AI Cuts Across Marketplaces to Accelerate Seller Performance

Amazon had a lot to crow about on its most recent earnings call. It started with record revenue for Q4 and the full year of 2023. 

It continued as CEO Andy Jassy ticked off the various successes AWS notched as the year closed. And among a torrent of revenue and sales statistics, one data point escaped the clutches of the analysts gathered for the announcement: Amazon Marketplace broke the 500 million order mark for its independent, third-party sellers over the Black Friday and Cyber Monday extended shopping event. There are now more than 2.5 million sellers on the platform, with thousands more joining every day.

Those data points certainly haven’t gone unnoticed at Pattern. Billing itself as an “eCommerce accelerator,” Pattern has specialized in using its artificial intelligence (AI) models to give Amazon sellers a voice, data to plan and measure performance, and access to the kind of expertise large retail enterprises have at their fingertips.

Its suite of solutions isn’t limited to independent Amazon sellers, nor is it limited to that marketplace. It has attracted major (and minor) brands across all retail marketplaces with a buffet of products and services that give retailers of all shapes and sizes an AI engine they can rely on.

“I’m having conversations about things that didn’t even exist three weeks ago,” John LeBaron, Pattern’s CRO told PYMNTS.

“You have to stay incredibly sharp in this market. There are changes happening every day that affect almost every process, from logistics and fulfillment to content creation to analysis and insights on products.

“I could sit down with a brand today and basically deconstruct their [marketplace] listings, their brand and their positioning against their competitors and against the growth rate of the market in a way that would absolutely blow their minds.”

LeBaron’s confidence comes from a wide variety of services on the Pattern platform and a unique AI tech stack to drive the kind of insights he spoke of.

The company has cast itself as an AI-driven machine that minimizes the friction between brands and their eCommerce customers. It does this using AI to generate insights and reporting, brand intellectual property protection, consulting services, creative services, influencer marketing and advertising, and SEO services. The result is that AI makes data and insights available that optimize everything from keywords and content to cross-channel launch strategies and pricing.

For example, the company recently announced a partnership with Amazon seller and D2C brand Hairmax. The brand is looking to stay more tightly connected customer sentiment, reduce ship times, and lower costs for its portfolio of brands. The Pattern AI model uncovers “patterns” and makes accurate predictions about those customers, increase efficiency within its supply chain and reduce costs. Hairmax CEO Ryan Zackon said the partnership is a significant step not only to grow Amazon sales but to enhance the customer experience.

Other use cases have different goals and work on different marketplace platforms. For example, vitamin and health supplement supplier Holland & Barrett have been in business in the U.S. for over 150 years. It wanted to expand into China via the TMall marketplace and chose Pattern as one of its trade partners.

Through its network of brand managers in the U.K. as well as an executing team in China, it provided operational guidance based on predictive insights into sales data and optimization opportunities. That data identified three new top SKUs for the China market. Results: The brand grew its Chinese revenue by 45% between 2021-2022, increased Singles’ Day sales by 54% year over year and sells more than 4,000 units monthly from those top three SKUs.

AI shows up almost every step of the way in the Pattern experience. LeBaron uses the example of a musical instrument brand to illustrate some of those capabilities. Suppose a company decides to make guitars and sell them on Amazon. With millions of data points generated every day, Pattern would be able to generate and analyze keyword data on the marketplace, price points, advertising creative and sales figures to get a sense of the competition.

Then when it’s time to go to market, it will use AI to create the right images and messaging to go with the display ads and product copy on the site. AI is used not only to analyze what happens on a specific marketplace, but also in the larger eCommerce universe.

“We may come back to that seller with a personalized recommendation that’s completely data-driven, showing how to increase the conversion rate for that guitar listing. We can show you the proven image archetypes. We can show you the proven positioning. Maybe we find out that the best guitar ad has a pet pictured with it. It’s wild.

“There’s a no way realistically try to analyze all of that information, but the fact that it can be done in minutes with our technology is still amazing to me.”

Pattern has enjoyed exponential growth since its founding in 2013, and boasts more than 1,400 employees operating from 24 global locations across hundreds of global marketplaces — including Walmart.com, Target.com, eBay, Tmall, JD, and Mercado Libre.

That growth is at least partially due to three trends LeBaron sees in today’s retail marketplace, with the acceleration of AI as number one. The second is the continued resetting of the post-COVID eCommerce landscape, forcing big companies to be smarter about their spending and even pull back on some D2C offerings. The third is the general trend toward complexity, which he sees Pattern solving for.

“Look at it from a seller’s point of view,” he said. “They’re just figuring out how to sell on Amazon and now they have to worry about Temu. And what about TikTok? And what about the 18 different plugins I need to manage on some of the other platforms.

“Now let’s go to the U.K. and the EU, where there are different regulations. Complexity keeps accelerating, the cost of goods is going up and the cost to acquire a customer isn’t getting cheaper. Brands are feeling the squeeze more than ever. They don’t want to pay any more than they have to for goods and services. They want more automation.

“We’re here to provide a higher level of service to brands and figure out a way to scale down those costs. I like our chances.”