Using tools such as Google Analytics, you can monitor the effectiveness of your content marketing and use those insights to take action and improve your website. In this article, let’s explore how you can combine a headless CMS with analytics tools.
Using data analytics tools to measure the success of our content
We produce a lot of content that we distribute across different channels. But are we sure that the content meets the goals we’ve set? Does it bring us more customers? In the digital age, it’s very easy to answer these questions and understand the customer journey thanks to the microservices architecture we use.
Data analytics & Headless CMS
Kontent.ai, as a headless CMS, does not have a built-in analytics functionality. If you want to do an in-depth analysis of your content, I recommend using a tool that focuses solely on analytics and can process complex data from Kontent.ai. The tool we’re talking about is Google Analytics. The latest Version 4 even connects mobile applications to the web, just like Kontent.ai does in the world of content. Google Analytics is easy to implement, but a more in-depth analysis requires a more advanced setup. Kontent.ai can help you gain interesting insights into your content’s performance by sending structured data to GA and other analytics tools in the data layer. Later, we can use this structured data for data segmentation.
It’s essential to remember that each analysis should be based on a question correctly formed in advance. Ideally, we should ask ourselves that specific question when designing our content model. If we know what we want to analyze, it’s easy to prepare a content model for this purpose and thus ensure data flow. This can be information about blog categories, resource type, product information available in Kontent.ai, etc. Our headless CMS sends this structured data via API to the front end, and from there, we can easily deliver it to data analytics tools.
In our team, we use custom dimensions for Google Analytics in this way. We can provide Google Analytics with information from Kontent.ai about which user persona the landing page, blog, or resource is intended for, and when evaluating the customer journey, we analyze only the given segment. We can do the same when sending events to Google Analytics. The content editor in the Kontent.ai app fills in the event name, which we send to Google Analytics when a given user action occurs. Subsequently, we can easily create a goal from the event in the Google Analytics environment and thus measure success.
Of course, not everyone needs to look at such detailed analyses. It’s often enough for a content editor to see how many people read their blog post and how they discovered it. For these purposes, Google Analytics also provides a very quick and clear answer. We can even find out whether people read the article on their mobile devices and where they are from to get more demographic and technological insights. Everything takes place in Google Analytics; however, we can make editors’ lives easier and, using our custom element, send them to Google Analytics directly from Kontent.ai to look at the data of a specific page.
Conclusion
To sum it up, the Kontent.ai headless CMS offers quality data inputs for basic as well as advanced analyses that require a combination of different data sets. By using microservices, we can get fascinating insights into the performance of the website and mobile application. There are many top data analytics tools on the market, and it doesn’t matter which one you use, whether Google Analytics, Adobe Analytics, or Amplitude. You can deliver relevant data about your content to all of them using Kontent.ai.
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Lucie Simonova
Jul 22, 2022
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