How to use "return frequency"

A few days back I spoke about the importance of return frequency (Are you looking at your return frequency, published on Monday, 11/9). I wanted to elaborate on how this metric can be applied to build a competitive advantage.

The purpose of a detailed analysis into return frequency is to "deaverage," i.e., help us understand our user segments and their corresponding site sections. We need to measure traffic at page level, aggregated to site sections, if that is relevant for your business. Secondly, we need to segment our users based on engagement with our content areas. The two data sets provide a unique look into site engagement that can be utilized to tailor the user experience.

Similar customization has been adopted in brick & mortar establishments for some time now, with a focus on streamlining product search and consumption. In a web experience, this can only be achieved when we track user data at page and/or site section level. Also, important to note here is that you should not be afraid to dump the pages/sections that are not meeting user needs and/or not aligned with your strategy and core strengths.

Once the data is available at this granularity, we can then understand if the user need is being met, monitor trending of popular pages in a given week/month and adopt editorial programming accordingly, and evolve monetization strategy based on targeted advertising, product displays, etc. This not only makes the site more dynamic and fresh, it also generates user interest that keeps driving return frequency. By the way, for you business planning folks, this data will be extremely helpful in defining strategic road-map and traffic/editorial/revenue targets for your next planning cycle.

Are you looking at your "return frequency" data?

Return frequency is probably one metric that is representative of customer satisfaction irrespective of the industry.

In a web based business, however, it is both, difficult to accurately measure return frequency and hard to utilize the data (provided we have a good sample) to promote our business.

In most reporting tools, return frequency is reported at site level - that is, how many times an average user is coming back to our site. And, therein lies the problem. First, it is only speaking about an average user. Second, it is only measuring the metric for the entire site. Unfortunately, there is no such thing as an average user, and more than likely, your site has more than a few dimensions. Consequently, a site-wide metric is only good for an "average user" - not a winning strategy for any business.

So, the first step is to adapt your anlytics software to show page and/or site section level return frequency. Then "de-average" the users into defined buckets, and classify site sections based on repeat visitation data. Combining these two insights will help you understand why a user is coming to a particular site section/page at your site. You can then tailor the experience to meet "most" needs of "majority" of users to the above site section/page. The reason I say "most and majority," is to emphasize that trying to classify 100% of your site usage will probably not yield best ROI on the effort invested. Picking top 5 or 10 site sections, for above improvements, will be a good start.

Do you have a specific question on this metric or others that you would like addressed? I promise to move it up my list of topics to discuss :)