Mastering Personalization in Digital Marketing Strategy – CMSWire

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 

Here’s an example of a model for that same healthcare company applied to a patient journey:

In this example, the stages represent the different milestones of a pregnant patient from signing up as a new patient, through each of the trimesters and post-delivery. This gives us a concise conceptual model to think through our patient’s needs and present them with offers when they make the most sense and have the highest likelihood for conversion.

These visual models help us discuss and agree on the approach. Once we align on that, next we need to define the best way of selecting an offer.

Related Article: 3 Ways Ecommerce Brands Can Use AI for Personalization

Propensity: Illuminating the Path to Personalized Offer Selection

While the process of decision-making might appear straightforward — selecting the first offer that aligns with predefined conditions — this approach assumes that all offers hold equal value. Yet, the reality is far more nuanced. Not all offers are created equal, and different customers exhibit varying inclinations to convert based on the offers presented to them. The essence of optimizing outcomes lies in delicately balancing these two factors: the inherent value of an offer and its likelihood to lead to conversion for a specific individual. This delicate equilibrium is what we refer to as “Propensity,” a dynamic force driving the art of offer selection.

Assessing All Valid Offers

In lieu of settling for the initial offer that satisfies all conditions, our approach involves assessing all valid offers and assigning them scores based on a composite of their anticipated value and their probability of converting. The pivotal criterion becomes the cumulative score, guiding us toward the offer with the most promising potential to magnify the impact of personalization.

Challenges of Harnessing Propensity

However, the road to harnessing propensity is not without challenges. The crux lies in accurately defining the probability of conversion — a task that often prompts organizations to adopt a more straightforward first-match approach.

Yet, the realm with the most transformative potential lies within machine learning. Driven by comprehensive data analysis, machine learning algorithms hold the promise of crafting predictive models that calculate probabilities with unparalleled precision. The good news is that getting there requires a large data set which can be generated by starting with the “first match” approach.

Related Article: How AI and Data Analytics Drive Personalization Strategies

Implementation Considerations

Having a conceptual model is key to a personalization strategy that you’ll be able to scale over time. Going through this process also uncovers the requirements that a development team will need to understand to turn your model into a working solution. 

Never Really Done

Also keep in mind that you’re never really done with the model. Over time, as you learn more about your customers, add additional offers and conditions, your model will evolve. Creating variations of models and testing them against each other is a great way to ensure continuous improvement.

Implementing Models

As to how to implement these models depends a lot on what tools you’ve already invested in, as well as the other “D’s” of personalization at scale: Data, Design and Distribution. There are plenty of tools that address some if not all the capabilities you will need to be successful. If you don’t have platforms that support your personalization strategy, I recommend taking a “composable” approach to evaluating your needs as described in my last article, “Navigating the Long tail of Composable in the Martech Landscape.”

Final thoughts on Personalization in Digital Marketing

In the world of personalization in digital marketing, strategy is the compass that navigates us through the intricate landscape of customer interactions. By embracing the foundational concepts of stages, offers, and conditions, we not only illuminate the path ahead but also craft a framework for impactful engagement.

This approach transforms personalization in digital marketing from a mere transaction into a meaningful dialogue. Stages delineate the journey, offers create connection, and conditions bring precision to the equation. As we adopt this conceptual framework, we empower ourselves to create experiences that resonate, capturing the essence of personalization in a strategic yet artful manner.

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