Picture this: a local bakery in Austin struggling to attract foot traffic until they claimed and optimized their Google My Business (GMB) profile. Within weeks, walk-ins tripled, phone inquiries surged, and their map listing dominated local results. This isn't an isolated story; it's the everyday reality for thousands of small...

Business Listings Database is the source of point-of-interest data and can provide you with all the information you need to analyze how specific places are used, what kinds of audiences they attract, and how their visitor profile changes over time.

The full fields description may be found on this page: https://docs.dataforseo.com/v3/databases/business_listings/?bash

Google My Business (GMB) is a platform designed to help you share detailed information about your business when it appears in search results. In addition to a URL and description, you can include photos, videos, contact numbers, operating hours, delivery zones, and links to booking services. Google My Business enables you to create eye-catching listings that enhance visibility when customers search online. It allows your in-store products to be displayed directly on your Google Business Profile. A cover photo, along with previews from Google Maps and Google Street View, gives potential customers a clear idea of what to expect when they visit. However, keep in mind that users can suggest changes to your profile, so it’s important to review it frequently to ensure accuracy.

Google My Business also highlights key factors to consider for verifying your business presence and enhancing your local search visibility through optimization.

Data Dictionary

Notice on Dataset Usage and Attribution

This dataset, created by Agung Pambudi, is entirely original and has not been shared previously. It is distributed under the CC BY 4.0 license, which permits unrestricted use, provided the author is appropriately credited. A DOI is included to ensure accurate citation. Please be aware that duplicating this work on Kaggle is prohibited.

According to data from a study conducted from 2017 to 2018 of over 45,000 businesses, 56 percent of actions taken on Google My Business (GMB) listings are website visits. After viewing a business on Google, 24 percent of customer actions involve clicking on the listing to call the business.

Number of State of Iowa Google My Business Profiles (office locations)

This dataset provides insights by month on how people find State of Iowa agency listings on the web via Google Search and Maps, and what they do once they find it to include providing reviews (ratings), accessing agency websites, requesting directions, and making calls.

This dashboard provide insights by month on how people find State of Iowa agency listings on the web via Google Search and Maps, and what they do once they find it to include providing reviews (ratings), accessing agency websites, requesting directions, and making calls.

The number of times during the month someone clicked through to the department or agency website from their Google My Business profile.

Comprehensive dataset covering strategies for Google My Business optimization, including service area setup, content creation, review management, and local SEO tactics for contractors, mobile services, and other field service companies in 2025.

This dataset provides a comprehensive analysis of the ongoing changes to Google's Business Profile algorithm and their impact on local businesses in Colorado Springs. It covers key trends such as AI integration, mobile optimization, user engagement signals, and the integration of social discovery signals. The dataset also outlines future developments that Colorado Springs businesses should prepare for, including augmented reality, sustainability, voice commerce, and enhanced focus on unique experiences.

The number of times during the month someone requested directions to State Offices from their Google My Business profiles.

Sharing my Sample Data (Bellabet) for my Google Analytics capstone course.

With this i was able to get a strong overview of the inner workings of the organization

The number of times during the month someone called State Offices from their Google My Business profiles.

This Dataset contains review information on Google map (ratings, text, images, etc.), business metadata (address, geographical info, descriptions, category information, price, open hours, and MISC info), and links (relative businesses) up to Sep 2021 in California.

Please note, this is a subset of the orginal datset found here. You can find other federal states there.

Format is one-review-per-line in json. See examples below for further help reading the data.

