Dogfooding is simply using the product as if you were the customer and experiencing it firsthand. It is a common practice but an unstructured methodology, as there is no script outside of using the product in the use case it was designed for.
Will the solution provide the value proposition?
Is the solution working right?
What is the minimum viable feature set?
Generative product research
Using one’s own product is a standard practice among many technology startups and entrepreneurs. In many cases, entrepreneurs are building a product to solve their own pain points, so it is common to then use the product.
There is no predefined script for dogfooding, and it is not a formal quality assurance (QA) process. The main advantage to this method is that it may reveal unorthodox use cases that were not covered in the requirements or QA tests. Dogfooding should primarily be considered generative research and not an experiment.
Companies that do not use their own products and services are sometimes criticized, in some cases very publicly.
If team members regularly encounter the use case of the product, then there is no time commitment or resources necessary aside from having a notebook and writing down the results.
If the use case is infrequent or complex (such as for booking and taking a vacation using AirBnB), then dogfooding can require a substantial use of time.
Make sure you have a place to take notes that is easily accessible and won’t interrupt your workflow too much.
Simply use the product in your day-to-day work. Take notes whenever something works surprisingly well or fails to live up to expectations. Record any additional insights or ideas that occur while using the product. Note any time when the workflow is interrupted or another service is needed to finish the task.
Be careful to interpret the results as generative and not evaluative. The makers of a product have an intimate knowledge of the product design and likely cannot capture the uneducated user’s perspective.
This is especially true in dogfooding the new-user process, where the makers of the product have a massive amount of prior information and expectations regarding the signup and onboarding.
Completely missing edge cases is also particularly common, especially if the team is not particularly diverse. For example, a team may not analyze the product for use by handicapped or minority users and thus overlook substantial aspects of its user experience. This can be more of a problem as a product scales beyond an initial niche audience.
When multiple team members dogfood their product, notes can be collected and sorted via card sorting, stack ranking, or other standard UX methods.
Confirmation Bias: Creators of a product can subconsciously avoid situations and use cases they know are incomplete or buggy, leaving a positive impression that the product works according to the specification, even if it has serious flaws in ordinary usage.
“Dogfooding only works when your team is as diverse as your customer base.” - @TriKro
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