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Seasonality Index

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A seasonality index measures how much a given month's sales deviate from the overall monthly average. An index of 1.0 means average demand. An index of 2.0 means that month sells double the average. FBA sellers apply it to their baseline demand forecast so they order enough for Q4 without overstocking in Q1.

How the seasonality index works

Every FBA product has months where it sells faster and months where it slows down. A seasonality index quantifies that pattern as a multiplier for each month of the year. You calculate it from at least one full year of sales data (two years is better for smoothing anomalies).

The index is a ratio: each month’s average daily sales divided by the overall average daily sales across all months. A month that sells exactly at the annual average gets an index of 1.0. A month that sells 40% above average gets 1.4. A month that sells 25% below average gets 0.75.

Once you have the 12 monthly indices, you multiply your baseline demand forecast by the index for whatever month the inventory will be selling during. This is what separates a flat forecast from one that actually matches your business rhythm.

Seasonality index formula

SEASONALITY INDEX
Index(month) = Month's avg daily sales / Overall avg daily sales
ADJUSTED FORECAST
Adjusted forecast = Baseline forecast × Index(month)
Overall avg daily sales = total units sold / total days in dataset
Use 2+ years of data to smooth out one-time anomalies
// Index values should sum to approximately 12.0 across all months

Example: a $38 holiday gift product

You sell a bamboo cutting board set at $38 ASP. It’s a popular gift item that surges in Q4. Here’s your 2-year average daily sales by month:

MonthAvg daily unitsSeasonality index
Jan150.60
Feb140.56
Mar180.72
Apr200.80
May220.88
Jun240.96
Jul210.84
Aug230.92
Sep281.12
Oct351.40
Nov481.92
Dec321.28

Overall average daily sales: (15+14+18+20+22+24+21+23+28+35+48+32) / 12 = 25.0 units/day

October index: 35 / 25 = 1.40

January index: 15 / 25 = 0.60

Now apply it. Your baseline forecast (from exponential smoothing) says 25 units/day. For a PO landing in November with a 75-day lead time, you’d place the order in late August. The inventory needs to cover November and December selling:

November adjusted forecast: 25 × 1.92 = 48 units/day × 30 days = 1,440 units

Without the seasonality index, you’d order 25 × 30 = 750 units for November and stockout halfway through the month. The index prevents a $27,360 revenue gap (690 units × $38 + lost organic rank).

FBA-specific considerations

Amazon’s seasonal storage surcharges add another layer. From October through December, FBA storage fees increase significantly, and aged inventory surcharges still apply. Your seasonality index tells you to send more inventory for Q4, but Amazon’s fee structure punishes you for sending it too early. The timing math matters: ship enough to cover peak demand but land it close to when it sells, typically arriving at FBA by mid-September for holiday products.

Also watch for Amazon’s receiving delays during peak. If your shipment takes 14 days to check in during October instead of the usual 5, your effective lead time extends by 9 days. Factor this into the forecast window when placing your Q4 PO. Amazon’s FBA inventory storage fees page details the current seasonal surcharge schedule.

Common mistakes

  1. Using only one year of data. A single year can be distorted by a one-time event (a viral TikTok, a competitor stockout, a bad review period). Two years of data smooths these out and produces a more reliable index.
  2. Applying the same index to every SKU. A kitchen gadget and a winter coat have completely different seasonal curves. Calculate the index per SKU or at minimum per product category.
  3. Forgetting to adjust for stockouts in historical data. If you were out of stock for two weeks in November last year, your November average is artificially low and the index will understate Q4 demand. Backfill stockout periods before calculating.

Related terms

How Profit Hawk handles this
Profit Hawk calculates your seasonality index automatically using 2 years of sales history and applies it to every reorder recommendation. No spreadsheet formulas required. It also detects and excludes stockout periods from the index calculation so your Q4 multiplier reflects true demand, not suppressed sales. You can see the index for every SKU and override it manually if you know something the data doesn't. See the seasonality engine.

Frequently asked questions

What is a seasonality index in Amazon FBA?

A seasonality index is a multiplier for each month that shows how much demand deviates from the annual average. An index of 1.0 is average, 1.5 means 50% above average, and 0.7 means 30% below average. FBA sellers use it to adjust reorder quantities so they stock up before peak months and scale back during slow ones.

How do I calculate the seasonality index?

Divide each month's average daily sales by the overall average daily sales across all 12 months. Use at least 2 years of data. Example: if your overall average is 25 units/day and October averages 35 units/day, October's index is 35/25 = 1.40. The 12 monthly indices should sum to approximately 12.0.

How many years of data do I need?

Two years minimum. One year of data can be skewed by one-time events like a viral social media post, a competitor going out of stock, or a listing suppression. Two years smooths these anomalies. If you have 3+ years, even better, but weight recent years more heavily if your product category is shifting.

Should every SKU have its own seasonality index?

Yes. A kitchen gadget, a winter jacket, and a yoga mat all have different seasonal curves. At minimum, calculate the index per product category. Per-SKU is ideal if you have enough sales history. Products with fewer than 12 months of data can use a category-level index as a starting point.

What if my product doesn't have clear seasonality?

Some products sell consistently year-round. If your monthly indices all fall between 0.85 and 1.15, seasonality is minimal and you can skip the adjustment. But check before assuming: even non-obvious categories like phone cases and pet supplies often show a 20-40% Q4 lift from holiday gifting.

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