Google Cloud introduces AI-powered solutions to enhance in-store & online shopping experiences

Google Cloud introduces AI-powered solutions to enhance in-store & online shopping experiences

Google Cloud has released four new AI technologies to help retailers improve their in-store shelf-checking processes and enhance e-commerce sites. Google’s announcements are another example of how retail shelves are being transformed with edge computing hardware, cloud data and decision software.

Google Cloud’s updated Vertex AI Vision and Discovery AI solutions provide retailers with more efficient shelf-checking, personalization, dynamic browse features, product ordering optimization and personalized recommendations for repeat purchases. Google says these AI capabilities will help retailers create better in-store and online shopping experiences.

“Upheavals over the last few years have reshaped the retail landscape,” said Carrie Tharp, the VP of retail and consumer at Google Cloud.

According to NielsenIQ, retailers lose billions of dollars due to empty shelves. That said, Google claims new AI technology offers a solution. By creating reliable AI models that detect and differentiate products, retailers can now more effectively monitor their in-store shelf availability and improve product availability.

Google Cloud says its new AI-powered shelf-checking solution helps retailers improve on-shelf product availability.

With billions of unique entities in Google’s database, Google Cloud has developed an AI that can accurately identify items from images shot at different angles and perspectives. The AI technology for product and price tag identification, now in preview, is expected to be available globally to retailers in the coming months.

Google Cloud has also introduced a new AI-powered feature in its retailer Discovery AI solution. It leverages machine learning to customize the online product selection within a given category. Google says this technology makes digital window shopping easier, faster and more enjoyable for customers.

“Despite uncertainty, the retail industry has enormous opportunity,” stated Tharp.

For example, Google claims AI-driven product ordering helps optimize e-commerce sites by learning ideal product ordering for pages based on historical data. This data increases accuracy, relevance and chances of making a sale.

E-commerce sites have traditionally relied on manually curated product results to drive sales. However, Google says this new technology can improve revenue per visit and save retailers time and money by self-curating and learning from experience with no manual intervention.

Google Cloud research also found that most shoppers prefer brands that personalize their interactions and offer tailored outreach, as well as those that understand their interests and preferences.

To this end, Google Cloud has introduced a new AI-driven personalization capability to help retailers create more intuitive online shopping experiences. This technology enhances the capabilities of Google Cloud’s Retail Search offerings, allowing customers to get personalized results when searching and browsing a retailer’s website.

It uses customer behavior to determine which products best match their preferences and moves them up in search and browse rankings.

That said, Google says retailers will own and control their customer data, giving them access to customer preferences insights.

This e-commerce optimization feature uses machine learning to offer better product recommendations and increase user session revenue. DeepMind collaborates to create a model that considers item prices, product categories and customer clicks and conversions. Additionally, a buy-it-again model provides personalized recommendations based on the customer’s shopping history.

Compared to the baseline recommendation systems, the company says that Recommendations AI has demonstrated double digits in conversion and clickthrough rates as tested by retailers.

“The leaders of tomorrow will be those who address today’s most pressing in-store and online challenges with the newest technology tools, such as artificial intelligence and machine learning,” added Tharp.

In mid-2022, Google Cloud unveiled a private networking solutions portfolio designed for its Google Distributed Cloud Edge platform. By collaborating with independent software vendors, the company tackles issues related to cellular networks for edge deployment.

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