The first thing that happens when you start working at Velocity (after the cup of tea and the introductions) is you get sat at a desk and are given time to read through our content library. It’s the best way to start a new job, and it’s incredibly valuable.
Getting under the skin of the core product is always the right place for a data analyst (like me) to start work. And one piece jumped out at me: Neil’s blog where we took a sly dig at the PR industry for failing to establish decent performance marketing metrics.
I knew what I had to do: create a metric portfolio to keep us looking smart, fresh and relevant. That’s why for the past few months I’ve been working on how to measure content marketing performance more effectively.
Why create Content Marketing Performance Metrics?
A lack of tangible metrics is a credibility problem that smacks of a non-essential service.
You want to look useful. Wait, more than look. You want to be useful. 100% on it. Essential.
That means you need a solid B2B content marketing performance kit: web analytics, data layer control, marketing automation, search engine marketing tools, tag management, and a data visualisation package.
And here’s what you could start to do today.
10 Essential Content Marketing Performance Metrics
One – Search Cluster Traffic Ratio
Creating search clusters (groups of thematic keywords) means you can focus your content on topics with high traffic potential. Start by understanding the traffic potential of your cluster and how much you’re currently getting. You want to improve that ratio relentlessly with your content investment.
So, you take your estimated click-through rate, multiply it by your cluster’s traffic estimate from, in our case SEMRush, then divide it by 30 to get your daily figure. Then you do the same with actual CTR and data from Search Console. And you’ve got your ratio.
Here’s what that looks like in practice:
(0.025 * 200,000/30) = 167: 13 = (0.04 * 10,000/30)
So our current ratio is 167: 13 or 13:1.
But we have a target ratio of 5:1. We want one of every five searches in this cluster to come to us.
The calculation gives us three important insights. We can:
- Choose to invest on lower CTR (with high volume) or higher CTR (with low volume)
- Understand relative cluster traffic: new proportions signal changing audience demand.
- Get insight on cluster progress to inform future content investments.
Two – Content Syndication Effectiveness Boost
GDPR turned many B2B marketing databases from roaring lions into meek lambs. And sent many marketers to content syndication platforms looking for leads at reasonable costs.
But how many of you are left wondering what number of these leads actually engaged with the content? You’ve got the name but have you got the interaction?
You can monitor this by differentiating your syndicated content – usually PDFs – with UTM tagging and well-crafted CTAs to inspire clicks.
Imagine two suppliers deliver you 250 leads but very different click-throughs of 14 and 33.
Partner A 14 / 250 *100 = 5.6%
Partner B 33 / 250 *100 = 13.2%
You can see whether content syndication partners drive engagement as well as leads, and whether that impacts subsequent funnel conversion paths.
Three – ABM Amplification
You want your ABM campaign content, tightly personalised to small audiences, to be shared across accounts. Sadly, identifying this “dark traffic” is a tricky task. But, again, tagging your content and using bespoke multi-channel funnels means you see if content, shared within accounts, inspires interesting visits to your site.
With a view of new visits and conversions across a target account, you can see how engaged a buyer group is. In the table below you can see that while account XYZ has fewer new visits but more, high-intent conversions.
|Account||First Visit||Content Download||ABM Amplification|
You turn a blind spot into evidence of account activity and help determine whether it’s worth pursuing with more time and resources.
Four – Educational Impact Score
There’s a good chance you have some comparable content in your arsenal. Maybe a bunch of rich web pages. And you’d like to compare their performance.
Consider three things: page views (total), unique page views (individual) and time on content (interest). And blend them together for a total engagement figure.
Page A (promoted) 20,766 / 19,666 * 244 = 106
Page B (not promoted) 2,927 / 1,911 * 244 = 374
The two pieces have very similar time on content but Page B’s higher quotient suggests it may be worth testing as an alternative promotion. It will also help to visualise the effectiveness of different channels at generating engagement.
Five – Content Engagement Metric
A way to measure consumption (for want of a better word) is seeing if the average time on page matches the time required to consume it. Imagine two blog posts with different lengths.
Blog 1 72% = (5.04 / 7) * 100
Blog 2 78% = (3.52 / 4.5) * 100
Reporting on this metric in a scalable manner often involves having a robust data layer functionality where, for example, you can combine your database with your user analytics data.
The figure (perhaps excluding mismatch bounces) should be similar to the expected time to consume the content. Too low and it’s likely not engaging. But too high and it could be causing difficulty. Either way it gives you an optimisation opportunity.
Six – Cross Promotion Premium
One stock hypothesis of content marketing performance is that content engagement drives commercial interest. If prospects engage with content but don’t ever register interest, something’s gone wrong.
By comparing your cross-promotion and standard conversion rate, you can see how much more effective your content is at converting than the rest of your site.
1.1 : 0.3
3.7 : 1
Again, you’ll need a diligent link tagging process in place to make this work. But even the grumpiest stakeholder won’t begrudge the effort needed for 3.7 times the commercial interest.
You can pinpoint the content and CTA combination that moves prospects down-funnel. The stuff that inspires action.
Seven – Defined Journey Success
Okay, assumption time. You probably have a blog. It’s probably your inbound engine. And it’s probably got a hefty bounce rate. Am I right? Thought so. Don’t worry, it’s not a disaster.
A user comes with a question and leaves with an answer. It’s a fair quid pro quo.
The important thing is that the users who don’t bounce move on to (from your perspective) the right place. So how do we check that’s happening?
Imagine a blog post with 700 ongoing journeys in a month. By dividing the 300 that go where we want by the total number of journeys, then multiplying by 100, we get the percentage of successful journeys.
43% = 300 / 700 * 100
This will shed light on effective signposting – particularly for your best traffic generators. If your audience is following the journey you created for them, you can bet it’s because they feel their needs are being solved.
Eight – Open to Click Comparison
Once you’ve got prospects in your database ready for nurture. The classic metrics here relate to short form copywriting skills (especially open rate). The one we like best is open to click.
27% = 130 / 483 * 100
While this may be a simple and common metric, it really comes into its own when used to analyse the impact of the type of message, used in different content formats, at different stages of the buyer journey.
|Content||Nurture Stage||Message||Open to click|
This process enables us to understand mismatches in nurture flows and optimize both composition and sequencing.
Nine – Opportunity Conversion Rate
Ever wondered how many measurement systems look at the content driving good conversions? Not enough. Focusing only on the channel means losing sight of the converting thematic or message. You can solve this by looking down the funnel at the role of different content pieces.
Imagine you find that four opportunities started their journey after downloading one of your ebooks.
0.7% = (4 / 563) * 100
Content worth gating had better deliver commercial value. If there are no opportunities then open it up to the world rather than hide behind a form.
Ten – Content Contribution Score
Our last metric goes from individual content to the overall portfolio. We love scoring models. But we do have to remember to look at high scoring prospects and accounts to consider how content contributed to a cumulative score (of a large enough sample size of opportunities).
32.5% = (390 / 1200) * 100
We leave you with a powerful metric to shed light on the overall content contribution. You can use this information to better understand the fit between your content and your best sales opportunities.
In today’s climate you must be creating effective content. But, even more than that, you’ve got to prove that it’s effective, and continue to evolve and optimize as part of a content-powered demand generation engine.
I hope these 10 content marketing performance metrics help you better understand your traffic and super-charge your engagement and conversions.
And let me know how you get on with them (or if you’ve any metrics of your own to share).
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