Lately, Google has explored adding products that have also seen a lot of consumer success to retail as services. All of it touches cloud computing in one way or another, with Google hosting the services it provides to its retail partners. During the National Retail Federation’s 2023 conference this week, we sat down with Jose Gomes, managing director of retail and consumer package goods for Google Cloud. TechRepublic got his insight on how enterprise cloud is changing and how the largest tech companies in the world use it.
For example, for approximately eighteen months, Macy’s has run a variant of Google Search enhanced by the Browse AI on its own website. It allows for natural language analysis — to a point. If a customer searched for a dress to wear for a baby shower, the website might return results for maternity wear, which is not necessarily the right choice.
Google Glass, once intended mostly for consumer use, is finding new life as a work tool. Demonstrations at the conference included a mostly seamless translation tool, and another demonstration showed how warehouse workers could use Google Glass to get hands-free direction on which item to pick and where to place it.
How the economy impacts enterprise cloud
Still, organizations may be wary now to make changes that don’t have immediate returns. The industry standard has moved from infrastructure cloud, where organizations “lift and shift” to the transformation cloud, Gomes said, echoing what Neiman Marcus also said the previous day.
“Organizations are, even more so than usual, focused on profitability, efficiency and a return on investment from what they’ve made,” Gomes said.
There’s also a sense of urgency to these processes now.
“If you’re going to save me money, you need to save it this year,” he continued.
As a result, Google focuses on enterprise offerings that can be implemented quickly or are already in place today. Use cases for cloud can still be elusive, so the smart thing to do is focus on what is already being implemented today.
Implementation should be discussed in terms of weeks, not months. Gomes used Loews as an example, which started with one cloud-empowered deployment for work and now does more on the order of twenty per day.
Retailers are also looking to move away from dealing with data centers, Gomes said.
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One of the themes that emerged in the conversation with Gomes was that organizations want the cloud to free them up to worry less about the technology and more about the value that can be extracted from the associated services. For example, Kroger uses Google database technology to merge a number of data signals and tell an employee what their next best action should be based on the value of that action and the condition of the store.
AI/ML can also come into play to consume and blend real-time data signals that normally aren’t connected. For example, a single dashboard could show and possibly correlate whether someone clocked in and also where the company truck is located. AI/ML can detect patterns that can eventually be mixed together to give actionable intelligence about where human labor is most usefully spent at the store.
The ideal path is “to move from proscriptive diagnostic insights to predictive recommendations and ideally proscriptive,” Gomes said. “People hope AI and ML can lead to more automation and more predictive recommendations.”
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What point are you at in the journey?
Enterprises may see the increase in value at the end of the cloud adoption process as the most important element, but different organizations are closer or farther to that end point, or embrace it more quickly or slowly.
However, Gomes said, retail is ahead of many other industries, as it’s been exploring applications to organize that data for a relatively long time. It’s also an area that supports the right engineering talent, although Gomes provides a caveat.
“Your organization to a large degree depends on the approach as well as how open you are to partners,” he said. “What we’ve seen is a two-pronged approach, which is either you move all the data to the cloud and then work out what you’re going to do with it, or the use case approach.”
The former can have much larger cost savings, because organizations can depreciate the technology they were using before.
“But to do it right, you need to do both,” Gomes said.
The organization has to decide whether to save money using the cloud at first and then unlock use cases or to have a novel use case in mind.
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Customer experience top of mind for retail
Improving associate experience and making training easier and faster came up in conversation at the show several times. In addition, many companies at NRF emphasized that the end goal was to create a positive customer experience. In retail, the largest barriers to that may start in the supply chain or from a lack of real-time visibility into shelves. What if a customer orders an item online that is listed as available on the shelf at the store, but turns out to not be in stock? They’re not likely to look for that product at that store next time.
Google Cloud’s shelf checking AI seeks to address this by automatically identifying items to improve on-shelf product availability and provide up-to-date information on which items are in stock. The Browse AI is API-driven, so enterprises can integrate it into their existing tech stacks and solutions.
“Every use case someone talks about today normally requires another piece of hardware, another set of infrastructure you have to put in the store,” Gomes said. “We believe by putting another layer to the platform you can obfuscate that. You can create a seamless platform.”
For more on retail cloud, see what Neiman Marcus said at the NRF conference about its cloud transition with AWS. Plus, Microsoft has just launched a commercial offering based on its Azure OpenAI Service, and the cloud opens doors for malware as well as legitimate actors.