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By4 Min Read
August 29, 2023
In part 3 of our series on engagement marketing’s obstacles and opportunities, we talk about dynamic personalization; why it’s essential, and how today’s personalized offers must be built on a solid analytical foundation.
For decades, marketers have understood the need for offer personalization. Thanks to improvements in Artificial Intelligence (AI) and machine learning platforms, the long-delayed dream of delivering personalization at scale is a reality. This ability is essential to deliver the reciprocal marketing required to pursue the path of Intelligent Offers.
We talked about the importance of earned data in our last post, so this begs the question; how can we best actionize that data to improve the value of our customer relationships? In the past, marketers focused on campaign management tools because the data wasn’t at their fingertips. Today, we can leverage the value of earned data to respond with offers that reflect the diversity of customer behavior, thought, and context.
As our market examples indicate, successful brands are becoming increasingly adept at delivering on the promise of dynamic personalization. It isn’t enough, however, just to deliver personalization to improve response rates. It is equally important to motivate customer behavior that optimizes the commercial value of your marketing programs. Done correctly, dynamic personalization is symbiotic: Customers perceive more relevance and value in the relationship, and brands can receive commercial value in the form of increased spend and retention. That’s the virtuous circle enabled by dynamic personalization at scale.
Traditionally, brands have struggled with delivering personalization at scale. Our ability to collect zero- and first-party data has increased, but our ability to derive actionable insight from it has proven a stubborn challenge. How can we leverage that data to deliver relevant offers, incentives, benefits, and experiences?
Today’s consumers expect brands to anticipate their needs. Dynamic personalization is the art and science of delivering offers to customers that reflect those needs in the moment and in the proper context. Your customers demand it—and delivering on this promise is a critical step on the path to Intelligent Offers.
Fortunately, marketers have new tools at their disposal. Today’s marketing platforms offer AI and machine-based learning tools, modular components, and engagement-driven CX to deliver relevance and value in real-time. Marketers can now enhance those “micro-moments” that can deliver increased engagement and profitable behavior.
These platforms increase customer retention by providing an analytical foundation that makes offers meaningful. These powerful analytical tools parse not only earned data from customers but also the components of the offers themselves. These systems learn as they go in order to effectively match the right offer to the right customer in the right context. That’s the power of dynamic personalization—and these tools are available now.
To successfully deliver on the promise of dynamic personalization, focus on these strategies:
Focus on individual customer behavior, not demographics. Deliver offers that reflect diversity of thought, timing, and context.
To keep customers engaged, continue to evolve offers based on what you’ve learned about them.
Show your customers they can trust you by collecting only the data you will use, and by using the data you collect.
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Dynamic personalization is the art and science of delivering