Fix Navigation to Improve Conversions, Part 1

  |  April 16, 2004   |  Comments

How to help online customers find what they want (even when they don't know what they want). Part one of a three-part series.

The biggest challenge e-commerce sites face is broken navigation. Traditional navigation methods are what's behind embarrassingly average 2 to 3 percent conversion rates.

One approach that adversely affects navigation and Web site structure is the information architecture technique called card sorting.

Traditional card sorting is flawed. Usability expert Jared Spool agrees. He recently wrote about his own Category Agreement Analysis (CAA) card-sorting technique. In standard card sort, you put the one product per card on index cards without regard to category. Users then group cards into user-defined categories. CAA differs by allowing users to sort items into multiple categories.

According to "Information Architecture for the World Wide Web," card sorting "can provide insight into users' mental models, illuminating the way that they often tacitly group, sort and label tasks and content within their own heads."

That's all wonderful, but it fails to recognize the difference between usability in a controlled environment and the voluntary nature of an online shopping experience. Below, what's wrong with CAA (and most other card-sorting approaches) and an alterative to help you sort better.

People approach categorization by identifying similarities in an upward process. If I say "cat," you think a cat is a feline, which is a mammal, which is a living thing. We intuit from specific to general. This right-brain, holistic approach considers how things are connected to other things. Only then do we potentially look back to see how top-down can illustrate differences, not just similarities.

CAA takes the opposite approach. It sorts based on top-level category, then requests possible secondary categories. It requires general-to-specific reasoning, which is left brain (more mechanical). No foundation is built by first observing similarity. Instead, it requires differentiation.

CAA also assumes people who perform categorization represent a single, homogeneous type of site traffic, another mistake. Usability folks focus on usability first, persuasion second. Survey solutions suffer the same limitations: Participants are in a lab looking at a Web site. It can't be assumed they'll look at it the same way under natural conditions.

The technique is deeply flawed, but it's how categorization for 99 percent of e-commerce sites is performed. When Sally looks for a red sweater online, she's successful because she knows exactly what she wants. The clothing site's navigation reflects women's clothes --> tops --> sweaters. The site created a category path she can use to navigate from general to specific to find that elusive red sweater.

Visit your own site as if you knew exactly what you wanted to buy (start with a search engine query, if you like). Start clicking. Ask a colleague to count your clicks. How many does it take to complete your purchase or inquiry? The number is your minimum-clicks-to-buy metric. This works only because of two inherent assumptions: you know precisely what you want (your brain already performed the specific-to-general categorizing) and the retailer implemented that path in top-down categorization.

What about people who shop without knowing precisely what they want? Say Sally's boyfriend Joe wants to buy her something for an upcoming winter trip to Quebec. He starts in "Women's Clothes" but is quickly lost. It doesn't help that 53 percent of CAA card sorters put the red sweater in "Tops." He isn't certain what he's looking for. He may narrow his search using a top-down approach but doesn't classify what he seeks that way. Joe's shopping in a right-brain mode. His goal is more emotional than the impersonal "Can she use the gift in Montreal?" His question isn't solely "Will it keep Sally warm?" (Imagine her reaction when she gets a hot water bottle!) CAA didn't help Joe accomplish his goal.

Visit your site as if you were browsing. Again, ask a colleague count the clicks. How many does it take to complete a purchase or inquiry? The number is your target-clicks-to-buy metric. Most shoppers fall into this category. Look at the top keywords on shopping search engines. Notice how imprecise they are.

Persuasion architecture demands you first identify each persona. Then, research keywords each is likely to use. To do this, use services such as Wordtracker, Overture's and Google's keyword suggestion tools, Web logs and internal search queries, and interviews with customers and customer-facing employees (sales and service reps). You'll get lots of clues for labeling categories. Finally, plan each persona's site experience as a persuasion path.

Only when that path is complete can you look for commonalities between pages that indicate globally accessible links and other categorization techniques.

Now can you perform any card-sort variants. CAA's statistical, left-brain approach should be applied only over a set of field-test respondents who can be identified as given persona archetypes. Joe and Sally are better served by the results of people like them, who categorize the same way they do.

In part two, I'll take you on a tour of some popular sites and demonstrate what's wrong with navigation.

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ABOUT THE AUTHOR

Bryan Eisenberg

Bryan Eisenberg is coauthor of the Wall Street Journal, Amazon, BusinessWeek, and New York Times bestselling books "Call to Action," "Waiting For Your Cat to Bark?," and "Always Be Testing." Bryan is a professional marketing speaker and has keynoted conferences globally such as SES, Shop.org, Direct Marketing Association, MarketingSherpa, Econsultancy, Webcom, SEM Konferansen Norway, the Canadian Marketing Association, and others. In 2010, Bryan was named a winner of the Direct Marketing Educational Foundation's Rising Stars Awards, which recognizes the most talented professionals 40 years of age or younger in the field of direct/interactive marketing. He is also cofounder and chairman emeritus of the Web Analytics Association. Bryan serves as an advisory board member of SES Conference & Expo, the eMetrics Marketing Optimization Summit, and several venture capital backed companies. He works with his coauthor and brother Jeffrey Eisenberg. You can find them at BryanEisenberg.com.

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