Anand Logani is Chief Digital Officer at EXXLa multinational data analytics and digital operations and solutions company.
Hyper-personalization has become the buzzword for consumer-facing businesses in industries as diverse as financial services, insurance, retail, media, and even utilities. Fueled by a confluence of events like the growth of direct-to-consumer business models, the emergence of AI-powered virtual agents, and the rise of digital as the primary engagement channel, the idea of knowing a customer inside and out and delivering highly personalized products and services across all channels has become the holy grail for marketers everywhere.
Despite all the excitement about the potential of hyper-personalization, a divide has emerged between the brands that are getting it right and those that aren’t. In fact, many brands are missing the mark with messages that fall flat, leading to fragmented customer journeys and negatively impacting the customer experience. Nothing frustrates consumers more than a generic or inaccurate message masquerading as personalization, and few experiences are more annoying than those that have to be completely relaunched when using a mobile device or contacting a call center.
A centralized approach for a connected customer experience
Increasingly, the difference between the promise of seamless omnichannel personalization and the reality of broken, frustrating customer journeys comes down to data. One of the most common areas where the process breaks down is when customers move from one channel to another (e.g., digital to voice) and the underlying data to maintain continuity throughout that process simply isn’t there to support the transition.
Getting the data formula right to support this connected customer journey requires a centralized approach to customer experience that many brands have yet to perfect. Too often, in their rush to improve one aspect of a customer support function or a specific digital marketing capability, companies implement an off-the-shelf AI chatbot or a basic customer journey analytics tool. While these tools may do a good job of fulfilling a specific function, things ultimately fall apart for customers if the entire process isn’t connected.
Fortunately, many companies are finding ways to address this fragmentation. One of the best-known and most proven examples of this approach is Netflix’s omnichannel customer experience, which allows viewers to pick up exactly where they left off, whether they’re streaming on the TV above, the TV below, their phone, tablet, or laptop. And based on that viewing activity, Netflix can tailor recommendations—sometimes even the trailers, descriptions, and thumbnails displayed in the navigation menu—to customers’ individual preferences. While this level of personalization has become commonplace in the entertainment industry, it can be more difficult to implement in industries with more diverse customer engagement channels, product lines, and problem types.
In another example, British Gas, an EXL customer, implemented generative AI-based agent assistance technology to monitor live customer support interactions and offer guidance to human agents. An important factor is ensuring the solution is fully integrated with the company’s knowledge base. This way, the solution can instantly search a customer’s full history with the company, records of previous customer service interactions, and company best practices to offer highly personalized guidance.
Choreographing a seamless omnichannel experience
No matter the industry, it’s critical to help customers navigate difficult conversations and focus on providing practical advice that addresses their specific needs. Here are three key steps every business should take Before they start investing in new technology.
1. Create a centralized customer experience information hub.
Historically, the data needed to get a 360-degree view of the customer experience was stored in many different silos within an organization. Customer support teams had call logs and customer history in one place; accounts payable and finance had payment history and pricing data in another; marketing had demographics and persona profiles in another. When deploying AI to predict the next best action and build a hyper-personalized engagement strategy, it’s critical to centralize all of this data.
2. Develop an AI-powered engagement layer.
Customers expect information immediately, when they need it, whether the business is open or not. AI-powered conversational solutions should be available via email, SMS, chat, voice and more to serve as digital guides to the company’s knowledge base and connect customers to human agents for more complex questions.
3. Close the loop.
The real opportunity to leverage an omnichannel customer experience strategy lies in the ability to analyze each interaction to improve the overall user experience. This means bringing together information gathered from hundreds of thousands of interactions—including customer experience surveys and net promoter scores, data from customer emails and phone calls, and customer satisfaction data—to improve workflows, develop more personalized offers for each customer, and continue to refine the process.
In conclusion
The progress we’re making today in leveraging data and AI to deliver more personalized omnichannel customer experiences is truly impressive. But we’ve also seen some bumps and growing pains along the way. To avoid these pitfalls and maximize the power of today’s technology, connect all data internally to support an equally well-connected customer journey.
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