Reaching potential customers through advertising has long depended on the use of demographic data. Classic segmentation.

Location. Age. Ethnicity. Gender. Marital status. Income. Education. Employment.

However, as the possibility of hyper-customization grows, many consider this approach to be outdated.  Instead, they focus on factors like interests, values, mindsets, and personal stories.

Cadillac’s Global CMO, Melissa Grady Dias, is among this group of innovators. In her interview with Ben Kaplan for TOP CMO, she explains how she uses regression modeling to find likely prospects.

So how exactly does it work? What results does it yield? How can its insights help you understand your potential buyers? Keep reading to learn all about it!

Regression modeling

In simple terms, regression modeling can analyze how factors like interests and values may influence the likelihood of someone buying a product.

Marketing agencies can provide you with information on people’s preferences and consumption trends, for example.

This type of study allows you to go beyond broad categories and focus on more specific patterns.

What two 25-year-olds from Los Angeles buy is probably harder to predict than what two Metallica-loving SaaS entrepreneurs do.

Regression helps you compare, combine, and test data to identify the most likely prospects. More clarity. More precision.

Listening to the data

By letting data speak to you and following its trail of crumbs, you can build customer profiles with higher chances of conversion.

These insights not only reveal the ideal target audience but also provide a deeper understanding of what motivates them.

You can integrate them into segmentation, product design, and brand development.

While correlation does not imply causation, you can leverage your discoveries to create messages, products, and services that truly resonate.

An ad that highlights your findings. A message tailored to your target audience. An experience aligned with its interests.

Innovation and progress

Data is also valuable when you’re venturing into new territories.

As you develop new features that may not be suited for your pre-existing audience, using this method eases the launch.

Innovation can feel too risky, especially if your original product is well-established with a formula you know works. 

It becomes essential to find any type of certainty. While success is not guaranteed, data-driven progress feels safer, guiding businesses toward the right design and effective segmentation.

Building the model

No system is perfect.

However, your insights will become more refined over time. You will be able to carefully evaluate your variables and characteristics, and their combinations.

Everything should be geared towards a true understanding of your customer base and potential buyers.

Data and numbers shouldn’t be your sole source of information, but letting them speak to you may inspire you to approach the challenge in ways you otherwise wouldn’t have thought of.

Cadillac’s Global CMO, Melissa Grady Dias, considers this approach as the secret to their renaissance. And they’re not doing too bad at all.

Take your time, stop and listen. Data can become a powerful weapon to differentiate yourself in a sea of companies.

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