
Have you ever felt lost in a sea of data, with no possible way out? If so, then you’re probably an Internet marketer, in some form or flavor. For a typical Internet marketing client, I find myself measuring several dozen different data points at any given time. From Quantcast metrics to Google Analytics, Social Mentions and Conversion Rates — I sometimes get the feeling that there’s just too much.
As Internet marketers, we have to measure everything… right? To prove our value, to prove that Internet marketing works, to show stakeholders that our efforts have an impact.
I mean, I get it. Numbers can’t possibly lie, and in this very digital age, there are very few things that can’t be converted to measurable numbers in some form. Plus, pretty charts and graphs make it much easier for decision makers to justify the expense (investment) of an Internet marketing campaign.
But have you ever asked yourself — how much is too much?
This is what I’d like to see: a consolidation of data. Let’s come up with a metric that either measures several different important data points and aggregates into a single number, or, we start cutting out data that just doesn’t matter, or isn’t accurate.
That said, an aggregate single data point may be too ideal to be a reality. Internet marketing measures are very subjective, and thus, a single point probably won’t work.
Cutting out useless data may be the best option. How do you do this? Find out what the true goals of a campaign are, and measure only the variables that will help to advance those goals.
For example, say you’re running a campaign that’s meant to increase conversion rates. Would you measure your Twitter reach and engagement? Maybe. But wouldn’t you rather measure your site traffic, actions, exit pages, flows and conversions? Yes! Of course! Twitter reach may in some way influence conversion rates, but I think when you get down to it, the extra data will cloud the picture and lead to some poor decisions.
The bottom line is, yes, data is important, and measuring campaign performance is not an option. But lets be sure we’re picking the right data to measure. After all, who wants to drown in data?
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