Good on-site marketing, such as related-product promotions, encourages emotion-driven “joy buying,” potentially boosting per-customer revenue and profit.
Online shopping can be both a practical and an emotional activity. Often buyers begin an online shopping experience because they seek to save time, save money, or simply for efficiency; but special offers, site interactivity, or good merchandising can encourage impulsive purchases.
Academic studies have shown a relationship between what researchers call “the convenience maximization orientation” (when shoppers make purchases in such a way as to be more effective) and “the recreational orientation” or spontaneous shopping. The relationship between the practical, efficient shopper’s behavior and the spontaneous shopper’s actions is important for ecommerce marketers because it shows us that, in spite of shoppers who say, “I look for the bargains,” they can actually be influenced to act spontaneously from an emotional response. I like to call this emotional response “joy buying,” since shoppers may actually like it better than the more practical bargain-hunting, price-comparing sort of shopping.
In this edition of “eCommerce Know-How,” I am going to describe some of the trends in related product merchandising in the context of joy buying. My goal is to give you an overview of natural product relationships and behavioral product relationships, which you can use to improve how your online store manages related products.
Natural Product Relationships
Related products are a popular ecommerce site feature for one simple reason. They work. Customers like related products because they remind them that they need or may want, say, batteries for a camera, extra memory for a new laptop, or shoes that match a new dress. Online retailers like related product promotions because they increase per-customer sales, boost profit, and offset shipping fees, which are disproportionately expensive for the first few pounds shipped. Everyone wins.
The most common form of product relationships is ontological or natural relationships. For example, the popular Wii video game console is naturally related to a Wii controller or a particular Wii video game. The very nature of the products ties them together.
If nothing else, at least create natural product relationships on your site.
Collective-Behavior Product Relationships
Collective behavior can also help to relate products, tying together products that may not have a natural relationship or at least not a close one. Instead, we discover behavior-based product relationships by monitoring sales data and relating the products that often share a single shopping cart.
Perhaps the best way to describe collective behavior may be with a specific example.
Let’s assume that over time you notice that customers to your online store who purchase George MacDonald’s Adela Cathcart and J.R.R. Tolkien’s Lord of the Rings are also likely to purchase C.S. Lewis’ Mere Christianity. This is a collective behavior that you can begin to use to relate products.
Other than the fact that these are all books, there is not a clear natural connection between the products. MacDonald’s Adela Cathcart is a collection of short stories written in 1864. Tolkien’s Lord of the Rings is an epic fantasy adventure, and Lewis’ Mere Christianity is concerned with Christian apologetics. But all of the books’ authors are related in that MacDonald and Tolkien were from Scotland, while Lewis was from England. This sort of complicated relationship is not something that an ecommerce merchant would normally think of, but by monitoring the aggregated buying patterns of many customers overtime, this sort of complex relationship can become obvious.
A savvy ecommerce merchant will monitor sales reports for just this sort of collective behavior trend and create related product suggestions based on the observed behaviors. There are also software tools available to help identify these sorts of trends.
Community-Behavior Product Relationships
If we take our analysis and use collective behavior one step further, we can really get to the cutting edge of relating products, and thereby improve both customer satisfaction and profit.
Community or group behavior is discovered when we divide collective behavior trends by demographics or specific behaviors. The goal is to discover buying groups or personas within collective behavior trends that we can use earlier in our relationship with new customers—based on an assessment of which community or persona she matches.
Again there are software tools to help track these sorts of community trends.