
In the fast-paced world of software and services, there's a time-honored practice that separates the truly committed from the rest: "eating your own dog food," or dogfooding. It’s the simple yet powerful idea that companies should use their own products internally. This isn't just about quality assurance; it's about deeply understanding the user experience, fostering innovation, and building better solutions. Ride-sharing and delivery giant Uber is no stranger to this philosophy, employing various forms of dogfooding across its vast technological landscape.

While specific, company-wide programs for employees to exclusively use beta versions of the core Rider app for daily activities aren't always publicly detailed, Uber's approach to internal software use and product iteration reveals a strong culture of testing, feedback, and in-house tool reliance.

## Riding on Experimentation: The Experimentation Platform (XP)

At the heart of Uber's product evolution is its sophisticated **Experimentation Platform (XP)**. As detailed on the [Uber Blog ("Under the Hood of Uber's Experimentation Platform")](https://www.uber.com/blog/xp/), this in-house system is pivotal for testing new features, design changes, and even machine learning models across all of Uber's applications – Rider, Driver, Eats, and Freight. XP allows engineers and data scientists to run over 1,000 experiments concurrently, employing A/B/N testing, causal inference, and more.

Before launching the completely redesigned Driver app, for instance, it "went through extensive hypothesis testings through a series of experiments conducted with our XP." This platform ensures that changes are data-driven and validated with real users (which can, and often do, include Uber employees themselves) before being rolled out broadly. While this is more akin to large-scale, controlled beta testing than traditional dogfooding of unstable builds by all employees, it’s a critical part of their iterative process. More recently, Uber has continued to invest in this area, [making their experiment evaluation engine 100x faster](https://www.uber.com/blog/making-ubers-experiment-evaluation-engine-100x-faster/), showcasing their commitment to rapid, data-backed iteration.

## Building with Drivers, For Drivers: The New Driver App Beta

A stellar example of targeted dogfooding and user-centric design at Uber was the development of their new Driver app. According to an [Uber Blog post ("Let's build together: the story behind the new Driver app")](https://www.uber.com/en-CA/blog/building-together-driver-app-ca/), the company didn't just rely on internal teams. They engaged over **400 drivers and delivery partners across 7 cities worldwide** in a unique Beta program.

These weren't just passive testers. Participants actively collaborated with Uber designers and engineers, providing ideas, sharing feedback, and reporting bugs. As Uber engineer Haider noted, "A typical Beta wasn't going to cut it for us...We truly had to understand how the app performed in various cities and in different circumstances for different drivers and delivery partners." Drivers like Eva highlighted the value of being heard: "Just the fact that I was heard and my opinion mattered was huge." This deep collaboration, including Uber employees doing ride-alongs, allowed the team to identify and fix issues, like improving the visibility of surge pricing on the map, based directly on the experiences of those who use the app to earn their livelihood. Over 16 weeks, these beta testers reported over 2,600 bugs, a testament to the power of real-world use.

## Internal Tools Get the Dogfood Treatment Too

Uber doesn't just dogfood its main user-facing apps; its internal tools are also built and refined through self-use.

* **uRate:** To streamline feedback collection, Uber developed **uRate**, an internal platform described on the [Uber Blog ("Thank You for Your Feedback: Improving the Uber Engineering Workflow with uRate")](https://www.uber.com/blog/urate/). This tool allows Uber employees (and potentially external users in some contexts) to provide instant feedback on various Uber tools and products. The uRate widget can be integrated into any internal application, enabling employees to report bugs, suggest features, or simply rate their experience. This creates a direct and continuous feedback loop, ensuring internal tools are as efficient and user-friendly as possible. For example, after embedding uRate into their internal "Whober" employee portal, the team quickly identified a common request for more searchable user fields based on the feedback received.

* **COTA (Customer Obsession Ticket Assistant):** Uber's customer support operations are enhanced by COTA, an in-house developed tool that uses machine learning and natural language processing to help agents resolve issues more efficiently. As detailed in blog posts about [COTA's initial development](https://www.uber.com/blog/cota/) and its [scaling with deep learning (COTA v2)](https://www.uber.com/blog/cota-v2/), this system is used daily by Uber's support team. The insights gained from this internal usage directly fueled its iterations and improvements, reducing ticket resolution times by over 10% while maintaining or improving customer satisfaction. This is a clear case of dogfooding a critical internal system to enhance operational efficiency and, ultimately, the customer experience.

