Why has Digital eXperience Management become indispensable to content scoring?
At the crossroads of user context and content, DXM is well positioned to provide an accurate measure of performance.
“Better understanding the customer experience by improving data analysis”: in a 2018 survey by eMarketer, 65% of respondents said this is their number one priority. A commendable ambition that clashes with a complex reality. At a time when Digital Asset Management (DAM) platforms, Content Management Systems (CMS) and Marketing Automation tools co-exist, data has become inherently very fragmented. But the good news is that a Digital eXperience Management (DXM) solution can help bring this data together.
In our martech landscape, marketers must ask themselves several questions. How do you get a unified view of this data? How do you draw important learnings about your data, for example how to adjust the famous mix of Paid-Owned-Earned media (POEM)? And above all, how do you identify the winning combinations? For example: What are the content formats that achieve the best completion rates according to the origin of the traffic (search engine, social networks)? Is it more likely that visitors who have consumed one or more videos also complete a buyer journey?
Go beyond the usual metrics
Answering these questions means facing one of the biggest tasks of performance measurement. That is, going beyond the usual analytical metrics (page views, bounce rate etc), to focus on analysis dimensions that give key performance indicators (KPIs) their relevance. 3 large categories of dimensions prove to be valuable: The first investigates the context of the user (their geographical area, their moment of connection, the device used); the second examines the user’s journey (from a landing page to the home page for example); and the third, the consumption of content that is served by the DAM and the DXM (the assets).
Looking at these 3 dimensions, one observation emerges: while conventional analytical solutions can cover the first two dimensions, most of them miss the third – the one associated with assets. Because for these solutions, the sessions and the URLs, rather than the content, represent the raw material. In practice, only a DXM solution can provide a deep view into asset consumption – and reconcile this data with the usual analytical dimensions.
Establish the relationship between context and content
And for good reason: let’s remind ourselves that the main goal of the DXM is to ensure a dynamic rendition of content according to the user’s context. As such, the DXM logs the actual consumption of each type of resource for a given user context, and across all points of diffusion. This guarantees a 360 degree view of content consumption.
Furthermore, the DXM provides a deep analysis because it analyzes consumption at the media level and not the channel level, whether it’s the website or a social network – because of course, the query data is not interpreted by the diffusion channel. This is why the measure provided by the DXM is described as “media-centric” as opposed to “site-centric.”
This advantage is all the more valuable as social networks tend to restrict access to important data, which is already hindering the work of companies specialized in social listening as well as advertisers. For example, analysts estimate that, on a network like Instagram, “the volume of data retrieved will decrease by about 40% despite the promises of different publishers to have the best integration with Instagram on the market.” This restriction of access is illustrated by the increasing adoption of data collection services that bypass the limits of social networks, such as proxy networks like Proxy Crawl or Common Crawl. Tools that will be used to indicate which sets of interest, media and the kind of engagement generated in this case. In short, there is no salvation outside a truly “media-centric” measure.
The DXM can also take advantage of content taxonomy, as it can analyze how current actions influence the consumption of different categories of content. These “categories” can be pieced together from to a wide variety of data: product range labels, product identifiers, campaign tags… All the metadata of a DAM can, in practice, be put to use, as well as those of third-party solutions – data for example from an e-commerce solution. As a result, the DXM is able to establish a correlation between the traffic of two sets of product marketing content and changes in basket rate (the rate at which items are added to the basket/shopping cart).
In this way, the DXM not only provides users with rich analytic dimensions, it equips them with the “test and learn” approaches. Since it is able to identify assets – and not just pages – the DXM also can differentiate between different versions of assets. An object with different backgrounds or a video that has been edited with different visual elements can be A/B tested to help identify which version is the most successful for a particular context.
Dataviz to the rescue of content scoring
Let’s be honest, this wealth of analysis can lead to a legitimate concern: is there two much data to complicate the analysis? That’s why Wedia combines content scoring and data visualization in its DXM module. And with one clear objective: to create synthetic visual representations that facilitate the understanding of trends, ratios and correlations.
Within these dashboards, the profiles involved (Content Manager, Brand Manager, Campaign Manager etc.) can view the actual and detailed consumption of each asset, but also explore the performance of content grouped by brand, product, campaign, format, duration… A personalizable control tower to, at one glance, embrace context and content.
It is also from this same tower that a brand content manager will be able to identify misuse. For example, the use of content on a channel where they are not intended (a social network) or the use of outdated content, such as old products or brand guidelines. A way to use Digital eXperience Management as a means to ensure brand consistency. But that is another story..