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The 4 Elements of Real-Time Customer Engagement
To adapt to customer moments of need, companies need strategies that enable real-time responsiveness.
Posted Mar 20, 2018
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Today’s customer engagements move at breakneck speed, empowered by a digitally connected ecosystem that we couldn’t have envisioned even 10 years ago. Leading digital disruptors have spoiled customers by making transactions so easy that the bar has been raised high for all brands to deliver seamless experiences in every aspect of our digital lives—and many cannot keep pace.

As a result, organizations encounter challenges on multiple fronts trying to deliver engaging, relevant, and lightning-quick brand experiences that customers now expect. And this means much more than being personalized; it dictates a whole new set of core competencies, ones that go beyond just making a “real-time decision.”

Furthermore, many are asking, how fast is fast enough? Seconds, minutes, hours, days, weeks? We can think of each of these as concentric circles, and the wider you go, the farther you get from strengthening relationships with customers or prospects. In today’s fast-paced society, the moment of opportunity is at the center of this circle and may only be open for a very short window of time.

To maximize opportunities and avoid customer relevance rifts, brands should employ a strategy that incorporates four elements of real-time responsiveness to adapt quickly to customer needs and preferences:

1. Detection. Historically, brands have relied on reactive customer engagement and blast marketing campaigns, mainly because they have not had the right tools at their disposal to truly know their customers in a personalized manner. But today’s artificial intelligence (AI) and analytics technologies have opened the door for brands to turn the model on its head, enabling them to think several steps ahead of the customer—and sense his or her needs—as they arise.

While event-triggered marketing has taken off in recent years (e.g., if a customer does this, then do that), the simple scenarios of the past no longer suffice. Advances in AI and complex event detection have revealed opportunities for brands to make their customer interactions more proactive. They do this by sensing real-time changes in data, including both events and non-events across multiple data sources—such as a normally solvent customer trending toward exceeding the balance, or a potential fraudulent transaction at the moment of early detection.

2. Data. Beyond the initial event detection, brands then need to quickly access even more data to better understand the individual and paint a real-time contextual picture of this person. The following characteristics represent the five facets of real-time context:

  • Emotion. Businesses should account for customer sentiment, how the individual “feels” in the moment. For example, an online shopper whose purchase has been delayed in the mail by a week is likely not happy.
  • Motivation. Every customer has an intent or end goal, such as opening a checking account, buying a new cell phone, or resolving a service issue. Companies need to better understand why their customers are interacting with them so they can more effectively prescribe the actions to take to meet these needs now and in the future.
  • Behavior. Real-time context must incorporate the individual actions the customer has already taken or is likely to take. These include aspects such as web browsing behavior, clicks, transactions, and social posts.
  • Situation. The customer’s unique state along his or her journey must be taken into account—e.g., he or she went to the website trying to buy a product but struggled to find it and decided to call a representative instead.
  • Environment. Finally, though easily neglected, environmental status—physical or digital, whether it’s real-time GPS or web location—can inform decisions. This includes such scenarios as the customer’s proximity to a customer service location, impact of the weather on traveling there, or what section of the company website the customer is exploring.

These five facets are the data building blocks that should be accounted for in order for businesses to truly understand their customers and inform engagement decisions. When combined, these facets can provide a much more complete view of the individual, for use in the next step of real-time decision making.

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