Accenture’s AI.Retail platform — which helps retailers better utilize data and artificial intelligence to optimize common operations such as customer acquisition, pricing and promotions, assortment and supply chain — can now be deployed on Google Cloud. The integration will allow merchants to merge the capabilities of AI.Retail with Google Cloud technologies such as data analytics, AI and product discovery to more holistically analyze their business.
Current customer Albertsons Cos. is already seeing the benefits of the pairing, with the company’s EVP and CIO Anuj Dhanda saying in a statement: “With Google Cloud and Accenture, we are integrating technology that enhances our supply chain operations by significantly increasing visibility into our inventory levels, helping us with forecasting and improving on-shelf availability so that customers have greater access to the products they want, wherever they shop.”
“We created the Ai.Retail platform several years ago [to offer retailers] a repository of capabilities that teams could quickly pull off the shelf as they’re figuring out what to do with all their data,” said Jill Standish, Global Retail Lead at Accenture in an interview with Retail TouchPoints. “So it could be markdown optimization or customer analytics or supply chain or assortment and merchandising — there are a lot of use cases that retailers tend to need. Everyone is grappling with a future that looks a little bit volatile and so companies are saying ‘I’ve got to really figure out how to be more productive, take cost out, get better assortment, get a better handle on inventory, make better use of my labor, etc.,’ and all of those have a data and analytics element, which is what we’re helping them figure out.”
AI.Retail doesn’t replace “execution systems” like a customer data platform (CDP), pricing system or assortment planning tool; instead, it helps retailers feed better information into those systems, explained Standish. Now, “what we’ve done with Accenture in this partnership is infuse our building blocks into their platform,” said Carrie Tharp, VP of Retail and Consumer at Google Cloud in an interview with Retail TouchPoints. “So you’re getting the value of Google innovation — we put 21 million people-hours into AI research every year — combined with Accenture’s pre-built tools.”
At the same time, the partners also announced that they will collaborate on a broad new initiative to apply intelligence from Ai.Retail to help businesses optimize their customer, workforce and storefront experiences. Use cases for the initiative could include everything from product discovery to brand loyalty to regulatory compliance.
Among the new capabilities available to retailers through the enhanced integration of the two solutions are:
- Centralized supply chain analysis: The combination of AI.Retail and Accenture’s Intelligent Supply Chain platform with Google Cloud products, such as Looker and BigQuery, will allow customers to better organize data and provide a real-time view of their most critical supply chain metrics, including procurement, logistics, inventory and sales. Retailers can then run “what if” simulations, calibrate demand forecasting, improve inventory planning, formulate strategies for supply chain segmentation and more.
- Personalized customer experiences: AI.Retail now leverages Google Cloud’s Discovery AI solutions for retail, which can reduce search abandonment through Google-quality search capabilities, deliver personalized recommendations at scale and help shoppers find products with images. Additional integrations with Accenture’s Customer Data Architecture and Google Cloud’s CDP will let retailers break data silos and drive predictive marketing engagements with AI or machine learning.
- Assortment optimization: Using Google Cloud’s BigQuery, Looker and Vertex AI, Ai.Retail now features new store clustering capabilities that will help retailers identify, group and optimize stores with similar characteristics, enhancing strategies for assortment, space management and inventory. This includes recommendations on whether to maintain, reduce or drop specific products that can be filtered by individual stores or store clusters, ultimately improving overall sales performance.
“The ingestion, sorting, cleansing and understanding of that data retailers are bringing in — things like what is useful, what is not and the veracity of that data — that used to be where people were spending 80% of their money and resources,” said Standish. “Now, because we’re automating a lot of that, they can move more quickly to make sense out of all this stuff and get to a better ROI.”