Independent Consumer Product · Travel
Solace
A solo travel planning product that matches people with destinations based on comfort, social preferences, interests, budget, pace, and remote work needs, then helps them build editable itineraries.
Defined, built, tested, and launched end to end · Live product
Role
Product strategy, design, and build
What I Owned
Problem definition, target user, product strategy, feature prioritization, design, build, usability testing, and launch
Status
Live product
The Product: Desktop & Mobile
Landing: Travel the world, beautifully alone
I independently identified the product opportunity, defined the target user and product strategy, prioritized the initial feature set, designed and built the experience, conducted usability testing, and launched the live product.
Product type
Consumer travel product
Timeline
Summer 2026
Primary users
People considering or planning solo travel
Looking for consumer wellness product work?
Explore A Place of CalmThe Problem
Why solo travel planning is hard
Travel platforms help people decide where to go, but they rarely help someone decide where they will feel comfortable traveling alone. Solo travelers often have to combine destination research, safety information, budgets, itinerary tools, maps, and personal judgment across multiple sources.
The product opportunity was to bring those decisions into one connected flow and recommend destinations based on personal fit rather than popularity alone.
Strategy
How I defined the product direction
Roadmap and Prioritization
Prioritized the initial product around destination matching, preference-based recommendations, and itinerary creation. Budgeting, map-based visualization, and manual planning followed based on how travelers actually planned.
Constraints
Independent product with no existing user base, built and launched by one person within a single summer.
Target User
People considering or planning solo travel who care about comfort, safety, pace, and the kind of experience they want as much as the destination.
Hypothesis
If solo travelers could match destinations to how they wanted the trip to feel, they would plan with more confidence and less reliance on popularity-based recommendations.
Product Framing
I defined the product around a planning confidence gap for solo travelers. Rather than recommending destinations primarily through popularity or cost, Solace uses personal preferences to help users evaluate where they are likely to feel comfortable and how the trip could work in practice.
Research & Validation
What I believed, what I tested, and what changed
My Hypotheses
- 01Solo travelers prioritize emotional comfort safety, social ease, and pace over cost or popularity when choosing destinations.
- 02Most travel platforms optimize for popular destinations, not personal fit, leaving solo travelers to piece together information from multiple sources.
- 03A match score with transparent reasoning would be more useful than an unexplained recommendation.
Testing & Validation
Who Was Tested
6 solo travelers with varying comfort levels and travel styles.
Method
Think-aloud walkthroughs of the matching flow, destination comparison, and itinerary builder, followed by semi-structured interviews.
What I Learned
- •The original ten preference dimensions created questionnaire fatigue, so the matching flow was reduced to six.
- •Users expected budgeting alongside the itinerary, so a budget summary was moved into the itinerary experience.
- •The full page city comparison caused users to lose their place, so it was changed to a modal.
- •Testing led to direct city selection, itinerary maps, and multimodal transportation options with travel times.
- •Users wanted honest downsides alongside positive recommendations.
What Failed & What Changed
What Failed
Budget was a separate page, requiring users to navigate away from the itinerary.
What Changed
Moved a budget summary into the itinerary view as a floating card so users could see costs while planning.
What Failed
Originally had 10 preference dimensions users found the long questionnaire fatiguing.
What Changed
Reduced to 6 dimensions: social energy, pace, comfort, budget, work schedule, and interests.
What Failed
City comparison was a full-page view users lost their place in the destination list.
What Changed
Changed to a modal so users could compare destinations without losing context.
Product Decisions
The decisions that shaped the experience
Matching people by how they want the trip to feel
User Need
Solo travelers needed a way to find destinations that fit how they wanted to travel, not just where everyone else was going.
Decision
Designed the experience around the type of trip the user wanted, using preferences for social energy, pace, comfort, work schedule, and interests to recommend destinations based on personal fit.
Tradeoff
Required more preference inputs up front in exchange for recommendations that felt personally relevant.
