How Exactly Amazon Measures Itself?

Very often, we see agencies and digital shelf service providers talk about what brands could achieve if they do things right on Amazon.

But let's go back in history and take a keen look at how Amazon defines its own metric, the mistakes they dealt with, and how they got it to where it is now. Here's a quote of how things evolved.

One mistake we made at Amazon as we started expanding from books into other categories was choosing input metrics focused around selection, that is, how many items Amazon offered for sale. Each item is described on a “detail page” that includes a description of the item, images, customer reviews, availability (e.g., ships in 24 hours), price, and the “buy” box or button. One of the metrics we initially chose for selection was the number of new detail pages created, on the assumption that more pages meant better selection.

Once we identified this metric, it had an immediate effect on the actions of the retail teams. They became excessively focused on adding new detail pages—each team added tens, hundreds, even thousands of items to their categories that had not previously been available on Amazon.

(…) We soon saw that an increase in the number of detail pages, while seeming to improve selection, did not produce a rise in sales, the output metric. Analysis showed that the teams, while chasing an increase in the number of items, had sometimes purchased products that were not in high demand.

"When we realized that the teams had chosen the wrong input metric—which was revealed via the WBR process—we changed the metric to reflect consumer demand instead. Over multiple WBR meetings, we asked ourselves, “If we work to change this selection metric, as currently defined, will it result in the desired output?” As we gathered more data and observed the business, this particular selection metric evolved over time from

- number of detail pages, which we refined to...

- number of detail page views (you don't get credit for a new detail page if customers don't view it), which then became...

- the percentage of detail page views where the products were in stock (you don't get credit if you add items but can't keep them in stock), which was ultimately finalized as...

- the percentage of detail page views where the products were in stock and immediately ready for two-day shipping, which ended up being called 'Fast Track In Stock'.

The point they’re making here is that to get to the right set of controllable input metrics, you’ll have to test and debate — and expect to do many iterations of both! The authors explained that even this narrative wasn’t as clear cut as you would think — Bezos was worried that the Fast Track In Stock metric was too narrow, but Jeff Wilke argued that the metric would yield broad systematic improvements. Bezos agreed to give it a go, and Wilke turned out to be right.

This is how much time, probably hundreds of man-hours, the retail giant spends to refine its metric system. Brands, big or small, as single entities in the Amazon ecosystem need to clearly define their pricing objectives and joint business plans with the retailer and category of operation while working alongside a digital shelf solution provider to track areas of actionability and improvement.