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Accelerating Sports Marketing with Generative AI

The Challenge

Weekly game footage overwhelmed creative teams, who received ‘pre-broken’ clips without a centralized, searchable way to find specific moments. To meet this need, the project aimed to:

  • Reduce Search Time: Move away from manual browsing to a fast, transparent search tool.
  • The client initially did not realize how Generative AI could solve their specific bottlenecks.
  • Scale Content Production: Enable a single editor to efficiently produce up to eight multi-platform video sets (Meta, YouTube, TikTok, Snapchat) per week.

To tackle these challenges, I served as the Lead Designer and Product Strategist, bridging the gap between AI’s technical potential and creative needs. I drove the product vision from zero to a high-fidelity prototype under a tight timeline.

  • I led workshops and interviewed users to uncover the real needs of editors and marketing staff.
  • End-to-End Design: As the sole designer, I was responsible for the entire UX/UI lifecycle, including user workflows, wireframes, and final mockups.
  • I educated stakeholders on the possibilities of GenAI and transformed technical options into a finalized product roadmap.

The Process

The project advanced in clear phases to deliver immediate results and support future growth:

  • Phase 1 (The Core): Launch a searchable library with precise clip descriptions, transparent metadata, and bulk download tools.
  • Phase 2 (The Ad Concept): Build a generative tool for editors to streamline ad plans and automate creative roadmaps. With the project phases outlined, focus shifted to discovery and user research, which informed critical design choices.

Discovery & User Research

  • I interviewed Social Media Editors and Sports Marketing teams to map the current Clips Distribution Process.
  • Identifying High-Value Content: Editors needed a way to instantly find “exciting” footage: touchdowns, interceptions, crowd celebrations, and player reactions.
  • Metadata Importance: Date, season, team, and player number are essential search filters.
  • Pain Point Analysis: Feedback on existing Proofs-of-Concept (PoC) highlighted low accuracy and the delivery of “useless” one-second clips as major blockers.

Ideation & AI Roadmapping

  • Once the needs were clear, I facilitated ideation sessions to show possible functionalities.
  • Natural Language Queries: We built a system that supports natural-language search, enabling editors to type “Messi goal with crowd reaction” and receive instant, accurate results.
  • Creative Expansion: Proposed future features like “Audio Search” (announcer name calls) and AI-generated social media captions based on clip content
  • Ad Assistant Flow: I defined a new process for ideation before editing an ad to optimize the workflow.

UX/UI & Workflow Design

  • I designed a clean, “search-first” interface that minimized UI “real estate” to prioritize video results.
  • To further support seamless workflows, I designed a visualization tool to track video processing and indexing in real time within the upload pipeline, ensuring users remain informed at every stage.
  • Multi-Level Workflow: Created a comprehensive user architecture (Level 0 to Level 3) covering everything from Sign-In to Bulk Download and AI Ad Planning.
  • Ad Concept Flow: I defined this creative process to enable users to maximize value from the platform.
App map flow
Mockup

Outcomes

  • Designing for Trust: Addressed potential AI failures (latency, bias, model drift) by designing clear user feedback mechanisms.
  • Simplifying Complexity: Translated sophisticated backend processes (Vector Embeddings, API Gateways) into a simple, intuitive search bar for non-technical creatives.
  • Leadership through Design: Acted as both the Product and Design lead to move a client from “AI curiosity” to a tangible, ROI-driven marketing tool.