Dogfooding refers to a practice where a company tests and evaluates its own products or product updates in real-life settings to collect feedback from its employees before public release. It comes from the phrase eating your own dog food.
Dogfooding can help businesses ensure the quality, usability, or reliability of their products and is a common practice in the tech industry. Dogfooding has two variants that are often combined:
Many companies use dogfooding before a product reaches its customers. This allows businesses to collect user experiences and identify bugs without harming their reputation. They process the feedback from the research process before the official release to actual customers.
Most companies also promote the internal use of their own software products after their release in order to collect more feedback on real-life issues other users might also face.
It’s essential to recruit employees with characteristics that mimic those of your end users to participate in dogfooding.
Published on
July 25, 2024
by
Julia Merkus, MA.
Revised on
November 21, 2024.
Predictive validity refers to the extent to which a measure or test accurately predicts future behavior, performance, or outcomes. It is considered a subtype of criterion validity and is often used in the fields of education, psychology, and employee recruitment.
By ensuring high predictive validity, researchers and practitioners can make more informed decisions and develop more effective interventions.
Published on
July 24, 2024
by
Julia Merkus, MA.
Revised on
November 11, 2024.
External validity refers to the extent to which the findings of a study can be generalized to other populations, settings, and contexts beyond the specific one in which the study was conducted. In other words, it’s about whether the results can be applied to other people, places, and situations.
External validity is important because researchers want to apply the results from their experimental designs (often conducted in laboratories or artificial environments) to the real world.
Published on
July 24, 2024
by
Julia Merkus, MA.
Revised on
October 8, 2024.
Content validity refers to the extent to which a test or instrument accurately represents all aspects of the theoretical concept it aims to measure. This concept, also known as a construct, often cannot be measured directly.
Content validity is critical for making informed decisions and drawing accurate conclusions based on the research data.