Rachel in Industry
Portfolio Overview
Hinge
D.A.T.E. Reports
I served as the sole quantitative researcher for Hinge's D.A.T.E. reports. These reports are meant to engage press and daters with novel research insights generated by Hinge.
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I purposively collected data to ensure representation across generations, sexual orientations, and gender identities within our core markets. I collaborated with my partners in Comms to ensure my survey would provide press-engaging statistics. Using R, I analyzed the data by comparing specific groups to identify novel and interesting data points to help shape the report. These data were shared in full through an interactive spreadsheet I designed so that all stakeholders could see how different segments showed up in our data. With a cross-functional team comprised of comms, writing, and strategy, I helped guide the narrative generation process to ensure insights accurately reflected the data.
I further facilitated the localization of these reports by collecting data from participants in target EU markets to strategically highlight unique trends that would resonate with daters abroad. This was a net new opportunity I was able to facilitate in my role.
Storytelling
I served as the sole quantitative researcher for Hinge's newsroom. Working with partners in Comms, I would help shape storytelling through collecting net-new data. I created survey instruments, collected data from participants in-app, segmented the data analysis to explore trends in particular demographic groups, and identified storytelling opportunities for my partners to pursue. I further worked with my partners in Comms to ensure these data were reflected accurately in the narrative.
Product Marketing
As the sole dedicated quantitative researcher for marketing, I also supported the product marketing team in collecting large scale survey data to inform broader strategic messaging decisions for external communications about new feature releases.
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I supported the product marketing team in one initiative to better understand how daters respond to messaging that Hinge uses AI to deliver new features in the app. I recommended an experimental approach that would compare daters' levels of desirability for particular outcomes when told those outcomes are facilitated by AI to those only exposes to the outcome. For example, ​"To be shown matches that are highly compatible for me", compared to, "For AI to show me matches that are highly compatible for me."
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Daters indicted a substantial amount of resistance to messaging about AI-delivered features, even when the outcomes they provide are highly desirable or core to our app experience. This was true across all demographic groups, even those who had positive AI sentiment.
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From this work, we aligned on an external and product comms strategy to focus on user outcomes for new features rather then the underlying tech facilitating them. This work was also used to inform additional research from the parent company to identify an AI communications strategy for other portfolio brands. This was the most cited research study in 2025.
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WillowTree Apps
Example #1: Mixed-Methods Research Project
Fitness App Strategy & Market Viability
Stakeholders: Large, global, house-hold name fitness brand (C-Suite, VPs, Directors)
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Objective: To explore the viability of and strategy for the development of a direct-to-consumer app.
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Research Activities: 8 Stakeholder interviews, in-depth 45-minute semi-structured interviews with 10 consumers (6 who had prior experience with the brand, 4 who regularly engage with the brand), a 750-person survey, a 400-person experimental survey, and in-depth 30 minute semi-structured interviews with 10 instructors over the course of 14 weeks.
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Team: Strategy, Design, Growth Marketing, Engineering, Product Management
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Project Outcomes: Through this process, we identified the market viability of the app and a price range for which the app would be appealing to consumers and fit within a competitive space. Implementation of product recommendations resulted in 400,000 app downloads in the first four months on the app store.
LiveRamp
Example #2: Mixed-Methods Research Project
Safe Haven Benchmarking Assessment
Stakeholders: Product Team
Objective: To explore how ease of use metrics, time to task completion, and user-noted pain points changed year over year in the Safe Haven product
Research Activities: 10 in-depth 60-minute usability interviews, survey, analytics
Process:
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I modified a pre-existing benchmarking plan to account for product changes that had occurred within the prior year. I recruited participants who fell into particular data-informed user personas based on their engagement with the tool and their job roles and responsibilities.
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Participants were asked to walk through a list of tasks that should be accomplishable by individuals who have similar regular daily tasks in the platform. During this process, participants were asked to share their thoughts as they navigated each task. Each task was timed to see if modifications to the product resulted in ease of use for users. Participants then completed a survey after the task-completion activity to complete the system usability score (SUS) measure to see if overall perceptions of product usability changed year over year.
Outcomes:
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I compiled a deliverable overviewing task-score changes year over year and highlighting whether the experience was unchanged, improved, or made worse. I tied in thematic assessments of participants' shared insights during the course of the study to ensure the user voice was present throughout the presentation. My recommendations rerouted the product roadmap for the next year.
Ashley
Example #3: A/B Testing
Mattress Configurator Multivariate Test
Stakeholders: Merchandising and UX teams
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Objective: To identify which button display for product options was most effective for customers on mattress product pages.
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Research Activities: Two Multivariate A/B tests
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Team: UX Design, Research, Development (Front End & Full Stack)
Process: This test employed a 2 x 2 x 2 multivariate design through which we explored the interplay between selection options for mattress sizing being displayed as text compared to an icon, a radio selector compared to no radio selector, and having an option selected by default compared to not having an option selected by default. Every user was exposed to one condition from each variable (e.g. text, radio selector, default selection). This test was run separately on mobile and desktop devices to account for differences in the volume of traffic coming from different device types. In addition, this test was run specifically on mattress product pages, only.
Data Analysis: I looked at both the main effects for each variable as well as the interaction effects between variables to see which variable and which combination of variables were driving effects. I then assessed differences between mobile and desktop users to appropriately make recommendations for each user group.
Outcomes & Recommendations:
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Add to cart rates were mostly impacted by having no default selection on product selection buttons for both mobile and non-mobile users.
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Radio buttons significantly impacted add to cart rates for both mobile and non-mobile users.
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Finally, the images and text buttons were differently effective for both mobile and non mobile users.
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From these results, I made different recommendations for mobile and non-mobile experiences, and made an iterative recommendation to assess the impact of default selection on product options across the website (beyond mattress detail pages) in future tests.
Mobile Option Selections (above)
Desktop Option Selection (below)
White Papers & Professional Publications
Voices from the drive-thru: Our research on quick-service restaurant loyalty programs
In this report, we share strategies and tactics to increase customer engagement, drive value for new and loyal customers and foster brand affinity across audience segments in the U.S. and Canada.
Beyond One-Size-Fits-All: Exclusive Research Reveals how to Capitalize on Differences in Credit Card Customer Loyalty Preferences Across Diverse Global Markets
This paper was featured in several media outlets, including BusinessWire, StockTitan, and Yahoo!Finance.
