The choice to become a data driven organization is a very important one (we’ve written about this topic often on Endless Plain) because it is the first step toward making big ROI gains. Once data becomes the focus for marketing decision making, it is important to ensure that you understand what to measure, what not to measure, and what to expect.  Most importantly,  you must have confidence in the data and findings you share among internal stakeholders.

But how do you know if your data is accurate? If it isn’t, the actionable recommendations you make based on the data generated by your Web Analytics program may not help you much.  This is why data accuracy is one of the key issues that a good Analytics Audit (one of our most popular service offerings) should address.

The first steps in our Audit process are to review all appropriate information and data sources, establish a good baseline and identify any anomalies or illogical patterns in the data. This generally takes a bit of time and a lot of skill.

We almost always conduct data comparisons (comparing numbers from one Web Analytics program to another) as a means of ensuring accuracy. This can be a confusing and frustrating endeavor if you are not aware of all of the factors that can impact how numbers are reported by each vendor.   However, the comparison process is essential to ensuring that your data is clean and accurate. 

The Analytics Audit can be an eye-opening experience.  Some of the common data accuracy problems we often discover in the course of an Audit include the following:

• Analytics are under-reporting because java script is not on all the pages or incorrect on some pages;
• Analytics are under-reporting because a Web site is load balanced and not all of the logs are being analyzed;
• Analytics are over-reporting visitor traffic because robots and spiders are being counted as visitors;
• Analytics are grossly over-reporting conversions because the conversion code is on the wrong page, so campaigns that looked successful were actually losing money.

Most clients are surprised to find these errors, but there are often even bigger problems that are identified in the course of an Audit — problems that can significantly impact a client’s marketing program and/or Web site.  In one recent Audit, we discovered that fraudulent clicks and no-quality clicks were wasting almost an entire campaign budget.  In another, we discovered that a minor change made to one of the steps in the shopping cart had increased abandonment rate by 27%.

If you’ve made the decision to become a data driven organization, a Serengeti Audit can help you assess the accuracy of your data before you go too far down the road in presenting numbers to internal stakeholders — or worse, making bad marketing decisions based on faulty data.

Filed under: Analytics, Audits on Tuesday, April 8th, 2008 by Joy Brazelle |
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