As an Omniture consultant over the past six years, I’ve repeatedly seen how organizational issues – not necessarily technical ones – have impeded the success of many well-meaning companies in their quest to become more data-driven. Becoming data-driven requires more than just tools or technology – it requires supporting processes and people. Too often companies obtain the necessary technology, but don’t add sufficient resources or make changes to their existing internal processes.

Over the past several months, I’ve covered the “Seven Keys to Creating a Data-Driven Organization” through a series of blog posts or articles. If you didn’t have a chance to read through the series or view the webinar, here are the seven key principles with links to the individual articles:

  1. Secure an Executive Sponsor
  2. Align Implementation with Business Objectives
  3. Invest in Staffing and Training
  4. Establish and Maintain Corporate Standards
  5. Deliver Quick Wins to the Organization
  6. Validate the Data
  7. Hold People Accountable

Focusing on these seven principles can help position an organization for data-driven success. Most of the web analytics practitioners I’ve talked to would say they want to work for a data-driven organization . . . one day. It’s the dream scenario for a web analyst. Your analysis and recommendations are important, trusted, appreciated, and acted upon.

For most companies, the path to becoming data-driven is a work in progress. Some of you may be relieved to hear that your company isn’t the only one struggling with these principles. It’s true that some organizations are further along than others, and I haven’t yet found a company (especially a large one) that has mastered all seven data-driven principles. Sadly, some web analytics professionals have come to the conclusion that it won’t happen in their lifetime at their current employer and may already be on the job hunt. If your company wants to hire and retain the best web analytics talent, you need to be serious about creating and supporting a data-driven culture.

Data-driven roundtable insights

At this year’s Omniture Summit, Omniture customers were able to share insights from their companies’ data-driven journeys during a roundtable-format session. Most of the table discussions seemed to focus on aligning the implementation with the company’s goals through a clear measurement strategy. Here is a sampling of some key takeaways or discussion points that the client moderators shared with me:

  • Many companies don’t have a clearly defined web measurement strategy because they have too many cooks (departments) in the kitchen, they focus on soft goals that are difficult to measure, they are indecisive in separating what should be measured from all of the things that can be measured, and they don’t appreciate the full value of what web analytics can do for their organization beyond reporting.
  • Without a clear measurement strategy, you end up with mountains of reports and data which aren’t necessarily helpful to the business.
  • The best web strategies are focused on driving insights and actionable intelligence to improve future performance, not just a scorecard on past performance.
  • The two essential elements in establishing a web measurement strategy are defining/articulating the business goals and determining the KPIs that measure or influence how successful the company is doing in meeting those goals.
  • Determining the business goals seems pretty straightforward, but is often difficult and contentious in practice, especially in larger organizations.
  • When interviewing stakeholders for your measurement strategy, interview at both management and individual contributor levels. Then circle back with the larger group to introduce findings, gain buy-in, and plan next steps.
  • Focus on the highest value KPIs (they’re called “Key” Performance Indicators for a reason).
  • In some cases there is no way of directly measuring performance, so proxy indicators need to be used.
  • KPIs should cover not just the top-line results (e.g. sales, leads, etc) but also the key levers or “supporting/contributing metrics” that impact those top-line KPIs. For example, if the top-line goal is increased sales, the supporting metrics may include things like conversion rate, average order size, leads, and retention rate.
  • Different parts of the organization may have different reporting needs in terms of which KPIs are important, the level of granularity required, and the area of the business they are interested in.

As I mentioned above, these comments were only a sampling of the takeaways and key points taken from this roundtable session. The engaged discussions at the tables showed how this topic has become top-of-mind for many concerned web analytics professionals and forward-thinking organizations. It’s great to see how web analytics is maturing as a discipline at both large and small businesses.

I hope this series of articles has helped you to pinpoint key areas where your organization can improve in order to become more data-driven. It would be great to hear insights from practitioners who are experiencing these organizational challenges first-hand. I’d love to hear if I’ve missed a key area or principle that has helped or hindered your company in its unique journey. As the late Jim Rohn stated, “Labor gives birth to ideas”.

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