Most new listings are priced by looking at three or four competitors and going slightly under. That prices you against a handful of products and tells you nothing about where buyers in the category actually spend.
A price distribution answers a better question: at each price level, how many products are there, and how much do they sell? Three numbers per band are enough to see which price points are crowded, which are empty for a reason, and which are underserved.
One call, eight bands
The price distribution endpoint takes a category and returns its products grouped into price bands:
curl --request POST \
--url https://ecommercedataapi.com/v1/amazon/market/price \
--header "Content-Type: application/json" \
--header "X-API-Key: ${ECOMMERCE_DATA_API_KEY}" \
--data '{
"marketplace": "US",
"nodeIdPath": "2619533011:2975241011:2975259011:2975263011"
}'nodeIdPath is the category's node path. You get it from the nodeIdPath field of any product in the category, through product details or product search, or from the categories endpoint.
We ran that request for the US cat fountain category on 12 October 2026. The response covered 100 products:
| Price band | Products | Estimated monthly units | Share of units | Units per product |
|---|---|---|---|---|
| $5–10 | 6 | 17,708 | 4.0% | 2,951 |
| $10–15 | 22 | 67,545 | 15.3% | 3,070 |
| $15–20 | 36 | 185,750 | 42.1% | 5,160 |
| $20–25 | 4 | 30,407 | 6.9% | 7,602 |
| $25–35 | 13 | 85,987 | 19.5% | 6,614 |
| $35–45 | 6 | 18,325 | 4.2% | 3,054 |
| $45–75 | 9 | 28,520 | 6.5% | 3,169 |
| Over $75 | 4 | 6,927 | 1.6% | 1,732 |
The first three numeric columns come straight from the response (products, units, unitsRatio). The last one is units divided by products, which you calculate yourself. It is the column that changes the reading.
Three numbers, three readings
Share of units shows where the demand is. $15–20 takes 42% of units. That is the price most buyers in this category pay.
Product count shows where the competition is. The same band holds 36 of the 100 products. Demand and competition sit in the same place, which is the usual pattern.
Units per product shows what one listing can expect. This is where the bands separate:
- At $15–20, the average product sells about 5,160 units. Large demand, split 36 ways.
- At $20–25, four products average about 7,600 units each, the highest of any band.
- At $25–35, thirteen products average about 6,600, and the band earns the second-highest revenue ($2.43 million against $3.54 million for $15–20).
- Under $15, 28 products average around 3,000 units at the lowest prices in the category.
The crowded band is not the best band per listing. In this category the two bands just above the mass-market price sell more per product, at a higher price, with far fewer competitors.
What a thin band means
Four products at $20–25 is a small sample, and that cuts both ways.
It may be a gap: buyers are willing to pay it, and few sellers have positioned there. Or it may be four strong products that would sell at any price, sitting in a range others have tried and left.
The distribution cannot tell those apart. What it does is tell you where to look next. Each band can return the ASINs in it (the asins field), so open the four products: are they one brand or several, how old are the listings, how many ratings do they have? If they are four different sellers with ordinary ratings, the gap reading is more likely. If it is one dominant brand, it is not a gap.
From bands to a price
1. Find the mass-market band by share of units. Decide whether you can compete there on cost. If your landed cost does not leave margin at that price, the largest band is not available to you whatever its size.
2. Look one and two bands up. Compare units per product. A band with higher units per product and fewer listings is where a better-featured product can sit.
3. Check what the higher bands sell. Higher price bands often hold a different product: larger capacity, a different material, a bundle. Read the titles before assuming you can charge that for what you have.
4. Check revenue, not only units. revenue per band shows where the money is. A band with modest units and a high price can out-earn a busier one.
5. Repeat in a month. One snapshot does not show whether a band is filling up. Pass month to compare periods.
The other cuts of a category, by listing age, seller type and ratings, are in Amazon category analysis. For how the estimates behind units are made, see what Amazon sales data can and cannot tell you.
What this cannot tell you
Your margin. The endpoint knows prices, not your costs. A band is only attractive if your product is profitable in it.
Why a band is empty. No products can mean no demand or no supply. Open the neighbouring bands before deciding.
Tomorrow's prices. Bands shift with promotions and seasons. Competitor price and coupon monitoring covers tracking individual products over time. For a past window in one request, see Amazon price history by API.
Anything exact. units and revenue are estimates. Use them to compare bands with each other.
Three practical notes
- The response covered 100 products in our test, so it describes the top of the category, not every listing in it.
- Band labels are returned as text such as
15-20; the top band's label came back in Chinese, so match on position or parse the numbers instead of relying on the label. - A product with variations can span several prices. Before reading a band's ASINs as single products, check their variation families; see parent and child ASINs.
Questions
How do I find a category's node path?
Look up any product in the category and read nodeIdPath, or use the categories endpoint.
Should I price in the band with the most sales? Only if you can compete on cost there. Compare units per product across bands first; the largest band is usually also the most crowded.
Can I see which products are in a band?
Yes. Each band returns its ASINs in asins.
How does this relate to where a listing gets its visibility? Price decides which products you are compared with on the page. Where a listing's visibility comes from covers the placements themselves.