Moody and Isabel were inspired by the movement to support local businesses during the pandemic. Online reviews, especially in this digital-dependent space, can be difficult to analyze for small business owners. Just finding the time to be able to read what your customers are saying about you can be a challenge. That is why our team wanted to create a platform that would help small to medium-sized businesses gain insights from online food reviews more efficiently.

What it does

Our app takes in a business category and location and returns related insights from customer reviews.

How we built it

We used Google Cloud Platform's Natural Language Processing API deployed on AppEngine to analyze customer review data from Yelp's API. It queries Yelp API and runs all reviews through an entity-sentiment analysis to show business owners what aspects people consider when writing positive/ negative reviews. We used Tabler-React to visualize the data.

Challenges we ran into

We were a small team of two and could not dedicate the entire weekend to the project, so we ended up rushing at the end.

What's next for Metasort

We want to improve our UI and add more insights about the business itself, such as which dishes are liked best in a restaurant or which products are liked best in a store.

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