What are experiment tests like?
Posted: Mon Apr 21, 2025 9:16 am
Any Netflix user will notice that the content on the home page changes every time they log in. These changes are made to make it easier for them to quickly find what they want to watch and are based on identified behavior.
In addition to each user's preferences, the type of film they watch and the ones they select as favorites, the company creates experiences considering the most diverse details. The goal is to encourage members to watch the content made available.
In testing, different content is offered to different groups. This allows us to identify reactions and select what works best to capture the user's attention more quickly — which is essential for retention.
In Netflix's logic, there are two costa rica mobile database main reasons for not achieving the best results. The first is, evidently, not providing the right content for each user profile. The second is not providing the evidence that the user needs to decide on a content.
Obviously, after numerous tests have been carried out, the company has identified general patterns that help achieve these goals. However, the tests continue to contribute to the verification and use of a system created to group, for example, different art formats.
The same background image can be made available with different retouching, proportions and title placement, allowing you to identify which one performs best. Some cases are enlightening. For example:
Tests with the series “Sense8” — which features a multicultural cast — showed that the results were different depending on the country in which the images were shown.
In the case of “Dragons: Race to the Edge”, it was noticed that, when they presented images with villains, the acceptance was better.
In the image tests for the second season of “Unbreakable Kimmy Schmidt”, the best performance was for those that showed the characters making faces. In fact, for the title “Orange Is The New Black”, the number of characters made the difference.
The first season was promoted with the entire cast in the promotional image. This seemed to make sense in the context of the story, but when they ran tests, they noticed that users understood what the film was about better with fewer characters.
What are hypothesis tests like?
An interesting case reported by Netflix was based on the design team's suspicions. They believed that visitors would be more likely to subscribe to the service if they could browse the film catalog. This hypothesis was supported by several studies and needed to be tested.
At the time, two different pages were made available to potential customers. One of them allowed access to the catalog and the other did not. To the team's surprise, conversion was higher on the version without access to the catalog.
It is interesting to note that the studies included surveys in which customers said they preferred the pre-accessed page. This proves the importance of testing and the fact that not everything a customer says is what they do.
Furthermore, this information can be cross-referenced and generate new tests. One question that could be asked in this case is: could the catalog be more attractive? Could something they saw or observed have discouraged them from subscribing?
In conclusion, it is worth mentioning that the application of A/B tests is not only useful because it allows us to gather effective metrics about the user experience, but constant practice helps the team learn about the customer's experience, how they think and act. Nowadays, there is a consensus that this knowledge is essential for the business' competitiveness.
In addition to each user's preferences, the type of film they watch and the ones they select as favorites, the company creates experiences considering the most diverse details. The goal is to encourage members to watch the content made available.
In testing, different content is offered to different groups. This allows us to identify reactions and select what works best to capture the user's attention more quickly — which is essential for retention.
In Netflix's logic, there are two costa rica mobile database main reasons for not achieving the best results. The first is, evidently, not providing the right content for each user profile. The second is not providing the evidence that the user needs to decide on a content.
Obviously, after numerous tests have been carried out, the company has identified general patterns that help achieve these goals. However, the tests continue to contribute to the verification and use of a system created to group, for example, different art formats.
The same background image can be made available with different retouching, proportions and title placement, allowing you to identify which one performs best. Some cases are enlightening. For example:
Tests with the series “Sense8” — which features a multicultural cast — showed that the results were different depending on the country in which the images were shown.
In the case of “Dragons: Race to the Edge”, it was noticed that, when they presented images with villains, the acceptance was better.
In the image tests for the second season of “Unbreakable Kimmy Schmidt”, the best performance was for those that showed the characters making faces. In fact, for the title “Orange Is The New Black”, the number of characters made the difference.
The first season was promoted with the entire cast in the promotional image. This seemed to make sense in the context of the story, but when they ran tests, they noticed that users understood what the film was about better with fewer characters.
What are hypothesis tests like?
An interesting case reported by Netflix was based on the design team's suspicions. They believed that visitors would be more likely to subscribe to the service if they could browse the film catalog. This hypothesis was supported by several studies and needed to be tested.
At the time, two different pages were made available to potential customers. One of them allowed access to the catalog and the other did not. To the team's surprise, conversion was higher on the version without access to the catalog.
It is interesting to note that the studies included surveys in which customers said they preferred the pre-accessed page. This proves the importance of testing and the fact that not everything a customer says is what they do.
Furthermore, this information can be cross-referenced and generate new tests. One question that could be asked in this case is: could the catalog be more attractive? Could something they saw or observed have discouraged them from subscribing?
In conclusion, it is worth mentioning that the application of A/B tests is not only useful because it allows us to gather effective metrics about the user experience, but constant practice helps the team learn about the customer's experience, how they think and act. Nowadays, there is a consensus that this knowledge is essential for the business' competitiveness.