People spent $54.2b on fashion eCommerce in 2013. This is the second largest eCommerce category after electronics and it’s predicted to reach $87.8b in 2016 (eMarketer). What makes fashion eCommerce so alluring? How is fashion eCommerce different from “traditional” in-store fashion? What kind of opportunities has eCommerce created in fashion and what role does analytics play in the growth of websites and apps?
The fashion industry is unique in its need to reinvent itself every season. Customer preferences, tendencies, needs and desires change all the time. This means that fashion has a lot to gain from applying and leveraging behavioral analytics in order to get the right offers to the right shoppers at the right time.
In the process of going online over the past ten years, the fashion industry has undergone not only cultural business changes, but logistical ones in terms of stock, shipment and storage. To state the obvious: fashion went global. Apparel is seen and purchased from every country in the world. This change entails more opportunities for retailers and consumers, but also much more brutal competition. The ease in which a consumer can switch between sites is basically a click away.
Another aspect which distinguishes current fashion industry culture from the past is that now everyone is a fashionista. Previously, top designers, fashion reporters and business analysts were absolute monarchs. They “wore the pants,” if you will, deciding what, where and when we should wear what we wear. But as fashion went digital, designers’ authority has diminished. Now social platforms rule the scene with likes, dislikes, comments and shares for looks, apparel and style. Anyone with a smartphone can become a thought leader.
The integration between eCommerce and social platforms opened new horizons. Mickey Drexler, chairman and CEO of J. Crew, said analytics play a major role here: “Digital marketing and social media have played an important part of our strategy in our recent history and are among our most effective marketing tools. We have found that customers who engage with us via our social media outlets generally spend approximately twice more than the average customer” (Business of Fashion).
Analytics are vital to the growth of any business which deals with an infinite amount of information. Tracking, measuring, analyzing and proactively predicting customers’ actions and interactions – all these are essential for the optimization of results. The ability to personalize offers is especially useful in fashion. After all, it is “tailor made”… The implications are endless, beginning with an accurate and detailed reflection of KPIs, to segmentation and targeted marketing campaigns, calculating Return on Investment (ROI) and predicting future trends. Digital retailers can act in real-time to drive Lifetime Value (LTV) and loyalty. They can also anticipate what costumers actually want to buy.
Analytics were always part of the game in terms of quantities and logistics, but going online introduced new metrics such as traffic, eyeballs, conversions, click trough rates (CTRs), cost per click (CPC) and cost per acquisition (CPA). Behavioral analytics provide more insights to help understand consumer needs and forecast what customers will order (read more). To get it right, one must go beyond these metrics with behavioral data. A few examples are:
- Sessionization: is the session too short because customers don’t like what they see, or pages don’t upload fast enough? Do customers abort prior to completing because it takes too long to complete a purchase?
- Intervals between sessions: how often do customers come back? What does it mean in terms of retention? Who churns?
- Path analysis: what is the sequence of events that a customer does before checking out? What is the sequence of events a customer does before abandoning a page or app?
- Cohort analysis: identifying and grouping customers according to common behavior, like frequency of use, and applying a specific marketing strategy which corresponds to this behavior.
The constant changes in fashion eCommerce are a challenge. Retailers can react to these changes in trends and customer preferences by applying innovative analytics, thus staying one step ahead in such a competitive landscape.