When it comes to enforcing minimum advertised price policies, only one thing matters: is a seller honoring it or not? If they list the product below the price set in the MAPP, the listing is a violation. Period. However, in an effort to not get penalized by the brand, sellers frequently point to their competitors, playing the “scarecrow on the fence”. Brands hear frequent refrains of “They did it first,” or “I’ll honor MAPP when they do.”
It’s generally understood that if one seller drops an advertised sale price below MAP, other sellers will quickly follow suit. Some companies believe it’s important to identify the first violator in this pricing cascade. Are there any benefits to this knowledge, versus simply enforcing the policy on every violator evenly and not worrying about who violated first?
Practically speaking, given the frequency and speed at which price bots match and change product listing prices, identifying which seller dropped first is nearly impossible. This is because you can’t monitor the products at precisely the exact time, across every domain, every second of every day. Even if you could determine that seller x dropped first, they could always claim, “we weren’t the first one to lower the price, we were the last one to raise it!” Unless the brand has access to the sellers’ bot programming and history, it could never prove otherwise.
If this practice of uncovering first-violators of your MAP enforcement is still important to a brand, then a real-world solution is to view daily pricing over time. If done properly, a pattern emerges that helps to reveal which seller “probably” dropped first or, at the very least, is one of the main price influencers. It’s not ironclad proof, but sometimes data-driven, anecdotal evidence is enough.
Changing Seller Behavior After a MAP Policy Violation
When presented with evidence, some sellers will actually change their behavior. And sometimes, Amazon, Walmart, Target, Chewy and other large sellers will agree to honor MAPP for a certain period of time. If the implicated first mover agrees, then, hopefully, once the price returns to MAPP, things will stabilize because the price matchers won’t have anyone to compete with.
There is some merit to this information. Rather than taking a shotgun approach to MAP compliance, knowing which seller drops price first and/or influences pricing overall provides a brand with focus. If the sellers are authorized, it gives a priority to which ones should get suspended first. If they are unauthorized, and are significant sellers, it provides a priority for cease and desist efforts.
Since it’s doubtful that the first violator question can ever be truly answered, understanding the patterns of pricing provides an insight into which sellers actually have an impact on erosion. Statistically, there are only a handful of sellers that follow one another and they ignore sellers with extremely low pricing. They know these sellers are one-hit wonders and will be gone quickly.
MAPP Trap provides reporting on pricing patterns so brands can understand and act upon this information. The platform allows users to set a baseline seller to expose which other sellers are at the same price. Pricing patterns are also very effective for determining omni-platform ecommerce stores with different names that are owned by the same business. They can show this by revealing when one seller drops the listing only to then be added by their other store.