AI will take over most of the seller’s tasks on Amazon. It will remove the gap between new and experienced sellers and between domestic and international sellers. But it’s never been harder to launch the next Anker, and no AI has the answer.
Starting brands decades ago, in the age of Walmart department stores, was an exclusive endeavor left to the largest CPG brands. Then Amazon created unlimited shelf space, and the Internet uncloaked the secrets of brand creation. Today, anyone with access to the Internet can start a retail brand in minutes. They can even use dropshipping to start with virtually zero upfront capital.
What was off-limits and expensive to most is now a matter of watching a YouTube video. Every step of retailing, from manufacturing to the shopper receiving the product, is solved by a software tool, a service, or a how-to video. The result is millions of sellers that created an explosion of brands: “In 2021, Amazon Brand Registry had over 700,000 brands enrolled, compared to 500,000 in 2020, a 40% increase.”
The core skill of retail used to be picking and curating brands. Brands, too, labored, trying to understand their consumers to answer the fundamental question, “What products should we make?” Before the Internet, the answer was a guess. Today, data is abundant. Amazon doesn’t pick products; it lets shoppers decide what ranks first via reviews and orders. And modern brands answer the question with data, too. For instance, one of the core tools Amazon sellers use is product research software like Helium 10, SmartScout, or Jungle Scout. The sellers aren’t guessing what might be in demand - those tools tell them.
The next evolution will be Artificial Intelligence (AI). AI will pick what products to source, manage inventory levels, create product content and images, optimize advertising and pricing, manage sales channel issues, and more. Some of those tools already exist, but more will come and integrate. For example, advertising has grown faster in complexity and options than any other part of Amazon. The market, best practices, and strategies are changing fast (it is starting to resemble high-frequency trading on Wall St.). Inventory forecasting is, too, simple on the surface but gets impossibly complex with multiple vendors, warehouses, and sales channels. Both tasks are perfect for AI, and even better when those tasks talk to each other - ads can only optimized in the context of inventory. And so is pricing and the rest.
The information asymmetry between rookie sellers and experts will disappear. If the AI is doing most of the work, a brand-new seller and a pro can manage advertising just as well. There will also be no difference between native speakers and international sellers. A seller from China and the US can create a perfect listing in English if the AI does the creation. “Chen, who sells medical devices and toys on Amazon, understood basic English, but needed help with his writing. He used to translate product descriptions using Google Translate and DeepL, but found ChatGPT to be more accurate and authentic,” wrote Viola Zhou for Rest of World.
The impact of AI will not be sellers operating their businesses with fewer employees or spending less time. It will not be a differentiator but rather the way of things, a new foundational level. The result will be even more products launched, with better positioning and market-leading presentation.
Benedict Evans wrote about the Jevons Paradox, which states that, in the long term, an increase in efficiency in resource use will generate an increase in resource consumption rather than a decrease. “In the 19th century the British navy ran on coal. Britain had a lot of coal (it was the Saudi Arabia of the steam age) but people worried what would happen when the coal ran out. Ah, said the engineers: don’t worry, because steam engines keep getting more efficient, so we’ll use less coal. No, said Jevons: if we make steam engines more efficient, then they will be cheaper to run, and we will use more of them and use them for new and different things, and so we will use more coal. Innovation can connect to price elasticity.”
“If, Jevons tells us, it becomes much cheaper and more efficient to do something, you might do more of it - you might do more analysis or manage more inventory. You might build a different and more efficient business that is only possible because you can automate its administration with typewriters and adding machines.” This rings back to the evolution of retail from a few CPG brands to millions of sellers and how AI will only accelerate it - AI will not just make every seller an Amazon expert but lead to many more sellers. And then to a new generation of sellers, only possible because of AI.
Today, out of the millions of sellers, some run the business using just Amazon’s own Seller Central, some with Excel spreadsheets, others with external software tools, and others with the help of agencies. AI will not change that overnight. But in the dystopian future, a seller’s job will be telling the AI how much capital they have available, and it will handle the rest. Its outcome will be a weekly payment for sales of products it picked, sourced, and sold.
A seller wielding an Excel spreadsheet will lose. But not using one is not a ticket for success either. AI is a solution, but not the whole solution.
Amazon already has millions of brands, but few built what, for example, multi-billion Anker managed. Most are technically brands because they own a trademark for the name. Yet only a tiny share of a percent are Amazon-native brands recognized and sought out by consumers. There are nuances in retail unknowable to automation. Thus, it’s never been easier to launch a brand like today, and AI will only make it easier, better executed, and managed. But it’s never been harder to launch the next Anker, and no AI has the answer.
