We recently touched on the topic of purpose vs. shiny object syndrome, so let’s dive a little deeper into that today by looking into data and insights. This will eventually evolve into a practical discussion about the difference between monitoring, measurement and analysis, so think of this as a small part of a bigger whole.
Let’s start at the beginning. The point of collecting data in the first place is twofold:
1. Funnel certain types of information to the right people and departments in real time (customers requiring immediate assistance, sales leads, the first phase of a potential PR crisis, etc.) and trigger a response.
2. Derive insights from data obtained from consumers.
We can talk about the response piece of this discussion in an upcoming post. For now, let’s focus on the insights part of it.
Simply put, the building blocks of insights are data, and insights are the building blocks of business decisions. The core equation you want to hitch your strategy wagon to is this: good data + good insights = good decisions.
Easier said than done, sure, but you have to start somewhere. (Ideally, the people in your organization tasked with translating data into insights and strategy are both competent and intellectually agile. For the sake of this discussion, let’s assume that they are.) As a CTO (chief technology officer) or CIO (Chief intelligence/information officer), your job in building a digital control center, no matter who ends up owning, running, and sharing it, is to equip the insights folks with the best data collection, management and communication ecosystem possible.
Aside from the response functions we mentioned earlier (tech support, customer service, community management, sales and PR), the driving force behind the design of that ecosystem must be to provide analysts and decision-makers with everything they need to quickly derive the clearest and most inspired insights from what would otherwise be endless oceans of data. A short list of the process you should focus on in choosing your monitoring and management software and designing your display structure would look like this:
Acquire Data (what channels & sources)
Filter Data (separate signal from noise)
Translate Data (format and clarify data)
You could collect data all day long, amass mountains of it, and still not have what you need to derive useful insights or draw helpful conclusions about the effectiveness of an activity (or of your overall business performance). So you have to know what data you want to collect and why, then figure out where and how to collect it. For all the bells, whistles and amazing displays one might expect to find in a digital control center, the primary purpose of that array of screens and keyboards is to properly acquire, funnel and manage data for customer-facing employees and decision-makers.
The selection of each monitoring tool assigned to this piece of your digital practice must be driven by an understanding of what kind of data are most valuable to each key function and why, where they can be collected, how quickly and how reliably. The tools you select must give you the ability to organize, manage and present that data in ways that make that data actionable. Simple, right? In theory. In practice, it takes a good deal of planning, testing and analysis to get this right. It isn’t hard, but it takes work. So don’t rush into investing into cookie-cutter digital control center solutions. Make sure that you build the right ecosystem for you. Make each screen count. Build best practices and functional workflows around your control center. It might seem like a little more work than you expected to do on the front end, but it will be well worth it in a few months when your data and insights ecosystem is humming along like a well-oiled machine.
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As always, we welcome your comments here, on Facebook and on Twitter. And if you haven’t tried Tickr alongside your other digital/social monitoring solutions, you’re about twenty seconds away from a test drive. Just click here.