The core idea behind real-time customer engagement, which I will speak on today at the Gartner Digital Marketing Conference, is the ability to recognize and interact with your customers at the speed and cadence that matters to them. Often misconstrued as social newsjacking or real-time PR, the concept of real-time customer engagement involves providing contextually relevant interactions and messages that foster a deeper connection between customers and brands. The more intimate understanding of the buyer journey that this represents – understanding device preferences, location, time of day, etc. – the more it allows brands to interpret intent and react to customers in the moment.
The always-on, always-addressable consumer will not agree to interact with brands that don’t provide relevant experiences. The speed of customer decision-making is increasing, and they have more avenues through which to research, make purchasing decisions, and more generally interact with your brand than ever before. If you don’t provide contextually relevant interactions at the speed the customer wants you to, they’re more likely to switch to a competitor that they think will do a better job. But what actually is real-time customer engagement, and why is it so important?
Imagine you’re at a networking event, or a social gathering. When you talk to someone face-to-face, in those settings, you instinctively watch their body language and listen to their tone of voice while talking. This information, or context, allows you to tailor your body language, word choice, and even what topics you choose, to the interaction at hand in real time. Real-time customer engagement in the digital world operates the same as that face-to-face conversation. You recognize a customer’s action and quickly provide a message or next-best action to drive further engagement.
Engaging with customers in real time requires organizations to master three core capabilities:
Today, much of this effort can be automated and optimized with A/B/n and multivariate testing, self-learning models, or predictive analytics to determine what audiences, segments, or individuals are the most likely to respond. If you’re able to react with a contextually relevant message regardless of engagement channel, you will go a long way to creating engagements that close the gap between customer experience and expectation.
Providing contextually relevant messages in real time can make a dramatic difference in your customer engagement efforts. Customers increasingly expect brands to know who they are, regardless of channel, and provide a frictionless buying experience. Real-time customer engagement strategies and technologies make that possible, which is why brands of all sizes should closely examine their goals and objectives to determine how they can apply real-time thinking to their own engagement efforts.