Keepa Sales Rank

Sales rank is a snapshot. A low reading does not mean a product sells well, and a higher reading does not mean it sells badly. This lesson covers how to read the rank history in Keepa and get an answer you can act on.

Finding the line

On the Keepa chart, sales rank is always green. If it is not showing, click the circle next to the Sales Rank entry in the legend.

Two display options are worth setting once:

• Sub ranks adds the subcategory rank as a second line. Most sellers ignore it; a subcategory rank always looks better and means less. Leave it off unless you have a reason.
• Axis direction. The small arrow flips the vertical axis so that zero is at the top. Some people find "better rank is higher on the chart" easier to read. It changes nothing about the data. Pick one and stay with it, because switching between conventions is how charts get misread.

The most important thing on the chart

The line rises gradually and then drops sharply, repeatedly. Every drop is at least one sale. It may be several; you cannot tell how many. But a drop means the product sold at that moment.

So the shape tells you the story:

• Many drops, closely spaced. The product sells regularly. This is what you want.
• Few drops with long flat climbs between them. It sells rarely, whatever the current number says.
• A single deep drop and nothing else. One order distorted the rank. This is the exact trap the Getting Started lesson warned about, and here you can see it happening.

Changing the range

Buttons switch between day, week, month and 3 months. Three months is the sensible default: long enough to show a pattern, recent enough to describe the listing as it is now. You can also click and drag across the chart to zoom into any period.

The statistics panel

Below the chart, hovering over the statistics gives the numbers rather than the shape. Two things to read:

• Average rank over 90 and 180 days. The example shows 11,283 over 180 days and 3,433 over 90 days.
• Drop count over 90 days. The example shows an average of 64.

Treat the drop count as an estimate rather than a measurement. Keepa cannot poll every listing every second, so real sales are usually somewhat higher than the count suggests. It is a floor, not a total.

The data tab, where the real comparison lives

Click through to the Data tab and you get a table of averages: rank over 30, 60, 90 and 180 days, and drops over 30, 90 and 180 days.

This is the most useful screen in Keepa for a buying decision, because consistency is what you are looking for and consistency is only visible by comparing periods.

• Similar averages across 30, 60, 90 and 180 days means a product that sells at a steady rate. You can plan around it.
• A 30-day average far better than the 180-day one usually means something temporary. Expect it to revert.
• A 30-day average much worse means the product is declining, and your stock will sell more slowly than the history implies.

The rank percentage

Keepa also shows where the rank sits as a percentage of its category. A product in the top 1 percent of Toys is selling very well indeed.

The percentage is more useful than the raw number for one reason: it is comparable across categories. Rank 20,000 means completely different things in Books and in Garden. The percentage does not have that problem, and it is the same measure the Arbitrage Hero sales rank filter uses.

One check that is not about rank

While you are on the Data tab, look for Amazon out of stock in the last 90 days, given as a percentage.

The example reads 18 percent, which means Amazon was selling the product 82 percent of the time. That product is rejected on the spot, and rightly.

The rule given here is to want Amazon out of stock at least 60 percent of the time over the last 90 days. Higher is better. This is a stricter version of the check in the Advanced Product Analysis lesson, and it is the one to use, because it is measured rather than eyeballed from the shaded areas on the chart.

The routine

1. Look at the shape. Are there frequent drops?
2. Open the Data tab. Are the 30, 60, 90 and 180 day averages close together?
3. Is the average inside the range you accept for that category?
4. How many drops per month, and how many sellers will share them?
5. Is Amazon out of stock at least 60 percent of the time?

If all five pass, the demand side of the decision is settled and you move on to price, which is the next lesson.