Trends Search Page A/B Testing

 Experiment planning

Overview

• What type of experiment is this?

  • Search Page A/B Testing

• What user problem is being solved 

  • Helps user navigate the search page and also reduces any confusion in using the trends page

Hypothesis

We hypothesize that the intuitive search page

will increase the active users and reduce bounce rate on the search page, decrease number of clicks & number of navigations to home page,

because a streamlined and clearer interface reduces user frustration and confusion.

Metrics

• primary metric

• Session Time

• Clicks

• No. of Times Navigated back to home page

• secondary metric

• Feedback/Rating pop window

Targeting

• Where will this experiment run?

  • Live on Trends page using randomly generated views for the same weblink

• Who will see it?

  • Current UTD students

• What is the traffic allocation (% in total let in based on targeting)?

  • 100%

Variations

	A: Control	B: Variation

	A: Control	B: Variation
Screenshot	Open	Open
% of visitors/users to see each variation

Pre-analysis

Add any baseline data or pre-analysis you have for this experiment.

Total Sample Size: 100

Time: 1 Week

Notes

Engineering Team will help facilitate the test:

• Randomly display the search pages each time

• Integrate Google Analytics for session time

• Provide a way to access click counts on each of the elements

Trends team will need to market the new page to get traffic and users to test the feature.

 Results

Add a short summary of the metrics below and whether you hit significance.

 Conclusions

Highlights

• Primary goal

  • increase / decrease,  by

• • increase / decrease,  by

Takeaways

Follow-up