Review SegMentor

Restaurant Concept Locality Yelp Review Share Analysis

author: Ojustwin Naik

date: November, 22, 2015

Inform Business Decisions with Segmented Yelp Review Share Data

Shiny App Name: Review SegMentor
https://ojustwin.shinyapps.io/RestReviewApp

Classify, visualize, and analyze restaurant review share data by restauarant Concept and Locality.

FOR: Restaurant Entrepreuneurs, Business Owners, Restaurant Industry Analysts, Curious Restaurant Reviewers

TO: Provide an alternative information avenue to visualize restaurant review market dynamics and identify competitive opportunities.

Current market share research sources include expensive restaurant market metrics compiled by research organizations. But, these likely do not include visualization of restaurant review share metrics segmented by detailed restaurant concepts or directly competitive localities.

Identify Concept and Locality

Classify Concept with attributes such as Region, Price, Ambiance, Cuisine, and more!

Classify Locality by providing Lat & Long.

Classify Concept and Locality

Slice & Dice Aggregated Review Share Data

Visualize Aggregated Review Share Metrics with Geographic Context.

Slice Dice Metrics

Problem, Methods, Data

This App was built to validate whether it is possible to use Yelp review data to cluster and segment restaurant “Concepts” and “Localities”, analyze aggrageted metrics, and inform new restaurant decisions. The App results were succesful in validating the hypothesis.

This App uses Concept and Locality clusters identified with Hierarchical Clustering. It also uses classification models buit using the Random Forest algorithm.

The data for Restaurants Reviews in Pittsburgh was provided by Yelp.

This App was built using R Shiny.