Leveraging Algorithms in Retail to Deliver Customer-Centric Experiences | The Garage Group

Leveraging Algorithms in Retail to Deliver Customer-Centric Experiences

At The Garage Group, we constantly ask ourselves, “What needs to be true for our clients and their brands to remain relevant?” Similarly, retailers have been posing the same question internally, and many are now able to deliver a shopping experience that is intelligent and relevant.

Department stores have been particularly vulnerable recently with many filing for bankruptcy, seeking buyers, or closing their doors altogether. Yet, department stores were early leaders in innovation. Selfridges, the UK retailer, was a pioneer in introducing customer-centric innovation. Its department stores brought purchasing to women of all classes and catered the shopping experience to them by offering public restrooms (a first), letting them browse merchandise, and creating spaces where they could meet and shop with their friends. Lord & Taylor and others continued this entrepreneurial behavior with the introduction of the price tag, and a policy around returning purchased items.

Today, consumers are looking for modern-day innovations that also deliver a memorable and satisfying experience. Their expectations, however, begin before they even set foot in a store or visit a website. And with so many choices available at their browsing fingertips, they expect personalized, data-centric solutions that are “for them” and also offer assurance of availability and/or delivery.

Retailers delivering customer-centric and data-centric experiences:

Stitch Fix uses data and human stylists to get to know its customers and predict which five items they will want each month in their personal clothing boxes. And, the longer an individual uses the service, the better the brand’s predictive algorithms can cater to their needs. In the long-run, inventory is managed more efficiently, and customers receive more apparel that works for them.

Former Stitch Fix COO Julie Bornstein – who helped establish eCommerce operations there and for other clothing retailers – is now the Co-Founder of The Yes. The Yes is an online retailer, which launched in May, and is reinventing the shopping experience. The Yes gets to know customers by having them respond “yes” or “no” to a series of apparel items shared on their app or website. From the responses, the retailer better understands the customer and her/his personal style; and its algorithms are able to curate and suggest items. Every user’s experience with The Yes is bespoke; and even the homepage is curated to deliver a unique encounter with recommendations tailored to her/him.

At the H&M group, artificial intelligence and predictive data are being used to help the retailer align supply and demand, and improve sustainability in sourcing. H&M also uses data to customize what it sells at individual stores with algorithms that analyze store receipts, returns, and loyalty-card data. Underscoring its commitment to leveraging data and AI, the retailer recently added an AI and robotics expert to its board of directors.

Retailers aren’t the only companies turning to algorithms to offer relevance. In CPG, brands found themselves abandoning long-term plans this past spring as the pandemic shifted the landscape of consumer purchase patterns. In a recent virtual Courageous Minds Only Chat, Claudine Patel (VP, Marketing, Upper Respiratory, Reckitt Benckiser) shared that RB is increasingly relying on data and tools that can help analyze and make predictions in order to reprioritize projects and plans to meet consumer needs.

“We’re still using the traditional tools of research, but data analytics and predictive data analytics more so are what I’m relying on now to help me think through the next 12-16 months until we get out of this.” – Claudine Patel

How is your brand leveraging data and algorithms to reach out and deliver products to consumers? If you need a partner in crime to think through this with you, get in touch. We help BigCo leaders tackle strategy and innovation challenges via startup-inspired approaches.

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