tmobilenear.me

An intelligent app to shape traffic into T-Mobile stores by using machine learning & location services

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Inspiration

T-Mobile has identified overstaffing as a major issue with stores. There are too many associates in stores based on the traffic coming into the store. By using a check-in app (mobile and web), the flow of traffic can be controlled. User are given time slots in the app based on the type of appointment they need.

What it does

T-Mobile (current and potential) customers are given time slots in the app based on the type of appointment they need. By using machine learning, the amount of time the different appointment types need can be identified. The goal is the smooth out the variability in the staffing needs by controlling the flow of customers. The variance of the traffic type is controlled by offering customers time slots at times that are expected to reduce this variance. Customers are incentivized to use the app by getting set appointments. Additional incentives can come from nearby local businesses near the store. Deals can also be used for traffic shaping by offering deals to delay customers if the store is too busy.

How we built it

For greatest compatibility, we used a custom, artisanal, bespoke, grass fed non-GMO locally-sourced framework tailored for web and mobile using primarily javascript (we grew it ourselves). We sprinkled on additional non-chemical organic machine learning technologies and connected to web-based location APIs to collect sustainably sourced data and a cruelty free consumer experience.

Challenges we ran into

The biggest challenge was the time constraint. 24 hours is not enough time, even with the overnight session. Also, we had a diverse skill set without much overlap.

Accomplishments that we're proud of

We came together as a team and pulled together what we think is a great idea and a great demonstration. We look forward to showing it off. Bringing together a full circle of development, research, and product direction skillsets allowed us to work together seamlessly & effectively deliver a polished product.

What we learned

We are proud of our tie-ins to various APIs to get the data we need and apply our algorithms. We all learned a little bit of the others coding languages. We got to discover & implement new APIs / technologies, deploy website applications, and workflow of the applications interface,

What's next for Tmobilenear.me

Tmobilenear.me is available for the low low price of one hundred million billion dollars. We will be acquired by T-Mobile & expect a call from John Legere any moment now... Seriously; Are you hiring?

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