The nature of retail has changed. The Covid-19 pandemic marked a turning point, propelling forward the transition to e-commerce. Retail now exists in a middle ground, not entirely physical, not entirely digital, but a combination: phygital.
In May, Avasant’s Empowering Beyond Summit held a panel discussion titled: From Aisles to Algorithms: Navigating the Phygital Retail Experience. Moderator Fred Pond, former CIO of Columbia Sportswear and Distinguished Avasant Fellow, spoke with Ronald Johnson, CIO of Gelson’s Market, James Whatley, CIO of Mary Kay, and Walter Yosafat, CIO of Capri Holdings, about using omnichannel strategies to improve the customer experience, the importance of robust data, and how AI is changing the future of retail.
Omni Channel Strategy
In a landscape where customers move between physical and digital avenues, retailers are adopting omnichannel strategies that offer new opportunities for interaction with customers and harmonize experiences across platforms. In an effective omnichannel strategy, “as customers move across these channels, applications and data move with them,” ideally creating a consistent and on-brand consumer experience.[1]
For Johnson, brick-and-mortar grocery stores will be a staple of the grocery industry for the next ten to twenty years, though, the company has increased its online presence. With Gelsons Market offering online ordering options, customers have been crafting their own interactions. By ordering certain products online and purchasing some in-person when they go to pick up online orders, Johnson notes that “customers have started to combine in unique ways the channels that we’ve got out there.” E-commerce has even spread to notoriously face-to-face business models like Mary Kay. A key challenge in the online shift is how to maintain brand culture in a non-physical space. James explains that “you need to have a stronger presence online with your brand than you really do in physical stores,” which Mary Kay has done by offering brand-specific online tools like the skin-analyzer to provide a semi-classic beauty consulting experience. A successful omnichannel strategy generates profit through each channel.
For James, this means having “commerce at every digital touchpoint.” The term “digital touchpoint” refers to any interaction or point of contact between a customer and a company through online channels. James advocates for commercial interactions at every point of contact, whether it is a customer visiting a company’s website or scrolling through its social media account. To successfully close deals at every touchpoint, companies need to have robust and synchronized client and company data across all channels. Fred notes that customer data is key to successful deals, “How you make that pitch, whether it be to bring them to an online experience or an in-store experience, is key. It’s critical that you do it in the right way and that you have the right facts about the data.” Since outdated information can hamper a sales pitch, an effective strategy entails sharing up-to-date data effectively across all operational channels.
Robust Data
Companies need quality data to succeed in the phygital realm. Acting through multiple channels, customers scroll online, add to cart, and either show up for in-store pick up or ship to their home. A seamless experience is made possible by a continuous flow of information. Without it, an online order might never be received, or may fail to show as out of stock, key inventory data that never reached the website. Data integration is needed to give “a single, clear overview across warehouses…retailers can ensure that whether customers choose to buy from their sofa or the shopfloor, they encounter a consistent, personalized journey.”[2] Supporting the success of omnichannel strategies, data access allows employees to deliver personalized experiences in their customer interactions, “store associates can deliver unforgettable in-store buying experiences, giving customers instant information on products and availability without running to the stockroom.”[3]
When quality data is key, companies with better data will have a leg up. Established online retailers have more comprehensive historical customer data, which is invaluable for deploying AI models effectively. At the onset of the pandemic, Yosafat faced the unique challenge of transitioning a company in the luxury retail industry – a space where high-quality, in-person experiences were the norm – into the phygital realm. Reflecting on the successful journey, Yosafat noted that he would have liked to have implemented more robust data collection techniques before the transition to ensure the availability of high-quality, error-free data. He envisions a future where AI, combined with rich data, tailors to the customer experience by leveraging past purchases for product recommendations. With data playing such an integral part of powering omnichannel interactions and harnessing the full potential of AI, what happens to companies who, like Capri Holdings, did not start robust data collection until recently? Pond believes that these companies should embark on catch-up efforts. At Columbia, Pond experienced how quickly innovative trends come about. He created a robust data collection system and then, within a few years, completely revamped it to align with technological advancements. Pond explains, “It will pay for itself and you’re never really completely out of the picture unless you just say I don’t want to do it or I’m too late.”
