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Remember Quibi? It was a short-form media platform that raised $1.75 billion, only to shut down seven months after its launch. Many factors led to Quibi’s failure: shifting consumer behaviors, TikTok, a global pandemic. But hiding there underneath it all?
Assumptions that weren’t tested or validated.
Products tend to underperform when their product teams fail to answer a simple question: who is our user as a person? What do they need? Maybe Quibi just assumed that people would need it, an assumption that proved costly.
Even if they don't lead to such drastic consequences, assumptions in product design contribute to:
Herein lies the power of user research, such a critical part of the modern design process. Neglect it, and you risk relying on guesswork alone. Nurture it, and you reveal objective truths about what your users actually need.
But what does growth-aligned user research actually look like? How does it help teams build products that resonate, drive engagement, and support broader business objectives?
We discussed this topic with Julia Kucherenko, Lead Product Designer at Transcenda.
You release an update to the login screen, assuming it will make life easier for users. Instead, customer support receives an influx of cases related to the new login process.
You build in a contextual overlay to guide users through a new portal setup, assuming they will need the help. Instead, heatmapping reveals that 90% of users are skipping it altogether.
Often, these types of oversights stem from assumptions. When we focus heavily on user experience research, we might design the perfect login interface—a gorgeous contextual overlay—but if we miss the broader context of the user's real-life experience beyond the screen, we risk losing perspective. Even the most seamless interface can lead to customer support issues if it doesn't align with what happens to users outside of the particular screen we’ve designed.
The longer you are on the project, the more assumptions tend to creep in.
Building products based on assumptions can be like building a house of cards: the farther along you get—the taller the house becomes—the more damage is done when one of those supporting cards proves unreliable.
That damage can come in the form of wasted time, effort, and resources. Or it can come in the form of products misaligned with organizational goals, revenue strategies, and the wants and needs of your particular user base.
At the extreme end, assumptions in product design can lead to missed market opportunities, revenue loss, or failure.
Quibi is not alone in this regard.
Recall the failure of Google Glass, in which certain assumptions proved fatal: it was too expensive; the birth of a Glass Explorers community was far-fetched; and the bridge to the fashion industry adoption was too far to cross.
That said, assumptions are a fine line to walk for product teams. These days, it’s relatively safe to assume that consistent look and feel, accessibility, and adherence to industry standards should be observed.
Product teams might also assume certain universal human behaviors. For example, we can expect curiosity and exploration to be part of almost any user’s interaction with a given product or technology.
It's always your responsibility to go and ask questions about users.
User research remains one of our most effective ways to remove guesswork from product design. What is user research? The means and methods used to learn more about the users' problems.
User research goes beyond feelings and sentiment. It’s not just, Okay, you opened a webpage, now what? It’s, Why did you open this webpage in the first place? One of the primary goals of user research should be to ensure that product teams are solving problems that their user base actually has.
“As lead product designer, I use user research everywhere,” says Julia. “Product users, stakeholders—who are these people? What do they need? What are their problems?” When designing for a client, this may include research into team dynamics and organizational direction. It may also include confirming hypotheses with internal stakeholders before testing and validating them outright.
Ultimately, user research can support a variety of positive outcomes:
For me it's like people science. What do users need? What do users want? What type of problems do users have? And do users even want to listen to us?
Most product teams employ some form of user research. As NN/g emphasizes in its UX Maturity Model, it’s the quality and consistency of these processes that mark a mature operation.
Leading a team that heavily prioritizes user research, Julia highlights three key user research methodologies:
UX discovery happens before product development begins. Its goal is to reveal what users actually need from the product, and where that product fits into the marketplace. UX discovery happens across four core steps:
UX validation happens further into the design process, when you already have a prototype. Its goal is similar to discovery, with one caveat: your target user base has the opportunity to see how product interaction actually works. UX validation includes:
User interviews
“I cannot imagine any project without some sort of interview,” says Julia. “At the very least, interview stakeholders. Ideally, interview the actual users.” Though there are many ways to run user interviews, a semi-structured interview style leaves room for unscripted and unexpected responses that lead to unique insight.
In her Ultimate Guide to User Interviews, Julia lays out some best practices for user interviews:
Supplemental research
“Beyond actual interviews, go to the places where your target user groups are talking,” says Julia. These can include:
The initial challenge is finding suitable candidates to interview. This begins by asking clients if they have a recommended pool of people or, if not, leveraging external resources like UserInterviews.com or Respondent.io to source participants.
We’ve written about the impact of AI in other areas of product development, such as software quality assurance and software engineering. Product teams are using AI for research, too, in how they plan and execute their research processes.
Synthetic personas
One area worth keeping an eye on is synthetic personas. Synthetic personas are AI-generated representations of users or user segments. You create them using a combination of machine learning algorithms and data analysis.
Why are synthetic personas making a splash? They can effectively mimic the behaviors, preferences, and characteristics of your target user groups—without requiring the same time and resources for in-person user research. Of course, every synthetic persona should still be validated against real users, since most AI models are still prone to mistakes/hallucinations.
You might argue that synthetic personas coincide with a greater push for scalable design. The Google Ventures formula comes to mind, in which a Google Ventures UX research partner helped 300 startups scale user research. While synthetic personas don’t play any explicit role in this particular formula, it’s easy to see a future in which they dramatically scale user research programs.
Or partner with a design and engineering team who knows how. Nearly all Transcenda projects include some form of user research, for a simple reason: “You don’t want to get ahead of yourself,” says Julia. “It doesn’t pay to dive directly into UX without understanding the users themselves.”
Transcenda case studies featuring user research:
In hindsight, it’s easy to dunk on the likes of Quibi and Google Glass. The truth is that user research was but one of the reasons that these products failed to find lasting success. But it’s safe to conclude that, somewhere along the way, assumptions were made. By committing to consistent user research, you limit the likelihood that assumptions inhibit growth.
Let’s talk about how user research can drive clarity, engagement, and growth for your product.
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