NativeAI

How to Measure Content Marketing Without Wasting Time on Vanity Metrics

By NativeAI / May 3, 2018

False success metrics are deadly for publishers. Hyping irrelevant metrics might sound good for the moment, or help save face in team meetings, but in the long run, they provide little-to-no value.

That's why they are called vanity metrics - and they do more damage to success than they help.

Data is incredibly valuable, and can reveal publishing opportunities to drive higher levels of engagement. However, the wrong data can seem helpful and attractive, but work against your goals. Vanity metrics can signal false positives and derail your objectives for truly data-driven publishing. The secret is in measuring the right content marketing analytics, and ignoring manipulatable and irrelevant vanity metrics.

The Value of Content Marketing Analytics

What do a million visits accomplish if 90% of that traffic did not find any value in your content?

Will it benefit a publication's bottom line?

What Are Vanity Metrics

Vanity metrics can include data about registered users, downloads, and raw page views. They can be easily manipulated, and do not correlate to the numbers that really matter. Bots or cheap clicks from outsourcing tools like Mechanical Turk, can exaggerate numbers for downloads or users, making publishers and companies seem more successful than they actually are.

Remember Clickbait?

Clickbait used manipulative or misleading titles to trick readers into going through an article. It was invented to accumulate visits and drive up circulation metrics. The numbers weren't actually useful for the publisher, as the content did not drive any value to the reader or the publisher.

Clickbait drove insane amounts of traffic for a while, then, the public wearied of the unfulfilled promises. There was significant backlash, and Facebook even tweaked their algorithm to penalize clickbait shares.

Clickbait metrics are an example of vanity metrics.

The bottom line is - these metrics don't mean anything. A spike in visits or clicks is not valuable if they all bounce. Without engagement acting as a North Star, it may seem like your audience is loving your content when they actually aren't.

What Metrics Matter?

For publishers, every significant metric is attached to engagement. There are certain metrics that signal engagement, which include time spent, scroll depth, user actions, story length, and more. All this data needs to come together to show the most accurate picture of reader engagement. When measured correctly, this information will show how effective your content and publishing tactics actually are.

This is important because, in order to grow your audience, you need your readers to be engaged. Your content needs to be intriguing. So as a publisher, prioritize measuring engagement over reporting on traditional website analytics, which won't show you the same picture. That's we developed the Engagement Quality (EQ) metric. EQ aggregates all engagement signals into a single, easy to understand metric that can be applied to entire websites, channels, audience segments, even down to individual pieces.

Given that there are so many factors that influence engagement, this metric combines those factors and distills the data into one simple score. Using this one score, at a glance, your editorial team can quickly assess what content is resonating the most with readers. With this data, teams can strengthen their weaker content, develop better content to fit their audience preferences, and sustain long-term growth for your publication.

Tracking Content Marketing Analytics

If you're still relying on the metrics that don't matter, you're risking a lot as a publisher. Without actual information about reader engagement, all of your content will be a shot in the dark. Soon, your audience will be drawn to publishers delivering the content they actually want to read.

It's a gamble that not a lot of publishers can afford to make.

That's why we developed NativeAI; to help publishers understand their content marketing analytics, and their users interests, so they can put data into action.

Read More: Complete guide to Content Analytics for Digital Publishers

If you would like to learn more about actionable data, we are launching a micro course on extracting actionable insights from deep audience intelligence. In this course, you'll learn how to navigate your engagement data and start using that information to put your content and engagement back on track. Register for the free course here. How to Extract Actionable Publishing Insights From Deep Audience Data

Written by NativeAI / May 3, 2018