Designed and executed evaluative and exploratory research to shape a pricing and bundling strategy that aligned with user needs while optimizing revenue. As part of the project, I conducted a series of UX follow-ups using heat maps, Google Analytics, and scroll maps to evaluate the design's impact. These insights informed iterative UX revisions to optimize user engagement and performance continuously.
Led research to shape pricing and bundling strategy, aligning user needs with revenue goals. Used heat maps, Google Analytics, and scroll maps to evaluate and refine UX, driving engagement and performance.
Impact Numbers
↑15%
User Engagement in flow
↑8%
Bundle add to cart
Impact Numbers
↑15%
User Engagement in flow
↑8%
Bundle add to cart
↓17%
Abandoned cart
Impact Numbers
↑15%
User Engagement in flow
↑8%
Bundle add to cart
↓17%
Abandoned cart
Overview
The Problem
Jetpack had been experimenting with product offerings but needed updated research to determine if bundling products can increase revenue per customer. We also aimed to identify a standard bundle that resonates broadly with customers to align product strategy with user needs and maximize growth potential.
Objectives
Assess bundling’s impact on value and revenue.
Understand customer preferences for products and bundles.
Explore ideal bundle configurations for broad appeal.
Analyze pricing sensitivity for bundles vs. single products.
Optimize strategy to boost revenue, satisfaction, and CVR.
1.Understand customer preferences for products and bundles.
Assess bundling’s impact on value and revenue.
Explore ideal bundle configurations for broad appeal.
Analyze pricing sensitivity for bundles vs. single products.
Optimize strategy to boost revenue, satisfaction, and CVR.
Research methodology
SURVEYS
My multi-pronged research strategy included exit surveys on the pricing page and a follow-up survey to understand users' long-term preferences for our product bundles.
This meter addressed consistent feedback that our products were perceived as too expensive and provided data to adjust our pricing strategy. My main goal was to uncover solid pricing sensitivity data to help us create a product offer that would convert.
THE VAN WESTERDROP PRICING SENSTIVITY METER
I chose this method because It's beneficial when you have existing customers who are familiar with your product and can provide insights based on their experience quickly.
Card Sorting
I strategically used card sorting to help control internal biases, emphasize that users' needs may differ from internal assumptions, and identify product bundles that resonate across all audience segments. The goal was to prioritize data collection and establish realistic KPIs from the outset rather than prematurely attributing a lack of lift to UI issues. attribute
Audience Stauration point
Struggling to determine the cycle time for audience saturation and lacking traffic for statistical significance, I recommended comparing results with historical benchmarks and improving audience segmentation.
SURVEYS
My multi-pronged research strategy included exit surveys on the pricing page and a follow-up survey to understand users' long-term preferences for our product bundles.
I included pricing questions because we had consistent feedback that our products were perceived as too expensive and provided data to adjust our pricing strategy.
THE VAN WESTERDROP PRICING METER
I chose this method because It's beneficial when you have existing customers who are familiar with your product and can provide insights based on their experience quickly.
Card Sorting
I strategically used card sorting to help control internal biases, emphasize that users' needs may differ from internal assumptions, and identify product bundles that resonate across all audience segments. The goal was to prioritize data collection and establish realistic KPIs from the outset rather than prematurely attributing a lack of lift to UI issues. attribute
Audience Stauration point
Struggling to determine the cycle time for audience saturation and lacking traffic for statistical significance, I recommended comparing results with historical benchmarks and improving audience segmentation.
SURVEYS
My multi-pronged research strategy included exit surveys on the pricing page and a follow-up survey to understand users' long-term preferences for our product bundles.
I included pricing questions because we had consistent feedback that our products were perceived as too expensive and provided data to adjust our pricing strategy.
SURVEYS
My multi-pronged research strategy included exit surveys on the pricing page and a follow-up survey to understand users' long-term preferences for our product bundles.
This meter addressed consistent feedback that our products were perceived as too expensive and provided data to adjust our pricing strategy. My main goal was to uncover solid pricing sensitivity data to help us create a product offer that would convert.
THE VAN WESTERDROP PRICING SENSTIVITY METER
I chose this method because It's beneficial when you have existing customers who are familiar with your product and can provide insights based on their experience quickly.
Audience Stauration point
Struggling to determine the cycle time for audience saturation and lacking traffic for statistical significance, I recommended comparing results with historical benchmarks and improving audience segmentation.
