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Google Cloud releases range of retail solutions

12 Apr 2019
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Google Cloud has released a number of new retail solutions, created in collaboration with its retail partners to solve business challenges specific to retailers.

Google Cloud for Retail offers a set of solutions that enable retailers to take advantage of cloud capabilities for specific use cases, from store operations to merchandising to customer acquisition and retention. 

eCommerce Hosting provides flexible, reliable and scalable hosting capabilities for a brand’s eCommerce platforms. 

In addition, Google Cloud’s CRE programme provides a white glove treatment with technical architecture reviews and peak season operations support to help retailers deliver a seamless shopping experience for their customers during the most critical times for their business (such as Black Friday). 

Shopify went all-in on Google Cloud as its infrastructure provider, with 100% of its retailers running on the platform. 

The Real-Time Inventory Management and Analytics solution developed by partners provides inventory visibility across shelves, aisles, and stockrooms giving retailers data to improve the in-store experience of their customers. 

The Empowered Associates solution brings the collaborative capabilities of G Suite along with the social intranet capabilities from our partners to organise, engage, and inform the entire retail organisation.

Advances in AI and machine learning have hugely impacted the retail industry and a number of solutions leverage Google Cloud’s offerings in this area.

For example, Vision Product Search, which uses Cloud Vision technology, helps retailers create mobile experiences by integrating Google Lens-type capabilities. 

Customers can take photos and screenshots from their phone of products they like, and the mobile experience will provide real-time results of similar or complementary items from the retailer’s product catalogue. 

Product Recommendations, powered by Google’s Recommendations AI, helps retailers automatically deliver personal recommendations, at scale. 

It continuously learns and adapts to real-time user behaviours and dynamic environments such as changes in assortment, pricing, and special offers.

Contact Center AI, now in beta, continues to help retailers build modern customer care experiences.

AutoML Tables, also in beta, makes it possible to automatically build and deploy machine learning models on structured data in just a few clicks, reducing the total time required from weeks to days. 

This means users can use enterprise data to predict outcomes to maximise revenue, optimise their product portfolio, and better understand customers.