Scouring for Sales: Why Better Measurement Yields Better Performance in the Search Strata
Internal Search — search within a site — is probably the single most important component of many sites. For retail sites with a large product mix and ad-based sites with lots of content, Search is absolutely vital to success. It isn’t unusual to have more than half of all visitor sessions — including the vast majority of the most productive sessions — include search as an essential component.
Unfortunately for web marketers, however, Search is one of the most difficult parts of a website to measure and optimize. Why? Search is — in a way — the ultimate “dynamic” page. It changes with every term entered and, potentially, with every new day on the site. It potentially routes to every single page on the site. It is entered from almost any page on the site. And, with entry, is associated a Search Term that drives the results. And that search term typically has tens of thousands of different values on a well trafficked site.
Each of these factors make Search challenging to measure. Most of the popular web analytics tools go at least part way to solving these problems. With fairly minimal setup, they’ll provide several types of analysis that are quite useful. You can typically analyze each of the following:
• Paths to Search
• Search Terms Entered
• Failed Searches (returned no results)
• Endpoint Conversion by Search Term
• Paths from Search
This seems like a fairly comprehensive list — but in actual practice it’s decidedly unsatisfactory in situations where Search is a major component of a site.
Paths to Search can be interesting for sites looking to understand when Search is being used as a fallback in a failed navigation session. By comparing Search routes (search is the next action from a page) to Total routes, the rate of fall-out to Search can be mapped for a complete site. And there are sites, in fact, where this is the most interesting Search analysis. But where search is an important first recourse, by far the most common path to search is from the home page, with most other pages having a fairly similar (and not necessarily bad) drive to search rate.
Measuring Search Terms Entered can also be revealing. For sites where Search is a “fallback,” highly-used search term may actually be indicative of failure (and often suggest holes in site navigation). For sites where Search is a primary option, search term volumes can often help track visitor interest patterns over time. Neither analysis, is really helpful for understanding or tuning Search performance.
Failed searches (where a visitor enters a term and gets no results) are a useful tool for tuning the operational performance of search. A failed search is nearly always a bad thing (assuming the term entered is at least borderline relevant). With a decent internal search tool, failed searches are usually quite a small percentage of the total. Where problems do exist, fixing them will have a big upside. In most cases, though, this analysis will be only sporadically useful in tuning search.
Search is often analyzed in terms of endpoint conversion. In this regard, Search is primarily viewed in comparison to non-search sessions — with designers trying to analyze whether search sessions are more or less productive than browsing sessions. This analysis is complicated for ad-based sites by the fact that search sessions are nearly always shorter than browsing sessions.
Conversion analysis can also be quite interesting and useful — but it’s necessary to put it into perspective. On both retail and ad-based sites, the visitor who searches often has a fundamentally different mind-set than one who browses.
On retail sites, search behavior is often indicative that the visitor is further along in the sales-cycle and has focused in on a specific product. On publishing sites, a search is generally indicative that the visitor has a particular information need. In either case, the main point is that a simple apples-to-apples comparison of search vs. non-search sessions may be misleading. Marketers should generally look askance at statements like “Search visitors are 40% more likely to buy than non-search visitors. They may be meaningful, but, equally possible, they may not!
This leaves the analysis of paths from Search. The function of search, after all, is to move visitors to the appropriate place in the web site. Typically, search competes with other pages (called Router Pages) that do the same job by presenting likely links to visitors as they move through one or more pages. To understand how well Search is doing this job compared to the alternative it’s essential to understand how Search routes visitors. Hence the importance of path from Search. Unfortunately, there are two problems with actually understanding paths from Search that make this by far the most problematic aspect of search to actually measure.
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