Ayzenberg VP of product and technology Chris Strawser on the challenges marketers face in adopting a data-driven marketing approach.

The pandemic has forced businesses to face radical changes overnight, mandating an even faster launch of digital transformations and marketing efficiencies. Having been in technology for almost 20 years now, I’ve seen a steady progression of brands pursuing what became known as data-driven strategies. In unforeseen circumstances like the pandemic, the need for these strategies is paramount as data helps you navigate with confidence so you can always position your business for growth.

Lockdown has led to a shift to digital channels and the acceleration of digital communications, throwing some brands for a loop—how do I reach my customer where they are now? Which is essentially in their living room, and will continue to be until we return to normalcy. Because prior effective strategies may not be enough to pivot, data-driven marketing is critical. However, some brands may be experiencing challenges in leveraging such an approach, which I’m breaking down here.

Building Underlying Infrastructure

What’s always been a really big challenge to utilizing a data-driven marketing approach is finding the time, the people and the money, as well as getting organizational buy-in, to break down the data silos. Typically, in most organizations, data doesn’t just live in one place; it’s owned by several different stakeholders, many of which don’t necessarily communicate on a consistent basis about how to access each other’s data. This devolves into a very fractured state internally. Many times I’ve consulted with clients who were spending $10 million over just a three-year period in order to get their technical infrastructure in a better spot to warehouse their data more effectively.

Understanding And Making The Data Usable

A problem that I run into consistently is that even if a brand has been taking their data seriously and they’ve had a roadmap in place, they still have to coalesce the data to a point where their marketing strategy can actually use this data. Sometimes that can take a long time. The challenge here is getting the data in a form that’s actually usable. You must merge all your different data sources in a way that allows you to harmonize that data around a particular consumer. You might have a pretty good understanding of their patterns and their behaviors, what they like, what they don’t like, what they tend to do and what they tend not to do. 

To market around what the data is saying to you about consumers on a consistent basis requires the creation of a system, which takes a while to do. For brands that are not using data as much as they would like to, a lot of times actually they really would like to, but they don’t have a system in place to leverage the data that they have floating around somewhere.

Tracking The Consumer

Today there is a proliferation of experiences outside of what a brand can hoist upon the consumer. Where the consumer journey was once linear, COVID has made it so the consumer journey is mainly digital, eliminating several experiences for some brands and verticals that were physical and/or hybrid. These challenges are heightened because all of a sudden now brands feel like they need even more data on the consumer; they want to know more about how they’re experiencing the brand and how they can make their experiences better. And they also want to be more sympathetic to their experiences, with some brands finding that their consumer feedback is, “You guys really need to get your act together.” This is reflective of a much larger trend, which is the evolution from a consumer journey to a consumer constellation that consists of multiple touchpoints.

For example, a small restaurant business won’t survive if all they’ve done to respond to COVID is shift to online ordering but fail to communicate to customers when their order will be ready to be picked up. Data and technology at people’s disposal makes end-to-end easier but you still can’t drop the ball. The technology is only there to facilitate a process that needs human intelligence to be applied to it.