Avoiding the Most Common Web Analytics Pitfalls

A checklist for how to successfully create a culture of analysis within your organization and avoid the seven most common Web analytics pitfalls.

This week, a checklist for how to successfully create a culture of analysis within your organization and avoid the seven most common Web analytics pitfalls. Note: There’s no glory in getting six out of seven on this list. Though anyone whose been marketing online over the last decade will undoubtedly identify with several of these issues.

Pitfall: Goals and Metrics Aren’t Clearly Defined

Recommendations:

  • Start by defining the key goals and metrics at all levels: business, Web site, team, and individuals. This seems obvious, but it’s more common than you’d imagine.
  • Map out a timeline for reporting needs and the overall process based on goals.
  • Establish benchmarks up front, so you can establish trending over time and track performance versus goals.

Pitfall: There’s Lack of Analysis Standards Across the Organization

Recommendations:

  • Standardize key performance indicators (KPIs) and your process so you can make true apples-to-apples comparisons. This is critical for companies with multiple sites and business units.
  • Define terminology, document it, and share it with all business users.
  • Create an executive-level scorecard for monitoring overall results.

Pitfall: Data Are Inaccurate and Staff Doesn’t Trust It

Recommendations:

  • Configure Web analytics tools based on data-collection and -reporting best practices.
  • Conduct ongoing accuracy audits to ensure data reliability.
  • Teach power users how to customize reports. Tools are so flexible now there are millions of report combinations available.

Pitfall: Staff Is Overwhelmed With Too Many Reports

Recommendations:

  • Configure reports per goals and metrics, and eliminate the noise. Avoid the data anxiety that’s inevitable with too many reports.
  • Create concise custom scorecards to share with the team (must have alignment and accountability inline and reinforced).
  • Teach marketers the specific metrics they need. Don’t skimp on training; new skill sets are required, and they won’t magically appear overnight.

Pitfall: You’re Uncertain of Site Changes’ Financial Impact

Recommendations:

  • Create monetization models (this critical step is often missed).
  • Understand the value of desired behavior beyond just a direct sale (e.g., leads, delayed conversions, cost savings).
  • Prioritize opportunities for the greatest ROI (define) to your business.
  • Implement changes and monitor the impact compared to the forecast.

Pitfall: You Have Trouble Analyzing the Data to Draw Valuable Insights

Recommendations:

  • Have monthly and quarterly reporting completed by a professional analyst (either an internal full-time employee or outsourced consultant).
  • Invest in comprehensive insights, including behavioral, attitudinal, and competitive data.
  • Customize end-user training to job roles and job functions (one size doesn’t fit all).

Pitfall: You’re Unsure How to Take Action on the Data

Recommendations:

  • Make site change recommendations based on monetization models.
  • Leverage A/B and multivariate testing techniques to realize incremental gains.
  • Design and develop creative for different test variables and recipes.

E-mail me to let me know if you have faced or are currently facing any of these common pitfalls within your organization and how you solved them. I’m always interested in your feedback. At minimum, send me your score (number of pitfalls you’ve experienced), and I’ll tally them and report on how ClickZ readers did with this list.

Shane is off this week. Today’s column ran earlier on ClickZ.

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