Marketing is becoming increasingly complex. Audiences, platforms, technologies and channels are in a constant state of change. Customers are expecting relevant, personal communications across multiple devices. Knowing who your customers are, where to target them and with what messages — and backward engineering all these steps to figure out what’s working and what’s not — is a daily challenge.

The main issue here is not only the overwhelming complexity of the system, but the fact that all of its influencing factors are constantly changing. Audience’s interests change, their level of understanding develops and their attitudes and beliefs can fluctuate. They migrate from one digital habitat to another. Their responsiveness waxes and wanes.

Aligning marketing with the realities of data-driven insights means that to stay on top of it all, brands first and foremost need to drill into the details of their customers’ behaviors, on an ongoing basis. They need to identify individual customer segments and adapt content and campaigns to their interests, level of understanding, attitudes, and beliefs.

The good news is, we’re in a new dawn for audience analysis that can help brands reach the holy grail of targeted marketing in the face of constant change.

A new era of audience analysis

There’s a wealth of information behind your customers’ activity; the updates they share, the comments they make, their purchase history — it can all yield extremely useful insights into what your customers think and feel. By analyzing and using this kind of data you can deliver relevant and meaningful campaigns, be confident that you’re creating engaging content and uncover new opportunities along the way.

A great example is Glossier, hailed as the ‘first socially-driven beauty brand’. If you’re a social media user, Glossier are everywhere you look right now. There’s no escaping them. They’ve tapped into — and are targeting —the millennial generation with undeniable success (Forbes, 2018). Using the analysis of social metric data in a highly operative and personal way, they are transforming their product development through incredibly personalized content.

Glossier’s content combines editorial how-to’s with product hero posts that answer specific beauty issues, based on social metrics and customer commentary. This content then generates conversations which further nurture the Glossier community.

Another shining example of data-driven marketing is beauty giant L’Oreal. They turned to Google to garner customer data that they used for a highly customized approach in their L’Oreal Paris Sugar Scrub 2018 campaign.

As a legendary global beauty brand, L’Oreal’s built up a legacy that comes with a loyal customer demographic of women in the 50+ age group. Keeping a generation of women loyal to your brand is no small feat. And L’Oreal realized that they would have to catch the new wave of millennials to nurture the next generation of loyal customers.

How did they do this? They turned data-driven insights into audience segments that would help them effectively target the millennial audience. They created 12 versions of a single video, each version appealing to Google’s identified audience segments. For example, music-lovers received content with the tagline: 99 problems, and your skin is one?

Their rigorous approach to data definitely paid off. They ran the campaign on YouTube using affinity segments, category, keyword and custom affinity targeting. They saw a whopping 144% increase in product interest, a 109% increase in brand interest and a 30% increase in purchase intent.

How can I analyze my audience data?

It’s important to point out that a data-driven marketing strategy isn’t something you can instantly develop overnight. It needs to be implemented and then built up over time.

You need to start from the basics before you can leap straight to the Glossier and L’Oreal type of data-driven campaigns (although they will come).

Identify your target market and target audience

Look at your current customers. Why do they buy from you? What are their common characteristics? What makes them tick?

You’ll need to do this by looking to your social and other data channels on a daily basis, searching for product/service reviews and any other data you’ve collected on past purchasers along the way. Compile a customer list with as much information as you can gather, including demographic, geographical and behavioral information such as personality traits (more on that coming up).

Segment the audience according to demographic and behavioral data

You need to take the data you’ve already gathered, then segment it depending on the different factors that potentially determine buying behavior.

You can approach segmentation using the following factors:

• Demographic information: Such as gender, age, marital status, income, education, and occupation.
• Geographical information: This can be as intricate as you need to go, ranging from town (for local businesses), or large cities (for global businesses).
• Behavioral data: This will delve into spending and consumption habits. Consider questions such as how often do they buy from you? Who else do they buy from?
• Psychographics: Look at components such as lifestyle and personality traits. What do they talk about? What are their hobbies? What is their work/life balance like? What are the desired benefits they seek from your product/service?

The more multi-layered your segmentation is, the more personal and therefore effective your messaging can be.

Analyze each segment

Look at your core audiences and actionable opportunities for each. How can you communicate effectively to each? Is there a different campaign that needs to be created for each segment?

Create personas for your core audiences, identifying their pain points, interests and beliefs. This will help you to decide on the best course of action you can take with your campaigns and content.

Prepare to spend time and deploy resources

Getting to know your customers better than ever before, unlocking new opportunities and creating through-the-roof campaigns is on every marketer’s wish list.

Of course, as with anything innovative and disruptive there are some pitfalls to watch for:

• Data problems: You’re going to run into them. There’s no way around it. There can be a lack of fresh data, too much or too little data, or platform-specific data to contend with.
• Frequency: If you engage in audience analysis once and then forget it, the rest of the world is going to continue changing without your brand along for the ride. Make sure you’re paying attention to the constant stream of insights that will be coming your way and make it a part of your daily routine.
• Resources: On-going audience analysis can be a heavy and complex undertaking that will eat into your resources, particularly if doing it manually.

But the data doesn’t lie (look at L’Oreal’s figures and Glossier’s digital success), and you want it on your side even if that means employing data platforms or putting up more resources towards consistent analysis (not a random flash in the pan every few months).

You need to find your real audience to make your campaigns work. In the words of L’Oreal Paris’ Product Manager, Thijs van der Werff: “dare to trust the data.” It could transform your brand as you know it.