Card Sorting
I strategically used card sorting to help control internal biases, emphasize that users' needs may differ from internal assumptions, and identify product bundles that resonate across all audience segments. The goal was to prioritize data collection and establish realistic KPIs from the outset rather than prematurely attributing a lack of lift to UI issues. attribute
Initial findings and recommendations
The data supported self-selecting bundles with personalized choices and minimal overlap. Exit surveys showed polarized results, indicating a mixed audience.
Due to limited data and time constraints, we could not reach statistical significance. We focused on low-risk strategies like iterative testing and qualitative feedback.
LACK OF STATISTICAL SIGNIFICANCE
Action Item
Focus on low-risk strategies, iterarive testing.
Action Item
Focus on low-risk strategies, iterarive testing.
Our traffic numbers we not enough to reach stat sig an not slow down engineering momentum.
no clear preference for a
single bundle
Action Items
• Use current data on the most popular products and likely bundles based on the user's site type. • Offer a discount for purchasing multiple products •Test new verbiage • Invest time to test audience segmentation for logged-in users
Action Items
• Use current data on the most popular products and likely bundles based on the user's site type. • Offer a discount for purchasing multiple products •Test new verbiage • Invest time to test audience segmentation for logged-in users
This data highlights the price range where users are equally divided between considering the product "expensive" and a "bargain".
Post launch results and recommendations
I revisited the data every 2 weeks, we continued to iterate until we found the optimal product offering that offered the best chance for increased RPC with the least amount of development effort.
Averted a costly proposed project through actionable insights.
Findings
The data favored self-selecting bundles with minimal overlap, while exit surveys revealed mixed audience preferences. With limited data and time, we relied on iterative testing and qualitative feedback to validate assumptions.
Impact Numbers
↑15%
User Engagement in flow
↑8%
Bundle add to cart
↓17%
Abandoned cart
Impact Numbers
↑15%
User Engagement in flow
↑8%
Bundle add to cart
↓17%
Abandoned cart
LACK OF STATISTICAL SIGNIFICANCE
Action Item
Focus on low-risk strategies, iterarive testing.
Action Item
Focus on low-risk strategies, iterarive testing.
Our traffic numbers we not enough to reach stat sig an not slow down engineering momentum.
no clear preference for a single bundle
no clear preference for a
single bundle
Action Items
• Use current data on the most popular products and likely bundles based on the user's site type. • Offer a discount for purchasing multiple products - Simplify tiers •Test new verbiage • Invest time to test audience segmentation for logged-in users
Action Items
• Use current data on the most popular products and likely bundles based on the user's site type. • Offer a discount for purchasing multiple products - Simplify tiers •Test new verbiage • Invest time to test audience segmentation for logged-in users
This data highlights the price range where users are equally divided between considering the product "expensive" and a "bargain".
Sketches and wireframes
Pairing with one excellent zing senior product, designers we fleshed ideas and wireframes to gain alignment with stakeholders
and engineers.
Post-launch findings and recommendations
Post-launch findings and recommendations
I reviewed data biweekly, iterating to optimize the product offering for higher RPC with minimal development effort.
Clicks to pricing page >
no purchase:
Action items
Iterate to clarifying the IA and adding more detailed pricing.
Action items
Iterate to clarifying the IA and adding more detailed pricing.
Hypothesis | Users clicking on 'Pricing' while already on the pricing page suggest confusion in the IA or a desire for a clearer breakdown of pricing options.
Clicks ON products >
no purchase:
Action items
Test more detailed product descriptions using heat map data to identify high-interest areas on product pages. Then, pull key information from those sections into the pricing page descriptions.
Action items
Test more detailed product descriptions using heat map data to identify high-interest areas on product pages. Then, pull key information from those sections into the pricing page descriptions.
Hypothesis | Users clicking on products seek more information before purchasing, potentially not seeing the information that would inspire a purchase.
Clicks to agency log in >
Leaves site:
Action items
Exclude this % (audience segment) from the pricing page CVR metrics for accurate goal setting.
Hypothesis | Indicates some users are likely browsing or completing different tasks..
Clicks to agency log in >
Leaves site:
Hypothesis | Indicates some users are likely browsing or completing different tasks..
Action items
Exclude this % (audience segment) from the pricing page CVR metrics for accurate goal setting.
Action items
Exclude this % (audience segment) from the pricing page CVR metrics for accurate goal setting.
Impact Numbers
↑15%
User Engagement in flow
↑8%
Bundle add to cart
Impact Numbers
↑15%
User Engagement in flow
↑8%
Bundle add to cart
Averted a costly proposed project by vetting with users.