Editor’s note: Today’s post is from Liz O’Neill from Kapost. Couple reasons I asked a Kapost writer to write again for the Funnelholic. First, the earlier post on managing an editorial calendar was awesome and got fantastic traffic. Secondly, they announced content scoring and I think it’s an exciting breakthrough in content marketing. Oh and they have great writers. Liz is one of those great writers as you can tell by this thorough and well-written post. Enjoy.

There’s no denying the imperative role content plays in propelling buyers down the funnel. 93% of B2B marketers use content marketing and 78% of CMOs think it’s the future of the industry.

Marketers are expected to publish content that results in a constant stream of valuable leads. While innovations like lead scoring offer insight into whether marketers are hitting lead gen goals, understanding exactly why they are — and what content influenced those leads — has involved a lot of “educated guessing.” Until now.

Content scoring is a process that reveals exactly how many leads and opportunities a piece of content generates. Unlike pageviews, uniques and shares, content score applies an actual numerical value (a “content score”) to the content an organization produces based on how leads, opportunities or closed deals interacted with that content.

The result is valuable insight into the true ROI of content, enabling marketers to make informed decisions about which content assets to produce.

How Content Scoring Works

So, how does content scoring work exactly? Put simply, it works backwards from a buyer’s journey to specified conversion stage, highlighting the content that buyer digested along the way.

Let’s explore by taking a look at the journeys of two marketing qualified leads (MQLs).

Our first MQL consumed or “touched” 6 pieces of content before becoming a lead.  These six content pieces are all scored since they influenced the buyer’s path to conversion. Since we’re working with a single journey here, we’ll calculate these scores out of a grand total of 1.

If we assume all of the assets had equal influence on this MQL, we would divide the one lead by the 6 pieces of content he or she interacted with. Each piece of content would each receive the same content score of ⅙ or 0.16.

But marketers often prefer to use a different attribution model, prescribing a higher value to first and last touch content since the first interaction is what brought the buyer in and the last interaction induced him/her to convert. Exactly how you weight these touches is up to the organization. In this model, we’ll attribute 45% of the MQL’s total value to the first and last touch, spreading the remaining 10% across the remaining assets in the journey. That scenario would result in the content scores listed in the following table:

Our second prospect touched only four pieces of content before becoming an MQL.  Again, because we’re only looking at one journey, we’ll calculate all of the content assets in that journey out of 1.

Because the infographic and the email were the first and last pieces of content this MQL consumed, we’re going to attribute a greater weight — 0.45 each — to them and divide the remaining 0.1 by the two remaining pieces of content, the blog post and the video, resulting in the following content scores:

Total Content Score

Now that we’ve calculated the impact of the content assets for each of our MQLs, we can calculate the total content score across both buyer journeys by simply adding up the scores of each asset:

Since we’re looking at two MQLs, the total content score across all assets would equal 2. The content scores above represent the number of leads each piece of content generated.

Scoring Content At Scale

While calculating content score for two buyer journeys is pretty easy, doing the same thing across hundreds or thousands of MQLs would be time-consuming and slow.  So at Kapost, we automated this process so customers can pull content scores across all of their assets easily. We do it by pulling the buyer journey data captured within their marketing automation solution (currently Eloqua and Marketo) and their CRM solution (currently Salesforce.com). Customers can see content scores by the stages they set within their marketing and sales pipeline. Here are three of my favorite product features:

1. Scoring Flexibility

Care more about opportunities than MQLs?  Users can score content on opportunities, closed wins, prospects and more.

2. Filtering Options

With content scoring, users have visibility not only into what content is driving the most conversions, but also into which content types, campaigns and even contributors are driving the most conversions.  If you’re only interested in what blog posts drove conversions last quarter, for example, you can collect that data in seconds.

3. Export Function

The export function allows users to slice and dice their content scoring data within any time frame they choose. They can build graphs or generate reports based on that exported data that track the goals most important to their organization.

Content scoring is a game changer for marketers. It reaches beyond the “vanity” metrics that are often used to measure content marketing success, but provide little insight into what is resulting in won business from the top to the bottom of the sales and marketing funnel.  This new insight will allow us to connect in a more meaningful way with our audiences and deliver the right content at the right time.  We’re really excited to see where content scoring will take us.

Liz O’Neill is a writer and content marketer at Kapost, a software that helps brands create, manage, publish and analyze their content in one place. Prior to joining Kapost, she managed social media campaigns at Location3 Media, and global marketing efforts at ONE.org, an advocacy organization based in Washington, D.C. She’s crazy about human-friendly content, playing outdoors and beekeeping. You can reach her at @lizkoneill