Walmart × American Pets Alive · 1st place

Helping communities return lost pets

A 48-hour hackathon concept for Walmart Technology and American Pets Alive that helps community members identify lost pets, contact owners directly, and safely return animals without adding pressure to shelters.

Timeframe: 48-hour hackathon
Role: Research · Product design · Developer liaison · Presenter

Helping communities return lost pets — overview visual

Background

Return to Owner is a system, not a single handoff.

The challenge was to improve the common Return to Owner process when a lost animal reaches a shelter. We relied on literature review, open-source research, and guerrilla research to understand the ecosystem and the stakeholders involved.

Research reference material used to understand the return-to-owner process. — Research synthesis under a compressed hackathon timeline.

Stakeholder map and return-to-owner flow. — The stakeholders and handoffs that make the process circular.

Diagram of the main return-to-owner problems. — Two high-impact problems emerged from the initial research.

Define + ideate

Break the loop at the weakest link.

The two major issues were circularly causal: crowded shelters make it harder to identify animals, while owners and community members lack the tools to intervene earlier. We identified community members as the most connected participant with the most direct possible link between a lost pet and its owner.

Challenge definition diagram showing the negative feedback loop. — The challenge was defined as breaking one link in the negative feedback loop.

Weakest-link analysis identifying the primary user. — Community members became the primary user to design for.

Primary user analysis for community members. — A focused view of the people best positioned to help.

Persona created from interviews with potential community helpers. — Ten short interviews grounded the primary-user persona.

Design goals

Give people a direct, safe way to act.

Help community members distinguish a lost pet from a feral animal within five minutes using only a mobile device.
Give community members a way to interface directly with the owner without involving shelters or authorities.
Use AI recognition and an owner-posted pet database to connect the right animal to the right person.
Use augmented-reality training and guidance to make the physical parts of the return process easier to follow.

Empathy and research synthesis for the return-to-owner experience. — Research translated into design goals for the community member.

Prototype

One experience for helpers and owners.

The proposed experience accommodates two roles: a community member who wants to help and an owner who needs to post a pet. From there, a guided AR flow helps the helper assess the situation, identify the animal, contact the owner, and safely complete the return.

Information architecture for the return-to-owner app. — The information architecture joined owner and community-member paths.

Early sketches for the return-to-owner experience. — Sketches made the roles and handoffs tangible.

Home screen for the return-to-owner app. — Home screen organized around the person’s role and next action.

Owner home screen for the return-to-owner app. — The owner path makes posting a pet and maintaining its record straightforward.

Wireframe sequence for the return-to-owner flow. — A step-by-step path from identification to owner contact.

Community-member flow for identifying and returning a lost pet. — Community-member guidance with identification, contact, and retrieval steps.

Reflection

A strong direction, with the next test clearly visible.

The 48-hour format limited user testing and prevented us from validating the interactive prototype beyond judge feedback. The next iteration would test the AI recognition and AR guidance with real community members, then verify feasibility and efficacy with technical partners.