Building a Strong Marketing Data Strategy

Posted on by Curtis Thornhill & Elizabeth Dobbin

Editor’s Note: Hear more on data and analytics from Curtis Thornhill at B2B LeadsCon, Aug. 22-24 in New York.

 

Geometric shapes on a wooden background.Any way you slice it, data expectations, are, well, big. And for good reason.

Effectively using data requires a building-block structure to know how, why and what to do with it. Companies are spending billions on tools and talent to compile and mine data—hoping to intelligently discern customer needs and make strategic decisions—and that will be marketing’s sweet spot for years to come.

Most companies know they have to collect data and having a strong data strategy. But deriving usable marketing insights from that precious information bedevils them.

Knowing the best way to classify and build a structure to successfully use data in marketing is essential. Where do you begin?

Keep It Clean

First things firstwe need clean data. It’s our foundation. With clean, quality and accessible data, most businesses are ready to begin a structured approach to pull marketing insights from their data. For now, let’s assume the data is clean, of high quality and accessible for marketing purposes.

Now we’re ready to look closer at a structured approach to extracting marketing insights from data. Our methodology segments into three strategic and ascending levels above our data hygiene foundation.

Campaign Strategy: Reports and insights

The first level is reporting and insights for campaigns to drive new strategies to reach out to customers. At this point, we are able to power segmentation of customers because we know enough about actions to see trends and enhance campaign and program performance. This level of visibility eases the way for programmatic approaches to marketing and creating lifecycle programs.

Consider this: Often the most accessible of data’s building blocks—custom reports and tools—are available within the systems that execute your marketing functions. Use data to segment and define populations for audience targeting, and campaign or program KPI’s. Through data you can effectively measure campaign performance and understand why a particular campaign won (or lost) to drive insights and future strategies.  

Functional Strategy: Communication

Think of this second level as the modes of communication with your customer. It’s where marketers can envision what’s next—modeling performance by channel, assessing penetration of customer segments, fixing leaks in a sales funnel, or understanding the customer’s communication preferences.

Consider this: Pooling data from multiple locations is required for marketers who have reached this stage of performance management. Whether it’s a custom solution or an import of data into your CRM, structure is the most important key to unlock these insights. Be certain that all marketing channels use a common standard to define key campaign attributes such as channel, date, recipient, or outcomes so that you’re a step ahead in gathering insights.

Business Strategy: Management

At the top of the structure, we begin to formulate the business value proposition and management philosophy—tackling broad questions about the performance of the business and what’s required to change those trends. Here we identify new audiences or customer targets, understand the costs and needs to continue to fuel growth, and provide insights into other business areas.

Consider this: The difficulty most marketers face when trying to answer business questions is the rapid change of your organization’s data insight needs. Here, a flexible, open and repeatable approach to accessing data is required. Most critical is the ability to structure your data in a way that can answer the question, “What’s happened over time?” Without a historical perspective of cycles of business such as purchases, changes in subscription, or ongoing activity it’s likely you’ll be unable to meaningfully predict what’s next to come.

Of course, few marketers work in an environment with perfect insight or access to data that satisfies all of these needs. Fortunately, there are creative workarounds should you need them:

  • Infer-actions: For many businesses it’s possible to use ‘inference-of-actions’ as a proxy for the outcomes you expect after a marketing campaign. By looking for macro effects (such as sales, traffic, or subscribers) after an investment in a campaign, you’ll be able to understand what’s driving engagement.

This approach requires a heavy investment of marketing capacity to be effective. With this method, the marketing exposure needed to understand if key metrics are being influenced will increase in proportion to the size of your business. An internal culture of testing and learning is also needed to help you discern what’s next and best while accepting that results may not always come back as planned.

  • Strategic mapping: Actively engage in mapping out what is and isn’t possible using the steps outlined above. This often leads to uncovering opportunities and establishing relationships that will fuel the development of enhanced marketing programs. It’s a bullets-not-cannonballs approach to building internal rigor around the use of data in marketing and uncovering initial opportunities that you’ll be able to take with the data you have available today.

Elizabeth Dobbin is senior director of relationship marketing at Eventbrite. Curtis Thornhill is CEO of Apt Marketing Solutions. 

Hear Curtis Thornhill and John Fernandez, director, analytics & operations at Diligent Corp. present “A is for Analytics: It All Begins With Data” at B2B LeadsCon, Aug. 22-24 in New York.

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