Signals, a new product launched by Epsilon as a part of Epsilon people Cloud Prospect, enables marketers to optimize audience and personalization across channels. It identifies near real-time consumer buying signals with back-end data science and modelling.
The product enhances a brand’s first-party data with Epsilon’s proprietary data. It yields insights like that of a consumer’s probability to be in the market for purchasing a product or source.
The President of Technology at Epsilon, Wayne Townsend said: “Signal strikes the right balance of predictive capabilities, ease of use and flexible activation for marketers who have been frustrated by siloed campaigns and fragmented personalization.” He further added, “The closed nature of most predictive audiences can cost brands millions in missed revenue and wasted marketing spend. Signals are designed to even the playing field and give control back to marketers, without the burden of building extensive AI and data science capabilities in-house. It’s something marketers appreciate, especially as they are navigating a path forward in a cookie-less world.”
Signals consist of three packages:
Custom: utilises Epilson’s machine learning models for optimisation towards an outcome.
Configurable: Triggers based on rules to leverage open web browsing and a client’s first-party data.
Pre-defined audience: Availing curated attributes which enable the organisation of users by life stage, interests and propensities.
Signals prove to raise customer lifetime value as it improves the effectiveness of up-sell and cross-sells campaigns. The first-party data of a client is enhanced with proprietary data. Following this, Epsilon then makes use of the machine learning to be able to deliver an audience that is up-to-date and optimized for specific KPIs and outcomes as per the client.