How Content Scoring Merges the Art and Science of Content Marketing

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Jesse Noyes

Sr. Director of Content Marketing

EDITOR’S NOTE: This post is part of a series of posts from Jesse Noyes, Sr. Director of Content Marketing at Kapost who will be sharing his expertise around content marketing and platforms to better help our audience navigate this very important area of marketing.

content scoring

Two disruptions over the last ten years have changed the way we market.

The first is that marketing transitioned from an art (some would say a “dark art” ) toward a science. Technology, such as CRM and marketing automation software, enabled marketers to deliver right-time-and-right-place messages to buyers, and score leads based on their behavior and purchase intent.

Adopting this data-fueled approach quickly exposed the flaws with the status quo model of marketing. Turns out, brochures and branded pens weren’t as enticing when prospects with an internet connection had access to the world’s largest library of research and peer reviews. Marketers needed educational, thoughtful content — and lots of it — to grip and hold a buyer’s attention. So content marketing took center stage.

Yet measuring the effectiveness of content proved difficult. Sure, you could track web traffic and get some stats on engagement. But measuring a content asset’s true impact on leads in your marketing pipeline remained elusive. Science and art just couldn’t get on the same page.

But that’s changing with a new process called content scoring. This methodology goes beyond vanity metrics to score individual assets based on how effectively they generate leads, opportunities, and sales. It measures the impact of content on your pipeline, not just your website.

So how does content scoring work?

Quite literally by working backwards from any conversion point in the buyer’s journey. Let’s start with a hypothetical Marketing Qualified Lead (MQL). And let’s call this lead “Bob.” Here’s Bob’s journey to becoming an MQL.

Touch #

Description

1

Reads BlogPostA

2

Watches VideoB

3

Attends WebinarC

4

Downloads eBookD

5

Opens EmailE

6

Watches ProductVideoF

BOB BECOMES MQL

The simplest formula to apply here would be to give each piece of content Bob digested equal credit for converting him into an MQL. Since six pieces of content were touched, they would each get â…™ the value of the MQL — or a content score of 0.16.

Companies tend to attribute greater weight to specific touches in a buyer’s journey. Most often, marketers use a first touch/last touch model, applying more credit to the lead’s first and last touches. We’ll use the same methodology for our friend Bob, giving the first and last touches 30% credit each, then spread the remaining 40% across content touched in the middle of his journey. So now, the content scores for Bob would look like this:

Content Asset

Score Earned from Sample MQL

BlogPostA

0.3

VideoB

0.1

WebinarC

0.1

eBookD

0.1

EmailE

0.1

ProductVideoF

0.3

But your marketing pipeline isn’t limited to Bob. You have many other content pieces to score across tons of other leads. This is where content scoring gets actionable.

Extend this same methodology across all the leads your marketing team generates in a quarter and immediately you’ll see which content assets are truly influencing buyers. Suppose we used the same attribution model and looked at 2,000 MQLs. The data set would resemble something like this:

Content Asset

Content Score

ProductPageA

238.9

WebinarB

122.3

VideoC

97.4

BlogPostD

89.9

BlogPostE

76.6

EmailF

75.9

 Etc.

The total content score extended across all these assets would equal 2,000 since you are attributing credit for generating these leads across all the content touched by all of the MQLs in that quarter. Armed with this data, marketers can easily see which assets or topics are responsible for producing leads. Additionally, you can use the same methodology across any stage you set — leads, opportunities, or closed deals.

As you can see, this type of evaluation tool is tremendously helpful for marketers as they assess their content marketing success. To make it easier for marketers to implement this methodology, Kapost (full disclosure: I work for Kapost) automated content scoring within its content marketing software platform. When you run a report on any given stage for a specified timeframe, the feature pulls each piece of content and assigns it a content score based on how many buyers digested that content, and when in their journey they digested it. By merging content scoring data with user journey and sales data in your marketing automation and CRM systems, marketers can see how many leads, opportunities, and even revenue a content asset has produced.

Whichever method you use to score content, it is certain to make the way you target buyers more efficient and intelligent. 

This is how content scoring marries the art and science of content marketing and enables organizations to see what works from the beginning to the end of the sales and marketing cycle. With this data in hand, content marketers can deliver content that serves the needs of customers, and not just the needs of a corporate website.

jesse noyes content scoringJesse Noyes is the Senior Director of Content Marketing for Kapost. In this role, he’s charged with producing and overseeing the company’s content marketing strategy and delivering high-value educational experiences for the industry. Jesse is the former Managing Editor at Eloqua (now owned by Oracle), where he ran the company’s award-winning blog and produced plenty of other stuff. You can follow Jesse on Twitter at @noyesjesse if you’re interested in content marketing and dogs.

content, content evaluation, content marketing, content scoring, content strategy, CRM, Kapost, marketing automation

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