AI and the Future of Retail
With robust data, the future of retail will harness AI to enable personalized interactions while improving operational efficiency. Currently, AI’s top retail use cases are store analytics & insights, personalized customer recommendations, adaptive advertising, promotions and pricing, stockout and inventory management, and conversational AI.[4] Not listed is trend prediction, which would require a complex, consumer-sentiment-based model. Though challenging to construct, Pond believes it will be a “crystal ball” with the power to revolutionize retail and inventory planning by letting retailers “infer what those changes are going to do and how the markets are going to react to them.”
Though that use case has not yet been perfected, retail leaders like Gelsons Market, Capri Holdings, and Mary Kay are making AI’s potential a reality by leveraging some of the top use cases. Utilizing its Salesforce platform, Mary Kay tracks site data and implements AI to gather customer insights. By capturing customer activity from click to purchase, collected data can be used to generate more personalized and accurate product recommendations. Along this vein of using AI to better understand one’s customer base, Gelsons Market has leveraged its loyalty program to create an AI-based solution that scores customers against their propensity to buy every item in the store. Giving companies quantifiable metrics for just how profitable and targeted their marketing techniques can be changes employee knowledge and customer interactions forever. Yosafat recognizes AI’s ability for personalized upselling opportunities but is also interested in its product development capabilities. Capri Holdings’ Michael Kohrs division is using 3D modeling for sustainable designing with minimal waste and effort, “you have the data, you put the designers there and they’re able to generate 3D models, it’s faster, it’s cheaper, it’s better.”
These undertakings reflect broader industry trends with retail giant, Walmart, deploying AI for inventory management – an area where inefficiencies have historically led to significant profit losses. Cameras attached to floor scrubbers send images to AI-powered data centers where inventory levels are evaluated and adjusted.[5] Industry-wide, companies are using seasonal trends, sales patterns, and global events, to help manage and predict supply chain issues.[6] These innovations reflect just some of the potential benefits that effective AI use can bring to the retail industry.
Moving Forward
The ethical considerations of collecting consumer data and AI’s potential for job replacement are hotly debated topics. For Pond, these are very real issues and companies need to put a lot of thought into how they want to present themselves to consumers. With data collection, companies should be straightforward rather than bogging consumers down with long terms and conditions, “the more you can get a consumer to opt in, join your loyalty program and within that, you know, there’s always a ‘you’re agreeing to do this’ and make it simple.” For Pond, AI is not going to replace jobs, and its potential for error requires employee oversight checkpoints. It will increase employee productivity which will allow employees “to get more done and be able to do some of the reviews and assessments that have to happen but, in the past, they were too busy for.” While no one can predict exactly what will happen, retail companies can prepare by getting consumers on board and leveling up data collection and management to adapt and prepare for advancements in the phygital age.
References
[1] What is Omnichannel Retail?. Intel. (n.d.). https://www.intel.com/content/www/us/en/retail/omnichannel.html
[2] Hughes, M. (2022, October 31). The future of Retail is Phygital. Forbes. https://www.forbes.com/sites/mikehughes1/2022/10/31/the-future-of-retail-is-phygital/
[3] Hughes, M. (2022, October 31). The future of Retail is Phygital. Forbes. https://www.forbes.com/sites/mikehughes1/2022/10/31/the-future-of-retail-is-phygital/
[4] Countouris, C. (2024, January 9). Putting the AI in retail: Survey reveals latest trends driving technological advancements in the industry. NVIDIA Blog. https://blogs.nvidia.com/blog/ai-in-retail-survey-2024/
[5] Retail Insider. (2024, August 5). How AI is Transforming the Retail Industry. https://retail-insider.com/articles/2024/08/how-ai-is-transforming-the-retail-industry/
[6] Retail Insider. (2024, August 5). How AI is Transforming the Retail Industry. https://retail-insider.com/articles/2024/08/how-ai-is-transforming-the-retail-industry/
By Adriana Guzman, Associate Consultant