Overview
LovePulse is a product concept exploration in the dating and emotional wellness space that reimagines how people engage with their romantic lives. By focusing on reflection and emotional insight, it aims to bring more intention and clarity to the modern dating experience.
Problem
Dating… it's messy, exciting, exhausting, and sometimes downright confusing. When attempts don’t lead to fulfilling relationships, people are left feeling discouraged, emotionally drained, and wondering what they're doing wrong.
Solution
Design a tool that creates meaning from the dating process. LovePulse is a data-driven journaling app that helps singles reflect on their experiences, feel seen, uncover patterns, and make more intentional dating decisions.
Impact
80%
80% of participants rated the app as useful in their dating journey
Boosted user motivation to continue dating by encouraging reflection, leading to more intentional dating decisions
Delighted users with creative use of AI insights that felt both actionable and supportive
Here's how I got there
EMPATHIZE
Modern daters crave tools and feedback to become more efficient in their dating process
After speaking with five individuals at varying stages of their dating lives, from those causally dating to happily partnered after heartbreak, I gained a deeper understanding of the emotional complexities, needs, and motivations that shape modern relationships.
Despite their unique stories, common threads emerged:
Dating motivation declines over time
as repeated, unsuccessful efforts lead to frustration.
Experience clarifies preferences
as daters learn more about their wants/needs.
Feedback is lacking or non-existant
as daters struggle to optimize first impressions
Ultimately, people craved tools or feedback to become more efficient daters (Efficient = finding a romantic connection in fewer dates with less heartbreak.)
Over time, they naturally became more skilled at perfecting their profiles, knowing what they wanted, and recognizing their unique dating patterns, but the process of discovering these trends often came with unnecessary heartbreak and frustration.
Survey confirmed this experience is widespread
The survey results further supported the understanding that singles who are actively dating are looking for a serious relationship and are frustrated with how long and emotionally taxing the process is with little to no feedback.
Top Goals:
Life Partner/Marriage (69%)
Long Term Relationship (63%)
Explore Connections (31%)
Top Frustrations:
Wishing to find their person faster (47%)
Knowing what they are doing right or wrong (63%)
Feeling that dating is emotionally taxing (31%)
Dating in the era of… spreadsheets?
Internet research revealed some turned to data analysis to support their dating process
Spreadsheet Dating
Chin Lu’s popular article “My secret to dating in San Francisco is a spreadsheet” highlighted how she used a spreadsheet to reflect on her dating choices, spot patterns, and find her ideal partner more quickly.
Data Hacking
Amy Webb’s TED Talk, “How I Hacked Online Dating,” which later became a book, described how she used data analysis to navigate her dating life more strategically and more efficiently find her partner.
Dating Wrapped


