Flag

We stand with Ukraine and our team members from Ukraine. Here are ways you can help

Get exclusive access to thought-provoking articles, bonus podcast content, and cutting-edge whitepapers. Become a member of the UX Magazine community today!

Home ›› How Uber uses psychology to perfect their customer experience

How Uber uses psychology to perfect their customer experience

by Jennifer Clinehens
4 min read
Share this post on
Tweet
Share
Post
Share
Email
Print

Save

PsychologyUber_Slider

Uber tackles their biggest pain points with science.

I think Uber is just very different; there’s no model to copy.

– Travis Kalanick

Available in 600 cities spread across 65 countries with more than 75 million users, Uber has become the default transport choice for many.

The scale and speed of adoption have been incredible, and Uber cites its unique business model and experience as the drivers.

So what are the most significant issues customers have with Uber? And how has Uber used science to fix them?

Imagine you’re out at 2 am on a winter night, waiting for your Uber while shivering on the side of a dark street in a new town. Or you’re late for an important meeting that you might just make if your Uber is on time.

In these high-pressure situations, your perception of time is warped. Every second takes a minute, every minute takes an hour.

Not only that, but people will use this warped wait time to judge their entire customer experience. Why? It’s all down to a psychological principle called the Peak-end Rule.

Peak End Rule

Image via UI Patterns.com

The Peak-end Rule says that people judge an experience based on how they felt at its peak and its end, not the average of every moment of the experience. And that’s true whether the experience was good or bad.

For brands, this means customers will remember their whole experience based on only two moments — the best (or worst) part of their experience, and the end.

Uber Driver

Photo by why kei on Unsplash

Because wait times are the key to a great customer experience, Uber has spent countless hours addressing this pain point.

In their research, Uber discovered three key principles dealing with how people perceive wait times: Idleness Aversion, Operational Transparency, and the Goal Gradient Effect.

Idleness Aversion

Photo by Fabrizio Verrecchia on Unsplash

“People dread idleness, yet they need a reason to be busy.”

– Researcher Chris Hsee

Recent studies into psychology, happiness, and customer experience have uncovered a principle called “Idleness Aversion”. It states that people are happier when they are busier, even if they’re forced to be busy.

How to apply Idleness Aversion

To keep people busy, give them information to engage with — animation, gamification, and visuals are ideal.

In the example from Uber below, they use an animation that keeps you entertained and informed while you wait for your ride.

Uber
Uber

“When customers are separated from the people and the processes that create value for them, they come away feeling like less effort went into the service.

They appreciate the service less and then the value the service less as well.”

— Ryan Buell, Harvard Business School

Operational Transparency is the deliberate inclusion of windows into your company’s operations, so customers can see the effort going into their experience.

According to recent research, Operational Transparency causes customers to value your product more highly and can even make people happier.

How to apply Operational Transparency

To keep people informed, make key information available, and help them understand where this information came from.

In the example from Uber Pool below, they provide information on how arrival times are calculated. It provides customers transparency but doesn’t overwhelm a non-technical audience with too many details.

Uber
Uber

Photo by Jonathan Chng on Unsplash

The Goal Gradient effect states that people are more motivated by how much is left to reach their target, rather than how far they have come.

And as people get closer to a reward, they speed up their behavior to get to their goal faster.

How to apply the Goal Gradient Effect

Think of the Goal Gradient Effect as a virtual finish line. The closer customers get to winning, the more encouraged they become.

You’ll often see the Goal Gradient Effect in UX elements like progress bars and profile completion — users are encouraged to complete a task by achieving objectives.

Uber applies this principle by illustrating what’s happening behind the scenes while customers are waiting. They explain each step in the process, making customers feel they are making continuous progress toward their goal.

Uber

There’s no doubt that a large part of Uber’s revenue comes from optimizing their experience using science. When an experiment was run with Uber Pool that applied Idleness Aversion, Operational Transparency, and the Goal Gradient Effect, the results were impressive:

“The Express POOL team tested these ideas in an A/B experiment and observed an 11 percent reduction in the post-request cancellation rate.”

– “How Uber Leverages Applied Behavioral Science at Scale

If you want to apply these principles to your brand, a testing mentality is critical. You have to be willing to test the application of the same principle in hundreds of different ways before discovering the best solution.

This experimentation mentality comes from the top down at Uber. As founder Travis Kalanick says:

“I wake up in the morning with a list of problems, and I go solve them.”

post authorJennifer Clinehens

Jennifer Clinehens
I’m an evidence-based marketer who combines art and science to create impactful customer relationships with brands. Writing where decisions, design, and behavioral science meet. Author, CX That Sings and Choice Hacking.

Tweet
Share
Post
Share
Email
Print

Related Articles

What if your AI didn’t just agree, but made you think harder? This piece explores why designing for pushback might be the key to smarter, more meaningful AI interactions.

Article by Charlie Gedeon
The Power of Designing for Pushback
  • The article argues that AI systems like ChatGPT are often too agreeable, missing opportunities to encourage deeper thinking.
  • It introduces the idea of “productive resistance,” where AI gently challenges users to reflect, especially in educational and high-stakes contexts.
  • The article urges designers to build AI that balances trust and pushback, helping users think critically rather than just feel validated.
Share:The Power of Designing for Pushback
6 min read

As UX research shifts and reshapes, how can researchers stay ahead? This article explores the changing landscape and how to thrive in it.

Article by James Lang
Hopeful Futures for UX Research
  • The article explores how UX research is evolving, with roles shifting and adjacent skills like creativity and knowledge management becoming more important.
  • It looks at how non-researchers are doing more research work, and how this trend challenges traditional UX research careers.
  • The piece argues that researchers can stay relevant by adapting, staying curious, and finding new ways to share their value.
Share:Hopeful Futures for UX Research
16 min read

Mashed potatoes as a lifestyle brand? When AI starts generating user personas for absurd products — and we start taking them seriously — it’s time to ask if we’ve all lost the plot. This sharp, irreverent critique exposes the real risks of using LLMs as synthetic users in UX research.

Article by Saul Wyner
Have SpudGun, Will Travel: How AI’s Agreeableness Risks Undermining UX Thinking
  • The article explores the growing use of AI-generated personas in UX research and why it’s often a shortcut with serious flaws.
  • It introduces critiques that LLMs are trained to mimic structure, not judgment. When researchers use AI as a stand-in for real users, they risk mistaking coherence for credibility and fantasy for data.
  • The piece argues that AI tools in UX should be assistants, not oracles. Trusting “synthetic users” or AI-conjured feedback risks replacing real insights with confident nonsense.
Share:Have SpudGun, Will Travel: How AI’s Agreeableness Risks Undermining UX Thinking
22 min read

Join the UX Magazine community!

Stay informed with exclusive content on the intersection of UX, AI agents, and agentic automation—essential reading for future-focused professionals.

Hello!

You're officially a member of the UX Magazine Community.
We're excited to have you with us!

Thank you!

To begin viewing member content, please verify your email.

Tell us about you. Enroll in the course.

    This website uses cookies to ensure you get the best experience on our website. Check our privacy policy and