Before Q4, a multichannel seller needs answers to twenty questions, and each one names the data it needs and the decision it drives. The list below is grouped by phase. Work it in order, because the later questions (ad budget, cash, channel mix) depend on the earlier ones (inventory position, storage exposure, margin by SKU). Where a question needs a number you do not have, that gap is the finding. The companion piece on Q4 inventory readiness covers the operational side; this one is about the questions.
Phase 1: Inventory position
- How many days of cover does each SKU have, by channel, at Q4 velocity rather than September velocity? Data: on-hand by warehouse and by FBA or WFS location, inbound in transit, last year's October-to-December weekly units by SKU. Decision: which SKUs get a PO this week and which do not. September velocity understates Q4 for seasonal products and overstates it for products that got a summer bump.
- Which SKUs will stock out before the last inbound cutoff each marketplace publishes? Data: days of cover from question 1, supplier lead time, each marketplace's inbound deadline for holiday availability. Decision: expedite, air-freight, or accept the stockout and pull the ad spend on that SKU.
- Which SKUs are over-covered, with more than the full quarter's expected units on hand? Data: the same cover calculation, read from the other end. Decision: these are the liquidate-or-discount candidates and the SKUs that get no Q4 PO.
- What is in transit, from where, and when does it land? Data: PO history with expected receipt dates, transfers tracked as in transit until received. Decision: whether a "stockout" in question 2 is real or a timing gap that closes on its own.
Phase 2: Storage fee exposure
- How many cubic feet do I have in each fulfillment network right now, by SKU? Data: unit dimensions, units on hand by location. Decision: the base for every storage-fee question that follows.
- What does peak-season storage cost me per SKU if I hold it through December? Data: cubic feet from question 5, each network's published peak rate. Walmart's marketplace pricing page lists WFS storage at $0.75 per cubic foot per month January through September, with an additional $1.50 per cubic foot per month in October through December for items stored more than 30 days. Amazon publishes its own monthly and peak rates on its FBA fee schedule; check the current one. Decision: which slow SKUs cost more to store than they will earn.
- Which units cross an aged-inventory threshold during Q4? Data: inventory aging by SKU and receive date, each network's aged-inventory surcharge schedule. Decision: remove or liquidate before the surcharge date, or accept the surcharge with the number in hand. The keep, discount, liquidate, or remove guide runs the arithmetic.
Illustrative numbers for question 6: a seller holds 900 units of a slow SKU in WFS at 0.30 cubic feet each, or 270 cubic feet. At the January-to-September rate that is 270 times $0.75, or $202.50 a month. For units held past 30 days in October through December, add 270 times $1.50, or $405.00, for $607.50 a month. If the SKU sells 60 units a month at $2.10 contribution before storage, it earns $126 against $607.50 of storage. Holding it through Q4 loses money every month. That is the decision the question exists to force.
Phase 3: Margin by SKU
- Which SKUs made money last Q4 after fees, ads, returns, and COGS, and which did not? Data: last year's October-to-December reconciled contribution by SKU. Decision: the promotion list and the do-not-promote list.
- Which SKUs have moved into a higher fulfillment fee band since last year? Data: current fee per unit from settlements versus last year's. Decision: repackage, reprice, or accept a thinner Q4 margin on that product.
- What is each SKU's current FIFO landed cost, and does the next PO layer cost more? Data: inventory layers with freight allocated, open PO pricing. Decision: whether the Q4 promotional price still clears margin once the new layer is consumed.
- What was each SKU's return rate last Q4, and what did each return cost? Data: refunds tied to orders by SKU and channel, return shipping. Decision: which products get pulled from the deep-discount list because returns eat the margin.
Phase 4: Ad budget
- Which SKUs earned back their ad spend in gross profit last Q4, by channel? Data: spend by SKU by channel, attributed sales, margin before ads. Decision: where the incremental budget goes first.
- What is my break-even ACoS per SKU at the planned Q4 price? Data: margin before ads at the promotional price. advertising.amazon.com's ACoS guide states the rule: ACoS has to be below profit margin to hold profit. Decision: the ceiling for each campaign's target.
- Which SKUs will stock out mid-quarter, and when should their ads stop? Data: days of cover from question 1. Decision: scheduled pauses, so spend does not run against an out-of-stock listing.
Phase 5: Cash
- How much cash is tied up in inventory today, by SKU? Data: units on hand times FIFO cost. Decision: the ceiling on new POs without outside funding.
- When do Q4 payouts land, by marketplace, and what is the gap between the PO due date and the first settlement that covers those units? Data: each marketplace's settlement cadence, supplier payment terms. Decision: how much of Q4 needs to be financed and for how long.
- What is the incremental cash contribution of holding versus discounting versus liquidating the over-covered SKUs from question 3? Data: sunk COGS set aside, future storage fees, expected sell-through, selling fees, expected cash recovery. Decision: hold, discount, liquidate, or remove, per SKU. Crunch, the analytics AI inside ConnectBooks, ranks SKUs on this basis when asked, treating already-paid COGS as a sunk cost.
Phase 6: Channel mix
- Which channel gives each top SKU the best contribution margin at Q4 prices? Data: normalized contribution by SKU by channel. Decision: where to allocate scarce units when a SKU cannot be stocked everywhere.
- Which channel had the highest return rate on each top SKU last Q4? Data: returns by channel by SKU. Decision: whether a channel's volume is worth its returns for that product.
- If I have to short one channel, which one costs the least in contribution and the least in account health? Data: contribution by channel from question 18, each marketplace's stock-availability metrics. Decision: the allocation order when inventory runs short in December.
What answers these questions
Every question above reads from the same base: settlements reconciled at the transaction level, FIFO landed cost per unit, inventory tracked by warehouse with in-transit stock and aging visible, and ad spend booked by channel. ConnectBooks builds that base, and its inventory reporting covers on-hand by warehouse, value, aging, and a restock report driven by sales history, velocity, lead times, and inbound stock. Questions 1 through 7 and 15 through 17 come out of that layer directly.
Crunch answers the questions in plain English on top of the reconciled data: what changed, over which periods, on which products, why, and what to do next. It cannot answer question 2 if supplier lead times were never entered, question 10 if the last PO went in without freight, or question 16 if the supplier's terms live in an email. It does not know your supplier's factory closes for two weeks in October. It does not place the PO. Ask the twenty questions, note which ones your data cannot answer today, and fix those first. Q4 arrives either way.
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