by Todd Scholl
Special to the eTail Blog
In the world of ecommerce, there are a variety of different options when it comes to metrics. Without a good framework, accurate interpretations of these metrics can be challenging. Today’s merchandising, online marketing, and ecommerce managers have complex jobs from optimizing their customer experience and site design to maximizing sales and managing ROI of their technology partners – all without disrupting the shopping funnel. Like any business investment, they are accountable for measuring the return of their personalization efforts. With so much at stake, where is the best place to start?
Before you can define what metrics work best with regard to personalization engines, you must understand one key factor. Today’s methods for benchmarking are often hampered with inconsistent tracking and reporting metrics that are out of context with regard to the segment group targeted, the date range in which the purchase is occurring and the channel and vertical in which the personalized recommendations are used. Clearing up these inconsistencies is the only way to truly measure the effectiveness of your personalization efforts.
Segmentation Defined: Who are you targeting?
Carefully defining the target of your personalization efforts is essential. To accurately measure how recommendations perform in a given vertical or channel—whether it be web, email, mobile, call center, or in store—online and multi-channel retailers must first distinguish between customers who interact with the recommendations and those who don’t, called responders and non-responders respectively. Responders are typically your best customers. They spend more time on your site, convert more often, spend more, and have a higher propensity to return than non-responders. As a result, they have distinct conversion behavior that must not be mixed in and confused with the conversion behavior across all shoppers in a channel.
Demand is essentially revenue. While demand can be sliced and diced into many segments, the first step to increasing your revenue is narrowing your focus. When it comes to personalization you want to be looking at responder and recommendation demand. Personalizing responder’s and other shopper’s recommendations is the single best way to motivate them to engage more as this can help them recall forgotten shopping carts, present items they want most or highlight items that are similar to what they have been looking at. In the end, with personalization strategies implemented, demand will increase as will, hopefully, profits.
In order to understand how well your recommendation system is working for you, it will be helpful to look at responder demand, recommendation contribution and average order value. Here are a few aspects you may want to analyze:
- Which strategies performed better against your baseline?
- Is your margin staying steady or increasing?
- What were your measurements before and after your personalization efforts or after changes to your personalization strategies?
- Are more shoppers responding to the strategy than non-responders?
As with any change, measuring the direct effect on business is an important aspect to determining success. The ability to define your recommendation demand in concrete numbers is THE metric to measure success from testing and optimizing personalization strategies.
Todd Scholl is the Director of Marketing for Certona, a personalization and revenue optimization provider for online and multi-channel retailers. To get the full version of Part 1 & 2 of Certona’s new industry-wide reference guide, click here.