Navigating the Complexities of Information Architecture vs Data Architecture

“Questions are never indiscreet, answers sometimes are.”Oscar Wilde

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Frequently asked question pages. Love them or hate them, I don’t think they’re going anywhere anytime soon. This debate has been going on for quite some time and there is an equal number of opinions on both sides of the FAQ fence. Nielsen Norman Group’s Susan Farrell says FAQs can still add value to a website when done properly, and Gerry McGovern says FAQs are the dinosaurs of web navigation.

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So, how do we really know for sure if they will or won’t add value to a design? Like anything in UX, you have to test it! I don’t know about you, but I’m a shake-it-and-see-what-falls-out kind of UXer, so naturally I decided to run a Treejack study. Scouring the web one fine day, I came across Sainsbury’s Active Kids. Its FAQ page was unlike any I had ever seen and I knew I’d found the one. I was also curious to see how it would test with people who don’t use the website — after all, anyone should be able to use it. Since Active Kids is an active lifestyle program for UK schools and sports clubs, I recruited my participants entirely from the US.

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Pull up a chair and get comfy because what I found out should serve as a lesson to us all.

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Why Active Kids? 🤸🏼

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First of all, why did I choose this in the first place? The Active Kids FAQ page caught my attention for three main reasons:

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• structure
• labels
• content

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The structure of this FAQs page is quite deep, complex and very different from the rest of the site — almost like another information architecture (IA) had been built within the main structure. Imagine you have a large warehouse with hundreds of shelves, and then somewhere in the middle of it, someone builds a house — that’s how it felt to me.

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There are two ways to get to it: through the “Help” label on the top navigation bar and the “FAQ” label in the footer. It also uses a combination of drop-down filters that the user needs to apply, but it also has automatic filter options and confusing labels that can send you down a path you don’t necessarily want to take.

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I also found it very interesting that most of the information contained within the FAQs section cannot be located anywhere else on the website and most of this is essential to gaining a fundamental understanding of what Active Kids actually does. Adding to the house in the warehouse analogy, it’s like the house holds all the key information the warehouse needs to function, but no one knows which room it’s kept in.

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Setting up the study 🛠️

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Treejack was the perfect choice for testing the findability of information on the Active Kids FAQ page and I decided to test the IA of the website as a whole — this means both the warehouse and the house. I couldn’t just test the house in isolation because that’s not how a user would interact with it. The test needed the context of the whole site to gain an understanding of what’s going on. Creating a Treejack study is quick and easy and all you have to do is build the structure out in a basic Excel spreadsheet and then copy and paste it into Treejack.

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My next job was to determine the task based scenarios that my participants would use during the study. I decided to choose nine and all were derived from content located in the FAQs section and related to tasks a user might carry out when investigating or participating in the program. Once I had my tree and my tasks, all I had to do was set the correct answers based on where the information currently sits on the Active Kids website and I was ready to launch.

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Recruiting participants for the study🙋🏾

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In my experience,recruiting participants for a Treejack study is quick and easy. All you have to do is determine the screener criteria for your participants and Optimal Workshop takes care of the rest. For this study I requested 30 participants and they all had to reside in the US. I ended up with 31 completed responses and it was all over in less than two hours.

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Treejack results 🌲

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So, what fell out of that tree when I tested a website aimed at parents and teachers of kids in the UK with 31 Americans? I’ll be honest with you: it wasn’t pretty. Here’s what I discovered in this study:

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• 81 per cent were unable to find out if home educators were eligible to apply (number 1 on the graph)
• 65 per cent were unable to find out what a Clubmark accreditation is (number 2 on the graph)
• 68 per cent were unable to find out how to share their wishlist with friends and family (number 3 on the graph)
• 64 per cent could not find the information that would explain the purpose of the £1 fee mentioned in the terms and conditions (number 4 on the graph)
• 97 per cent could not locate the information that would tell them if they could use a voucher from 2014 in 2015 (number 5 on the graph)
• No participant was able to determine if students from a middle school would be able to participate in Active Kids (number 8 on the graph)
• 58 per cent of participants in this study were unable to find out what the program is even about (number 9 on the graph)

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On the flip side, 68 per cent of participants in this study were able to locate a phone number to contact Active Kids directly (number 6 on the graph) and 97 per cent were successfully able to work out how to redeem vouchers (number 7). Overall, it wasn’t great.In addition to some very useful quantitative data, Treejack also provides detailed information on the pathways followed by each participant.

