Content Marketing Analytics and Attribution for B2B Enterprises

Content marketing is no longer an emerging trend, but is arguably the most important facet of a digital marketing strategy for any business, particularly those in a business-to-business sector. The B2B Content Marketing 2015: Benchmarks, Budgets, and Trends — North America, produced by the Content Marketing Institute, notes that 83% of businesses surveyed have a content marketing strategy and that 70% of respondents report that they have produced “more”, or “significantly more” content over the last 12 months than they did over the preceding period.

As far back as 2012, a Corporate Executive Board study of nearly 1,500 business-to-business customers found that, “On average, nearly 60% of a typical purchasing decision—researching solutions, ranking options, setting requirements, benchmarking pricing, and so on—before even having a conversation with a supplier”. Rather than contacting a supplier, doing a needs analysis, and relying on a sales specialist to identify and recommend a solution, today’s B2B buyer prefers to make much of their decision-making independently using online research.

Understanding Content Marketing Analytics & Attribution

Using analytics tools, today’s marketers have the ability to glean insights into the customer journey, and better understand how exactly a new customer goes from the initial discovery process to ultimately making the decision to buy. There are now many potential touch points between buyer and seller along the way, ranging from paid search ads to social media, infographics, articles discovered via organic search, email marketing, and more. In this environment, defining proper “attribution” becomes difficult. However, taking the time to properly understand “how, where and in what stage prospects are engaging with specific types of content” ultimately can help reduce the length of the sales cycle and increase conversion.

Common Attribution Models

When thinking about how to properly set up attribution, businesses need to identify which portions of the customer journey hold the most importance with respect to generating a sale. With that in mind, below are 3 basic, but common attribution models, along with an overview of how and why they might be used:

  • Last Interaction: Attributing the source of the most recent click that resulted in a completed goal (online sale, completed form, etc.) is very common. For example, using this method, if a site visitor first discovered a vendor through a paid search click, took notes, then returned to the site via a direct click several days later and made a purchase, the sale would be attributed as “direct traffic.” This method makes the most sense for products and services with a very short sales cycle where purchasing decisions are made very quickly.
  • First Interaction: Attributing the conversion to the source of the original click is another used form of attribution. In this model, all credit is assigned to the channel that generated the initial visit to the website. For brands with little awareness who place a premium on initial exposure to new prospective customers, this model makes sense.
  • Position-Based: For many marketers, particularly those in a B2B industry, the ability to give partial credit to the multiple touch points throughout the sales cycle makes the most sense. Rather than giving all credit to the 1st or last interaction, credit can be assigned based on a percentage model to different points along the way. A common attribution scenario suggested by Google Analytics would be to “assign 40% credit each to the first interaction and last interaction, and assign 20% credit to the interactions in the middle.”

With customers doing an increasing volume of sales research and decision making online, and independently of sales representatives, content marketing is more important than ever, as is an understanding of how to appropriately measure the analytics and ROI associated with content marketing efforts.

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Written by:
Andrew Armstrong is a technology enthusiast, business owner, and digital marketing strategist based in the San Francisco Bay Area. A graduate of UC Berkeley in 2003, Andrew enjoys Cal Football games, experimenting with new technology, and chasing around his toddler son with his wife.
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