Building a Better Mousetrap for B2B Content Marketing

B2B marketers must shift their mindset to ensure that originally produced content aligns with both customer needs and company goals and objectives


Article adapted from Association of National Advertisers


The theory that compelling content alone is enough for B2B marketers to achieve their business objectives is evaporating fast. According to research conducted by the content strategy firm Buzzsumo, companies that haven’t changed their approach to content during the past three years are 50 percent less effective in reaching their audiences and meeting their business objectives. But it’s not for lack of investment. According to the “B2B Content Marketing Report,” produced by the Content Marketing Institute and MarketingProfs, nearly 60 percent of marketers reported spending more on content creation in 2018 than in 2017.


There are myriad reasons the traditional content-focused approach to content marketing isn’t having the desired impact. One major factor: B2B marketers all too often produce videos and write blogs and e-books that the C-suite wants, even when there’s little discernible connection to the company’s strategic imperatives or objectives.

When content marketing strategy is based on whim, it should come as no surprise to brand managers that the way B2B content is measured and quantified will also have little to do with tangible business metrics and outcomes.

“Marketing leaders have historically lacked knowledge about content marketing, leading to a gap in attributing content campaign performance to bottom-line metrics,” says Jon Chang, a global product marketer at IBM Watson Marketing. “This is especially problematic when attempting to measure the ROI of content that requires sizable budgets to create, such as videos, e-books, and podcasts.”

Content Marketing Fueled by Data and Research

None of this is to say that B2B content marketing can’t be an effective way to drive legitimate business benefits. But there is clearly a need to rethink the approach to ensure that the content produced is better aligned with both customer needs and company objectives.

Improved use of data is a critical ingredient to this approach. Stefana Rusu, VP of marketing at Acxiom, which provides data to help marketers, argues that research revealing the “voice of the customer” improves the relevance of content.

“A good way of doing this is using direct qualitative and quantitative research to fuel your content development,” Rusu says. “This ensures topics are laser-focused on the key challenges your customers are facing and how they prioritize them. Focusing on client needs first always drives the top line and bottom line of the business.”

So how does that work in the day-to-day operation? For Acxiom, qualitative approaches can be interviews and focus groups, such as win-loss reviews, buyer journey interviews, and user group feedback sessions. “Qualitative approaches are used to gain an understanding of underlying reasons, perspectives, and motivations related to a challenge or problem,” Rusu adds.

Besides providing insights about the challenges customers incur, qualitative research can also inform quantitative research that gathers numbers and statistics that reveal what customers are experiencing and thinking about. “For example, what percent of your customers may be experiencing certain data-driven challenges or investing in particular services and technologies,” Rusu says. “This type of research is great to fuel not only bite‑sized content such as infographics, but also longer-form pieces such as e-books and briefs.”


Tag, Measure, Repeat

While important, a data-driven approach to formulating a content marketing strategy and specific pieces of content is just one component of a more sophisticated methodology for successful content marketing. It’s also critical to define two things: what marketers want each piece of content to achieve — it’s rare that content will have just one objective — and the KPIs to measure how it performs. For instance, is the purpose of producing and distributing original content to drive leads? Is it meant to lower costs by providing self‑service information that customers can access without calling a customer service representative? Whatever the goal or goals for blogs, e-books, and white papers, there must be a commitment to measuring how well they achieve those goals.

While part of effective measurement requires knowing precisely what needs to be measured, another is having the tools to actually do it. IBM Watson Marketing’s Chang says that inaccurately tagging content (or not doing it at all) can “break the entire measurement and attribution system.” 

Chang stresses that often happens because the writers, designers, and other content producers tasked with tagging content don’t have the tools, skills, or time to do it properly. “Content tagging is foundational to achieve accurate attribution of content to the bottom line,” he says. “However, tagging content can take months if the asset library contains hundreds of thousands of images, videos, and documents. For example, writing six tags for each piece of content might take 30 seconds. Multiplied by 200,000, tagging an entire library would take 1,666 hours.”

As an alternative, Chang suggests combining the use of artificial intelligence (AI) to automate tagging and deploying a central content management system to ensure that the right content is delivered to the right audience. IBM Watson uses this approach to manage its own customer community, a private online group and resource platform for existing customers. Chang says the purpose of the content is to drive very specific business goals and that IBM measures how each piece of content fares. “Quality community content marketing can increase critical business objectives, like net promoter score (NPS) and customer retention,” he says. “To make sure the right content is delivered to the right customer, the team uses the content management system IBM Watson Content Hub. It not only provides valuable data, such as the performance of individual pieces of content, but also uses AI to appropriately tag content as the customer’s behavior evolves.”

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Article credit:  Chris Warren

Image credit:  Tang Yau Hoong/Getty Images





Alex Howard

Alex Howard

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