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Understanding the journey they took is just as valuable as discovering how many found their way to the correct destination. This additional level of granularity will show you where and when your user is getting lost in your structure and where they went next. It’s also handy for spotting patterns (e.g., multiple participants navigating to the same incorrect response).

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I always set my studies to collect responses anonymously and when this occurs, Treejack assigns each participant a numerical identifier to help keep track of their experience without the participant having to share his or her personal details. For task 6, the paths chart below shows that participants numbered eight to 20 were able to navigate directly to the correct answer without deviating from the correct path I defined during setup.

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For Task 3 (below) , the story told by the paths was quite different. Participant number five navigated back and forth several times through the structure in their attempt to locate information on how to share a wishlist. After all that effort, they were unable to find the information they needed to complete the task and nominated to contact Active Kids directly. Not only is this a bad experience for the user but it also puts unnecessary pressure on the call centre because the information should be readily available on the website.

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Treejack also provides insights into where participants started their journey by recording first click data. Just like Chalkmark, this functionality will tell you if your users are starting out on the right foot from that all important first click.In this study I found it interesting that when looking for information regarding the eligibility of home educators in the Active Kids program, 42 per cent of participants clicked on “Schools & Groups” and 19 per cent clicked on “Parents & Community” for their first click. Only 6 per cent clicked on “Help”, which happens to be the only place this information can be found.

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I also found the first click results for Task 9 to be very interesting. When looking for basic information on the program, more than half (52 per cent) of the participants in this study went straight to “Help”. This indicates that, for these participants, none of the other options were going to provide them the information they needed.

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What can be learned from this study? 🎓

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I mentioned earlier there was a lesson in this for everyone, and rather than dwell on how something tested, it’s time to move on to some lessons learned and constructive ideas for improvement. Based on the results of this Treejack study, here are my top three recommendations for improving the Active Kids website:

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Rethink the content housed in the FAQs section

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Most of the key information required to master the basics of what Active Kids is all about is housed entirely in the FAQs section. FAQs should not be the only place a user can find out basic information needed to understand the purpose of a product, program or service. I believe this website would benefit from some further thinking around what actually belongs in the FAQs section and what could be surfaced much higher.

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Another idea would be to follow the lead of the Government Digital Service and remove the FAQs section altogether — food for thought. Frequently asked questions would not be frequently asked questions if people could actually find the information on your site in the first place. Figure out where the answers to these questions really belong.

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If you’re using Treejack, just look at the fails in your results and figure out where people went first. Is there a trend? Is this the right place? Maybe think about putting the answer the user is looking for there instead.

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Restructure the FAQs section

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If you must have an FAQs section (and believe me I do understand that they don’t just disappear overnight! Just try to keep it as an interim solution only) please consider streamlining the way they are presented to the user. Ditch the filtering and display the list on one page only. Users should not have to drill down through several layers of content and then navigate through each category. For further reading on getting your FAQs straight, this Kissmetrics article is well worth a read.

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Review the intent of the website

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Looking at the Active Kids website and the results from this study, I feel the intent of this website could use some refining. If we come back to my warehouse and house analogy, the main chunk of the website (the warehouse) seems to be one giant advertisement, while the house (the FAQs) is where the action-oriented stuff lies. The house seems to hold the key information that people need to use the program and I think it could be displayed better. Don’t get me wrong, Active Kids does some incredibly good work for the community and should absolutely shout its achievements from the rooftops, however a sense of balance is required here. I think it’s time for the house and the warehouse to join forces into a solution that offers both rooftop shouting and usable information that facilitates participation.

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The value of fresh eyes 👀

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This study goes to show that regardless of where you are in your design process, whether that’s at the very beginning or a few years post-implementation, there is value to be gained from testing with a fresh set of eyes. I’m still undecided on which side of the FAQs debate I belong to — I’m going to sit on the fence and stand by the “if in doubt — test it” school of thought.

