Google Search Appliance Creating the Search Experience - Manual (Page 39)

Google Search Appliance: Creating the Search Experience Best Practices 39
Getting Baseline Measurements
Before you begin personalizing the search experience, identify the initial state of the search experience
by taking baseline measurements. You can get baseline measurements by:
1. Generating an advanced search report (see “Generating an Advanced Search Report” on page 40)
2. Calculating the percentage of satisfied queries (see “Calculating the Percentage of Satisfied
Queries” on page 39)
3. Calculating the average click rank (see “Calculating the Average Click Rank” on page 39)
As you personalize the search experience, continue to generate advanced search reports that you can
compare with baseline measurements.
Calculating the Percentage of Satisfied Queries
Using the information in the report, you can calculate the percentage of satisfied queries. A satisfied
query is a search that ends with a user clicking on a result, as indicated in the report by a click type of c.
When counting the total number of satisfied clicks only count the first click type of c after the first load.
The formula for calculating percentage of queries that are satisfied is:
total number of satisfied clicks / total number of queries x 100=percentage of satisfied clicks
For example, if the total number of satisfied clicks is 54 out of 90 total queries, the percentage of
satisfied queries would be 60%.
Calculating the Average Click Rank
To calculate the average click rank, you must first identify the absolute click rank for an individual entry.
Using the click rank alone will not give accurate results because a click rank number does not indicate
the results page of the click. For example, when a user clicks on the first result on the first page, the click
rank is 1. However, when a user clicks on the first result on the tenth page of results, the click rank is
also 1. By using the following formula, you can account for the page of the user click.
The formula for identifying a click rank for an individual entry is:
(click start x 10) + click rank=absolute click rank
where click start is the page of the click
The formula for calculating average click rank is:
total of absolute click ranks/number of clicks=average click rank
For example, if the total of all the click ranks was 255 for 75 clicks, the average click rank would be 3.4.
Analyzing User Clicks
To analyze user clicks, determine how users are searching based on click type and how the search ends.
For example, you can identify top queries by sorting an advanced search report by query. After sorting
queries, you might check the click types on the top queries. For satisfied queries with low click rank and
unsatisfied queries, you might improve search by creating a KeyMatch, applying source biasing, or
developing a OneBox module.
You also might want to identify IP address ranges for most queries. This might indicate that members of
a specific group of users, such as the sales department, are all searching for the same information.You
might consider personalizing their search experience by creating a collection (see “Segmenting Data in
the Search Index” on page 83) and front end (see “Creating a Front End” on page 90) especially for this
group.