We’ve all experienced the magic of marketing personalization - it sure is nice when companies make our lives easier by showing us exactly what we want to see precisely how and when we want to see it. Companies that run personalized marketing programs featuring customized product recommendations, marketing offers, and content suggestions can expect not only a significant conversion jump – around 19% - but also a shorter sales cycle and less churn through improving the efficiency of transactions and the overall customer experience.
While 88% of marketers state that they recognize the importance of personalization, only 6% are actually doing it. This disconnect is largely attributable to a technology gap – marketers can’t effectively reach their customers with the right offer within the narrow window of opportunity when they’re most receptive.
To close this gap, marketing innovators are focused on three game-changing technologies:
Traditional real-time big data analytics technologies typically rely on batch data processing. This means that highly perishable customer data streams in and sits in a repository until an on-demand query is issued. The problem with batch processing lies in data latency – with each passing second that data sits in storage awaiting analysis, the window of opportunity to reach a customer with a timely, valuable and customized offer is closing.
Streaming analytics, by contrast, involves continuously collecting, correlating and analyzing data as it streams in - there is no latency in analysis. This capability empowers marketers to automate offers based on predefined parameters as events are unfolding – when recipients are most receptive - not after the fact.
Real-Time Locational Capabilities
Nearly two thirds of Americans currently own a smartphone, and about 27% of all online transactions are completed on a mobile device. The mass migration to mobile as the primary online device presents the opportunity to use customer locational data to automate offers in real-time. For instance, if a retailer can detect when a customer has physically entered a store location, it can automate an in-store offer issued via text message or email to drive conversion. Or, if a QSR detects that a customer is within a predefined proximity of its drive-thru window, it can issue an automated offer to convince a customer to stop by and make a purchase.
Capturing customers when they’re not only receptive but also proximate skyrockets conversion.
Predictive analytics provides the final piece of the marketing personalization puzzle. When companies can correlate past behavior with real-time activity along with physical location, they can predict what customers will do and need next. How does this work? Here’s an example. A telco provider has identified a usage pattern that indicates that a given customer will turn off data roaming when traveling overseas. If that provider can correlate this pattern with real-time locational data that indicates that the customer is at the airport, it can issue a data roaming offer via text message in real-time before the customer turns off service.
Cutting edge marketing personalization relies on the ability to correlate what a customer has done in the past with what they’re doing and where they are as events unfold. From there, predictive analytics and automated offers take care of the rest.
Photo Credit: Steven Depolo