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Further reading:

• "Strategic design for frequently asked questions" - This ebook from Nielsen Norman Group explains how to design world-class FAQs.
• "Infrequently asked questions of FAQs" - An article from R. Stephen Gracey published on A List Apart, discussing FAQs and their place on the web.
• "Anatomy of a website: website architecture" - An article on our blog explaining website architecture and how to test your own structure.

The Ministry for Primary Industry’s (MPI) customers have some of the most varied information needs — possibly the most varied in New Zealand. MPI provides information on how to follow fishing rules, what the requirements are to sell dairy products at the market, and how to go about exporting honey to Asia. Their website mpi.govt.nz has all the information.

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However the previous website was dense and complicated, and MPI’s customers were struggling to find the information they needed, often calling the contact center instead — one of several indicators that people were lost and confused on the website.

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Ruth Hendry, Head of Strategic Growth at Springload, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, about how new IA helped MPI’s broad range of customers find the information they needed.

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In her talk, Ruth takes us through the tips and techniques used to create an IA that met a wide variety of user needs. She covers the challenges they faced, what went well, what didn’t go so well, and what her team would do differently next time.

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Background on Ruth Hendry 💃🏻

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Ruth was Springload’s Content Director; now she’s Head of Strategic Growth. She has broad experience in content, UX, and customer-led design. A data nerd at heart, she uses analytics, research and testing to drive decision-making, resulting in digital experiences that put the customer at the forefront.

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At Springload Ruth has worked on large-scale content and information architecture projects for organisations including Massey University, Vodafone and Air New Zealand. She got into the world of websites in her native UK, working on Wildscreen's ARKive project. After she arrived in Aotearoa, she spent four years looking after Te Papa's digital content, including the live broadcast of the colossal squid dissection. She's Springload's resident cephalopod expert.

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She finds joy in a beautiful information architecture, but her desk is as messy as her websites are tidy.

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Contact Details:

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Email address: ruthbhendry@gmail.com

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LinkedIn URL: https://www.linkedin.com/in/ruth-hendry-658a0455/

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Food recalls, fishing rules, and forestry: creating an IA strategy for diverse audience needs 🎣

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Ruth begins her talk by defining IA. She says, “If IA is the way information is organized, structured, and labeled, then an IA strategy is the plan for how you achieve an effective, sustainable, people-focused IA.”

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Considering this, applying an IA strategy to the Ministry of Primary Industries (MPI) website was a challenge due to its diverse user groups. MPI is responsible for a range of things, such as publishing food recalls, looking after New Zealand’s biosecurity, outlining how much fish can be caught, how to export products, and even how to move pets between countries. Needless to say, the scope of this IA project was huge.

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The current state of the website was challenging to navigate. In fact, one customer said, “It’s hard to find what you need and hard to understand”. MPI Contact Center staff often found themselves simply guiding customers to the right information online over the phone. 

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So, in solving such a massive problem, does having an IA strategy work? Ruth says yes! And it can have a huge impact. She backs up her strategy with the results of this project before broadly outlining how she and her team achieved the following improvements.

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The project achieved:

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• 37% decrease in time spent on the home page and landing pages
  • Customers found where they needed to go, faster, using the new IA and navigation elements
• 21% decrease in on-page searches
  • People could find the content they need more easily
• 53% reduction in callers to MPI saying that they couldn’t find what they needed on the website
  • Users could more easily get information online

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Developing an IA strategy 🗺️

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Ruth attempts to summarize 14 weeks' worth of work that she and her team delivered in this project.

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Step one: Understanding the business

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During this step, Ruth and her team looked at finding out exactly what MPI wanted to achieve, what its current state is, what its digital maturity is, what its current IA was like (and the governance of it), how the site got to be in the way that it was, and what their hopes and aspirations were for their digital channels. They conducted:

• Stakeholder interviews and focus groups
• Reviewing many, many documents
• Domain and analogous search
• Website review

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Step two: Understand the customers

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In this step, the team looked at what people want to achieve on the site, their mental models (how they group and label information), their main challenges, and whether or not they understood what MPI does. They conducted:

• A review on website analytics and user needs
• In-person interviews and prototype testing
• Card sorts
• Intercepts
• Users surveys
• Treejack testing

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Step three: Create the strategy

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This talk doesn’t cover strategy development in depth, but Ruth shares some of the most interesting things she learned (outlined below) throughout this project that she’ll take into other IA strategy projects.