* **Devpod:** Even the tools used by Uber's developers are dogfooded. **Devpod**, Uber's remote development environment, was created to boost engineering productivity. According to the [Uber Blog ("Devpod: Improving Developer Productivity at Uber with Remote Development")](https://www.uber.com/blog/devpod-improving-developer-productivity-at-uber/), internal Net Promoter Score (NPS) feedback from Uber developers consistently identifies Devpod as a major productivity booster. This internal usage and feedback cycle helps the Devpod team refine the tool, addressing everything from IDE experience to cost efficiency.

## The Unspoken Expectation and Potential Pitfalls

Beyond formal programs, there's often an implicit expectation in tech companies that employees will be regular users of their own services. As one [Bubble.io blog post on dogfooding](https://bubble.io/blog/dogfooding-startup-tech/) suggests, "Uber employees should regularly use Uber to get to and from the office." This day-to-day usage naturally leads to employees experiencing the product just as any customer would, spotting pain points, and ideating improvements.

However, relying solely on internal software can sometimes lead companies astray, especially if the employee base isn't representative of the broader user population or if the tools are used for purposes beyond ethical product improvement. An example of Uber's internally developed software leading to controversy was the "Hell" program, reported by [GeekWire](https://www.geekwire.com/2017/report-uber-used-secret-hell-software-track-drivers-competitor-lyft/) and others. This software was allegedly used between 2014 and 2016 to track drivers working for competitor Lyft, reportedly to gain a competitive advantage by luring them away. While it demonstrates Uber's capability in building and deploying its own software solutions, it also serves as a stark reminder that dogfooding's positive intent can be overshadowed if the application of internal technology isn't guided by strong ethical principles.

## Conclusion: A Culture of Iteration and Internal Reliance

Uber's approach to software development is deeply intertwined with the practice of using its own solutions. From the rigorous A/B testing managed by its Experimentation Platform to the collaborative beta program for the new Driver app and the continuous refinement of internal tools like uRate, COTA, and Devpod, Uber leverages its own technology to learn, iterate, and enhance its offerings.

This internal reliance fosters a deep understanding of their products' strengths and weaknesses. While the path of dogfooding isn't without its potential for missteps, Uber’s commitment to building and using its own tools is a significant driver in its continuous push for innovation and an improved user experience for riders, drivers, eaters, and its own employees.

How Uber Eats Its Own Dog Food: A Look at Internal Software Use and Product Evolution


In the fast-paced world of software development, there's a time-honored practice that often separates good products from great ones: "eating your own dog food," or dogfooding. It's the simple yet profound idea that companies should use their own products and services internally as a primary way to test, understand, and improve them. Etsy, the sprawling online marketplace for handcrafted and vintage items, has woven this philosophy into its development culture, leading to a more robust and user-centric platform.

While Etsy might not always shout "dogfooding" from the rooftops with a formal, branded program name, the principles are evident in their engineering practices, product rollout strategies, and company culture. They understand that to truly serve their vibrant community of millions of sellers and buyers, their own teams need to be deeply familiar with the platform's every nook and cranny – experiencing both its triumphs and its frustrations firsthand.

**Early and Continuous Internal Use: The Mobile App Example**

One of the clearest illustrations of Etsy's dogfooding commitment comes from its approach to mobile app development. As far back as 2014, reports highlighted how Etsy leveraged continuous integration principles not just for their web stack, but rigorously for their mobile applications as well. Instead of solely relying on external beta testers, Etsy would roll out continuous releases of its mobile apps to internal teams. This meant that Etsy employees were among the very first to use new features and iterations in real-world scenarios.

To facilitate this internal feedback loop, Etsy even developed tools like an internal "Bug Hunting tool." This allowed employees to report bugs directly from their devices, often attaching screenshots to pinpoint issues. Adding a touch of fun and engagement, there was even a level of gamification, with leaderboards recognizing the most prolific bug hunters. This approach not only helped in identifying and fixing bugs early but also fostered a sense of collective ownership and quality assurance across the company.

**A Culture of Experimentation: Dogfooding at Scale**

Etsy is renowned for its deeply ingrained culture of experimentation, particularly its extensive use of A/B testing. As detailed on their "Code as Craft" engineering blog and in various discussions by their product teams, nearly every change, from a button color to a new search algorithm, is often tested with a subset of users before a full rollout.