{
 'user_id': '106533466896145407182', 
 'name': 'Amy VG', 
 'time': 1568748357166, 
 'rating': 5, 
 'text': "I can't say I've ever been excited about a dentist visit before, but there's a first for everything! Loved my experience at Lush today. Every person in the office was friendly and personable- plus the office itself is gorgeous! Great experience, I highly recommend!", 
 'pics': [
 {
  'url': ['https://lh5.googleusercontent.com/p/AF1QipMBzN4BJV9YCObcw_ifNzFPm-u38hO3oimOA8Fb=w150-h150-k-no-p']
 }, 
 {
  'url': ['https://lh5.googleusercontent.com/p/AF1QipNS1PEXEvadfUlhRkRDJ09id
  Mxh3CveZGZYuTo5=w150-h150-k-no-p']
 }
 ], 
 'resp': {
  'time': 1568770503975, 
  'text': 'We love getting to meet new patients like yourself. Thanks for giving our office a chance to take care of your dental needs and thanks for the nice review!'
 }, 
 'gmap_id': '0x87ec2394c2cd9d2d:0xd1119cfbee0da6f3'
}
{
 'user_id': '101463350189962023774', 
 'name': 'Jordan Adams', 
 'time': 1627750414677, 
 'rating': 5, 
 'text': 'Cool place, great people, awesome dentist!', 
 'pics': [
 {
  'url': ['https://lh5.googleusercontent.com/p/AF1QipNq2nZC5TH4_M7h5xRAd
  61hoTgvY1o9lozABguI=w150-h150-k-no-p']
 }
 ], 
 'resp': {
  'time': 1628455067818, 
  'text': 'Thank you for your five-star review! -Dr. Blake'
 }, 
 'gmap_id': '0x87ec2394c2cd9d2d:0xd1119cfbee0da6f3'
}

where

user_id - ID of the reviewer name - name of the reviwer time - time of the review (unix time) rating - rating of the business text - text of the review pics - pictures of the review resp - business response to the review including unix time and text of the response gmap_id - ID of the business

Citations

UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Mining Jiacheng Li, Jingbo Shang, Julian McAuley Annual Meeting of the Association for Computational Linguistics (ACL), 2022 pdf Personalized Showcases: Generating Multi-Modal Explanations for Recommendations An Yan, Zhankui He, Jiacheng Li, Tianyang Zhang, Julian Mcauley The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023 pdf

Acknowlegement

Foto von Maarten van den Heuvel auf Unsplash

Recent analysis of Google My Business (GMB) data in select countries found that there was an increase of customer conversion based on the average review star rating of a business. As of 2019, businesses experiences a pivotal growth moment of customers conversions when reaching a *** rating on a * star scale.

Introduction: I have chosen to complete a data analysis project for the second course option, Bellabeats, Inc., using a locally hosted database program, Excel for both my data analysis and visualizations. This choice was made primarily because I live in a remote area and have limited bandwidth and inconsistent internet access. Therefore, completing a capstone project using web-based programs such as R Studio, SQL Workbench, or Google Sheets was not a feasible choice. I was further limited in which option to choose as the datasets for the ride-share project option were larger than my version of Excel would accept. In the scenario provided, I will be acting as a Junior Data Analyst in support of the Bellabeats, Inc. executive team and data analytics team. This combined team has decided to use an existing public dataset in hopes that the findings from that dataset might reveal insights which will assist in Bellabeat's marketing strategies for future growth. My task is to provide data driven insights to business tasks provided by the Bellabeats, Inc.'s executive and data analysis team. In order to accomplish this task, I will complete all parts of the Data Analysis Process (Ask, Prepare, Process, Analyze, Share, Act). In addition, I will break each part of the Data Analysis Process down into three sections to provide clarity and accountability. Those three sections are: Guiding Questions, Key Tasks, and Deliverables. For the sake of space and to avoid repetition, I will record the deliverables for each Key Task directly under the numbered Key Task using an asterisk (*) as an identifier.

Section 1 - Ask:

A. Guiding Questions:
1. Who are the key stakeholders and what are their goals for the data analysis project? 2. What is the business task that this data analysis project is attempting to solve?

B. Key Tasks: 1. Identify key stakeholders and their goals for the data analysis project *The key stakeholders for this project are as follows: -Urška Sršen and Sando Mur - co-founders of Bellabeats, Inc. -Bellabeats marketing analytics team. I am a member of this team.

1. Identify the business task. *The business task is: -As provided by co-founder Urška Sršen, the business task for this project is to gain insight into how consumers are using their non-BellaBeats smart devices in order to guide upcoming marketing strategies for the company which will help drive future growth. Specifically, the researcher was tasked with applying insights driven by the data analysis process to 1 BellaBeats product and presenting those insights to BellaBeats stakeholders.

