Pricing Optimization
13 experiments testing pricing changes across Direct Energy and NRG brands. Win rate: 15%. 2 winners found.
Key Findings
exp-80.0-dp-all-price-points-on-plan-cards
Hypothesis: We will add all 3 price points to the product chart view, as well as adding a callout for the Bill Credit Bundle 20 product, and making sure that product shows up first on product chart when available.
Winner: exp-80.0-dp-all-price-points-on-plan-cards. We will add all 3 price points to the product chart view, as well as adding a callout for the Bill Credit Bundle 20 product, and making sure that product shows up first on product chart when available.
Hypothesis: We will add all 3 price points to the product chart view, as well as adding a callout for the Bill Credit Bundle 20 product, and making sure that product shows up first on product chart when available. Next steps: Lead to Experiment
Pricing Prominency on Grid
Hypothesis: Reducing the saliency of pricing information will have beneficial outcomes for the business as rates will be at an all time high in the months prior to fall.
Winner: Pricing Prominency on Grid. Reducing the saliency of pricing information will have beneficial outcomes for the business as rates will be at an all time high in the months prior to fall.
Hypothesis: Reducing the saliency of pricing information will have beneficial outcomes for the business as rates will be at an all time high in the months prior to fall.
We're Holding Your Rate Urgency
Hypothesis: If we add a component to the checkout page that indicates that direct energy is guaranteeing that rate for the next X amount of time (similar to a checkout timer when buying concert tickets, or a quote guarantee when looking at insurance) we can increase the urgency that a user feels to complete the checkout flow and sign up for the plan. Test archive - countdown timers Category analysis - quote guarantees, ticket price countdown timers Lift point - urgency
Loser: We're Holding Your Rate Urgency. If we add a component to the checkout page that indicates that direct energy is guaranteeing that rate for the next X amount of time (similar to a checkout timer when buying concert tickets, or a quote guarantee when looking at insurance) we can increase the urgency that a user feels to complete the checkout flow and sign up for the plan. Test archive - countdown timers Category analysis - quote guarantees, ticket price countdown timers Lift point - urgency
Hypothesis: If we add a component to the checkout page that indicates that direct energy is guaranteeing that rate for the next X amount of time (similar to a checkout timer when buying concert tickets, or a quote guarantee when looking at insurance) we can increase the urgency that a user feels to complete the checkout flow and sign up for the plan. Test archive - countdown timers Category analysis - quote guarantees, ticket price countdown timers Lift point - urgency
Rate Toggle
Loser: Rate Toggle.
[Cirro] - exp-79.0-cirro-all-price-points-on-plan-cards
Hypothesis: If we display all three price options on the plan card on the landing page and make the cheapest price option the most prominent, then the conversion rate among prospects will increase. This is because prominently highlighting the most affordable option provides clear and immediate pricing information, emphasizing the value proposition and encouraging prospects to make a quicker, more informed decision.
Loser: [Cirro] - exp-79.0-cirro-all-price-points-on-plan-cards. If we display all three price options on the plan card on the landing page and make the cheapest price option the most prominent, then the conversion rate among prospects will increase. This is because prominently highlighting the most affordable option provides clear and immediate pricing information, emphasizing the value proposition and encouraging prospects to make a quicker, more informed decision.
Hypothesis: If we display all three price options on the plan card on the landing page and make the cheapest price option the most prominent, then the conversion rate among prospects will increase. This is because prominently highlighting the most affordable option provides clear and immediate pricing information, emphasizing the value proposition and encouraging prospects to make a quicker, more informed decision. Next steps: Lead to Experiment
Frequently Asked Questions
What is the "Pricing Optimization" insight cluster?
This cluster aggregates 5 research findings, test results, and optimization principles related to pricing 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 Pricing optimization?
These findings are specifically relevant to pricing optimization. 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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