Exclusive Q&A: Create omnichannel customer profiles with AI

Dan Berthiaume
Senior Editor, Technology
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Cloud-based AI and ML technology

Cloud-based artificial intelligence and machine learning solutions enable retailers to obtain a single, unified view of customers for enhanced personalization.

Kashif Rahamatullah, national Google Cloud practice and alliance leader, Deloitte, recently discussed with Chain Store Age how retailers of all sizes can leverage the capabilities of the cloud to develop highly individualized customer profiles that are consistent across all channels.

What are the advantages of having a single view of your most profitable customers in a single profile?
The ultimate nirvana for retailers is creating a positive consumer experience across the value chain both online and in store – from evaluating a brand or product, to making a purchasing decision, to receiving, using and servicing the product. Retailers have the chance to connect with consumers at these various touchpoints throughout their retail journey, but too often, they’re missing out on opportunities to engage at the right time due to siloed processes.

To avoid these missed opportunities and enhance the customer experience, it’s vital to create a single view. By synthesizing customer data into a unified profile, this empowers retailers to further segment and retarget their resources, ultimately improving the consumer experience by using a hyper-tailored approach.

How can retailers leverage customer segment information for personalized customer service experiences, both online and in store?
Gone are the days where demographics, geographics, etc. alone are enough to accurately segment customers. However, through cloud offerings such as artificial intelligence/machine learning (AI/ML), and by leveraging first and third-party data, retailers can get a detailed look into their customer’s behavior to create individual personalized customer experiences.

This process enables small to mid-market retailers to adopt personalized, effective customer service tools across their operations in a cost effective and timely manner. It’s equally important to note that retailers should value post-purchase service and think about how to build customer loyalty and get consumers back into the online and physical stores after they make a purchase.

How is the omnichannel customer experience evolving, and how can retailers react with advanced data analytics?
‘Omnichannel’ was once used to describe the world between physical stores and online commerce, but today’s definition has expanded to include social channels as consumers increasingly engage with retailer’s digital presence. In this new age of social buying, many retailers struggle to be strategic about how to narrow down their product offerings in a social, omnichannel model.

To tailor offers to consumers to the level of specificity successful to social selling, retailers must leverage the scalability that analytics allows, to boost consumer personalization. Also critical to the omnichannel customer experience and the overarching future of retail is the role third-party sellers play.

Consumers may not land on a retailer’s owned website, but it’s paramount that retailers understand customer needs and have the right mix of products scaled to their third-party vendors, so that consumers have a tailored experience across all mediums of shopping.

What are the details of how Google Cloud and Deloitte are helping retailers cleanse and aggregate data?
By leveraging first and third-party data combined with Google Cloud’s smart analytics and AI/ML capabilities, along with Deloitte’s depth of business expertise across retail and commerce, the alliance provides retail clients a 360-degree view of their customers.

In order to boost the effectiveness of customer data platforms (CDPs), the two organizations not only help clients capture data, but in tandem, provide a streamlined approach to cleanse and combine the disparate data, for a stronger, competitive offering. Creating this single view establishes the opportunity to make data-backed decisions to enhance personalized experiences, further driving meaningful insights and opportunity for consumer engagement.

[Read more: Key considerations for digital transformation in retail]