Your content’s live. Now what?

If you want content with true value and longevity, it’s time to analyze and iterate.

How to consistently measure content performance

Measuring content performance consistently is a notoriously difficult objective, especially when you’re breaking long-form content down into atomized pieces. A taxonomy might just solve that conundrum for you. It’s a labeling structure you can use to track content across your digital channels. The most common taxonomy in marketing is the ‘utm’ tag.Think of these as labels you can manually attach to digital activities with any information you want to track and measure. Understanding which content, campaigns, and audiences drive performance in your pipeline helps you focus on content and approaches that offer the best ROI.A data taxonomy will help you get the most out of utm tags. How to design a robust taxonomy, implement it into your marketing activities, and capture data in your CRM will be the subject of a separate guide. Here are a few top tips for making the most of taxonomies:

Start with the standard ‘utm’ values, only building custom properties when required

Build a consistent structure across your property values

Align your taxonomy across all digital channels

Ensure adoption extends across all digital channels with URLs or technology integrations

Test property mapping in your CRM and website forms to make sure that information is captured

Which performance metrics should I focus on?

With so many data points available, it’s difficult to cut through the noise of vanity metrics.

We’d recommend splitting your metrics into ‘primary’ and ‘contextual’ groups. Primary metrics are the main indicators of performance, while contextual metrics help you understand the ‘why.’

As your program matures, you may also start to measure content based on qualification and performance within the pipeline.

Primary:

Spend
Conversions
Conversion rate
Cost per lead

Contextual:

Impressions
Clicks
Click through rate
Average read time

Future:

MQLs
MQL rate
Cost per MQL
SQL rate

With Turtl, we take an events-based approach to engagement metrics. Reader actions such as…

Turning a page
Opening an Immerse level
Answering a poll
Following a link
Zooming in on a chart, map or image
Listening to audio or watching a video
Sharing or downloading the Doc

…all feed into analytics to support lead scoring models—or even trigger automated campaign activities.

How to consistently iterate content performance

Once your content is live, that’s when the lead generation work really starts. Optimization is what drives consistent performance, but for many marketers, a lack of measurable engagement data and limited iteration processes can make that tricky.

To build a robust iteration process, you can follow this four-step process: execute, measure, report, and refine. Let’s break it down…

01. Execute: This is your starting point, when you activate your content. Once it’s published, you can start analyzing, testing, and refining to maximize its long-term impact.

02. Measure: Next, it’s time to collect data on the metrics that matter, like read time or how many onward links your prospects follow. With a smaller readership, you may want to set a testing period to closely monitor how the content performs. If it’s a popular piece, it might work better to track performance across a predetermined number of readers instead.

03. Report: When you report on your data, focus on providing insight, not just a summary. Instead of talking about what you’ve measured, think about the factors that contributed to those results, whether it’s the channel, where you’ve placed it on your website, or particular strengths and flaws in the content itself.

04. Refine: Finally, it’s time to start iterating. Use that insight to design improvements to your content, and then set up a test to see if your changes have the desired effect. Keep it scientific—stick to an agreed timeframe and only alter one variable at a time.