Mastering Personalization in Digital Marketing

Mastering Personalization in Digital Marketing

The Gist

  • Strategic vision. Personalization in digital marketing thrives when there’s a well-defined conceptual model, emphasizing stages, offers and conditions.
  • Decisioning gap. McKinsey’s 4 D’s framework lacks practical guidance on the “Decisioning” aspect, which is pivotal for personalization scalability.
  • Continuous evolution. A personalization strategy is never static; as more data and insights are gathered, the conceptual model must adapt and evolve.

“Begin with the end in mind, with a vision and blueprint of the desired result,” as emphasized in the timeless wisdom of Stephen Covey’s “The 7 Habits of Highly Effective People,” has resonated with me for years.

This principle holds even truer in the realm of personalization in digital marketing. It struck me that organizations often struggle to ignite their personalization initiatives because they lack a means to conceptualize its essence. Absent a strategic framework for personalization in digital marketing, the approach can remain confined to tactical applications, hindering scalability.

McKinsey’s paradigm of the 4 D’s — Data, Decisioning, Design and Distribution — provides a structured approach to personalization at scale. Within this framework, conceptualizing your personalization strategy aligns seamlessly with the “Decisioning” component. Curiously, despite the framework’s comprehensiveness, there remains a notable absence of practical guidance on executing the “Decisioning” aspect. In a subsequent piece, McKinsey lamented the prevalence of “black-box systems” or, worse yet, the absence of decisioning logic, which ultimately fragments the customer experience.

While discussions on decisioning often drift toward the allure of machine learning and AI-based solutions, it’s important to address the foundational essence. True, there’s a place for advanced technologies in decisioning strategy; however, their potency remains incomplete without a sturdy conceptual model. Delving into the intricacies of machine learning can sometimes lead to “hand waving,” as the practical complexity can be overwhelming. My conviction lies in the fact that a robust conceptual model forms the bedrock — a compass guiding effective decisioning.

With this perspective in mind, let’s explore how a solid conceptual model lays the groundwork for successful decisioning to drive your personalization in digital marketing strategies.

The Essence of Conceptual Models in Personalization in Digital Marketing

At the heart of every conceptual model lie three pivotal components that pave the way for effective decision-making in personalization: stages, offers and conditions.

  • Stages: Mapping the Customer Odyssey
    Stages represent the phases of the customer journey, akin to chapters in a captivating novel. Each stage encapsulates a distinct moment in the customer’s interaction with your brand. Whether mirroring stages of awareness, consideration, conversion, or even tailored to customer personas, stages provide the canvas upon which personalized experiences are artfully woven.
  • Offers: Personalization in Action
    Within each stage, offers take center stage as personalized touchpoints. These touchpoints encompass tailored content, recommendations or interactions that resonate with individual needs. Offers transform generic interactions into personal dialogues, inviting customers to explore, engage and connect on a deeper level.
  • Conditions: The Guiding Compass
    Conditions, the guiding principles of personalization, steer the journey from stage to offer. Think of them as the intricate rules that govern which offers are presented to which customers. Conditions consider a multitude of factors, including customer attributes, behaviors, purchase history, and context, ensuring that the right offer reaches the right customer at the right time.

Related Article: 5 AI Analytics Trends for CX Personalization

Visualizing the Personalization Model

To get this conceptual model correct, we need to be able to visualize it. Just like we wouldn’t build a house without a blueprint, we need a blueprint to visualize our personalization strategy. This helps us to discuss the strategy, agree on the offers and conditions and define the requirements that our developers will need to implement a decision-making approach.

Here is an example of a model for an online retailer:

online retailer

Across the top, our stages are defined as the typical stages of a customer journey: Awareness, Consideration, Purchase, Service and Loyalty. Within each stage are potential offers. Each offer would have associated content that can be used to drive personalization but defining that content is not necessary for defining the model, so is not depicted.

Conditions as Positive Statements

I’ve found it helpful to define all conditions as positive statements. Things that should evaluate to true. This avoids confusion or duplication. Instead, I apply the conditions to offers as either “Requirements” — it must be true; or “Restrictions” — it must be false. In the model above, we have an offer defined in the “Purchase” stage to “Share on Social.” It has a requirement that we wouldn’t use that offer unless they have recently completed a purchase. Similarly, in the “Service” stage we have a “Sign Up for a Credit Card” Offer with a restriction that ensures they don’t already have a credit card.

What Personalization Looks Like

These concepts give us the language needed to discuss what a personalization in digtial marketing model can look like. This is not limited to Journey based approaches, but any organization of offers that helps us discuss our strategy. Here is an example of a model for a healthcare company based on the Persona of a patient.

patient persona

Instead of Journey Stages, we have personas across the top, with collections of offers that are applicable to each persona. 

It’s important to note that the goal is not to create one model to rule them all. Having multiple models that are applied in different contexts and maybe even different channels can be highly effective.

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