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Why it matters 🔥

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Throughout the project, Ruth felt that there were eight fundamental things that she would advise other teams to do when creating an IA strategy for large organizations with massively diverse customer needs. 

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1. Understand the business first: Their current IA is a window into their soul. It tells us what they value, what’s important to them, and also the stories that they want to tell their customers. By understanding the business, Ruth and her team were able to pinpoint what it was about the current IA that wasn’t working.
2. Create a customer matrix: Find the sweet spot of efficient and in-depth research. When an organization has a vast array of users and audience needs, it can often seem overwhelming. A customer matrix really helps to nail down who needs what information.
3. Card sort, then card sort again: They are the best way to understand how people’s mental model works. They are critical to understanding how information should be organized and labeled. They are particularly useful when dealing with large and diverse audiences! In the case of the MPI project, card sorts revealed a clear difference between business needs and personal needs, helping to inform the IA.
4. Involve designers: The earlier the better! User Interface (UI) decisions hugely influence the successful implementation of new IA and the overall user journey. Cross-discipline collaboration is the key to success!
5. Understand the tech: Your IA choice impacts design and tech decisions (and vice versa). IA and tech choices are becoming increasingly interrelated. Ruth stresses the importance of understanding the tech platforms involved before making IA recommendations and working with developers to ensure your recommendations are feasible.
6. Stakeholders can be your biggest and best advocates: Build trust with stakeholders early. They really see IA as a reflection of their organization and they care a lot about how it is presented.
7. IA change drives business change: You can change the story a business tells about itself. Projects like this, which are user-centric and champion audience thinking, can have a positive effect throughout the business, not just the customer. Sometimes internal business stakeholders' thinking needs to change before the final product can change.
8. IA is more than a menu: And your IA strategy should reflect that. IA captures design choices, content strategy, how technical systems can display content, etc.

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Your IA strategy needs to consider

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• Content strategy: How is content produced, governed, and maintained sustainably going forward?
• Content design: How is content designed and does it support a customer-focused IA?
• UI and visual design: Does UI and visual design support a customer-focused IA?
• Technical and functional requirements: Are they technically feasible in the CMS? And what do we need to support the changes, now and into the future?
• Business process change: How will business processes adapt to maintain IA changes sustainably in the long term?
• Change management and comms plan: How can we support the dissemination of key changes throughout the business, to key stakeholders, and to customers?

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Finally, Ruth reemphasizes that AI is more than just designing a new menu! There’s a lot more to consider when delivering a successful IA strategy that meets the needs of the customer - approach the project in a way that reflects this.

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As information professionals, we work with the “stuff” of information in our everyday work. We search for information, we spend time analyzing and synthesizing it, and we carefully create and structure it. Whether you elicit information from users and stakeholders, explore large data sets, design ‘journeys’ or interfaces, or create information architectures, understanding the information you are using and creating as information can help you do your work better.

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Kat King, Business Intelligence Analyst at the University of Michigan Library, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, about understanding exactly what information is, and where it is, in our work.

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In her talk, Kat uses simple examples to teach you to “see” the information around you and understand what makes something “information” in the context of working as a human to accomplish something.

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Kat King bio 🎤

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Kat King is an Information Architect interested in language, meaning, and the things we make. She currently works as a Business Intelligence Analyst for the University of Michigan Library.

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Contact Details:

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Email: Katalogofchaos@gmail.com

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Where is the information? 📍🗺️

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Information theory can be dense and jargon-filled, and discussions in academic texts can feel divorced from the practice of actually working with information. We’re all told that information architecture is much more than website navigation. So, what is it? IA has a reputation for being difficult to understand, and in her talk, Kat attempts to help us understand what it is, where the information is, and what is it that we’re doing when we use IA methods.

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Kat defines IA as “the practice of ensuring ontological alignment”. ‘Ontological’ relates to concepts, categories, properties, and relationships. ‘Alignment’ means arrangements into appropriate relative positions. Therefore, information architecture is “the practice of ensuring concepts, categories and their properties and relationships are arranged into appropriate relative positions.”

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To align information then, you need to begin by sorting it into concepts and categories, which is difficult because information can sometimes be “slippery and abstract”. Kat argues this is the real reason that IA is sometimes hard to wrap our heads around. So, getting to the heart of the question, what is information? 

