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Reimagining future of customer conversation   

Today, cutting-edge companies are building what we call intelligent experience engines to assemble high-quality customer experiences by using AI-powered by customer data. The aim is to design end-to-end solutions—for example, finding a location, scheduling an appointment, sending appointment reminders, providing directions, and guiding users through any necessary follow-up—that proactively lead customers toward achieving their goals. They also combine human enablers (cross-functional, agile teams) with data and technology that allow for rapid self-learning and optimization. Although building an intelligent experience engine can be time-consuming, expensive, and technologically complex, the results allow companies to deliver personalization at a scale we could only have imagined a decade ago.   

Ways to create personalized customers conversation.

Most brands don’t personalize customer experiences at the scale or depth necessary to compete with the world’s leading companies. Personalizing an end-to-end customer experience requires orchestration across channels—a capability that no brand has fully mastered. But merging the flow of customers’ physical and digital experiences may be the only way challenger brands can compete against digital natives like Amazon and Google. Early tech movers have tapped into newer technologies, such as the internet of things, machine learning, marketing tech (martech) platforms, and a growing number of digital media tools that can create formidable advantages when combined with agile methods. Brands that want to surpass—or simply catch up with—early movers need to think about their data and technology foundation.  

Building an intelligent Experience engine   

Intelligent experience engines are not built just at the highest level of an end-to-end experience, such as enabling better security services at companies. They must also be surgically focused on micro-goals—positive individual moments that compose the total experience—and ensure that all those goals get stitched together.

Moreover, those engines are “intelligent” in more than one way. They are crafted creatively and insightfully, using the best possible data and expertise. And they employ ever-improving machine-learning algorithms to figure out the right next step to enable the customer’s progress—constantly testing, always learning, and fueling decisions about how the interaction works. What the customer gets is a seamless, positive, and distinctive experience that will only improve over time.

Connect Data Signals & Insights 

The first requirement for building an intelligent experience engine is constructing a 360-degree view of each customer, using the expanding range of possible ways to capture new signals from each one. For example, when a guest makes a purchase at a retail location for the first time, she is asked to provide her email address to receive a receipt. Emails are also collected when customers sign up for free in-store yoga classes. Brands normally use this personal information to augment basic customer demographics from a service like Experian or Acxiom, enabling marketing actions such as gender- and geo-based targeting. As people continue to engage with the brand, they often download the app or shop online, and clickstream data is used to understand which items customers browsed, which ones they spent a long time considering or came back to, and which ones they quickly moved past. This data can be leveraged to infer intent and target future recommendations accordingly  

Summing it up

Today businesses are going further by endowing teams with even greater responsibility for leveraging data. The teams essentially serve as product managers dedicated to continually improving end-to-end customer interactions.

To begin the process we’ve described, you should ask: What experiences do we want to revolutionize, and how can we build an intelligent engine to achieve our goals? Once you’ve decided on the answers, research a few customer records in your CRM and marketing automation platforms to determine whether you’ve captured all the relevant data needed to power more-valuable experiences. Did you use the data to make the customer experience better? Did you do so seamlessly across channels? The answer to both questions is probably no.

Most CEOs and their C-suite colleagues claim to recognize the importance of the customer experience. But we often see more talk than action. That must change. Every company needs an explicit strategy for building an intelligent experience engine, which can align the organization toward using AI, personalization, and agile processes to build deeper, more enduring brand loyalty.

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