Enabling Effective Personalization with Just a Few Attributes

BrandPost By Aaron Goldberg
May 20, 2020
IT Leadership

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Credit: iStock

When it comes to brand interaction, the pandemic has given rise to new needs and demands for customers and prospects. Fundamental changes have brought more nuance, specificity, and urgency to many of these interactions. The result is a high level of expectation for personalization. Both customers and prospects want to be seen as individuals with unique needs. This is driving brands to double down on personalization.

However, personalization at scale is still difficult for many brands. Their legacy systems often require too much manual intervention or can only do it for one channel or mode of interaction. Solving the problem requires a new generation of digital tools that have been designed to support personalization at scale and utilize new technology components that make that possible.

Adobe is taking a leadership position in solving this problem, allowing brands to deliver personalization at scale by enhancing the capabilities of Adobe Audience Manager with artificial intelligence (AI) and machine learning (ML). Predictive Audiences is a new capability that brands can use to deliver personalization with just a few trait associations (for example, it can turn site visitors into distinct personas in real time, even if those visitors are not yet categorized into a segment) to maximize the impact of marketing initiatives. Marketers can now classify visitors into distinct audiences to improve personalization across channels and devices. It is also possible to deliver a higher level of personalization for unknown audiences and visitors.

Predictive Audiences delivers the answer to key questions brands are facing. Brands can focus more on optimal customers by defining specific categories or personas that they want and focus on those prospects. Predictive Audiences uses machine learning to match an unknown user’s propensities against an already known audience, enabling the brand to instantly predict which persona best fits this user. And that enables the brand to immediately personalize the customer journey across channels and devices leveraging Adobe Audience Manager’s identity management capabilities.

It’s an intelligent solution that supports compelling use cases. For example, an advertiser can classify unknown audiences by behavioral attributes, or retarget customers on ad platforms with personalized messages that will increase conversion rates. Predictive Audiences can also support offer personalization based on where a specific prospect is in the customer journey.

Predictive Audiences has been available in beta, and the results have been impressive. In the last few years, Sprint/T-Mobile has been undertaking a game-breaking digital transformation project with a strong emphasis on personalization. This new solution has really delivered for that brand.

Kevin Day, martech manager at Sprint, sums up the benefits for their team: “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 personalized experience.”

Personalization will be an important means of creating competitive differentiation and advantage. Predictive Audiences enables a broader use of personalization for visitors about whom less is known. Using AI and ML allows a brand to personalize at scale and in real time, and that’s central to a successful effort. Putting this technology into broad use supports a brand’s ability to meet the new personalization demands of audiences and individuals.