When talking about e-commerce or online retailing metrics, there is a standard set of metrics that everyone must track. However, every now and then someone discusses a non-obvious set of relationships between a metric and its consequence for revenue. One such article on GigaOm recently talked about two such metrics:
Revenue Per Visit
Revenue Per Minute on Site
I am especially interested in talking about Revenue Per Minute on Site, since it holds some important consequences for the online retailer and more so because that article in itself did not go into the details of how this metric could be maximized.
Firstly, this metric is closely tied to the most simplest of qualitative measures, i.e. user experience or in more concrete terms, the number of clicks it takes a visitor to buy an item. Higher the number of clicks, the longer time it will take the user to buy a product and this will lead to a lower revenue per minute on site.
Secondly, even when the site is optimized from the landing page to the payment stage, there is one critical aspect that is generally over-looked, i.e. site search. The flow from the landing page to the payment stage is mistakenly modeled as a sequential process rather than an iterative one. While a sequential process would assume that the visitor finds the product of his/her interest in one step, in reality, it takes a couple of iterations. If one accepts that search iterations are a reality of the purchase process, then it becomes imperative that those search iterations be minimized or eliminated altogether, thereby reducing the time to purchase the product. Reducing the time taken to purchase directly increases the revenue per minute on site. An awesome site search then becomes the key to reducing those iterations and increasing revenue per minute on site. This is the first actionable insight.Finally, time to purchase is not just about revenue but also directly related to operational expenses. The longer a visitor stays on the site, the more data center resources it takes to serve that visitor. This is where the type of visitor starts mattering, i.e. one who is a browser versus one who is a buyer. A browser does not end up as a revenue per visit figure while a buyer does. In effect, online retailers are then basically expending data center resources on browsers.
The challenge here is to convert even browsers into buyers. The key is knowing that there is a threshold of product attractiveness, price and delivery time, etc. at which even browsers can be turned into buyers. This is where applying behavioral targeting techniques figure. Measuring visitor behavior and using these metrics to tailor search results for turning browsers into buyers is the second actionable insight towards increasing revenue per minute on site. An ideal e-commerce search should enable such behavioral targeting along with promotions and merchandizing to display products in search results in order to grab browsers’ attention. The sooner you catch the attention, the shorter is the time to purchase and higher the revenue per minute on site. Whether this happens through search or through the catalog browsing, you need to apply similar techniques in both purchase paths.