AI & Machine Learning

How Cloud AI is shaping the future of retail—online and in-store

Technology has played a key role in retail for decades, from early innovations like barcode scanning and digital point of sale devices, to the global frontier of modern logistics. Through it all, however, the fundamentals remain the same: retailers generate huge quantities of data, face unpredictable environments, and need to continually adapt to the ever-evolving needs of the customer. Throw in the chaos of Black Friday and Cyber Monday, and you’ve got one of the most complex enterprise challenges in the world.

It’s also a challenge tailor-made for AI: a technology that thrives on big data, adapts to change fluidly, and can deliver personalized experiences at scale. With the holiday rush upon us, let’s take a look at how two Cloud AI customers—3PM for online shoppers and Tulip for in-store—are helping make retail more efficient, more personal, and more trustworthy.

Tulip is helping brands across the world bring the flexibility and personalization of e-commerce to their in-store experiences. Online, 3PM continuously tracks millions of sellers across a range of e-commerce marketplaces, helping to turn the tide against predatory practices like counterfeit products and trademark infringement.

3PM: Safeguarding online marketplaces at a global scale

Trust is the foundation of every retail experience, and that’s especially true online. With the proliferation of online marketplaces like Amazon, eBay, and, however, trademarks, copyrighted content, and other brand assets are often spread across too many places to be effectively monitored.

Particularly disconcerting is the fast-growing world of counterfeit products. It’s not just knock-off sneakers and handbags, either. Fraudulent supplements, prescription drugs, and even baby food are readily available online, presented in convincing detail intended to fool customers, and could pose a danger to consumer health. Small merchants and global brands alike have found it difficult to contain counterfeiting, largely due to its decentralized nature. This calls for a solution that lies outside marketplaces. 

3PM Solutions saw an opportunity to help. By combining the power of advanced analytics with data at a global scale, 3PM’s suite of tools can detect counterfeit goods automatically, monitor a brand’s reputation over time, and help the brand understand its customers more deeply.

But getting such an ambitious vision off the ground presented some significant technical challenges for 3PM. Online marketplaces routinely change the format and structure of their listings, quickly confounding hand-written rules and filters. To make matters worse, the content within those listings is notoriously unreliable. For example, counterfeiters often intentionally misspell brand and product names to keep their goods under the radar. It’s a level of complexity that calls for a particularly flexible solution that’s capable of ingesting massive quantities of data, while also evolving as the nature of that data changes.

These challenges prompted 3PM to migrate to Google Cloud Platform, bringing the company’s data and infrastructure—and, more importantly, a state-of-the-art AI toolkit—into a single environment.

Google Cloud’s flexibility helped 3PM implement a creative, agile development process. The company’s developers designed a TensorFlow-based image classifier and trained it on billions of examples, forming the basis of a self-serve tool that lets brands accurately detect improper use of product photography, logos, and other trademarks. They built custom machine-learning models to intelligently analyze product listings. These models can look past the basics like image and title to incorporate a wide range of data points to detect subtle features correlated with fraud that rule-based systems—not to mention humans—would miss. 3PM even used the Cloud Translate API to transcend language barriers automatically.

Tulip: Bringing digital personalization to the in-store experience

Of course, brick-and-mortar remains fundamental to the identity of countless brands, with 80% of all sales still taking place in physical stores. Nevertheless, the speed, flexibility, and extreme personalization of e-commerce is influencing customer expectations everywhere—even when shopping in person—and retailers are scrambling to keep up.

Tulip helps retailers keep up with these demands with a suite of powerful mobile apps that gives retail workers the power of the digital world anywhere in their store, whether they’re looking up products, managing customer information, checking out shoppers, or communicating with customers. Tulip helps physical stores establish deeper relationships with their patrons based on their preferences, behaviors, and purchases—just as they would online—and it’s changing the way global brands do business.

A major challenge in any retail application is forecasting. Whether it’s an unexpected fashion craze or an annual event like Black Friday, retail’s surges and lulls can make traditional allocation of compute resources extremely challenging. 

"Because we had to scale for peak demand, we had to buy capacity up front, which sat idle much of the time when sales demand was lower," explains Jeff Woods, director of software for infrastructure at Tulip. "It became difficult and expensive. We were constantly asking the vendor to waive arbitrary limits. We had to use massive instances, and it was difficult to scale down."

After migrating to Google Cloud, Tulip could deploy on an infrastructure capable of scaling to any size at a moment’s notice—and only pay for what they used. In the process, they also gained access to some of the world’s most advanced machine learning technologies. Now, with their data, infrastructure, and AI tools in one place, the stage was set for Tulip to build an entirely new level of intelligence into their solutions.

Tulip’s solutions use a set of custom TensorFlow models running on AI Platform to identify customer insights and sales opportunities based on data from a customer’s in-store mobile applications. This drives recommendations on when to connect with customers and how to engage them with highly personal and relevant communications. 

Tulip’s solution is a textbook example of what makes Deployed AI so powerful: using previously unseen patterns in large quantities of data to solve a clearly defined business challenge, all at the speed of retail. "Every day, Tulip collects millions of data points from customer interactions across its channels," says Ali Asaria, Tulip’s founder and CEO. "By integrating Google machine learning and big data products into our core platform, we can now use that data to provide intelligent insights and recommendations to retail associates."


Just a few years ago, AI seemed too expensive and complex for companies like 3PM and Tulip. In both cases, however, moving to Google Cloud has demonstrated this technology’s affordability, interoperability, and ease of use. And the results have been transformative.

Whether the crowds are in stores or online, companies like Tulip and 3PM are demonstrating the power—and sometimes, the necessity—of using AI to make every retail interaction safer and more engaging. It’s another example of Deployed AI in action: using state-of-the-art technology to overcome age-old business challenges.