I want to share a useful tip about Auto-Ranking since an increasing number of Omniture Merchandising customers are taking advantage of this feature. For those of you who are new to Omniture Merchandising, Auto-Ranking is a means to use product data captured by analytics to adjust the ranking of site search results or to drive merchandising actions triggered by specified data conditions.
We’ve found that one of the most critical determinants of Auto-Ranking success is ensuring retailers properly set the “Best” and “Worse” values in the attribute files driving their ranking formulae.
What do the “Best” and ”Worse” values mean to me and my data?
The Best and Worse values are, simply put, your top and bottom of the range for that the particular metric or data point. So, in the case of conversion, perhaps the range is from 0.00% to 10.5%. In the case of inventory the range could possibly go from 0 to 100,000 units.
Why are these values so important?
These values are very important because they will then determine where a particular product’s metrics will fall within the established range for that metric.
In the case of conversion you would want your Best and Worse Values to only range from 0.00% to 19.99%, for example (you’d want to use the highest number you’re likely to experience). This will give you a true ranking of the Conversion metric.
On the other hand (and not best practice), if the conversion range was set at 0.00% to 100.00% then all the actual conversion data will appear to be ranked quite close. The deltas between a 4.5% conversion and a 6.5% conversion will appear to be less than a 2% difference when it really is a much bigger difference from a conversion perspective. The conversion scores of 2.5%, 4.5%, and 9.9% are just too close together to range them from 0–100. They must be ranged must closer to produce good Auto-Ranking results.
Remember – it’s all relative. Your merchandising strategy depends in large part on the numbers, but the key to really taking advantage of them is to understand what they really mean relative to business goals. Take the time to check on the Best and Worse values that you are setting in your data feeds – it will really pay off.