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Why Digital Analysis Projects Fail

Good analysis can stall out before it even begins because people do not understand its purpose. This leads to fuzzy analysis projects that take forever to accomplish, have no focus and provide nothing more than a collection of random data points. It’s really painful to witness and can sour your organization on the value digital analysis can provide in guiding your digital initiatives.

There are more than a few reasons why digital analysis projects fail. People mistaking analysis and reports as the same thing or not understanding that there should be a difference are two.

Analysis and Reports: Know the Difference

When I think of reports or dashboards, I think of regularly scheduled outputs of metrics that provide you with a way to understand effectiveness of the digital property in attracting visits and visitors, counting conversions, tasks completions or engagement activities, visitor journey through the digital property, and use of site functions such as search, forms and tools. It is essentially a reporting of what happens and may help you understand how to predict future activity of behavioral segments.

Analysis Explains the 'Why' Behind the Metrics

Analysis doesn’t occur as frequently as a report or dashboard. Analysis focuses on data collected over a period of time, such as a quarter, six months or a year.

Where a report might tell you that you received 1,000 visits from a particular keyword term from your organic search efforts, you would conduct an analysis to find out how many of those visits completed site registration and how many who did were either first time or repeat visitors and whether these visitors were predominantly from New York or California.

Analysis Improves Reporting

In my experience, organizations don’t tie analysis into the overall analytics program. Reporting is considered the main product of the analytics program and analysis is considered a “throw in” if there is leftover budget, or an ad hoc task if an executive is interested in finding a particular piece of information. Rarely are analysis projects baked in to the budget or planning. This is a real missed opportunity and it holds back the analytics value to be gained from reports. Here a few examples:

  1. Run experiments to define behavioral segments that you can apply to reports. For example, determine whether there is a real difference in how many pages visitors read before registering for an account or the number of visits within a time frame before making a purchase. Analysis gives you the freedom to do this experimentation and discovery.
  2. Answer questions that guide site and campaign optimization. A client created a website that had two call to action tasks on the same page. In the client’s perspective if visitors completed the first call to action, they would naturally continue to the next one. This wasn’t the case. Analysis showed that most visitors completed the first call to action and left the site. For visitors, there was no clear connection between the two calls to actions. The analysis revealed a gap between client expectations and the reality of visitor site usage. We recommended that the client consider testing text, visual call outs and linkages between the calls to action.

Want to get more value from digital analysis? Lay out a plan for analysis for the next 12 months. Prioritize the analyses based on persistent questions that come up from your reports. Think about how to identify the valuable segments that can move your business if target them with content and campaigns that map to their behavior. It’s a sure way to drive more value from your digital channel.

Looking forward to the second Digital Analytics Association Symposium in Washington, DC — June 5, 2014 — Getting to Simple: Turning Complex Data into Actionable Outcomes

Editor's Note: Now that you've mastered the difference between analysis and reports, make sure your presentation doesn't fall flat: Don’t Put Your Audience to Sleep: Why Presentations Fail

Title image by Sean Pavone (Shutterstock)

About the Author

Phil is senior manager, Enterprise Intelligence Digital Analytics of Ernst & Young. Phil was one of the earliest adopters and advocates for the use of analytics and has 16 years of experience in the field as a practitioner, industry analyst and consultant.

 
 
 
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