Consider these six factors when implementing web analytics in your organization.
In my previous column, I talked about how to increase our web analytics effectiveness. But in order to truly get the most value out of web analytics, it's important to have a holistic approach to implementation. Today I'd like to delve deeper into a framework for implementing web analytics.
Now web analytics is nothing new to digital marketers. In fact, most brands and agencies have been doing web analytics for years. If you're one of those marketers, then ask yourself honestly the following questions:
My guess is you answered no to more than one of these questions. That's because most companies treat web analytics as a reporting tool, while it's really an approach to accountable and data-driven digital marketing. A complete web analytics implementation should fundamentally change the way digital marketing is done in your organization.
According to the Web Analytics Maturity Model below by Stephane Hamel, a clear direction is needed in all the following areas for web analytics to be successful: Management/Governance, Objectives, Scope, Team and Expertise, Process and Methodology, and lastly Tools and Technology.
Before I talk about each area of the framework, let me first show you an example of how most companies approach web analytics. Consider the evaluation below:
Now what happened here? The marketing director probably went to some digital marketing conference and saw the wonders of Omniture or Webtrends. As he gets back to the company, he mandates the digital team should immediately evaluate and purchase a web analytics tool. Hence the focus is all about how to choose the best tool, and how to magnify scope by tagging anything and everything under the sun. But as this company rolls out the shiny new tool, no one is clear on the business objectives of what and why they're tracking. Since it's a technical tool, the IT team gets slapped with the weekly reporting duties. But the IT team has no clear methodology in reporting the right metrics for the marketing team. And most importantly, no one is clear on a governance model on how insights and recommendations will be executed. As a result, this company's web analytics effort ends down the road of data puke. Where reports are produced with no purpose and no action.
Instead, the correct approach for implementing web analytics should address all dimensions as depicted below:
It's important to take baby steps in each and every area before growing too fast in one:
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Currently digital director for Mindshare Beijing, Charlie has over five years of experience covering both IT consulting and ad agency industries. He was previously technical director at Tribal DDB Hong Kong, where he led the implementation of analytics and technical innovation across digital campaigns. His previous experiences include data analytics director at Bizcom Consulting in Beijing, and business intelligence analyst at Deloitte Consulting in the U.S. Charlie's project portfolio includes digital analytics, digital campaign production, marketing data integration, as well as large scale data warehouse implementations. He has worked on numerous digital accounts including: McDonald's, Manulife, Wrigley's, Smart Communications, Financial Times, and Friso.
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