In IA Thought, Information Architecture

“The future is already here — it’s just not very evenly distributed.”
– William Gibson

As we move into 2017, we celebrate the new year and wonder at the incredible quality in much of our digital world. And yet consumer still use many systems that are consistently and demonstrably bad. What most of these systems have in common is poorly articulated, firehose deliveries of information.

I call these “high-information interfaces”—that is, sites that depend on the delivery and selection of a wide range of elements in order for a user to get what they need. The archetype of a high-information interface is Netflix or almost any e-commerce site.

There is broad consensus that many of these interfaces are bad, which is usually blamed on design. Information architects, however, don’t agree. User experience (UX) and design practices are extremely good right now. But UX is being overwhelmed by the information challenges of many system interfaces.

Start with Information Architecture

IAs have two major advantages as a starting point in these high-information environments:

  • An understanding of place-making in digital environments.
  • The need to define what information is actually needed before decisions about design occur.

To put it another way, the organization, sharing, and differentiation of information is critical to good design. Without it, designers can do little more than push against a flood.

IA anti-patterns of high-information interfaces

The IA issues that seem to be the most prevalent here fall into four major categories:

  • Zombie Lists – long, undifferentiated result sets.
  • Black Box – insufficient information scent to make selections (or rejections).
  • Ten-Stop Shopping – big gaps between user-oriented relationships.
  • Hey Stranger – no historical behavior to guide and assist in use.



Saaaaaaames…

Zombie Lists

As our options expand, so do our scrolls. The archetype of ecommerce isn’t a product page or a shopping cart, but a giant list of similar but not explicitly undifferentiated items. The core failures of almost every system with a large inventory can be seen in these lists.



Wow I know EXACTLY what’s in here…

Black Box

A close cousin to the zombie list, the black box anti-pattern occurs when a list of items in a list is insufficiently detailed to confidently make a selection or a rejection. If the only way to actually learn more about an item from a list is to click into it and peruse the item in more detail, the user may lose the thread and be unable to make a good selection between multiple items.

The example below shows how a Zombie List and Mystery Meat can exist in the same interface. It is from the Amazon App store, but really this problem is endemic in digital marketplaces today.

Amazon App Store


Ten-Stop Stopping

This is basically the Information Architecture of all e-commerce sites.

The simplest way to describe this is the number of times a consumer has to “reset” in a product hierarchy in order to complete a large shopping list. Because of how SKUs are organized on most e-commerce websites, food items are organized by type, not by related function.

So, for example, to get all the ingredients to make chocolate chip cookies, a user would have to dive into five or six diverse categories:

  • Seasonings and Spices – vanilla
  • Dry Goods – flour and salt
  • Snacks – walnuts
  • Dairy and Egg – egg
  • Oils and Dressings – oil
  • Baking goods – chocolate chips and baking powder

Compare this to a typical supermarket, where the person would end up in, at most, three aisles:

  • The baking section (for flour, vanilla, chocolate, and walnuts).
  • The oil section.
  • The dairy section.

This is the biggest problem with online shopping: it is not organized like a store. Every now and then a user will get lucky and be able to pick the next item in their list from the “related” sections that lie below the product, but this is a risky endeavor as well.

Hey Stranger

Closely related to ten-stop shopping. The implicit problem with any taxonomy is that it organizes certain things together and in doing so pushes other potential relationships away. One way to deal with this is to use personalization to drive selection. Yet many products, like television menus, don’t automatically start moving favorites higher into a pick list, or change a taxonomy to more closely accommodate the user’s past patterns.


Fighting the Anti-Patterns in High-Information Interfaces

Next time, we’ll talk about the organizational causes of these problems and how we can use these IA anti-patterns to address the four major causes of confusing high-information interfaces.

If you want spoilers, drop us a line!

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