Putting the AI Into Retail
In today's fast-paced digital world, personalized experiences have become an expectation rather than a privilege. From tailored recommendations on streaming platforms to customized news feeds on social media, consumers have grown accustomed to having their preferences catered to. This desire for personalization has long extended to the retail industry, but recent studies continue to reveal significant gaps between consumer expectations and what retailers are delivering.
A leading market research firm conducted a survey that found 78 percent of consumers get frustrated by businesses that do not offer personalized experiences. They want retailers to understand their preferences, anticipate their needs, and provide recommendations aligned with their individual tastes. However, the same study found that 83 percent of consumers are willing to share data with brands to receive personalized experiences, yet only 31 percent of companies felt they were successfully achieving omnichannel personalization.
Historically, implementing personalized product recommendations, targeted offers, and dynamic page layouts has been complex and costly. Technological barriers, high setup costs, and the need for data scientists to make sense of vast amounts of customer data have hindered progress. Retailers often faced multiyear road maps or expensive third-party contractor implementations, forcing them to choose between delays or significant capital costs.
Fortunately, the emergence of new artificial intelligence-powered predictive personalization offers a solution that bypasses the need for large-scale IT projects and expensive third-party implementation. Cloud-based secure personalization allows any organization to implement a headless, cost-effective cloud solution that delivers true AI personalized experiences at scale and across every channel. Unlike traditional methods, AI-driven personalization enables teams to create tailored experiences for both known customers within their customer relationship management systems and anonymous shoppers in a matter of days, not months. It also provides actionable consumer insights that are visually presented and designed for the marketing team to use and share throughout the organization.
One key advantage of AI-powered personalization is its minimal integration requirements. Retailers no longer need extensive infrastructure changes or expensive technology upgrades. Instead, they can harness the power of AI through cloud-based solutions seamlessly integrated with their existing systems. This democratizes personalization, allowing even smaller retailers with limited resources to provide experiences that rival those of industry giants.
The beauty of AI lies in its ability to learn and adapt over time, as recent headlines have highlighted. By analyzing individual site visits and customer data, AI can identify patterns, preferences and trends. This enables brands and retailers to deliver targeted recommendations that resonate with each shopper, regardless of whether they're browsing online, shopping in-store, or engaging through social media. AI-powered personalization transcends channels, providing a seamless and consistent experience throughout the entire customer journey.
AI-driven personalization also has a significant impact on basket building. By understanding individual preferences and purchase history, AI algorithms can suggest complementary products or cross-sell opportunities. This leads to increased sales and customer satisfaction, enhancing the overall shopping experience and encouraging customers to return for future purchases.
The potential of AI-powered personalization goes beyond just product recommendations. From tailored promotions to exclusive offers, marketers now have the opportunity to deliver exceptional customer experiences that foster loyalty, drive revenue growth, and gain a competitive edge in an increasingly crowded market.
With minimal integration requirements, faster implementation timelines, and the ability to provide omnichannel recommendations, retailers can bridge the gap between consumer expectations and their ability to deliver personalized experiences. By embracing the power of AI, teams can unlock new levels of customer engagement and create a retail landscape that truly puts the "AI" into retail.
Diane Keng is the CEO and co-founder of Breinify, an AI- powered predictive personalization platform that helps consumer enterprises deliver relevant and personalized experiences at scale.
Diane Keng is the CEO and co-founder of Breinify, an AI and predictive personalization engine that helps brands curate dynamic, meaningful experiences for their consumers at scale. Diane is on Forbes’ 30 Under 30 for enterprise technology and has been featured in The Wall Street Journal, HuffPost, TechCrunch, OZY, and Inc. Magazine. Diane ran three successful businesses before she was 18 and is a noted software innovator who frequently speaks on the intersection of AI, personal data, privacy, and the future of smarter products. Breinify works with retailers and consumer packaged goods brands to enable data science in marketing campaigns that secure 51% year-over-year online sales, 20 times the click rate, and six times the reaction rate.