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Kat defines information as “a patterned relationship between differences that reduces uncertainty”. The key word here is ‘differences’. The trick to understanding and taming information is to identify what is different about sets of information. The next trick is to identify consistencies between these differences.

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This can be a little confusing, so Kat uses the example of picking fruit. We tend to use color (the difference) to identify when fruit is ripe and sweet. We know for a fact that, at some point, the fruit will be at its sweetest and, while there is a scientific way of identifying this point, we have to use the information we have at our disposal instead i.e. the colour of the fruit. The skin of the fruit in this example is like an interface - allowing a flow of information from the fruit’s ripening process to our eyes.

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Information categories 🧺🧺🧺

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The relationship between the information described in the fruit example can be split into two categories. “Information 1” is a factual, objective description of when the fruit is ripe (i.e. the science of why the fruit is the color that it is right now), whereas our subjective observation, based on color, is “Information 2”.

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• Information 1: Matter and energy, and their properties and interactions i.e. the laws of physics and universal truth or rules

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Information 1 poses challenges for us because we have a narrow range of perception, attention, and aggregation, which means we, as humans, can’t possibly understand the laws of nature just by observing. We have evolved to be simple, efficient observers of what is important to us. In other words, we don’t need to understand everything in order to get things right. We see patterns and generalize. Going back to the fruit example – we only need to know the color of ripe fruit, not the exact chemistry of why it is ripe.

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• Information 2: This is Information 1 that is given meaning by humans. This is done via processing semantic information, or “differences and structures that create meaning for people”.

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We use semantic information by processing concepts, patterns, categories, mental models, and even language as inputs to form our understanding. As social animals, we tend to reinforce general ‘truths’ about things because we’re constantly cooperating using shared information. General ‘truths’ are good enough.

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Kat uses the following interaction to demonstrate the interplay of different information.

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• Person 1: If the raspberries look good, can you get some for me?
• Person 2: How can tell is they’re good?
• Person 1: Get the ones that are the most red.

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In this interaction, the different pieces of information can be broken down by category:

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• Semantic information = Words and concepts
• Information 1 = Meaningful signs
• Information 2 = Perceptible differences
• Real life information = Raspberries

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Using our ability to communicate and understand concepts (words “red”, “good”, and “raspberries”) helps us to understand Information 2 (processing the words and concepts to understand that a red berry is good”), which aligns with Information 1 (the evolutionary science and ongoing consistency of red/ripe berries being sweet) that helps us decide when processing all of this information.

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So, now that we understand a little more about information, how does this influence our roles as designers?

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Why it matters 👀

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Thanks to our individual lived experiences, people have many different inputs/concepts about things. However, Kat points out that we’re pretty good at navigating these different concepts/inputs.

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Take conversations, for example. Conversations are our way of getting a “live” alignment of information. If we’re not on the same page we can ask each other questions to ensure we’re communicating semantic information accurately. 

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When we start to think about technology and digital products, the interfaces that we design and code become the information that is being transmitted, rather than words in a conversation. The design and presentation become semantic information structures, helping someone to understand the information we’re putting forward. This highlights the importance of aligning the interface (structure and semantic information) and the users' ontology (concepts and categories). For the interface to work, IA practitioners and designers need to know what most people understand to be true when they interact with information, concepts, and categories. 

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We need to find some sort of stability that means that most users can understand what they need to do to achieve a goal or make a decision. To do this, we need to find common ground between the semantic information (that might vary between users) so that users can have successful Information 2 style interactions (i.e. absorbing and understanding the concepts presented by the interface).

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To wrap up, let’s remind ourselves that information architecture is “the practice of ensuring concepts, categories and their properties and relations are arranged into appropriate and relevant positions”. As IA practitioners and designers, it’s our job to ensure that concepts and categories are arranged in structures that can be understood by the nuance of shared human understanding and semantic information – not just in some physical diagram.

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We need to present stable, local structures that help to reduce uncertainty at the moment of interaction. If we don’t, the information flow breaks and we aren’t reducing uncertainty; instead, we create confusion and disappointing user interactions with our digital products. Making sure we present information correctly is important (and difficult!) for the success of our products – and for better or worse, it’s the work of information architecture! 

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