine.

Then forecast the events separately, because they follow completely different rules. Event demand is driven by your deal acceptance, your ad budget, your discount depth, and your rank going into the sale, not by last week’s run rate. A SKU that idles at twenty units a day can do two thousand units across a four-day event if it lands a lightning deal and the ad spend is there. No baseline forecast on earth predicts that from the run rate. You predict it from the plan.

What goes into an event forecast

Last year’s same event, adjusted. Your single best anchor. Take the comparable event from the prior year and adjust for how much your rank, catalogue, and ad budget have changed since.
Deal type and visibility. A lightning deal or a featured placement multiplies volume far beyond a quiet listing discount. The slot you secure changes the forecast more than the price does.
Discount depth versus the category. Shoppers comparison-hunt hardest during events. Your relative discount, not your absolute one, drives conversion.
Planned ad spend through the window. Spike demand is partly bought. If the budget is not committed, the volume will not arrive, and you should not stock for it.

This is why event planning starts months out, not days out. The deep version of this for Flipkart’s flagship event is its own discipline, and we have written separately about planning inventory and ads for Big Billion Days well ahead of time precisely because the forecast and the inbound shipment have to be locked before the platform even confirms your deals.

Buffer stock is not a single number

The instinct after a stockout is to crank safety stock up across the board. Hold more of everything, always. That is expensive and it still does not protect you, because a flat buffer is sized for average variability and your variability is anything but average around events.

Buffer stock should flex with the calendar. For most of the year you hold a lean safety buffer sized to cover normal demand noise plus your replenishment lead time. In the weeks before a known event, that buffer expands deliberately to absorb the spike plus the forecasting error on the spike, which is large. After the event, it contracts again so you are not paying festive-season storage rates to warehouse units that will now sell slowly for two months.

The right buffer also depends on where your stock physically sits, because the fulfilment model dictates your lead time and your reaction speed. A unit in a platform warehouse converts to a sale instantly but cannot be repositioned quickly. A unit you ship yourself gives you control but adds days to every replenishment cycle. That tradeoff sits underneath every buffer decision, and it is the same calculation we walk through in the fulfilment math comparing FBA, Easy Ship and self-ship. Your forecasting and your fulfilment choice are not separate problems.

The asymmetry that should bias you

When you forecast a spike, you will be wrong. The only question is which direction, and the two directions are not equally costly.

Overstock on a fast-moving SKU going into a festive period is a cash and storage problem. Annoying, recoverable, and on a SKU that already sells, the excess usually clears over the following weeks. Understock during the same event is a different category of damage. You lose the immediate sales, you lose the deal slot you may not get back, and on Amazon especially you lose velocity at the exact moment the algorithm is watching hardest. The rank you drop can take weeks of full-price selling to climb back, which means a few days of empty stock quietly taxes you for a quarter.

We have argued before that the true cost of a stockout is mostly the ranking damage you cannot see on the invoice, and that argument is exactly why your event buffer should lean heavy. When the downside of one error dwarfs the downside of the other, you bias your forecast toward the cheaper mistake. For your hero SKUs during a major event, planned overstock is not waste. It is insurance priced correctly.

Quick commerce breaks the model again

Everything above assumes a marketplace where you ship into one or a few central warehouses. Quick commerce inverts the problem. Demand still spikes, but now it spikes locally and you are forecasting per dark store, where a single SKU’s daily volume is small enough that ordinary statistical noise swamps the signal. The buffer logic survives. The forecasting method does not. That is a distinct enough problem that we treat it on its own in forecasting inventory for quick commerce dark stores, and you should not assume your marketplace model ports over to it cleanly.

What changed recently

The last festive cycle made the case for event-led forecasting better than any argument could. On 22 September 2025, India’s GST 2.0 reform collapsed the old four slabs into a simpler structure and cut rates on more than two hundred items, deliberately timed to land with Navratri and the festive run. The effect on demand was immediate and uneven, exactly the kind of engineered spike a moving average cannot see coming. Consumer durables sales reportedly jumped forty to forty-five percent and e-commerce platforms were among the biggest beneficiaries, per Outlook Business. If you had stocked to last year’s run rate, you were short on the categories that moved hardest.

The platforms then converted that demand into record events. Amazon reported its Great Indian Festival 2025 drew over 276 crore customer visits with the highest-ever number of sellers recording a sale and seventy percent of traffic from tier 2 and tier 3 cities, per About Amazon India. Flipkart’s Big Billion Days 2025 leaned on the same tax tailwind and on Flipkart Minutes, with quick commerce reshaping festive delivery expectations rather than sitting beside the main sale, per Coresight Research. The deeper tier-2 and tier-3 pull matters for forecasting because it widens which SKUs spike and where, and it rewards brands that already understand how demand behaves beyond the metros.

