Flybit 2.0

Inspiration

In a world of data, there is so much information that is not being used to its fullest potential! Not only are businesses missing out on future profits, consumers are wasting time and money. We wanted to create a product that would benefit both sides!

Personally, as two students with low income and very busy schedules. We wanted to create an idea that was practical while taking into account the feelings of the consumers. All the while, bridging a gap in the industry.

What it does

Our project uses the plethora of contextual data that is linked to an specific individual to offer personalized recommendations and offers. Flybit 2.0 is unique to its competitors because Flybit 2.0 leverages its predictive capabilities. Before, consumers were completely isolated from what

How we built it

Due to time constraints, we had to use the No-Code solution provided by Flybit's Experience Studio platform. With that being said, we were able to compile plausible attributes to a specific consumer and attach context-based rules to these specific cases to generate unique consumer offers.

Challenges we ran into

Even though our team was smaller with little coding experience. Every member focused on their strengths to bring our ideas to life! Using the Mobile Experience software was a learning experience for each of us. Our gaps in understanding allowed the members to help and rely on one another!

Accomplishments that we're proud of

We are proud of our journey, the time and effort dedicated to our final product. From brainstorming multitudes of ideas to fine-tuning the details of our program, we are proud of what we made for Biztech 2022 Hackathon.

What we learned

In terms of the consumer-facing finance industry, we learned that there is a large untouched opportunity for improving consumer experience and satisfaction. In terms of codes, we learned how to manipulate different contextual attributes to deliver one specific experience for the consumer.

What's next for Flybit 2.0

Flybit aims to continually increase its 'smartness' when personalizing offers. With that being said, we also hope to make Flybit truly multi-dimensional, in a sense not only will it be able to consider data points and contexts, but also being able to understand consumer on a deeper, and more meaningful level. We believe this is attainable through machine learning technologies.

Built With

• flybitexperience