CrowdCue

Inspiration: As someone who has worked in the food service industry for 8 years, at places like Chipotle, Krispy Kreme, and Buffalo Wild Wings, it’s clear to me that the current system for balancing the demand of customers and the supply of staff is broken. In downtown, the constant cycle of concerts, sports events, and conferences often leads local businesses in a bind. With large crowds during peak hours, and spikes of foot traffic from local events, staff are often left overworked, and customers left unsatisfied. Having seen this cycle play out firsthand, I had the idea to create CrowdCue, a system for helping balance customer needs with staffing availability, helping to manage employee morale, while also providing the best possible experience for customers.

What it does: CrowdCue utilizes publicly available API’s to track ongoing events in the Seattle area, and make recommendations to business owners and managers on their staffing needs. CrowdCue also considers the schedule of staff when making decisions, offering tailored recommendations that balance the demand of customers and the needs of staff.

Here is a polished, corrected version that keeps your original structure and tone:

How we built it:

We used an API to extract information from a database and stored it locally for debugging. We then used that information to suggest a schedule using the Eclat algorithm.

Challenges we ran into:

Ensuring the Eclat algorithm was valid, developing the front end, and overcoming miscommunication about how the product should be built.

Accomplishments that we're proud of:

Developing a backend system that is able to generate scheduling suggestions.

What we learned:

How to use an unsupervised learning algorithm, specifically Eclat.

What's next for CrowdCue: Although we initially didn't plan on working on CrowdCue past the end of the Hackathon, after many people expressed real interest in our idea, we've been considering continuing to work on CrowdCue going forward. Were still not 100% on trying to make it a full on service or anything, but we're planning on potentially looking into making it into a full product later down the road.

Built With

• api
• python
• ticketmaster
• turbooverpass