Viral TikTok trend, “Dating Wrapped,” where people showcase their annual dating stats like a Spotify Wrapped recap, revealed a growing fascination with using data to observe the dating experience.
These aren't the only examples. Chin also noted that many others have publicly shared they used spreadsheets for various purposes:
To feel a "sense of accomplishment … even if a date is bad"
To start anew in finding love in one’s 40s
DEFINE
Bottom line: dating sucks… so how might we fix it?
It was time to narrow down my problem. I knew I wanted to explore ways to help people who are actively dating find a long term relationship more efficiently.
How might we…
Create tools or activities that help individuals reflect on their personal values, relationship goals, and what they are looking for in a partner?
How might we…
Design experiences that encourage people to explore their emotional and psychological patterns in the context of dating?
How might we…
Use feedback mechanisms to help individuals gain insights into their dating behaviors and preferences?
Goal: Design an app that empowers users to understand their dating patterns and gain self-awareness so they can be more effective in dating by making more conscious dating decisions.
POV: I'm a user who's been dating for years but still haven't found my person
Our user persona became our North Star and anchor for design decisions.
Meet Sam! She’s serious about finding a relationship, but dating has left her drained. She’s ready for a more efficient, intentional approach.
How might we… help Sam stay motivated and find meaning amongst the constant stream of dating disappointments?
IDEATE
Exploring data-driven dating
I used a variety of brainstorming methods when thinking of potential solutions. While my ideas ranged from a rejection text generator that notes when a relationship has gone stale to an anonymous date review site, my research inspired me to focus on creating a solution where dating data is used to help users become more efficient and inspired.
Inspired by the term Business Insights and my operations background, I'm calling the solution a dating insights app.
People who tracked their dating experiences did so using a wide range of methods and metrics
A second round of user interviews specifically targeted potential users who have tracked their dates lives in some manner.
Methods
Some leaned into self-reflection through journaling, while others took a more analytical approach, tracking data to find patterns.
Motivations
Motivations ranged from identifying trends across failed relationships to finding encouragement in positive patterns, especially after a breakup, or when starting over.
Metrics
People tracked everything from names and attraction levels to values and breakup reasons, either logging in real time or reflecting periodically.
Let's make a "dating insights" app!
With a clearer idea of which direction I’d be going, I created a feature matrix and prioritized based on the goals and needs of my target user. From this, I knew the key features to focus on were:
Users want to make more intentional dating decisions but often don’t take the time to process how each date went.
Date tracking to log dates and evaluate the experience
Users want to evaluate compatibility and sometimes need help recognizing what they are attracted to in a partner.
Love Interest profiles that capture insights and metadata about each person dated
Users want to better understand themselves and their dating experiences and are motivated by positive patterns
Data insight graphs and descriptions to surface dating trends across tracked data
User flows outlined how users could track dates, view love interests, and explore insights
Throughout the development of this project the user flow went through multiple iterations. The two shown below demonstrate the shift from the original to the final concepts.
PROTOTYPE & TEST
Wireframes transformed ideas from insights to interface
Mid-fidelity wireframes allowed me to design with enough detail to spark meaningful feedback without overloading participants with unnecessary polish.
Reflect on Dates
Users can log individual dates, rate their experiences using default or custom categories, and add notes about their experience.
Time to test this crazy concept
Because dating insights is a new concept, I decided to start with a concept test. I had four potential users explore the mid-fidelity designs with the goal of validating the overall idea.
Evaluate the perceived usefulness of a "dating insights" app
Evaluate the usability of the app based on satisfaction
Identify potential pain points and areas of confusion
Result: Users liked it but were most excited about the personalized journaling prompts
This concept test validated the idea. Users were excited by the thought of dating insights and some were even surprised an app like this doesn’t already exist. However, while they appreciated the scoring and trend graphs, the journaling prompts stood out most.
Users were intrigued and excited about an app that reveals personal dating patterns (ie dating insights)
Users saw the personalize journaling prompts as potentially the most impactful feature
Users wanted and expected to engage with journaling prompts directly within the app
Users felt tone was too clinical and wanted a softer, friendlier tone with more actionable takeaways
Reframing around reflection
Though originally a secondary feature, user feedback made it clear that personalized journaling prompts were more than a nice-to-have. One user even called this the "gold mine" of the app.
This led us to pivot and shift focus toward journaling and more qualitative insights.
Competitors now included AI-powered journaling tools
Initially, there were few direct competitors with just one dating-focused app (Dateforce), a handful of personal tracking tools, and, of course, spreadsheets. But as journaling became central to the experience, AI-powered journaling tools emerged as relevant players.

Rosebud
Interactive AI journal designed alongside mental healthcare professionals to complement traditional therapy at a fraction of the cost.

Untold
Voice journaling + AI reflection that allow users to reframe and see their life from a personally tailored, objective and compassionate third-party perspective.

Stoic
AI journaling app that analyzes entries to uncover patterns and offer personalized prompts to support self-reflection and personal growth.

Mindsera
AI powered journal designed to give personalized mentorship and feedback for improving users’ mindset, cognitive skills, mental health, and fitness.
By observing the features that are prioritized in competitors, I could get a sense that users’ top priorities are personalized AI generated reflections on the user's reflections and conversational, chat-like experiences.
No competitors focus on dating or combine qualitative journaling with quantitative data to provide user insights
Adding reflections into the flow
While users can add a reflection at any time, the ideal flow was designed to prompt reflections after logging a date. This allows users to quickly capture date details, receive initial AI-generated insights, and then seamlessly transition into deeper reflection.
Date Summary
Reflection Chat
Saved Reflection
A second concept test solidified our pivot
Participants rated the app’s usefulness highly, with most expressing genuine excitement about its potential to support self-reflection, growth, and even early-stage relationships. They valued the app’s potential to aid in self-reflection, personal growth, and even supplement therapy or coaching.
Then it was time to develop the app's style + branding
Before I could move onto designing the high-fidelity wireframes, it was time to develop the brand identity and bring the app to life.
And bring the vision to life
With the visual direction established, I built out the high-fidelity screens and connected them in a clickable prototype.
Usability testing revealed some wins
In usability testing, participants quickly saw the value of the app, highlighting its potential to support self-reflection and growth in dating.
80%
Average Trust Score
(Score out of 5)
Boosted user motivation to continue dating by encouraging reflection and intentional dating decisions
Delighted users with creative use of AI insights that felt both actionable and supportive
While some terms, such as "reflect" or "love interest," weren’t immediately intuitive, users adapted quickly. The average time to add a date dropped by more than half on the second try, and perceived difficulty decreased from 1.9 to 1.3, signaling increased familiarity and confidence with use.
Yet more updates were needed
Key iterations included updates to the Date Summary page and Insights graphs.
DATE SuMMARY
Improved visibility of the Dating Summary by using a dark background and light text to highlight the autogenerated content.
Before
After
DATing insights
Reduced scroll fatigue by splitting active vs. ended insights into separate pages and converting vertical graphs to horizontal scroll.