Business usually works best when decisions are based on data, instead of “gut”. The headwaters of truth, for many organizations, lives within their customer base. Want to know which way to vector product development? Ask your current customers. For websites, it’s important to understand the distinct communities of interest that live on your site, and the directions those segments are heading.
But how can you collect the right data? We’re all familiar with the “garbage in, garbage out” axiom and we know some sources of data provide the basis for better decisions than others.
We share a common philosophy with Greg Linden (founder of Findory and formerly a key developer with Amazon) regarding the advantage of implicit vs. explicit personalization and search mechanics. We both believe that a more accurate picture of a person’s interests and preferences can be developed from their implicit online behavior vs. any information they may decide to explicitly provide themselves.
For Collarity, this is especially important because we cluster this anonymous behavioral data, creating implicit communities around key subject areas of interest on a web site. We then provide community-driven site search and content discovery relevance from these clustered groups of “like-minded” visitors. In addition, we develop a rich source of business intelligence regarding the behavior of a site’s most important customer segments (the Pareto 20% that normally generates 80% of the revenue).
Greg succinctly outlined the primary problems with explicit personalization data way back in an April 2004 post on his blog:
When you rely on people to tell you what their interests are, they (1) usually won’t bother, (2) if they do bother, they often provide partial information or even lie, and (3) even if they bother, tell the truth, and provide complete information, they usually fail to update their information over time.
The primary advantages of a system that leverages existing implicit anonymous search and browsing behavior, like Collarity’s or Findory’s, is the following:
- You do not alienate your web visitors by requiring them to provide explicit feedback like tagging, rating, or bookmarking. Logically, it would be best to use a system that takes advantage of the implicit dialog already happening between a site and its audience, rather than burdening users with a new one.
- You move from a very small minority of people willing to tag/rate (often 1% or less) for the benefit of other users on a site, to 100% participation - providing a much richer and complete data set to distill relevance from.
- An implicit system is much more efficient and is capable of operating in realtime (very important for certain sites), because it doesn’t rely on users themselves to maintain explicit feedback.
Greg, in a post on his his blog last week, pointed to yet another paper being presented at the WWW 2007 conference this week titled, “Open User Profiles for Adaptive News Systems: Help or Harm?”, and again concludes that explicit mechanics can lead to less accurate results.
Greg also reminds us of a great quote from a Jason Fry recommendation engine article in the Wall Street Journal that summarizes implicit vs. explicit truisms most of us are all familiar with:
When it comes to describing us as customers and consumers, recommendation engines may do the job better than we would.
In other words, we lie — and never more effectively than when we’re lying to ourselves … I fancy myself a reader of contemporary literature and history books, but I mostly buy “Star Wars” novels and “Curious George” books for my kid.
So, whether you’re using customer feedback to refine site search results, generate content recommendations, or figure out “which way the wind is blowing” with your most important segments, we think user actions speak “truer” than words.