Data Puke vs. Actionable Data


There is a misunderstanding with some online marketers that simply believe looking at your website’s visits and pageviews is indicative of the successes or failures of your site. Really? Come on, you can do better… a lot better.

I challenge everyone to dig deeper, but not so deep that you generate data puke. Data puke is the difference between ‘Web Reporting’ and ‘Web Analysis.’ It’s a term that Avinash Kaushik, Google’s Digital Marketing Evangelist, uses heavily and it’s one that has stuck with me ever since first reading about it. In essence, most of the time Web reporting generates data puke, where Web analysis generates actionable data.

In Avinash’s blog post, The Difference Between Web Reporting And Web Analysis, he gives readers a list of 10 signs you’re doing Web analysis in hopes that you can identify data puke when you see it. While I agree with what Avinash has to say, I would like to put my own spin on this list and share with you 5 signs you are generating data puke and then give you 5 signs you are generating actionable data through performing Web analysis.

5 Signs You Are Generating Data Puke

  1. The only numbers you are looking at are the high-level “dashboard” numbers (most of the time dashboards are data puke).
  2.  “What’s this?” or “What’s this showing?” is how someone else looking at the report you just created instantly responds.
  3. It doesn’t pass the “so what?” test. Ask yourself “so what?” for every statistic you pull, and if you don’t have a measurable or economically identifiable reason to measure it, then don’t. You’re wasting your time.
  4. If you are looking at a report and there is no mention of a ‘target’ or ‘goal’.
  5. There is no context behind anything you are presented with or presenting to others.

Now, keeping in mind the 5 things listed above…

5 Signs You Are Generating Actionable Data through Web Analysis

  1. The “thing” you are looking at isn’t just data, but data along with measurable action items that the business can take based off of that data. Or in the same vein, it is showing data that directly corresponds to the targets and goals the business has set in place.
  2. If you are looking at something that has a clear and defined path of how the analyst got to the point of gathering that specific information, it probably took some analysis (a breakdown of big data into actionable datasets).
  3. If, when looking at or generating a report, you see an explanation of the business implications, or economic value, that the data is showing outlined in the report itself.
  4. Any glimpse that you can see where someone is comparing data to previous timeframes and giving someone a visual queue of whether things are improving or getting worse. The person is at least looking at the numbers now compared to where they used to be, which is showing some form of business analysis through the analytics (although it still needs to pass the “dashboard” and “so what?” scenarios listed in the previous section).
  5. When viewing or creating a report that effectively has segmented data or user information, that is probably the product of someone performing Web analysis. After all, according to Avinash Kaushik, “All data in aggregate is crap.”

So, does any of this ring a bell? Are you performing Web analysis or creating Web reports filled with data puke? Challenge yourself. Challenge your peers. Stop generating Web reports that are filled with data puke and start performing Web analysis, which in turn generates actionable data.

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Matt Hacker

About Matt Hacker

As Geonetric’s client analytics strategist, Matt helps clients define goals and measure online success. He goes beyond numbers, translating data into actionable guidance. This former manager of Web services for a busy Web design and video production company has experience in everything from search engine optimization and social media management to usability and design. Matt received his bachelor’s degree in management information systems from the University of Northern Iowa. He is also a certified Google Analytics Individual.

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