A hotel in Indonesia has a website for their customer to book their rooms. Besides that, the website has an important role to attract and engage more customers to book their rooms. Hopefully, it would also make the hotel to be more well-known in the city.
The manager of this hotel wants to make changes in some features in the website to increase their purchasing rate (more customers rent their rooms). Therefore, the manager initiates the changes by elaborating A/B testing to the website for the new features. The experiment has a month to extract the data and then do the hypothesis testing to check whether the new features have a greater impact on the increase of their purchasing rate. After a month, the data is ready to use in hypothesis testing.
From the z-test p-value which is 0.0245 (less than 5%), we can conclude that the new website features has different conversion rate with the default website features. The relative uplift for the new website features is 82.72% from the default website features. So, we can conclude that the new website features has significant effect on the increased of purchase conversion rate in the hotel website.
Therefore, we can suggest to the manager of the hotel to update their website using the new features.