I'm back! Well, I wasn't really ever gone. I just have been feeling rather uninspired (and I got Netflix) for the last couple of months. I have a lot of half and mostly written articles I aim to refine of the coming weeks and try to start posting again.
Recently I have had a few interesting discussions with a few friends of mine about reporting. Being a web analyst most of my day to day work revolves around pulling reports from Google Analytics (GA), cleaning the data if required and merging it in with CRM or financial management data. What got me thinking was that my friends were looking at a report and telling me how bad this web page was because it had a really high bounce rate (upwards of 85%).
"This page is terrible, it's bounce rate is about 85%!" my friend exclaimed,
"Why does that mean it is bad?" I ask,
"Doesn't that mean that people just came to the page and left? That is a bad thing right?" my friend responded, less confidently then before.
The problem here is that my friend didn't understand two things - what a bounce is and the context of that data. My friend thought a bounce was someone who visited the page and left immediate (within 5 seconds), whereas the average time on page for that page was over 4 minutes. Admittedly the bounce rate was high, but people were engaging with the content. Furthermore, most of the traffic to that page was driven by email traffic. Email traffic typically has higher than average bounce rates so this high bounce rate didn't surprise me, nor did I think it was an issue. However someone who does not know the data does, which is a problem.
I am going to make a bold claim here, I guarantee most high level management would have little idea on what makes up the numbers in their reports, or why the numbers are where they are in the report (think sales channel attribution). We don't question reports, we don't question the logic behind them which means we accept the report as truth. If reports are automated without an analysts input decisions are then made by a management who, whilst meaning well, lack a holistic understanding. Think of my bounce rate example from earlier. That page could be cut or labeled a failure because it is being measured by the wrong yardstick. Whilst decisions are data driven, they are not being driven by the right data.
Most CRMs and business intelligence tools have really complex data models that when reporting on you can split many different ways and get different numbers when seemingly reporting on the same thing. Furthermore with the rise of automated reporting out of these systems and simple dashboards who will actually understand what the data is saying? This is a problem. We are constantly being told that smart businesses are data driven, the future is data, back your ideas with data. Data by itself is just that, data. It doesn't point to anything or say anything itself. Analysis and interpretation does. Decisions shouldn't be data driven, they should be insight driven. If people don't know how to interpret the data or are interpreting it incorrectly you may as well not use it.
So please, stop blindly consuming reports and dashboards without trying to understand why the numbers are like they are. Know your data. Ask questions, dig deeper, find out why and then make insight driven decisions.