Quick commerce kept compounding the local-forecasting problem too. Through 2025 Blinkit pushed past a thousand dark stores with plans toward two thousand, and Zepto crossed nine hundred on its way past eleven hundred by early 2026, per Akoi. Every new store is another node where your per-location forecast is thin, noisy, and unforgiving of a flat buffer. The platforms answer this with AI-driven demand forecasting and replenishment as core infrastructure, and brands selling into them need a matching discipline, not a spreadsheet.

Make the calendar the spine of the plan

The brands that get this right are not running smarter algorithms. They are running a discipline. They keep a rolling event calendar twelve months out, every platform sale marked, and they build the inbound shipment plan backwards from each event date through the inbound lead time so stock lands before deals go live, not during. They forecast baseline and events as two separate exercises with two different methods. And they accept that on hero SKUs in peak windows, a deliberate overstock beats a stockout every single time.

None of this is exotic. It is operational rigour applied to a demand curve that punishes anything less. This is the core of what our Operations & Logistics Management work does for a brand, and it sits directly alongside the Marketplace Performance and Advertising & Media Buying teams, because the ad budget and the deal slots are what create the spike you are stocking for. Forecast the calendar, not the average. Buffer for the event, not the steady state. The math only works when it respects the heartbeat.

Amazon Great Indian Festival: A Sane Prep Plan for Lean Teams

Every year, sometime in August, a small brand team looks at the Great Indian Festival calendar and quietly panics. The catalogue has forty SKUs. The festival is six weeks out. The team is four people, maybe three, and one of them also runs customer support. So they do the natural thing. They try to get everything ready. Every listing refreshed, every SKU discounted, ads spread thin across the whole range so nothing gets left out. And then the event arrives and the brand finishes the biggest sale window of the Indian year having done a mediocre job on everything and a great job on nothing.

That is the failure mode, and it is almost universal among lean teams. The Great Indian Festival rewards concentration, not coverage. A small team that backs three SKUs hard will beat a small team that backs thirty SKUs softly, every time. The whole prep plan below is built on that one decision, made early and held without flinching.

Pick your heroes before you do anything else

Before you touch a single listing, decide which SKUs you are actually going to fight for. Not which ones you would like to do well. Which ones get the budget, the deal slots, the inventory, and your limited attention. For most lean brands that number is between three and six. Everything else rides along on a baseline discount and gets no real push.

How do you choose? Look for the SKUs where you already have proof and room.

Existing rank and review depth. A SKU sitting on page one with a healthy review count converts during a sale. A SKU buried on page four does not magically surface because you discounted it. The festival amplifies position you already hold, it does not create it.
Margin that survives the discount. A hero SKU has to take a festive-grade discount and still leave you something. If a SKU only works at full price, it is not a hero, it is a trap.
Inventory you can actually hold. A hero you stock out of mid-event is worse than a SKU you never pushed, because the rank damage outlasts the sale.
A deal slot you can realistically win. Lightning deals and featured placements are rationed. Concentrate your asks on the SKUs most likely to get them.

A lean team’s edge is focus. The Great Indian Festival is a focus test disguised as a logistics test.

Lock inventory backwards from the event date

Inventory is where festival prep actually lives or dies, and it is the part lean teams under-plan most. Your hero SKUs need to be in the warehouse and live before deals go active, not arriving during. That means working backwards from the event date through your inbound lead time, and committing the shipment weeks ahead of the sale.

The hard part is that festive demand does not behave like your normal run rate. A SKU that idles at thirty units a day can do many multiples of that across a deal window, and a naive forecast off recent sales will leave you short. This is its own discipline, and we walk through it properly in our piece on forecasting inventory for marketplaces when demand is spiky. The short version for the festival: forecast the event separately from your baseline, anchor on last year’s same window adjusted for your current rank and budget, and then bias deliberately toward overstock on your heroes. The cost of overstocking a fast SKU is storage and a slow clearance. The cost of stocking out is the deal slot, the velocity, and weeks of rank you cannot buy back.

If you also sell on Flipkart, the same logic governs Big Billion Days, which usually runs in the same window, and we cover that planning cadence in planning inventory and ads for Big Billion Days months ahead. The two events often overlap, which makes the case for fewer heroes even stronger, because your inventory and your attention are now split across two platforms.