What Changed After Testing
Testing reduced the preference dimensions from ten to six after users found the long questionnaire fatiguing, confirming that fewer, well chosen preferences still produced relevant matches.
Explaining why a destination fits
User Need
Users trusted a recommendation only when they understood why a destination was suggested.
Decision
Designed the experience to explain how a city aligned with the user's preferences rather than presenting it as an unexplained result.
Tradeoff
More explanation added content to each card, but increased trust and reduced second-guessing.
What Changed After Testing
Testing confirmed users wanted transparent reasoning, including both reasons to choose a city and things to keep in mind, which became the structure of every recommendation card.
Supporting both assisted and manual planning
User Need
Not every traveler wanted an automatically generated itinerary; some wanted control over the schedule.
Decision
Added a manual itinerary builder so users could create their own schedule while still using Solace's recommendations as inspiration.
Tradeoff
Increased scope, but served travelers who wanted control without losing those who wanted assistance.
What Changed After Testing
Testing led to direct city selection and editable planning controls, confirming that both assisted and manual planning were necessary.
AI Transparency
What the AI does, and what it doesn't
Preference-weighted, not AI
Match scores come from six declared preferences: social energy, pace, comfort, budget, work schedule, and interests. The weighting is transparent and rules-based, so the same inputs always produce the same result.
Where AI is used
AI assists with itinerary drafts and the natural-language reasoning that explains why a destination fits, turning structured scores into readable guidance.
Always user-controlled
Every generated output is editable. Users can build itineraries manually, adjust preferences at any time, and see the factors behind each recommendation.
Delivery
From Product Vision to Live Launch
I independently moved the product from opportunity definition through launch. I defined the positioning and feature set, built the end to end planning flow, tested the core decisions with target users, and revised the product when testing revealed friction or missing context.
Conception
Conception
Defined the product vision and feature set from scratch, then designed and built the working product.
Research
Research
Identified the factors that make a destination feel right for solo travel: social energy, pace, comfort, budget, remote-work needs, and interests.
Design & Build
Design & Build
Designed and built the full flow: matching, recommendations, itineraries, budget, and map visualization.
Product Walkthrough
The product in motion
Finding your match
I designed matching around how users want the trip to feel social energy, pace, comfort, and work schedule rather than just where they want to go.
Recommendations with Reasoning
Perfect Cities: Handpicked destinations with the why behind each match
City Comparison: Side-by-side to help you decide
How the matching works
The matching approach considers comfort, social preferences, pace, budget, and remote-work needs to recommend destinations that fit the individual traveler.
The Approach
Understanding a destination
Each city includes a first-24-hours itinerary, soloist metrics, and a budget view so travelers can evaluate whether a destination is right for them.
City Detail: How Vancouver fits solo travel, with a first 24 hours matched to what you want from the trip
Budget: See what your stay leaves room for
Building an itinerary
Users can generate an itinerary or build one manually. The itinerary also accounts for transportation, showing walking, public transit, and driving times between stops, and the map view shows whether a day is geographically realistic.
Making It Practical
Itinerary: A day in Copenhagen
Mobile itinerary: A day in Copenhagen on the go
Managing your trips
The My Trips page keeps planned and active destinations in one place, with match scores and trip status visible at a glance.
The Destination
Validation, Launch, and Next Steps
6 of 6
Participants expected budgeting with the itinerary
10 → 6
Preference dimensions reduced after usability testing
Page → modal
City comparison changed after users lost context
A live product, validated through qualitative testing and iteration.
The product is live, but it is still early for behavioral or retention claims. The current results reflect qualitative validation and product iteration rather than scaled market impact.
What I Would Measure Next
- 01Conversion from first destination match to a saved or shared itinerary.
- 02Which preference dimensions most influence destination selection and satisfaction.
- 03Whether users return to plan a second trip and what they change.
- 04Drop-off points in the assisted to manual planning handoff.
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