Amplero, a provider of machine learning and adaptive optimization to maximize customer lifetime value and loyalty, today launched the Influencer Optimization capability as part of its Amplero Intelligence Platform (AmpIP).
Through the automatic aggregation of behavioral data, Amplero now makes it possible to map customer influencer ego networks that identify the number, strength, and intensity of connections as well as the influence a customer has over the behaviors and actions of those connections.
"Using Amplero's new Influencer Optimization capability, marketers can now think beyond one-to-one personalized customer interactions and understand the full network impact of their campaigns. Identifying and targeting the most connected influencers and empowering them to spur friends and connections to take the desired action can lead to significant incremental revenue, retention or engagement results for our clients,” said Olly Downs, CEO at Amplero, in a statement.
Amplero Principal Research Software Engineer Matt Danielson partnered with researchers from Columbia Business School and HEC Paris to quantify the ripple effect of marketing campaigns on non-targeted customers in the targeted customer's network. In a randomized field experiment using Amplero to deliver highly contextual messaging and observing the behaviors of nearly 6,000 mobile customers, the researchers found that social connections of targeted customers increased usage and were less likely to churn due to a campaign that was neither targeted at them nor offered them any direct incentives.
"This research has considerable implications for the way marketers think about their customer relationships," Downs said. "While most marketers are focused only on the behavior of specifically-targeted customers in a given campaign, machine learning that takes into account ego networks enables continuously-optimized interactions with the customer that take into account how they interact with one another."