Set pricing so the discount means something

During the festival, shoppers comparison-hunt harder than at any other time of year. Your absolute discount matters less than your discount relative to the category. A flat ten percent off when the category is running thirty will read as no discount at all. So the pricing question for each hero is not what can I afford, it is what does this need to be to win the click against the listings next to it.

That tension between winning the sale and protecting the margin is the whole game, and it is easy to give away more than you needed to in the heat of the event. We lay out how to think about it in protecting margin when everyone discounts. The festival-specific point is this. Because you have only a few heroes, you can afford to price them aggressively and precisely, instead of spreading a thin, defensive discount across forty SKUs that fools nobody. Concentration buys you the room to be sharp where it counts.

Concentrate the ad budget, do not spread it

Here is where lean teams leak the most money. They take a modest festival ad budget and divide it evenly across the catalogue, so every SKU gets a trickle and none gets enough to actually move. During an event, that trickle is worse than useless, because everyone’s bids spike at once and a small per-SKU budget gets outbid before it does anything.

Pour the budget into the heroes. Let them dominate their search terms for the window, win the placements, and ride the velocity into better organic rank that outlasts the sale. A few SKUs funded properly will return far more than the whole catalogue funded thinly. If you are still calibrating how to read your spend during the event, our note on reading ACoS against total advertising cost of sale is a useful frame for the festival push, because the festival is the same problem under pressure: spend concentrated, measure honestly, do not spread yourself into irrelevance.

What to do in the days right before

Raise hero bids ahead of the spike, not during it, so you are not scrambling against the whole category at once.
Pause spend on non-heroes that cannot convert, and move that budget to the SKUs that can.
Pre-write and check your deal listings, so a typo or a missing image does not waste the slot you fought to get.
Confirm stock is live, not just inbound, on every hero before deals activate.

What to deliberately ignore

The discipline of a good festival plan is as much about what you refuse to do as what you do. For a lean team, the non-heroes get a baseline festive discount, no special ad spend, and no extra prep. That is not neglect. That is the plan. The energy you would have spent making forty mediocre pushes goes into making four excellent ones.

This feels uncomfortable the first time, because it means consciously letting most of your catalogue coast through the biggest event of the year. But the brands that try to be everywhere during the Great Indian Festival end up nowhere, and the ones that pick their ground and hold it walk away with rank gains that compound for the rest of the quarter. Fewer bets, backed harder, is not the cautious option. It is the aggressive one.

What changed recently

The 2025 festival made the case for concentration stronger, not weaker. Amazon reported a record 276 crore customer visits across the Great Indian Festival, with 70 percent of traffic coming from tier 2 and tier 3 cities, per Amazon India. The brands that won were not the ones spread thin. The category spikes were sharp and specific, with premium smartphones above thirty thousand rupees up around 30 percent and festive home decor up several multiples, which is exactly the pattern a hero strategy is built to catch.

The other shift worth planning around is the GST rate revision that landed just before the season. Redseer found the first eleven days of festive 2025 ecommerce clocked more than sixty thousand crore in GMV, up 20 to 22 percent year on year and nearly double the prior year’s pace, with smartphones and appliances driving most of that growth on the back of GST-led price cuts, per Redseer. If a tax change has moved your landed price, fold it into your hero pricing before the event, not after. Fashion, notably, showed only low single-digit growth because year-round discounting has spread that demand across the calendar, which is one more reason to put your heroes where the festive lift actually concentrates.

And do not assume the festive surge follows shoppers onto quick commerce. Redseer noted quick commerce held its usual growth trajectory of over 120 percent during the season but did not see a festive spike, because for large-ticket and considered purchases traditional ecommerce is still where people buy. If your category leans considered, the Great Indian Festival on Amazon and Flipkart remains the event to plan your heroes around, not your ten-minute listings.

The plan in one breath

Choose three to six heroes on proof and margin. Lock their inventory backwards from the event date with a forecast that respects the spike. Price them sharply against the category, not defensively across the catalogue. Pour the ad budget into them and starve everything else. Let the non-heroes coast on a baseline discount and do not feel bad about it.

None of this needs a big team. It needs an early decision and the nerve to hold it through the noise of the event. That concentration is exactly what our Performance Marketing & Ads work brings to a festival, and it sits alongside the Marketplace Management and Operations & Logistics teams, because the deal slots and the inbound shipment are what turn a chosen hero into an actual win. Pick your few. Back them hard. Ignore the rest on purpose.