Information Architecture Expl(AI)ned

Information architecture is the foundation for an Artificial Intelligence — augmented Customer Experience.

We’ve all had an idea of something we wanted to buy, maybe a new drone, or maybe you’re researching a new idea/concept for an article you want. So you online type in a few search words but the search engine results are a bit weak. You try again with another search term and still, can’t find what you’re looking for. Your enthusiasm dampens as you work your way through webpage after webpage of irrelevant/mildly useful information that isn’t really helping you accomplish your task. Sound familiar?

Did the search engine fail us? No. The root of this problem is disorganized information (content) on a website due to a lack of developing a way users can find information. Organizing information so that it can be found efficiently is called Information Architecture (IA).

Finding relevant information on a webpage is hard if the content in it isn’t logically structured. The role of an Information Architect is to categorize, label, and tag information to make content on a webpage easier to find.

To understand the importance of using an information architect, picture the following: you have dozens of spices in your kitchen, some spicy, some mild, some are aromatic. When you need one you literally have to open each on since they’re not labeled. When you do open them you still have to taste it since you don’t know if they’re spicy or not. We can all agree that it would be incredibly inefficient for you to sort through all these everytime you needed a specific one.

So you buy a spice rack and get to work. You set aside cabinet space designated for those spices, you’ve categorized. Then, you organize the spices on the rack; spicy goes on top (you use these the most), mild goes in the middle tier, and aromatic goes at the bottom, this is creating a hierarchy structure (labeling), then, you write the name of each spice on the bottle in a visible place (tagging). We can agree that this approach is much better than having a chaotic pile of mystery spices and playing the guessing game, right? The benefits of organizing your spices are threefold: You spend less time searching for the spice you want, you reduce your frustration level and you may increase the overall experience of cooking.

With the spice example in mind, this is exactly what information architects do; they take the content of a webpage and organize it in a way that makes sense for you (the user) to navigate and locate what you’re looking for, or in other words, it increases the usability.

Usability, in this case, decreases the frustration for the user to find what they want to find and exactly when they want to find it. Whether it is information, a product or customer support. Crafting the information logically also increases ‘stickiness’ — the time a user spends on the page, helping the user stay in one place and complete the task they set out to do.

The usability of any page is greatly improved with Information Architecture (IA), but there are a few points in the customer’s journey for information that still leave something to be desired.

First off, while IA organizes the content within a page, that content might only be available for search (or recommendation) if the exact term is entered. For example, you’re on your favorite news site with the intention of gaining information on current economic events. You read a few articles about the current situation, but find that the ‘suggested content’ is giving you information from a couple years ago. You scroll down only to find that the content is getting more unrelated, and soon you disengaged (i.e., get distracted) and find yourself looking at celebrity gossip.

The problem here is that the IA can’t always properly find the associations between what you’re searching for and relevant content. In the aforementioned search scenario, trade deals and celebrities are categorized under ‘international news’ but the association between trade deals and what you’d like to continue seeing isn’t there. This is a classic IA problem.

Now, while it may not be possible to map out all the associations of interest with other articles, what Information Architects can do is work on defining and refining similar categories, labels, and tags. But as the availability of information grows exponentially and categories expand, it becomes difficult for any IA to manage.

Add to the growing information and category expansion the fact that many users are now engaging websites through different devices (e.g., laptop, mobile phone, smart tablets) which bring up the issue of ‘presentation’ per device. This means that the architect now has to take into consideration how the information is displayed on different devices, operating systems, and browsers while still making it easy for the user to navigate and find what they’re looking for efficiently.

On the other side of this equation, marketers and customer experience designers recognize that a user might be looking for something across different channels and would ideally, like to be able to suggest their products or services in the form of ads, marketing emails and website recommendations (Think about Amazon’s ‘Customer’s Also Bought..’ recommendations). This helps the user find items associated with their needs, and it helps marketers sell more.

IA can categorize and tag similar items, but referring and recommending products or services that a customer is most likely to want is a challenge. For an IA to be able to recommend or suggest a product is easy when the number of products are few. But what happens when the number of products, accessories, and options exceed, let’s say, 1,000. It would be next to impossible for an IA to anticipate and architect every possible combination a user (client) might need. If a user bought a mobile phone, which accessories should be shown? In what order? IA alone doesn’t have the capabilities to solve this. It is, however, certainly the foundation.

Enter Artificial Intelligence (AI). It’s the missing puzzle piece to optimizing the customer’s experience from their first search attempt to finding the right product or piece of information they needed.

Artificial intelligence (AI) are programs or algorithms with the ability to perform complex predictions and associations from massive amounts of data that would require an impossible amount of time, effort, and manpower to process. AI algorithms learn from data and use the data to predict patterns on a scale that no team of human IA would be able to do.

Where the limits of an IA’s processing ability ceases to be effective, that’s where the limitless possibility of AI exists. Using AI to help IA develop better website flows is how users will be able to find what they’re looking for much quicker and with less frustration.

Soon there will be an algorithm to help you sort your spice racks more efficiently. And, don’t be surprised if this spice rack is connected to the Internet and is able to predict when you run out and therefore it