Illustration by Mallory Haack

Choice Architecture: Introduction to Designing for Decision Making

Designing to enable better decision making, not just better interfaces — Part 1 of 3

Zeke Franco
6 min readJul 16, 2018

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Choice architecture is the holistic presentation and framing of information throughout a decision making process. It’s the design of how you frame and display information and often extends into the design of the product or service. It goes beyond filtering and sorting and dives into presenting information that users will understand, giving them the support they need to move through the decision making process. This series (three articles) will introduce you to choice architecture, principles and “behavior variables” to get you started, and lastly how to best communicate decision making with diagrams.

Decision Making Conundrum

The research studies by economist and social psychologist Sheena Iyengar and the psychologist Barry Schwartz provide insight into the complexity of choice and decision making. Dr. Iyengar’s jam study on choice overload and Dr. Schwartz’s work on “The Costs of Seeking Alternatives” made a splash in the business world when they were able demonstrate that increasing choices can prevent [1] most customers from making a purchase. Additionally, for those who do make a purchase, they are less satisfied [2] with their purchase.

Think about that: a person who wants to make the best decision may be drawn to an abundance of options. They will spend more time and resources choosing an option and will be less satisfied with their purchase afterwards. This problem may be minor when trying to find the best pair of jeans, but it becomes a major issue when making important or expensive decisions. Consider self-employed workers looking for health insurance for their family, or people deciding to go back to school to improve their career options. Choice architecture helps people make complex decisions, without which would require them to understand specialized information and leaves them to predict a future outcome based on limited information.

Enhancing your Design Strategy with Choice Architecture

Choice architecture is a skill set that should be used by UX and product designers, but is often neglected. Many business models implicitly assume their users know and understand what they want and how to best accomplish their goals. These assumptions result in most systems providing the following patterns as tools to help the user accomplish their goal.

  • Flow: chunking and organizing a process into steps
  • Search: narrowing results based on a keyword(s)
  • Filters: narrowing a set of results based on a criteria
  • Facets: narrowing down results based on attributes that can be combined in multiple ways (Filters vs Facets)
  • Comparison tools: comparing attributes of selected results

These patterns often work well enough for an e-commerce or a clothing brand, but may not be sufficient for needs like purchasing health insurance, comparing home loans, or creating a retirement plan. A way to decide if and how to employ choice architecture is through design research. Your baseline research should attempt to answer the following questions:

  • Do users understand the domain? How much do they need to understand to make an informed decision?
  • Do users understand their goals and how they should achieve them?
  • Do users understand the categories, keywords, and attributes they can search?
  • Do users understand the terminology of the filters and facets?
  • Do users know how to compare qualities and the tradeoffs associated with different dimension of attributes?

Combining Secondary & Primary Research

It’s becoming increasingly important to understand how people make decisions within the products and services we design. Good interface design is fundamental to creating a usable system, but understanding how we can better tailor services and products often goes much deeper than interface and the user flow. To do this you need to have a good set of qualitative and quantitative data about your audiences.

Academic research is a great place to learn about how people think, how they approach decisions, and how their decision making may differ depending on seemingly unrelated factors. Academic research can often spark creative ideas for user research studies or design concepts.

In order to apply choice architecture most effectively you’ll need good data from user research. Qualitative and quantitative research are helpful for testing design that employ choice architecture. The research you conduct should help you gain an understanding of your audience’s mindsets, mental models, and values. You should make sure you have a deep understanding of the domain (work closely with a subject matter expert) and the organization that is providing the service or product. Conducting primary user research is a key step in a solid design strategy, followed by concept testing to validate potential approaches. In the follow-up to this post, I’ve compiled useful choice architecture principles to get you started and to help better plan your research and design strategies.

Robust user research will let you know how your users are being affected by the paradox of choice. If you’ve done the research to create behavioral personas focused on decision making mindsets, not demographics, you’ll find the proportion of your audience that are maximizers [3], the type of consumer who want to make the most informed decision to get the best outcome. Often this type of user isn’t as abundant as UX designers and product owners think. Most of the time people are actually satisficers [3], they have a few criteria which is important to them; once these criteria are met they will make a decision. These criteria can vary widely for different types of people which is why research and validation is key to defining choice architecture that works.

The final article in the series Communicating Decision Making via Task Modeling shows how we can visualize our research and/or explore a decision making process to inform research.

Aside: How Brands Use Curation to Ease Decision Making

A designed point of view (POV) is often a strategic output of an organization’s business model and brand values. Often the first decision a consumer makes is where to source their purchase. If they already have a store in mind this reduces the set of options they can choose from. Their decision is further simplified if there is a brand they are already familiar with and interested in purchasing.

To be effective at explicit curation, the service needs to be seen as a trusted brand by the people who use the service. For example, this might be a system to provide an expert recommendation or to filter out things based on a lifestyle association. Gilt, an online shopping company, curates by combining haute couture lifestyle products with a discounted pricing model. In contrast, a site like Kayak aggregates as many options as possible, then gives the shopper tools to do their own culling and sorting.

Let’s look at camping equipment as an example. Imagine how each store’s representative customer would purchase a tent. REI and Walmart cater to different audiences, with some overlap. How each store operates and the products they choose to sell have an impact on their service model works and who they attract as customers.

REI promotes high quality, expert product features, and an array of options that best represent a category. Their service model makes talking to a knowledgeable staff member a key experience and enables enthusiasts to get assistance with what to purchase. Their model assumes you want to expend energy on maximizing what you get out of your purchase and often results in a higher price. REI doesn’t need to carry every tent option, because consumers are familiar (often implicitly) with their business model and brand values. Loyal consumers would even say they trust REI’s inventory and recommendations.

Walmart focuses on classic brands with perceived value and they aspire to provide an array of options focused on affordable price points. Their service model is mostly self serve and focuses on carrying items that sell best even if they risk missing out on representing certain feature sets. This model works great for consumers who value low price and who don’t prioritize maximizing their choice of products and specific product features.

Next Article

Foundational Principles for Choice Architecture focuses on principles that can help guide your user research strategy and design concepts. These principles are starting points to increase your understanding of the psychology of decision making. Let’s go beyond visual design principles and dive into principles for reducing decision fatigue, helping people make a decision, and how to frame a set of options.

Footnotes

  1. Iyengar, Sheena S., and Mark R. Lepper. When Choice Is Demotivating: Can One Desire Too Much Of A Good Thing?”. Journal of Personality and Social Psychology 79.6 (2000): 995–1006. Web.
  2. Dar-Nimrod, Ilan et al. The Maximization Paradox: The Costs Of Seeking Alternatives. Personality and Individual Differences 46.5–6 (2009): 631–635.
  3. Waude, A. (2016, December 14). “Maximizers Vs Satisficers: Who Makes Better Decisions? Retrieved from psychologistworld.com

Additional Source

  • Iyengar, Sheena. The Art Of Choosing. New York: Twelve, 2010.
  • Thaler, R. and Sunstein, C. (2015). Nudge. 2nd ed. Clitheroe: Joosr.

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Zeke Franco

Experience Director at Huge Inc • Cofounder and UX Instructor at Designation.io (acquired by WeWork) • Latin X • He/him • https://zekefranco.com