Web Analytics in an organization should be just like a development cycle starting from requirement gathering to validation. Below is a visualization of an ideal Web Analytics process. This process is more suited for tech organizations which already have defined KPIs and regular weekly/monthly releases of new features on their website.
1) Requirement Gathering: This is the start of the Web Analytics process and it deals with an Analyst collecting tracking requirements from stakeholders. Similarly this step will also involve review of feature specifications of new items that are part of a release cycle. An example of a new feature can be a new page being added on the website or a new outgoing/external link being added or even an A/B Test.
2) Creating a Tracking plan: Once all the requirements have been gauged, the Analyst will create a Tracking Plan/Analytics plan/Solution Design document to define the variables for Web Analytics vendor tools (custom variables, pagename variables etc) like Omniture SiteCatalyst, WebTrends, Clicktracks or Google Analytics. This is usually an excel document containing a matrix of all the variables and their corresponding values.
3) Development: In this step, the Analyst will usually work along side a developer to get the features implemented on the website. This step also requires the Analyst to assist the developer with any questions she has regarding the Web Analytics code or the Tracking plan. This applies especially to new developers who do not understand the Web Analytics snippet.
4) Data Validation: This step deals with the QA/testing of Web Analytics data that land up in the Web Analytics tool. I have written a comprehensive article detailing the importance of this step as this in itself is a separate process.
5) Reporting/Analysis/Recommendations/Next Steps: After the data is found to be clean, it is the responsibility of the Analyst to report numbers resulting from the feature which went live during the previous release cycle. The Analyst will also provide analysis (explaining the data or conversion etc) and possible recommendations/next steps to improve the website even more.
This, according to me is an ideal end to end process which organizations should be following to manage Web Analytics. It is vital for a big organization to incorporate these steps in their overall plan for Web Analytics to ensure smooth functioning.