Homepage Optimization
16 experiments testing homepage changes across Direct Energy and NRG brands. Win rate: 31%. 5 winners found.
Key Findings
Homepage Redesign 2.0
Winner: Homepage Redesign 2.0.
Homepage Use Case
Hypothesis: A first test could be just the pathways but no actual changes to the grid (or minor changes) in order to test as an MVP and see if users engage. Follow up experiments couple include adding/removing certain filters or plans from the next step to ensure the plans shown are most relevant as well as additional headline and copy changes for that audience. Category analysis - this is done on competitor sites for apt/home and on comparison sites for multiple use cases. *Zip code:* 77024, 77080 *Address*: 30 mott ln (the number 30 can be changed to anything)
Winner: Homepage Use Case. A first test could be just the pathways but no actual changes to the grid (or minor changes) in order to test as an MVP and see if users engage. Follow up experiments couple include adding/removing certain filters or plans from the next step to ensure the plans shown are most relevant as well as additional headline and copy changes for that audience. Category analysis - this is done on competitor sites for apt/home and on comparison sites for multiple use cases. *Zip code:* 77024, 77080 *Address*: 30 mott ln (the number 30 can be changed to anything)
Hypothesis: A first test could be just the pathways but no actual changes to the grid (or minor changes) in order to test as an MVP and see if users engage. Follow up experiments couple include adding/removing certain filters or plans from the next step to ensure the plans shown are most relevant as well as additional headline and copy changes for that audience. Category analysis - this is done on competitor sites for apt/home and on comparison sites for multiple use cases. *Zip code:* 77024, 77080 *Address*: 30 mott ln (the number 30 can be changed to anything) Next steps: Lead to Hypothesis/Idea
Homepage / Grid
Winner: Homepage / Grid.
Homepage
Winner: Homepage.
Homepage Hero Redesign
Hypothesis: Evidence - Heatmap: Here we can see that when presenting users with the option for non-conversion journeys, a majority of users who land on the homepage are looking for a way to sign up. Evidence - Competitor Research: When users are already personalizing their plans from first impression, there is a higher commitment to purchase as the user moves down funnel. Evidence - Removing Distraction: https://docs.google.com/presentation/d/194ySs7bvSlBKl_hbxtTfGXZTl1fNTWRc7pXMeOm8VvU/edit#slide=id.p7
Winner: Homepage Hero Redesign. Evidence - Heatmap: Here we can see that when presenting users with the option for non-conversion journeys, a majority of users who land on the homepage are looking for a way to sign up. Evidence - Competitor Research: When users are already personalizing their plans from first impression, there is a higher commitment to purchase as the user moves down funnel. Evidence - Removing Distraction: https://docs.google.com/presentation/d/194ySs7bvSlBKl_hbxtTfGXZTl1fNTWRc7pXMeOm8VvU/edit#slide=id.p7
Hypothesis: Evidence - Heatmap: Here we can see that when presenting users with the option for non-conversion journeys, a majority of users who land on the homepage are looking for a way to sign up. Evidence - Competitor Research: When users are already personalizing their plans from first impression, there is a higher commitment to purchase as the user moves down funnel. Evidence - Removing Distraction: https://docs.google.com/presentation/d/194ySs7bvSlBKl_hbxtTfGXZTl1fNTWRc7pXMeOm8VvU/edit#slide=id.p7
Frequently Asked Questions
What is the "Homepage Optimization" insight cluster?
This cluster aggregates 5 research findings, test results, and optimization principles related to homepage optimization. Each entry includes expected lift ranges, confidence levels, and source attribution so you can evaluate applicability to your own tests.
How reliable are the expected lift ranges in this cluster?
Lift ranges represent aggregated outcomes from multiple experiments and research sources. They are directional estimates, not guarantees. Your actual results will vary based on traffic volume, audience, current baseline, and implementation quality. Always validate with your own A/B test.
How do these findings apply to Homepage optimization?
These findings are specifically relevant to homepage optimization on homepage pages. Use the expected lift ranges to prioritize your testing roadmap and the key learnings to inform your hypothesis development.
Where does the data in this cluster come from?
Data is sourced from published UX research, aggregated experiment data across multiple organizations, industry studies, and validated internal findings. Each entry includes its source type so you can assess credibility. Entries marked as validated have supporting statistical evidence.
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