BRKAWAY
Designing a smarter way for brands to discover content creators.
Overview
Designing an AI-powered creator discovery tool that helps brands find the right creators in seconds.
Intro
Brkaway aims to make content creator discovery effortless for brands. With AI-powered search, brands can find creators in seconds. Brands can upload a reference video or simply describe the type of creator they’re looking for. This dual approach removes barriers, saves time, and ensures brands always find the right creative fit.
Problem
Brands struggle to discover content creators who truly match their content needs. Current discovery tools force them into endless scrolling, guesswork, and manual vetting, slowing campaigns down and leading to missed opportunities.
Outcome
I designed an AI-powered creator discovery tool with two entry points: reverse video search for when brands have a reference, and text search for when they know the type of creator they want. This reduced search time by 40% and made it easier for brands to quickly find creators who fit their vision.
Role & Responsibilities
As the sole product designer, I led the project end-to-end:
Partnered with engineering to scope technical feasibility of both video and text-based search.
Conducted competitive research and mapped user journeys across discovery workflows.
Designed, prototyped, and tested high-fidelity flows for both search types.
Iterated through design reviews with leadership and shipped a production-ready tool.
Timeline
4 months
Problem
Searching for content creators that can produce brand-aligned content is time consuming.
Brands spend hours combing through social media apps to find creators who can produce content aligned to their branding. The process is slow and inefficient, leading to missed opportunities and inconsistent posting.
Solution
From video uploads to text prompts, Brkaway makes creator discovery effortless and flexible.
Brkaway brings AI-powered discovery into one streamlined experience, giving brands two powerful ways to find creators: reverse video search and text-based search. Whether they have a top-performing video to reference or just know the kind of creator they’re looking for, Brkaway reduces the time spent searching and ensures matches are relevant and aligned with their needs.
Exploring & Ideating
Going broad, then narrow.
Starting with stickies, I led brainstorming session with the cross-functional team to ideate on different ways we could make the search process easier for brands.
Some standout ideas included:
Advanced filter & search
Allow brands to search and filter Brkaway’s catalog of creators. Filter by style, tone, industry, audience demographics, content types.
AI-powered matchamaking
Use machine learning to match brands with creators whose content style aligns with brand’s identity.
Dynamic gallery
Offer a dynamic gallery where brands can explore different content styles and save preferences or shortlist creators/content.
Consultation chatbot
AI-driven chat support that answers questions and can suggest creators in real time.
At the end of the brainstorming session, we unanimously decided to move forward with AI-powered matchmaking because it'd be an innovative solution that provides users with targeted and relevant search results.
Early Designs
Starting with low-fidelity designs to quickly ideate different layouts.
Review & Refine
I ran design reviews with my CEO and team, iterating quickly to align on vision and refine the user experience.
Home page
I redesigned the homepage from a static “get started” screen to a functional entry point for discovery. Now, brands are guided toward AI search options (video or text) while also surfacing featured creators, allowing for creator discovery in multiple ways.
The homepage was instructional but uninspiring, relying on static text to explain how discovery worked. Users were told what to do, but weren’t given an engaging or intuitive way to begin their search.
The redesigned homepage feels like a creator marketplace. It guides users directly into AI-powered search (video or text), highlights featured creators as inspiration, and offers browsing of the full creator catalog making discovery both functional and dynamic.
Search input
Initially, we explored combining video and text search into one input, but it created unnecessary complexity. We refined the flow by separating the two search methods, giving brands clarity and control over how they want to discover creators.
The “Add Content Example” CTA was vague, making it unclear that users could upload a video as well as type text. This led to confusion about how to start the search.
Dedicated sections for text vs. video search make the choice explicit. Brands can either upload a video or type what they’re looking for, without second-guessing the process.
Showing matches
The challenge was presenting multiple video matches per creator without overwhelming users. We also needed to provide richer context like industries, content types, and social stats so brands could make informed decisions.
Rows of repeated creator videos cluttered the results, with little creator context beyond the video itself. This made it harder for brands to evaluate fit.
Creators now have dedicated cards that group all matched videos together while surfacing bios, industries, and content types. This structure highlights both style and substance, giving brands everything they need at a glance.
Final Designs
Putting everything together.
The final result was an AI reverse video search tool that allows brands to upload content they like and find creators on our platform that can produce similar content.
Outcome & Impact
The new AI-powered search reduced discovery time by 40%, lowered entry barriers for brands, and improved creator match quality across campaigns.
Faster creator discovery
Creator discovery became 40% faster, allowing brands to find relevant creators in minutes instead of hours.
Stronger creator matches
Campaign match rates increased by 30%, with AI recommendations leading to stronger creator-brand alignment.
Lower barriers to entry
Engagement from brands without reference videos doubled, showing that text search significantly lowered the barrier to entry.
Challenges & Lessons Learned
What we uncovered during the process, and how we used those insights to shape future releases.
Challenge: Balancing two search methods
We debated whether to merge video and text search into one input. Testing showed this added confusion about what to prioritize.
Lessons learned
Keeping them separate gave brands clarity. For future iterations, we’ll explore adaptive search that intelligently recommends the best path based on input.
Challenge: Limited user testing
Tight timelines meant early iterations relied on internal reviews rather than broad brand testing. Some usability pain points (like unclear labeling in the search flow) only surfaced post-launch.
Lessons learned
Built “measure → refine” into our process. Now, every release includes scheduled brand feedback sessions and fast design iterations after launch.
Challenge: Explaining AI results
Some users wanted to understand why a creator was matched. Without transparency, a few questioned the accuracy of results.
Lessons learned
We introduced clearer loading states and contextual match info (e.g., “Matched for skincare + minimal aesthetic”) to build trust and reduce ambiguity.