Sift
Danny Nguyen, Isabel Abonitalla, Thuy Le, Taylor Hines (Team Ditto)
Helping restaurant owners sift through the noise and gain constructive feedback.
Agenda
The Problem
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Quantity of reviews
Hard to digest feedback
Difficulty pinpointing customer issues
This is Gunther’s Ice Cream in Sacramento, CA
How might we help small to medium sized businesses, like Gunther’s in the Sacramento area and beyond, efficiently gain insights from their online reviews?
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For example, Gunther’s Ice Cream has 2,000+ reviews on Yelp
Reading and trying to get helpful feedback from each review would take a long time
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Our Solution
A web platform powered by machine learning that helps business owners...
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Sort through thousands of reviews quickly to save time
Visualize data for KPIs
Aggregate high level insights from reviews
Natural Language Processing allows us to extract entities (keywords like the restaurant’s dishes or other features) then perform sentiment analysis to determine whether the entity is spoken of positively or negatively (in this case, within the reviews).
Powered by Machine Learning
We used IBM Cloud’s Natural Language Understanding API
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Our code
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Team Ditto was blocked by an API paywall and was unable to build and hook up the following front-end designs to the working machine model, but this is what we hoped to implement.
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Front-end Designs
Sift offers quick high level visualizations
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Front-end Designs
At a glance metrics with more information if needed
Generated word cloud from text strings in reviews
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Links
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Thank you SacHacks 2021!
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