Why Brands Need Data-Driven Personalization to Be Customer Obsessed


According to Forrester research, 61% of consumers said they are “unlikely to return to a website that does not provide a satisfactory customer experience.” This puts unprecedented pressure on brands to know what consumers want and be able to deliver on those desires in effective ways, and in real time.

One way many brands have dealt with this growing pressure is by putting more focus on the customer. “Customer obsession” has been a buzzword for some time now, most likely because brands have realized that the only way to truly captivate consumers is by delivering the most relevant experiences based on their individual preferences and behaviors.

But while it’s easy for brands to claim they’re customer obsessed, it’s difficult to actually be. The only way to be objectively obsessed with your customers is by knowing what your customers want, as well as when and where they want it. The key to “customer obsession” is data.

In order to be customer obsessed in 2018, organizations have to lead with data

Over the last two decades or so, organizations have begun using customer data in an attempt to personalize their marketing efforts, mostly via segmentation. And personalization remains a key priority for businesses to this day. According to Forrester, 89% of all digital pros are prioritizing investment for personalizing the customer experience.

Personalization has historically been driven by segmentation, which is the process of dividing your entire customer and prospect database into different groups based on data points such as age, gender, location, and past purchase history. For decades, marketing organizations have relied on broad-based segmentation to check the box on delivering “personal” experiences.

Today’s digital leaders must prepare for the next evolution of personalization, which will rely more on individualization rather than segmentation. Individualization is a strategy that uses machine learning, a subset of artificial intelligence (AI), to predictively personalize the content experience based on user behavior, context and lookalike analysis. Individualization is the pinnacle of customer obsession because it enables content delivery on a 1:1 basis for each individual. Through individualization, you can generate unique content experiences for individual members of your audience to repeatedly engage them across channels.

4 characteristics of a data-driven individualization strategy

A solid individualization strategy that’s based on customer obsession can only be built with customer data that spans the realm of customer behavior and activity. We’ve found that a data-driven individualization strategy is built upon four unique characteristics:

  1. Data-rich customer profiles: A data-driven individualization strategy enables customers to be identified and treated as individuals using rich customer profiles. Brands acquire customer information to build such rich profiles by offering content and experiences of value in exchange for valuable data.
  2. Real-time data analysis: A data-driven individualization strategy enables customer data to be assessed in real time and dynamically calculates customer intent. Every time a customer takes an action, a data point is stored in their customer profile. Sophisticated individualization technology learns from that action to fine tune the customer experience.
  3. Omnichannel content experiences: A data-driven individualization strategy enables personalized content to be delivered equally across every screen and channel.
  4. Connected technologies: A data-driven individualization strategy utilizes connected technologies to enable far richer and more relevant engagements.

Today’s consumers demand individualized experiences across every touchpoint, and content is playing an increasingly crucial role in how brands and publishers deliver on that experience. But the strategy becomes challenging when you mistake individualization with traditional, segmentation-based approaches. Watch our on-demand webinar to learn how personalization has evolved into individualization and how to get started.


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