In today’s hyper-connected world, customers expect enterprises to cater to their needs in real time, all the time, no matter which channel they happen to be using. In order to make this level of engagement a reality, however, enterprises must secure a new means of understanding their customers; one that is built for the requirements of a new engagement paradigm. To this end, enterprises not only need to access and leverage “customer DNA”—the constant stream of all customers’ activity data—but they must also ensure that this data is optimized to provide in-the-moment understanding about the ever-changing context of individual customers. Only when enterprises achieve these deep insights into customer readiness and receptivity will they be prepared to delight customers with real-time, personalized engagement.
For enterprises, what makes up the customer DNA? At its core, our patented real-time event analysis with customer DNA is clickstream data from the activity pattern of an individual customer as it manifests across a multitude of channels.
This clickstream data has traditionally been aggregated into channel-specific silos, which reside within software packages such as Omniture or Google Analytics. These platforms allow the data to be leveraged for the purpose of establishing collective insights about customer behavior in aggregate; but could clickstream data also be evaluated at an individual level in order to understand the intent of unique customers in a given session, to then appropriately personalize their user experience?
ZineOne has done just that! We collect, assimilate, and examine clickstream data for individual customers across channels (web, app, m.com, t.com) to read a customer’s intent in-the-moment and then react in any given session based on what our machine learning (ML) models deem as the “influence zone” of that particular customer.
The notion of “influence zones” adds a layer of immediate situational awareness to the concept of personalization. In the past, personalization was largely based on an individual’s propensity score towards a certain offer or product and their eligibility for that same offer or product. This speaks to the “What?” element of the personalized engagement equation. Influence zones expand this notion of personalization in order to establish the “When?” element. It considers additional factors such as customer readiness and receptivity. These considerations take into account the customer’s in-the-moment activities and situation to determine the exact point at which he or she will be most amenable to a message.
How has ZineOne gained an understanding of customer readiness and receptivity?
The answer lies in our machine learning (ML) algorithms, which examine incoming event patterns while they are still in-memory (not yet stored). This empowers us to understand customers’ immediate context and, therefore, adjust engagement based on their “influence zone” in that same session. We have seen significant results with this approach—in fact, our algorithms are able to predict whether a customer will complete a transaction in any given session with 75% accuracy. When a customer is not likely to complete a transaction, the ZineOne Customer Engagement Hub incentivizes them using influence zone models to deliver the right message at the right time based on their current receptivity and readiness.
Learn more about ZineOne’s AI-powered, personalized Customer Engagement Hub here, and keep an eye out for my next blog, where I’ll be exploring more about influence zones and real-time personalized engagement.