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Become A Data Hero So You Can Prove Your B2B Marketing Worth

Check out AITech's most recent article to learn the fundamentals of creating a data layering effect.

In a recent survey of B2B marketers, we uncovered a group we call Data Heroes, marketers who are using the right data to convert audiences into customers, and they have the analytics to prove it. At every stage of their marketing strategy, they’ve employed data to help them be more precise and more relevant – and to measure their results.

These marketers are getting better results (43% saw significant revenue growth this past year vs 13% of other marketers) and are getting bigger budgets (78% of them!) because of their data-driven approach. The good news is that any marketer can become a data hero, but it does require a commitment to add new data and new processes to get there.

Know Where to Grow

A lot of marketers are stuck in a rut. Without access to data, marketers must take a generalized approach to messaging.

  • They don’t know which companies to target, which products to focus on, or which offers to focus on.
  • They can’t segment out where their wins are coming from, it’s tougher to know what channels and campaign messaging to focus on.
  • Marketers can’t interpret the results they’re getting. They can’t reverse engineer and figure out what success looks like to recreate it and scale it.

There are two common pain points that hold marketers back from becoming data heroes. Marketers want a dashboard that has complete insights about each target prospect and buying group, details about every campaign that was run, who responded to what offer, and the ROI of every campaign but that’s impossible without two things in place.

First, marketers need to focus on building out a complete customer and prospect data set. If there are gaps in prospect and lead information, then it’s impossible to know who to target and why. A lot can be done in-house. Marketers can connect with other parts of the organization to merge customer and prospect data, clean up lead records and identify the elements that are missing so that they can be focused on the type of data they get from partners. For example, adding firmographic and intent data could provide a layer of information that helps marketers time messaging or focus on the right products for a specific buyer.

This exercise can also help marketers get savvier about how they gather leads. The old “more is more” approach can be swapped out for lead generation efforts that deliver fewer leads that have a lot more relevant information so that marketing can be more targeted and more effective.

Second, marketers need to address their measurement gaps. Targeted campaigns that aren’t tracked don’t provide the insights needed to prove that they worked or to make calculated adjustments over time. It’s also important to have an array of metrics to better understand prospect movement through the funnel and how spend is driving ROI. Data heroes don’t just look at clicks – they are much more likely than other marketers to track conversion, lead velocity and sales pipeline generated.

Create a Data Layering Effect

Not surprisingly, data heroes use a much wider variety of data than other marketers. While most marketers rely on a combination of demographic and campaign data, data heroes layer in behavioral, intent, technographic and firmographic data to get a much richer picture of their prospects, what they’re doing and what they’re reacting to.

Luckily, layering in additional data types is relatively simple. Marketers should start with the data they already have and ensure that it’s updated and consolidated in a way that’s accessible across marketing channels. This will require partnerships across the marketing, sales and other teams, but it’s worth the extra work to bring everyone together. Not only do different teams have access to different data, once they see what can be done, they’ll become allies in driving towards better data and measurement.

Here are some basic steps marketers can use to get started:

1. Create a standardized approach to data enrichment. Create a framework where the data will live and how it will be organized so that it’s usable and can be reported on. Then build out a process that happens regularly where data is consolidated and updated.
2. Backfill as much data from owned data. Marketers should think in terms of building a complete data set for analysis. Work with a data provider to fill gaps.
3. Segment the database by intent topics that are correlated to different possible outcomes such as product or service offerings, company industry, company size, company revenue, job titles, etc.
4. Look for patterns and establish a few factors for testing. Experiment and learn.

Grow From A Better Baseline

With a data foundation in place, marketers will be well on their way to becoming a data hero. We found, for example, that data heroes are leaning into intent data, and 66% agree that it drives more pipeline than other data types. They know this because they not only test a variety of data types, they can measure the results.

Marketers looking to add intent data should first build out their data foundation so that they can get the most out of this new and growing data type.

What’s more, data heroes aren’t just shelling out big bucks to buy data, they’re scrappy about enriching what they have by improving their own marketing processes. For example, marketers can grow their own intent data by labeling all of their content by product persona and and funnel position and gain insight by running reports to see what content is resonating with contacts that become opportunities and customers.

Once marketers get used to focusing on data (both customer data and reporting) a positive cycle kicks into gear and they’re well on their way to becoming data heroes.

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Carissa McCall,  Director of Marketing Operations at Anteriad

Carissa McCall, Director of Marketing Operations at Anteriad, is a seasoned professional with a proven track record in optimizing marketing operations for success. Leading a dynamic team, she establishes priorities, allocates resources, and serves as the subject matter expert on marketing operations and automation best practices.

Carissa oversees all facets of marketing automation, the marketing tech stack, and web analytics, ensuring streamlined processes and robust infrastructure. Her strategic prowess extends to critical business processes, including systems integrations, data enrichment, and record flow. She takes ownership of the marketing database strategy, focusing on process, quality, and governance.

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