The Beginner's Guide to a Data-Driven Content Marketing Strategy

Angela Crimmin    By under Content Marketing.

This article below is an editorial written by Molly Clarke, Senior Marketing Manager at Zoominfo, a leading B2B contact database that helps companies accelerate growth and profitability. Molly writes for ZoomInfo's B2B blog on topics related to sales, marketing, and recruiting.

A typical content marketing strategy involves the creation and distribution of content with the sole purpose of attracting prospects to convert into paying customers.

Although simple in theory, content marketing is a lot easier said than done. In fact, 93% of marketers use content marketing as part of their overall strategy, but only 30% report that these efforts are effective. So, what's the deal? Why do so many marketers fail to achieve results with content marketing?

Here's our take: In a world where consumers are constantly connected to an endless supply of content, it takes truly remarkable, relevant, and personalized marketing materials to stand out from the crowd. Although it's difficult to create that caliber of content, those who get it right see impressive results. Consider these statistics:

So, what's the key to content marketing success? Enter, data-driven content marketing.

What is a Data-Driven Content Strategy?

Data-driven content marketing is exactly what it sounds like: The process of using customer data to inform and evolve your content strategy. This approach eliminates the guesswork from content marketing. It allows you to understand your customer on a deeper level and serve them content that will truly resonate with their interests, pain points, and buying preferences.
Today we teach you how to master the art of data-driven content marketing to generate more business for your organization. Ready to get started? Keep reading.

How do I execute a data-driven content strategy?

Although there are many ways to approach this type of strategy, we've discovered that the most successful workflow contains three critical steps. Let's get into it.

Step One: Collect and analyze your data.

Before you can use data to inform your content strategy, you must first collect and organize your data in a way that allows you to recognize important trends and commonalities. Here are a few key types of data to consider:

Customer and prospect data:

This data tells you exactly who your customers and prospects are. Where do they live? How old are they? What technologies do they use? What are their job titles? Do they work in a specific industry? What are their buying preferences? Your corporate contact database contains this information and is typically housed in your CRM or marketing automation platform.

Behavioral data:

This type of data gives you deeper insight into how your best buyers behave on your website, with your content, and throughout the sales cycle. To get started, ask yourself: What content format do they engage with most? Do they engage with a particular subject matter more than others? What channels did they use to first engage with your company or brand? How many pieces of content did they engage with before making a purchase?

Behavioral data is a little more difficult to nail down and can live in many different places and formats. Depending on your specific company, these details can be found in your CRM, your marketing automation platform, Google analytics, or any user experience software you use.

Content and platform analytics:

This type of data shows you what kind of content performs best with your audience. Which blog post has the most page views? Which whitepaper has the most social media shares? Do you have a specific campaign that generated the most leads? This information is necessary to complete the full picture of your prospects and customers.

Once you've compiled your data, it's time to analyze it. The purpose of this step is to identify common traits and characteristics among your best customers. Eventually, you'll use this information to create buyer personas--or semi-fictional profiles that represent your ideal customer.

A sample buyer persona might look something like this: A 35-45-year-old male, working in finance at a company of 1000+ employees, who has 'manager' in his job title. A more complex buyer persona will include everything from personality traits to favorite social networking sites.

Step Two: Apply Insights to Your Content Marketing Strategy

Once you've gathered your data, analyzed it, and made important connections between your best buyers, it's time to apply this information to your content strategy.

As previously mentioned, a truly data-driven approach to content marketing requires all decisions to be supported by data. Because this is a very broad definition, here are a few specific ways to apply your data to your content process:

Content audit:

Perform a content audit to assess the effectiveness of your existing content library. Compare each piece of content with your buyer personas and ask yourself the following questions: Was this piece created with my ideal customer in mind? Does this piece use language, graphics, or statistics that my audience will understand and find interesting? How will this piece move my buyers further into the sales funnel? Does this piece mirror my buyer's preferences?

