In the age of Amazon it is unclear yet what it means to be a brand. The foundation brands build value on doesn’t translate well online, and it almost completely disappears on Amazon. In fact, the number of well-performing private label brands on Amazon indicates that consumers shop without paying as much attention to the brand as they would otherwise.

“Using technology and a billion people who will write reviews and then putting in algorithms, we can destroy that price premium that brands have commanded through consistency, all this advertising, and all these things like packaging and shelf space and in-store promotions that we can go after, it really doesn’t add any value and we can destroy it.” – Scott Galloway, Founder at L2

Amazon wants to replace trust in brands with algorithms. Instead of consumers picking the brands they trust, Amazon wants them to pick products recommended by the algorithm. Product reviews and ratings are thus key in surfacing the best products from Amazon’s ever-growing catalog. In this worldview Coca Cola, one of the most recognized brands, is no better than any other drink brand with 5-star reviews.

The problem is that building brand trust takes time and investment, while pleasing an algorithm is often much faster and easier. And thus as all thing fast and easy it attracts more people trying. The result of which is Amazon today - a chaos of new “brands” launched every hour.

Searching for “wireless headphones” on Amazon returns more than 40,000 different results, some of which appear to be well-liked by consumers, many of which are close copies of each other. Names like ENACFIRE, Mpow, Otium, KUPPET, Senso, Kissral, and Aonlink dominate the list, and they all cost less than a quarter of what established brands like Bose or Sony charge for theirs.

For headphone brands like those, and for many other categories, amassing 5-star reviews is most important. Thus for the last few years different tactics have been used to get there, from now-banned incentivized reviews to reviews groups on Facebook, to black-hat techniques. All to make the Amazon algorithm trust the product and rank it number one.

There are more a million brands on Amazon today. Some of which are the established brands most customers would recognized, many more of which are random names for when the brand is irrelevant. In the wireless headphones example the consumers buying them are fully aware that they are probably low-quality, but at a price cheaper than traditional brands they are worth the risk.

Amazon is a breeding ground for weak brands built on little else than making the algorithm rank them number one. This has created a cottage industry of companies trying to out-do each other. “We start with what the customer needs and we work backwards.” Jeff Bezos, CEO of Amazon. Very few of those brands care about the customer. Amazon is thus self-contradicting.

Amazon sometimes looks less than a retail operation and more like a computer game for brands to play. The winning prize, of course, is being the top seller. But this game is frustrating to established brands (Birkenstock called it “an environment where we experience unacceptable business practices which we believe jeopardize our brand”) and confusing to consumers as they are overwhelmed with thousands of choices.

There is also increasing number of counterfeit goods on the platform thanks to the lax rules for new sellers to join. Which means consumers not only need to pick the best product, but also hope the unit they get is legitimate. All of those issues are a small percent of overall volume on Amazon, but as Amazon grows bigger that percentage represents a non-trivial number of unhappy consumers.

There are more than 550 million products on Amazon. At this rate it will double in five years. The idea is that even then customers will be able to shop thanks to the algorithm surfacing best choices. Amazon’s catalog is putting quantity instead of quality first. But what if Amazon is wrong? What if the amount of trickery from those pushing their own brands will make customers question the choices the algorithm makes.