Today’s consumers expect more than just products — they crave personalized experiences that cater to their unique preferences, interests, and needs.
They’re used to brand interactions that are convenient, fast, digitally driven, and on their terms – regardless of the time of day, the device they’re connecting from, or the issue they’re having. As a result, retailers are fighting for a key differentiator that will make them stand out from the crowd.
AI capabilities present a major opportunity for retailers to enhance self-service, online, and in-store experiences and tailor products and services that improve customer satisfaction and deliver tangible, transformative business outcomes.
However, with Forrester highlighting that only 26% of US adults believe that the brands they buy from do a good job of understanding them as a person, there’s plenty of space for retailers that want to harness the full potential of AI-powered innovation to increase loyalty and maximize lifetime value.
In this blog, we lay out the journey and foundational factors you need to get right to deliver truly tailored, customer service-driven experiences enabled by AI.
AI and the Advance of Big Data
The term ‘dark data’ refers to an all-too-common occurrence within the retail industry, in which companies have access to, but fail to leverage customer data effectively because manually sifting through vast amounts of data is complex and time-intensive.
It has also long been the norm for marketing, loyalty, and customer service to operate in silos – with each focusing on their own objectives and metrics. And one of the consequences is that a treasure trove of customer data is needlessly being held back within each department.
Breaking down these silos and finding ways to utilize customer data to add value is no longer just a nice-to-have — it’s a critical first step in delivering harmonious brand interactions that drive satisfaction, loyalty, and advocacy.
By fostering collaboration across departments and implementing a centralized customer experience management platform system that serves as a single source of truth, businesses can tap into streamlined data behind the scenes. Additionally, the combined data can help build a true 360 view of their customers. And, here, AI allows retailers to take things one step further.
Through AI-powered analytics, you can record and analyze every customer interaction, providing deep insights into customer sentiments and engagement. Transaction records, customer contact histories, ad click-throughs, product hierarchies, and CSAT scores all unlock the expertise to deliver a frictionless experience – both online and in-store.
Automating Tailored Experiences at Every Stage of the Retail Journey
Even with a unified bank of actionable customer data, if you’re not leveraging it efficiently, you will not get the results you want – and neither will your clients.
Retail businesses can use AI-enabled customer data analytics to build a bespoke omnichannel experience, providing tailored product recommendations and exclusive offers that meet each individual’s unique needs – no matter where they are on their purchasing journey.
Currently, 62% of American marketing executives admit they are most likely to leverage personalization when individuals register for a service or set up a product they’ve just bought. But this approach neglects the remainder of the customer lifecycle where personalization remains vital. Consumers need to see you care, even after purchase.
And a prime opportunity to leverage automated personalization after purchase is your customer service. For example: when the omnichannel CX platform powered by AI identifies a customer asking repeated questions, it can automatically pass them over to a human support assistant – improving the experience for both agents and customers by streamlining the issue resolution process and maximizing agent productivity.
Take our work with a global conglomerate’s automotive retail entity, leading a digital transformation spanning the entire customer lifecycle. Deploying AI platforms, we unlocked new actionable insights, seamlessly diverting shoppers to the right live agents, based on their inputs to an AI chatbot, spanning interactions across the entire customer lifecycle, from new customer acquisition to how many miles are left on a lease.
This approach reaped benefits for client and customers alike: seamless, relevant conversations took place quickly for better issue resolution, and the business secured greater agent efficiency. The result was a 10% cut to average handling time and a 5% jump in CSAT scores.
Getting Started With AI-Powered Personalization
AI is increasingly essential for building the next generation of automated retail experiences.
From deconstructing departmental silos to leveraging customer data at the right moments, retailers might want to consider these five key steps in the implementation process to deliver AI-powered hyper-personalized experiences:
Assess Current State and Identify Goals:
Evaluate current customer data management systems, departmental structures, and technology capabilities. Also define clear objectives and goals, such as improving customer satisfaction, increasing loyalty, or driving sales growth.
Break Down Data Silos:
Identify and dismantle organizational silos and implement centralized data management systems and processes to encourage cross-functional teams to share insights, data, and expertise to drive innovation and deliver seamless customer experiences.
Choose the Right Technology Stack:
Invest in omnichannel CX, AI, machine learning, data analytics, and automation tools that can examine vast amounts of customer data and deliver personalized experiences at scale.
Identify Key Consumer Touchpoints:
Map out the customer journey to identify critical touchpoints and opportune moments where personalized interactions can make the most impact.
Implement Hyper-personalization Strategies:
Utilize advanced analytics and AI-driven algorithms to segment customers based on behavior, preferences, and demographics, and develop personalized messaging, product recommendations, and offers tailored to individual customer segments.
Unlocking the full potential of AI platforms and automation for retail is complex and requires detailed end-to-end planning from design through to development and delivery across a range of business operations and processes. It takes a specialist approach to turn the AI opportunity into the win retailers need.
Want to find out more about how to build a foundation for AI-driven hyper-personalization in your retail operations?
Share this: