From here, we address the “what” of our data. I’m not going to dive into a discussion of User Sessions, Time on Site, Pageviews, Bounce Rates, etc. - rather, my focus is on what data can do, thus leading to how you’ll want to create systems of measurement for your data program.
We’ll start with the Google Products. GA, Search Console, Page Speed Insights can all teach you important information that is intrinsic to site performance and how users are engaging and finding content that is relevant and useful to them. These all provide data and information about how users are finding your site and the content within, as well as how valuable that content might be and, in some instances, what they might be doing to take action. Data here is potent for the purpose of understanding your organization's place within the world of search and social networking. This will become the lynch pin for many decisions about content and what avenues you explore for spreading the content your team can produce.
The CRM data serves a different purpose. It can give you detail about what user types are finding your digital products, but it can tell you about your business in more detailed ways. What industries and archetypes do you appeal to, what are some of the demographics, things like job, job position, locale, and ability to make decisions. CRM information can become more useful depending on the information collected. I have seen organizations that collect information in great detail, which can help them learn as much about themselves as it does about the users that offer it.
Deeper levels of data from heatmap tools, or site recording software offer information that we normally attribute to intuition. Assumptions about user behavior and preference can be studied here. These tools should be assessed carefully and reviewed in-depth before any actions are made. They can be incredibly useful, but that use can cut the other way if a trend pushes to a bad assumption.
BI Tools are also a double edged sword in my opinion. Incredibly useful for assessing an organization's data driven performance, but tend to be too high level and may miss important facets of competition and other potential data that could impact performance. It lacks the qualitative information that can be necessary to actually make decisions, but it should prompt important questions that lead to deeper levels of analysis.
From our point of view, the “what” of data is linked to the purpose of its use more than actual sessions. Volume isn’t a guarantee of performance success and given that users are prone to error, driving traffic shouldn’t be the only indicator of performance. Quality matters and using your data to mine for quality should be a primary goal of investigation. At the end of the day, if you can’t build better quality content, your product will suffer, so look to your data and assess the content and it’s quality with that in mind.