While A/B testing isn't dogfooding in its purest, most isolated form (where only employees use a pre-release version), it functions as a type of scaled dogfooding in Etsy's context. Employees, being active users of the platform for their own shopping or even as sellers themselves, are inevitably part of these experiment groups. They experience new features organically, providing an invaluable layer of sophisticated, internal "first users" before changes reach the entire user base.

This continuous experimentation allows Etsy to:

* **Gather Real-World Data:** See how new features perform under actual usage conditions.
* **Validate Hypotheses:** Test assumptions about user behavior and preferences.
* **Iterate Rapidly:** Make data-driven decisions and refine features quickly.

Etsy's "Building Better Tools With Experiments" guide for sellers even explains this philosophy, stating, "By testing new features with a small percentage of Etsy users, we gather valuable data that helps us ensure that the changes we make will have a positive impact for the majority of Etsy sellers." Employees are a critical, albeit often undifferentiated, part of that "small percentage."

**Encouraging Company-Wide Product Immersion**

Beyond formal testing, there's a cultural expectation at Etsy that encourages employees to engage deeply with the product. Cap Watkins, a former VP of Design at Etsy, articulated this well in a blog post about his design process. He emphasized the importance of company-wide dogfooding during development:

> Hopefully you've already had your entire company dog-fooding your new release during development. If not, it's time. Get everyone to use your product under real, live conditions. Gather feedback. Make adjustments.

[Cap Watkins, _My Design Process Part 3_](https://capwatkins.com/blog/my-design-process-part-3)

This sentiment underscores a proactive approach to getting the product in front of internal users. It’s about more than just QA; it’s about fostering empathy and ensuring that everyone, from engineers to marketers, understands the user experience from the inside out. When employees are encouraged to use the platform for their personal shopping, or if they run their own small shops, they naturally become critical and insightful testers of new seller tools and buyer-facing features.

**Focus on Seller Success: Internal Testing for a Better Toolkit**

Etsy's success is inextricably linked to the success of its sellers. Therefore, a significant portion of their development effort goes into creating and refining tools for shop owners. Recent pushes to enhance the Shop Manager dashboard, introduce AI-powered listing assistance, and provide real-time feedback on listing quality are prime examples.

While Etsy often beta tests these new seller features with "a select group of sellers," it's highly probable that employees who also run Etsy shops, or dedicated internal testing accounts, are among these early adopters. This allows Etsy to:

* **Understand Seller Pain Points:** Internal users can quickly identify clunky workflows or missing functionalities in new seller tools.
* **Refine Usability:** Ensure that new features are intuitive and genuinely helpful before a wider release.
* **Catch Edge Cases:** Discover unique scenarios or problems that might not be apparent in controlled testing environments.

**The Nuances and Potential Pitfalls**

Dogfooding, for all its benefits, isn't a silver bullet. One potential challenge is the "expert user" syndrome. Employees who are intimately familiar with the platform's architecture and upcoming features might not use the product in the same way a brand-new, less technically savvy user would. They might unconsciously work around bugs or understand convoluted features that would baffle an average customer. Etsy mitigates this through its extensive A/B testing with broader audiences and dedicated user research.

Another aspect is ensuring that feedback channels are open and that employees feel empowered to provide honest, critical feedback without fear of reprisal. Etsy's engineering culture, which emphasizes collaboration, transparency, and empowering developers, seems conducive to fostering such an environment.

**Conclusion: A Living Lab for a Thriving Marketplace**

Etsy's application of dogfooding principles, whether through direct internal releases, widespread experimentation, or a culture of product immersion, plays a crucial role in its continuous improvement. By having its own team members regularly use and scrutinize the platform, Etsy gains invaluable insights, catches issues earlier, and ultimately builds a more resilient, user-friendly, and innovative marketplace.

It’s this commitment to living within their own creation, to experiencing what their buyers and sellers experience, that helps Etsy "Keep Commerce Human" – not just as a tagline, but as a practiced reality in their product development lifecycle. While they may not always use the term "dogfooding," their actions speak volumes, demonstrating a clear understanding that the path to a better product often starts by looking inward.

Articles tagged with "Agile"

How Uber Eats Its Own Dog Food: A Look at Internal Software Use and Product Evolution

Etsy's Secret Sauce: How 'Eating Their Own Dog Food' Fuels a Better Marketplace