This is Part 1 of a multipart series focusing on how Amazon is using artificial intelligence (AI) and how B2B manufacturers can use AI to grow their business. Check back for more articles in the series.
Artificial Intelligence (AI) is not just a buzzword; it's a transformative force shaping the way businesses operate and deliver experiences.
While there has been an explosion of interest in new services using AI over the past year or so, much of the recent talk has been centered around generative AI: Services like ChatGPT that generate text; Midjourney, Dall-e, and others create detailed, mind-blowing images based on text that can look real, like a cartoon, like an oil painting, or just about any other style you can think of. Still, other generative AIs can transform text to video, create narration using a wide variety of voices, or even music. And that’s just scratching the surface.
A cat wearing a suit sits on a park bench reading the newspaper - all generated using AI.
Yet, despite generative AI recently getting the spotlight, another type of AI has been widely used across Amazon’s business, and has largely flown under the radar. We’re talking specifically about machine learning AI, also called ML.
Machine learning is a subset of AI that focuses on using data and algorithms to simulate the way humans learn, improving its accuracy over time. It operates by training models on data to find patterns or make predictions. If using data to develop models sounds familiar, it’s because businesses have been using ML for longer than a decade. Remember the Big Data craze a decade ago? Much of the buzz of Big Data was centered around using ML to derive actionable insights from exponentially growing amounts of data.
Amazon, a pioneer in Ecommerce, has been using AI and ML practically from the company’s inception. But before we can begin looking at how AI can enhance your B2B business on Amazon, we feel it’s important to understand how Amazon itself is using AI.
In this first part of this article series, we’ll take a look at a handful of ways Amazon has implemented AI to benefit customers, sellers, and itself. Subsequent posts will address how B2B manufacturers and distributors can leverage this cutting-edge technology.
What Is AI According to Amazon?
You might be surprised to know that artificial intelligence systems have been developed since the mid-1950s. At its core, AI is technology that enables computers to, essentially, do tasks that humans do. Typically, AI is focused on solving problems, leveraging data and computing power to enhance efficiency, make better decisions, and ultimately, drive better user experiences. Amazon's journey with AI began at the inception of their business, and it continues to evolve, reshaping operations at all parts of their business.
As Amazon states:
The goal with AI is to create self-learning systems that derive meaning from data. Then, AI can apply that knowledge to solve new problems in human-like ways.
How Amazon Leverages AI and ML for Ecommerce
While there are likely many ways Amazon deploys AI and ML across its business units, for our purposes, we’ll focus solely on Amazon’s implementations in its Ecommerce and fulfillment operations.
1. Front-End Digital Experience
To become the "everything store," Amazon understood early on the critical importance of delivering a seamless digital experience. One of the key ways to do that was to ensure that users can find what they’re exactly looking for quickly.
To achieve this, Amazon developed its AI-powered A9 search algorithm, a tool dedicated to optimizing search results. By continually refining and enhancing search algorithms, Amazon has strived to deliver accurate search results that lead to sales faster. And today with billions of products available on its marketplace, this early and ongoing investment in AI-powered search has allowed Amazon to become the #1 product search engine in the United States, surpassing Google all the way back in 2015.
AI isn't just about optimizing search results based on keyword relevance, the company also uses the technology to personalize the Ecommerce experience by weighing factors such as individual customer behavior and a seller’s sales velocity and conversion rate. In other words, their AI can determine if products are selling, and will show better selling products in the most prominent positions on the web site and more frequently in search results.
Lastly, Amazon employs AI to deliver a tailored shopping experience through personalized product recommendations. This level of customization is a key element in making Amazon the top destination for product searches for both B2C and B2B buyers.
2. Product Purchasing Decisions
Amazon doesn't merely use AI to enhance the customer-facing aspects of their platform; they leverage it in their own product purchasing decisions through the Vendor Central program (i.e. products sold to Amazon by suppliers in a traditional wholesale model). Considering the volume of products Amazon offers, it’s clear that Vendor Central account managers (the employees responsible for making bulk product purchase decisions for Amazon) need an ML-driven tool to help them identify what products to buy, at what price and at what volume.
Vendor management teams at Amazon are empowered by ML-enabled data analysis tools, enabling them to make informed decisions, while managing hundreds of seller accounts.
3. Pricing Algorithms
Amazon's pricing algorithms are a testament to the company’s dedication to offering the most competitive prices. Amazon feeds its pricing algorithms pricing data for every product in every category from not only its own site, but also other online platforms and even offline sources. The ML-enabled pricing system crunches all that data and adjusts product prices in real time. Amazon ensures that customers receive the best deals, reinforcing their position as a trusted and customer-centric platform.
It’s important to note that (for the most part) this only applies to products sold through Vendor Central; pricing on Seller Central products is controlled by the seller, which is one reason why we often counsel B2B manufacturers to use this method of selling. Maintaining retail price control on Amazon can limit conflict with other traditional distribution and retail channels.
4. Operational Side: Fulfillment and Kiva Robots
Amazon has not only successfully deployed machine learning and other AI systems to create an unparalleled user experience, but they have also deployed it in their fulfillment centers, which ultimately also contributes to the company’s well-regarded and world class customer experience. The complexities of managing hundreds of warehouses, routing orders for shipping, replenishing products, and optimizing warehouse storage are all streamlined using AI. Geographical demand, fulfillment cost and speed, product novelty, and other factors are considered when deciding where items should be shipped, how and when to replenish stock, and even where to place it in the warehouse to ensure optimal picking and packing.
Speaking of which, a notable addition to their operational efficiency is the use of robots in their fulfillment centers. With an army of more than 750,000 robots, Amazon uses these machines to help pick products and deliver them to human workers for packing, as well as sorting outbound orders. Proteus, Amazon’s next generation autonomous robot designed to efficiently store, move and sort products in the company’s fulfillment centers, uses cutting-edge advancements in computer vision and sensing technology to operate safely around humans.
As AI continues to evolve, so too will Amazon's use of it. Their commitment to enhancing customer experiences, optimizing operations, and staying competitive will continue to drive them to be a trailblazer in AI in the Ecommerce landscape.