Section 2 - Prepare:

A. Guiding Questions: 1. Where is the data stored and organized? 2. Are there any problems with the data? 3. How does the data help answer the business question?

B. Key Tasks:

1. Research and communicate the source of the data, and how it is stored/organized to stakeholders. *The data source used for our case study is FitBit Fitness Tracker Data. This dataset is stored in Kaggle and was made available through user Mobius in an open-source format. Therefore, the data is public and available to be copied, modified, and distributed, all without asking the user for permission. These datasets were generated by respondents to a distributed survey via Amazon Mechanical Turk reportedly (see credibility section directly below) between 03/12/2016 thru 05/12/2016.
   *Reportedly (see credibility section directly below), thirty eligible Fitbit users consented to the submission of personal tracker data, including output related to steps taken, calories burned, time spent sleeping, heart rate, and distance traveled. This data was broken down into minute, hour, and day level totals. This data is stored in 18 CSV documents. I downloaded all 18 documents into my local laptop and decided to use 2 documents for the purposes of this project as they were files which had merged activity and sleep data from the other documents. All unused documents were permanently deleted from the laptop. The 2 files used were: -sleepDay_merged.csv -dailyActivity_merged.csv

2. Identify and communicate to stakeholders any problems found with the data related to credibility and bias. *As will be more specifically presented in the Process section, the data seems to have credibility issues related to the reported time frame of the data collected. The metadata seems to indicate that the data collected covered roughly 2 months of FitBit tracking. However, upon my initial data processing, I found that only 1 month of data was reported. *As will be more specifically presented in the Process section, the data has credibility issues related to the number of individuals who reported FitBit data. Specifically, the metadata communicates that 30 individual users agreed to report their tracking data. My initial data processing uncovered 33 individual ...

Reports the average customer ratings for State of Iowa Google My Business profiles.

"This dataset forms a vital component of my Google Data Analytics Capstone Project, representing a culmination of the skills and knowledge I've acquired throughout the program. As a responsible data analyst, I've meticulously cited the sources and references in the accompanying documentation, ensuring the highest data integrity and transparency standards.

I welcome and encourage any constructive feedback and reviews to enhance the quality and depth of my analysis. Collaborative efforts are at the heart of data analytics, and your insights and suggestions can play a pivotal role in refining the outcomes of this project.

Exploring this dataset has been an illuminating journey, and I'm excited to share my findings and insights with the Kaggle community. Stay tuned for a comprehensive analysis that deepens the data, uncovers patterns, and provides valuable insights. Together, we can harness the power of data to drive meaningful change and innovation.

Thank you for joining me on this data-driven adventure!"

Discover the booming interactive map creation tools market! Our in-depth analysis reveals a $2 billion market in 2025, projected to grow at 15% CAGR through 2033. Learn about key trends, leading companies (Mapbox, ArcGIS, Google), and regional insights to capitalize on this expanding sector.

What is this ? In this case study, I use a bike-share company data to evaluate the biking performance between members and casuals, determine if there are any trends or patterns, and theorize what are causing them. I am then able to develop a recommendation based on those findings.

Content: Hi. This is my first data analysis project and also my first time to use R in my work. They are the capstone project for Google Data Analysis Certificate Course offered in Coursera. (https://www.coursera.org/professional-certificates/google-data-analytics) It is about operation data analysis of a frictional bike-share company in Chicago. For detailed background story, please check the pdf file (Case 01.pdf) for reference.

In this case study, I use a bike-share company data to evaluate the biking performance between members and casuals, determine if there are any trends or patterns, and theorize what are causing them by descriptive analysis. I am then able to develop a recommendation based on those findings.

First I will make a background introduction, my business tasks and objectives, and how I obtain the data sources for analysis. Also, they are the R code I worked in RStudio for data processing, cleaning and generating graphs for next part analysis. Next, there are my analysis of bike data, with graphs and charts generated by R ggplot2. At the end, I also provide some recommendations to business tasks, based on the data finding.

I understand that I am just new to data analysis and the skills or code is very beginner level. But I am working hard to learn more in both R and data science field. If you have any idea or feedback. Please feel free to comment.

Stanley Cheng 2021-09-30