There are many ways to make it easy for customers to look through online merchandise. Jeff Schueler of Usability Sciences Corp. details the best approaches.
For some reason, browsing the categories and subcategories of an online store satisfies a basic human shopping need of seeing the contents of a store in a way that searching does not. In fact, retail sites usually host three times as many browsers as they do searchers, making the stakes in creating successful browsing quite high.
As we have seen in dozens of analyses, failure to find a product influences more than just conversion rates. The negative experience carries over to brand affinity, customer satisfaction, likelihood to return to the site and the inclination to recommend the site to a friend. The navigation preference of the majority of visitors makes it essential that your information architecture supports easy, efficient browsing.
Not so easy
Creating easy and efficient browsing is easier said than done, however, and comes under the category of effective category management. What that means is that you need to understand your data architecture and present your products in ways that customers find easy and intuitive.
Improved category management offers the promise of higher rates of visit success at each stage of the purchasing process. Data suggest that there is, for each site, a set of optimum ratios between categories and sub-categories, and between sub-categories and product pages. Clickstream data and survey responses captured as an integrated data set can allow online retailers to understand the relationship between categories and sub-categories and between sub-categories and product pages and address the persistent problem of ineffective category management.
Here`s the story behind the idea.
Category management emerged as a crucial component of site design for the online grocery sites that arose in the late 1990s, many of whom became our clients because of our long-standing relationship with Procter & Gamble. What, they all wanted to know, is the best way to arrange tens of thousands of items so that visitors could complete their grocery lists easily and quickly?
Questions such as "How many high level categories should there be?" and "How many sub-categories in each major category?" demanded answers different from those that worked for the brick-and-mortar grocery stores.
Where`s the mustard?
Where should mustard go, anyway? In the physical store, it didn`t make sense to stock mustard in more than one or two places--condiments or sauces? But the online world allowed new possibilities. What about placing mustard in the meat section next to the hot dogs? Or in picnic ideas? Or with imported or specialty items? Through an advanced card-sorting methodology called Content Aggregation, users told our clients that mustard could go in any category that made sense to them. Having mustard at hand for any shopping context, they said, delivered on the promise of convenience.
Freed from the constraints of not being able to stock physical product in multiple locations, e-grocers listened to their customers and put Cheerios in cereals, in breakfast foods, in the kids section, and even linked them into the nutrition and specials and promotions sections. Placement proliferation worked--for a while.
What seemed like a good idea, though, brought its own problems, a fact that screams out from visitor feedback data across the spectrum of Internet retailers. Whether you are selling apparel, gifts, hardware, electronics, or sporting goods, you have the same issues as the online grocer: How many high level categories should there be? How many sub-categories in each? And in how many sub-categories do you place the same item?
Most online retailers expect their merchandisers to answer these questions. Many of these merchandisers have their roots in the brick-and-mortar world. The online world is a whole different game, and the new virtual merchandisers need ways to measure the effectiveness of their decisions. When merchandisers take the lead in designing the category structure, it`s a matter of good news and bad news. If the merchandisers establish common standards (based on proven methods) across all departments, the result can be a consistent, user-friendly category structure. But if different merchandisers are responsible for different categories, and the standards vary across departments, inconsistencies will result in shopper confusion, failed visits, and lost revenue.
Devising a system
Each retail site (and the online retail industry as a whole, for that matter) needs a systematic way to assess the efficacy of its content structure. And that method must look at the data from the user`s perspective--not just the merchandiser`s. Navigation behavior linked to visit success (based on intent) and conversion rates can tell online merchandisers what works for their shoppers and what doesn`t. The site can then make intelligent decisions on how to manage the categories in the store.
Here is what we have found in the research we`ve done:
l The more often visitors find a product, the greater their likelihood to report their visit a success. In navigational terms, the higher the number of product page loads per subcategory visited, the more successful they feel. It appears that a ratio of 1:2 (that is, you get 1 product page load for every 2 subcategories clicked on, giving a value of 0.5 in the table) indicates success in a category. We have seen categories on sites that only got 1 product page load per 10 sub-categories and their success rate was abysmal. The table shows example ratios from an online sporting goods store. Visit success evidently correlates closely to product-to-sub-category ratios.
l Successful visitors browse more subcategories per category visited than unsuccessful visitors. Because it is easy to find products, visitors tend to look into more sub-categories and investigate more products. In sites we have looked at, a ratio of 3:1 (sub-categories-to-categories, giving a value of 3.0) or higher is symptomatic of successful visitors.
l Visitors who actually buy have much higher sub-category-to-category ratios and product-to-sub-category ratios loaded than non-buyers.
If you look at the example table it is clear that the baseball and basketball categories were well received by site visitors and that the "outdoor" categories of camping and fishing were a comparative disaster. What caused this to happen? This particular retailer wasn`t focused on the outdoor market. Its selection in camping and fishing was very thin. Visitors expected these categories to be stocked like bassproshops.com and they weren`t. The bigger problem was that those categories were causing drops in customer satisfaction and brand affinity. The retailer would have been better off eliminating them from the online store.