Help us tell a story with an AB test analysis
Budget: £10 – £80 GBP
We are looking for a skilled data analyst to help us analyze an AB test on the Booking Form of a website. The analysis should be targeted to a senior executive audience for a 15-minute presentation. I will attach a CSV file containing the test data and a description of each column in a separate file.
The test we carried out compared the display of guest ratings against star ratings on the 'Price Panel' of the booking form. Our hypothesis was that by showing guest ratings instead of star ratings on the booking form, customers would be more likely to book.
We would like you to analyze the data and create a 15-minute presentation that covers the following points:
• Overall test result
• Key highlights from the data
• Recommendations for actions on the website
• Additional analysis that should be undertaken
• Any follow-ups or additional test ideas
Our key metric in most AB tests is conversion (purchasers/unique visitors). However, we encourage you to look at other metrics to support your decision-making and drive any follow-ups or additional test ideas. Consider whether any segments are performing better than others and add hypotheses to your results. You may find pivot tables and visualizations helpful in understanding the data.
The test we carried out compared the display of guest ratings against star ratings on the 'Price Panel' of the booking form. Our hypothesis was that by showing guest ratings instead of star ratings on the booking form, customers would be more likely to book.
We would like you to analyze the data and create a 15-minute presentation that covers the following points:
• Overall test result
• Key highlights from the data
• Recommendations for actions on the website
• Additional analysis that should be undertaken
• Any follow-ups or additional test ideas
Our key metric in most AB tests is conversion (purchasers/unique visitors). However, we encourage you to look at other metrics to support your decision-making and drive any follow-ups or additional test ideas. Consider whether any segments are performing better than others and add hypotheses to your results. You may find pivot tables and visualizations helpful in understanding the data.