Don't be afraid to trash anything that doesn't speak to your audience's core interests. Make an effort to refresh anything that's out of date, thin, or lacking, and recycle any content that's proven to be effective in the past. The goal is to end up with a body of content that will resonate with your potential buyers.

Content creation:

Data is key when it comes to creating new content. Just take a look at a data-drivenĀ piece like this from ABODO; they used rental data to tell a story for their audience. Your data tells you what to create, how to create it, where to publish it, and so much more. Your data can also help you uncover gaps in your content library, new content opportunities, and ways to generate more leads.

Keep reading, we talk about this more in the example below.

Content mapping:

Content mapping is the process of strategically aligning your content to your buyer's journey. When you map your content correctly, you can serve exactly the right content, to exactly the right people, at exactly the right time. The key to this, however, is to know what the right content is and who the right people are. You can't do this without data.

Using the information gathered during the data analysis phase of this process, you can pinpoint who your best buyers are, how they behave during each phase of the buyer's cycle, and what types of content will increase their chances of making a purchase.

Content distribution: Once you've created your content and mapped it to the buyer's journey, you'll have a pretty good idea of when and how to distribute it. Use your data to determine where your best customers spend time online. Do most of your qualified leads come from LinkedIn? Or does a certain type of customer spend a lot of time on review sites?

Use this information to decide what channels to use, how frequently to use them, and to determine which types of content perform best on each channel.

Step Three: Assess campaign results and continue to calibrate your content strategy.

Content marketing, particularly data-driven content marketing, is not a one-and-done activity. Even after you analyze your data and apply it to your marketing efforts--you're never, truly done.

After a campaign has been deployed, it's important to take the time to analyze any new information you receive. Did your content perform how you expected it to? Or, did you misinterpret some of your data? If a piece of content doesn't perform it's critical that you figure out why. Then, make the appropriate adjustments for your next campaign. This is the only way to improve your marketing efforts.

You must also consider data decay--as people change jobs, companies come under new ownership, and buying trends evolve, your data will become obsolete. For this reason, you must prioritize database hygiene and revisit your buyer personas constantly.

Data-Driven Content Marketing Example

We thought we'd finish up this article by providing you with a real-world example of data-driven content marketing. This example involves a fictional company called HR101 that sells a payroll solution called Payroll101.
HR101 follows the initial steps of this blog post--they collect their data, they form buyer personas, and they start to integrate their newfound insights into their campaigns. As they do this, they realize the majority of their organic search traffic comes from a single, long-tail search query, "examples of payroll workflows."

After some more investigating, HR101 finds that this search query leads to an old blog post of theirs. The post, though related to the search query, was out of date and poorly written. Based on analysis of behavioral and customer data, they knew the post used language that was too technical for their average customer. As a result, the bounce rate on this page was astronomical.

Seeing this, HR101 decides to turn the post into a more comprehensive guide using language and ideas that were more likely to resonate with their target audience. But that's not all--the company knew, based on analysis of other blog posts, that visitors were more likely to stick around if they were served related content towards the ends of their articles. Because of this, HR101 added a visually compelling CTA to the bottom of their new blog post to promote an eBook titled, "5 Effective Payroll Workflows Using Payroll101."

Making these data-driven changes drastically increased time-on-page and reduced bounce rates. But, even more importantly, 50% of all traffic to the page went on to submit a form to download the related eBook--thus generating more leads for the company. After seeing this success, HR101 implemented similar changes to the rest of their blog posts and, as a result, the company saw a dramatic uptick in free trials, demos, email subscribers, and more.

Key Takeaways

If we haven't already made it clear, we're going to say it one more time: One-size-fits-all marketing is a thing of the past. Your customers and prospects demand more relevant, personalized, and useful content. If you can't deliver that, someone else will, and ultimately someone else will earn their business.

With data, however, you can't go wrong. In fact, 64% of marketing executives strongly agree that data-driven marketing is crucial to success in a hypercompetitive global economy. So, what're you waiting for? Start leveraging the power of data today.