Content marketing analytics is measuring and analyzing content marketing efforts. The metrics are shown in an online dashboard. Content marketers can use this data as a feedback loop to enable them to measure progress, find areas of improvement and link back to business results.
Before proceeding further, if you do not know enough about content marketing metrics, I recommend the following articles.
- What are some content marketing metrics to follow?
- Why type of content marketing metrics does Nudge provide?
- Why is bounce rate important for content marketing?
- What are the best free content marketing measurement tools?
- What are the best tools that work with agencies?
- What are some good content marketing KPIs?
- What are content marketing metrics?
- How do you measure the success of content marketing?
- What is a better tool than Google Analytics for content marketing?
- How do I make an effective content marketing report?
- What considerations do you need to make when selecting content marketing analytics?
- Factors which Drive Content ROI
- Content Marketing ROI
Table of contents:
- How do you use analytics to measure the success of content marketing?
- What are the different types of content analytics?
- Site Analytics vs Content Analytics
- The evolution of Content Analytics
- What is the future of Content Marketing Analytics?
- What are the best practices for content marketing analytics?
The need for content marketing analytics grew as a byproduct of the high adoption of content marketing. Older analytics systems like Google Analytics and Adobe were not fit for purpose. And content marketing bridges more of art and science; how good the content is but also how well it engages customers. This created the need for specialized solutions. This also has meant that many companies use 2 or more analytics platforms to get the data they need.
Content marketing analytics enables marketers to achieve a number of things at once:
- Better understand the performance of their content
- See how customers engage with their content
- Link content marketing to strategic goals
- Link the success of content to other business goals, like MQLs, leads, sales
- Set KPIs for the team
- Understand ROI
- Help with setting budgets and securing new budget
- Find areas of improvement
Without content marketing analytics marketers would be operating in the dark. They wouldn’t understand how effective their content is resonating with customers. And would struggle to prioritize where to focus. Often analytics is an area they turn to when they are struggling with performance. Analytics can help uncover areas of opportunity.
Each year one of the world’s leading analytics agencies, Cardinal Path releases a report on analytics used by brands. They skew towards big brands, and at the moment focus on site analytics and less so on content marketing analytics. But it’s a good starting point, this is where most of us reading this post have/are starting.
You probably have site analytics, such as Adobe Analytics, or Google Analytics- but now you’re in search of something more specific, to help with content.
We have found that these traditional page analytics tools are great for your website – but, when content is a key part of your business, they have clear gaps.
Related reading: Content Marketing Metrics.
Analytics helps to quantity how many customers engaged with your content and what happened next. This then informs a marketer how successful the content has been.
If we were to distill it, it would look like this:
- The best tool is the one you use.
- Use tools built for purpose.
- Does the company itself dog food? I.e. use the tool themselves.
That should get you ahead of the pack.
Different types of content analytics
There are many different types of content analytics tools. The primary use case, is measurement and analysis of the content. With some more specialized tools for other workflows.
- External tools, e.g. Nudge, to get meaning across many different types of content (built for content marketing, branded content, and content distribution).
- Built-in tools, platform-specific analytics provided by the social platform itself, to help analyze social posts (e.g. Facebook Insights).
- Creative analysis, i.e. heat maps, or similar. Like RealEyes.
Other examples within the wide spectrum of content analytics tools include data/text mining, pattern matching, visualization, semantic analysis, neural networks, and complex event processing.
These are mainly quantitative tools, you can also get more qualitative analysis of your content through surveys & panels.
Six consideration you should make when selecting a platform:
- The best tool is the one you use
- Third-party measurement is vital
- Time to insight
- Distribution impacts success too, so make sure it is measured effectively
- A good tool will help improve your old content too
You can read a full rundown of these considerations.
A preview of what a content analytics dashboard looks like
Site Analytics vs Content Analytics
Website analytics help understand how a website has performed. Content marketing analytics go a bit deeper to find out how engaging it has been. This higher fidelity is needed to ensure the content is effective. Content lives on websites, The two are intertwined, you can’t have one without the other (in most use cases). And this is very common; marketers today use multiple tools to deliver on their goals.
The key thing is that content analytics has metrics which are fit for content.
What is the future of Content Marketing Analytics?
Some of the future trends in content marketing analytics:
- Diversity in specialized tools. It is common to use 1-2 tools. As organizations become more digitally-centric, this will only increase, as business demands do. At some point, it will consolidate but not in the next 2-3 year horizon.
- Privacy-centric or privacy respectful tools. Marketers are finding that this isn’t a trade-off that is productive for either the brand or the consumer.
- Better content workflows. In recent history, marketers have aimed to get data into dashboards, the next trend will be towards, getting data into action, through integration into marketing workflows.
- Increased maintenance. With more digital tools, every organization will need to increase its technical maintenance to keep all their data up to date and reflective of the organization’s needs.
- Tighter feedback loops with paid distribution of traffic. I.e. Google Adwords has begun to integrate more data from Google Analytics.
- Digital content expanding into connected TV and digital out of home. Our content will now branch out from the regular screens. Requiring new ways of understanding content success.
- The merging of brand and performance. All brand advertising and marketing should perform. All performance should grow the brand. They still have different roles but will be more integrated than in the past.
- Machine learning democratizes insights, data collection and the feedback loop to creating more effective content. Now small businesses can really compete with big businesses.
- The shift from data scientists to insight curators, people that understand the data and how it is created but can then link it to business objectives.
- The intersection of content, personalization, and distribution will begin to blur. As they all get further integrated.
- Adoption of AI, in the workflows of content creation and making suggestions from data.