Say Real Time Like You Mean It!

By Team ZineOne September 19, 2016
Innovative AI and ML enhances data analytics to drive real-time customer engagement.

Streaming analytics push big data in the realm of real time

The notion of real-time engagement has been talked about for a while and does not hold that much value a a new technology. What does the term “real time” really mean and what is its value proposition to the consumer and to the business in today’s hyper online world?

We believe that the true value proposition is in how it can be used to influence a customer journey. For instance, can an enterprise recognize what the customer is trying to do in that one moment, in a particular channel, and engage them right there and then with value added information that the customer desires, to propel their customer journey?

The question then is what is needed to enable such real-time interactions? And the answer is …. Streaming Analytics

Streaming analytics are critical to capitalizing on the true sense of real time. According to a recent Forrester report, “Streaming analytics solutions can capture perishable insights on real-time data to bring immediate context to all IoT, mobile, web, and enterprise apps.”

However, we think we can take this one step further and us these perishable insights to take action. As the saying goes, nothing like striking while the iron is hot, to get the results you are looking for. So, can a brand act on these real-time insights while the user is on their digital property to propel them in their customer journey?

Consider the following scenarios:

  • Suppose a customer is on a brand’s website and flip-flopping between two product pages. Perhaps the user is trying to compare two products to make a purchase. Can the bran serve up a discount offer or some helpful comparison information at that moment? This might the nudge the customer needs to make the purchase decision.
  • Continuing with the above example, when this user is on the brand’s app, the app recognizes that this user is a preferred customer and immediately informs the user that because of her loyalty status, she is eligible for a discount on certain kinds of products today. In this case, the app is correlating the customer’s in-app activity with her profile to make the brand-to-user-interaction more targeted.
  • Additionally. the brand can also use historical user data housed in its CRM and marketing database to embellish the streaming data to add yet more context. Again, consider the above example, except that now the app not only knows the customer’s preferred status, but it also maps the user profile to the fact that her Reward points will be expiring in a week. The brand can give this information to the user while she is on the app and incentivize her to use those reward points before they expire.

It’s all about harnessing and analyzing data on the go to produce real-time insights and using them to power real-time interactions to influence the customer journey. It’s also about making this process flexible and agile. It would be very time consuming and near impossible for a brand to hard code multiple such scenarios to take real-time actions. The key is to engage in that moment with value added information that the user desires. It is about providing the right message at the right time on the right channel, based on real-time activity of every user, and not communicating to them after that moment is gone.

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