Adobe has released Predictive Audiences in Adobe Audience Manager to help marketers send personalised messages at scale. The platform leverages AI and machine learning framework to enable new ways for brands to deliver seamless messaging. With Predictive Audiences, brands and marketers can maximise the impact of personalisation initiatives by:
Users are classified into distinct audiences to personalise across channels and devices. By leveraging Adobe Audience Manager’s identity management capabilities, machine learning will match an unknown user’s tendencies in real-time, against an already known audience. It can then predict which persona this user should most likely belong to.
Improving intelligence and personalisation for unknown audiences and users who have limited trait associations. A marketer can leverage Predictive Audiences to classify website visitors into different categories. An advertiser can classify unknown audiences by behavioural attributes, to retarget customers on ad platforms with personalised messages to up conversion rates.
Facilitating the data privacy choices of their customers. Privacy-by-design is a fundamental principle. Predictive Audiences adopts Data Export Controls. This enables marketers to create predictive segments with complete control. In addition to the auto enforcement on the type of data that is collected and exported. The model also classifies only those users who are opted in, based on their preferences.
Design, classify, differentiate, personalisation
Adobe says Predictive Audiences solves for a number of challenges brands are facing today. It achieves this through tailored customisation of each model based on specific needs and use cases. It allows marketers to define specific categories or personas by which they want to group their audience. Machine learning matches an unclassified user’s propensities against existing segments and predicts which persona this user should most likely belong. This is based on the information the user shares. This classification happens in real-time. Coupled with a distinct prediction, to personalise across channels and devices leveraging Adobe Audience Manager’s identity management capabilities.
According to Liron Goren Snai, Product Manager at Adobe, “We’ve seen brands embrace personalisation strategies due to shifting customer needs. What remains stagnant is the challenge around personalisation at scale – delivering tailored, meaningful and relevant messages that customers actually want.”
Multiple brands have already been testing Predictive Audiences in beta, including Sprint. Kevin Day, Martech Manager at Sprint said, “Adobe Audience Manager allows Sprint to better understand the needs of customers when they visit our website. The journey of each customer is very clear allowing us to move quickly and provide a personalised experience.”
Enterprise Times: What this means for business?
In these uncertain times, optimisation and personalisation can be powerful tools. However, delivering customised experiences widely is often a painstaking process for enterprises. This is because customers are interacting with content across an increasing number of channels in a wide range of contexts.
Leveraging artificial intelligence and machine learning technology, Adobe Audience Manager is releasing new ways for brands to deliver personalisation at scale. At the same time, facilitating user choice and control with Predictive Audiences, Adobe says brands can maximise the impact of marketing initiatives by classifying an unknown audience. For instance, people that are visiting a brand’s site but not yet categorised into a segment, into distinct personas, in real-time.
Marketers can classify users into audiences to personalise across channels and devices. The platform can then improve intelligence and personalisation for unknown audiences and users who have limited trait associations. This is the holy grail for marketers. So, Adobe has set the expectations bar high. Only time will tell if Adobe is able to achieve it’s own standards.