CRaP – that insidious situation where Amazon Can’t Realize a Profit on your ASIN – can easily lead to your product being suppressed in search results or shown as unavailable; Amazon may even stop ordering the product, even with an unfilled PO, meaning you are not generating revenue from it. Addressing this issue is a twofold problem: first, you have to know that it is happening, next, you need to be able to do something about it.
The difficulty of identifying CRaP danger scales with the number of ASINs you have. If you have ten ASINs, a human being can manually monitor their performance against Amazon’s Net Pure Profit Margin (PPM), a proxy for contribution margin (which is what really matters to Amazon) on each one in a timely enough fashion to detect trouble. It’s an order of magnitude harder with 100 (literally!) and pretty much impossible when you get into the thousands. Keep in mind that PPM benchmarks can vary wildly across products; for example, liquid products such as detergents, which have much higher shipping costs than, say, wristwatches, will have a much higher PPM target than products that are cheaper for Amazon to store and ship.
Now, Amazon provides plenty of signals that an ASIN is in danger of CRaP-ing out; it may be made a Prime Exclusive or Add-on Item, or dropped from Subscribe and Save. But again, if you have any significant number of ASINs, do you have the ability to detect those signals against the backdrop of everything else that is going on?
When you do identify CRaP candidates, how can you find out what is putting you at risk? And how can you figure out what to do about it? Again, with a very small number of ASINs and some reports on the margins on your products it is possible to get to the source of the problem, but relying on people to do this just doesn’t scale, especially in an environment characterized by rapid growth like Amazon.
This is where automation is critical: machines have the ability to sort through the vast quantity of data generated by Amazon to isolate those ASINs that are at greatest risk of being dinged for CRaP reasons (and even to determine the revenue impact of an ASIN CRaP-ing out, so you know which ones to focus on first). And with machine learning looking at how data interrelate, the same machine that spots the problem can determine what is causing it.
CRaP is usually a function of price compression, which can be driven by a number of different causes. Often it is in response to competitive pressure from other retailers, who may be driving down the price on Amazon by setting aggressive prices on their own sites (which Amazon’s algorithms then follow). In each of these cases, the cause can be revealed by algorithmically sifting the data. For example, if Amazon’s price is being driven down by what is happening on Walmart.com, you may be able to work with your company’s Walmart team to take corrective action.
Here at Boomerang, we have identified a number of courses of action you can pursue to deal with CRaP. Perhaps the most important is to reduce traffic going to an affected ASIN, by stopping any AMS spending or promotions – as the old adage holds, when you find yourself in a hole, stop digging.
For those situations driven by price wars initiated by another e-commerce site selling your goods, you may be able to work with your colleagues supporting that other site to reduce the pressure on Amazon’s prices. Another tactic that we have seen work is directing some of the traffic going to the affected ASIN to a closely-related one with higher margins by placing a variant ASIN with higher margins on the PDP of the product at risk of CRaP to capture some of the traffic going to that page.
In each of these cases, the ability of automation to detect the danger and determine why it is occurring is the only way to avoid CRaP before it happens. In the longer term, changes in packaging to create more e-commerce friendly form factors (e.g., Tide Pods, or individual serving size boxes of dog food, rather than large, bulky, expensive-to-ship bags) can help boost Amazon’s contribution margin on your product, reducing the CRaP danger without having to write Amazon a check to keep PPM within Amazon’s dictated limits and your product for sale.
In this short (under two minutes) video clip, Andrew Freeman of Kellogg’s describes how the iconic consumer brand manufacturer relies on automation to detect ASINs at risk of CRaP-ing out and to determine what the cause of the problem is so it can be addressed easily.
Are you afflicted by CRaP and interested in learning more about what you just saw and heard? If so, contact us at firstname.lastname@example.org. We can share with you where you are at CRaP risk on Amazon and steps you can take to automatically detect CRaP risk in 2019.