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Please find below my final deliverable from Shorthand emphasizing why proper Research and a Data-driven approach are necessary in the Restaurant industry.
Changes identified for Part III during Part II
Based on the feedback from the user research and interviews, and also from discussion and feedback from my Professor, I have decided to make five essential changes. These changes were implemented in my final deliverable.
Putting out the story of the “Intuitive Brother” in front of readers.
Find out surveys that support the reasons for Restaurant Failures.
Linking the real story with the hypothetical story.
Two of my users (User 1 and User 3) suggested making images bigger, deciding on intuitive colors, and adding a story between the series of visualizations that Ross, the Data Analyst created.
Based on my Professor’s feedback in Part II “to think about what a new entrepreneur starting a restaurant would really need”, I will be adding resources, and guidebooks which will help new entrepreneurs.
Additionaly, feedback from Interview 3 and the class on 21st February that had a critique session, where I collected feedback from my peers, I gathered insights on strengthening the point that data-driven decision is an important aspect of deciding business success. I also cited all the images that were not already cited on Shorthand to avoid any copyright issues. I also provided references to all the sources I used at the end of the storyboard. I also made sure that I check that there is uniformity across my portfolio, in terms of images, fonts, titles, and visualizations. Finally, I made sure that there were no grammatical errors in my work and that all the visualizations (interactive and non-interactive) were properly rendered.
Please find the detailed steps that I followed to make the above-mentioned five changes for my final decisions:
Visibility on Story of the “Intuitive Brother”: Based on the feedback of User 3 who mentioned “Would like to read/see more about the intuitive brother”, I contrasted and compared benefits and mentioned that “Analytical Brother” could get over “Intuitive Brother” for every visualization.
For example:
The Restaurant Density Map will help Chandler, understand the density distribution for all the restaurants available in the location which Joey is unaware of.
Restaurant Ratings will help Chandler identify the competitors available in the choice of location while Joey has no idea of his competitors.
Find out surveys that support the reasons for Restaurant Failures: I gathered data on the reasons for the failure of restaurants. I gathered statistics and reports from CNBC.com, National Restaurant Association (NRA), and MenuTiger. These insights clearly specified the top reasons why restaurants fail. To support the insights, I added a bar graph illustrating the top reasons for restaurant failure.
Linking the Real story with the Hypothetical story: Adding real research done in the past with my own research on business metrics, I tried to bridge the gap between the real story and the hypothetical story. This was feedback from User 3 who mentioned “There could be some more valuable data to be added - the success of restaurants that took data-driven business decisions vs those who didn’t”
Two of my users (User 1 and User 3) suggested making images bigger, deciding on intuitive colors, and adding a story between the series of visualizations that Ross, the Data Analyst created: I expanded the Average Restaurant Profit Margin pie chart to make the labels and percentage shares clearly visible. I added bigger labels on the donut chart which highlighted the failure of restaurants. I also added intuitive colors to the visualizations (Heat Map - Best to Worst with shades of Red color), and stories between the Tableau visualizations for a smoother transition.
Based on my Professor’s feedback “to think about what a new entrepreneur starting a restaurant would really need”, I added the following resources, and guidebooks which will help new entrepreneurs carry a research of their own. Users can get extensive data using any API tool like Postman. The below resources have also been mentioned in the Shorthand story for easy navigation to external links.
| Source | URL | Description |
|---|---|---|
| Yelp API (Open Source, Unlimited free responses) | https://api.yelp.com/v3/businesses/search | This endpoint provides business metrics of more than 1000 businesses across industries. |
| Google My Business API (Open Source, Limited free responses) | https://mybusiness.googleapis.com/v4/{parent=accounts//locations/}/reviews | This endpoint offers a detailed response with numerous business metrics, with the first 100 responses accessible for free. |
| United States Census Bureau | https://data.census.gov/webpages?q=restaurants+in+the+US&y=2021&n=722 | Provides data on restaurants in the US. |
| Trip Advisor | https://developer-tripadvisor.com/content-api/description/ | Provides access to Trip Advisor’s content API. |
At the start of my project (Part I), I was primarily focused on my own journey as an aspiring real estate entrepreneur. However, after the critique session on 21st February and after the interviews, it was evident to me that there are many aspiring entrepreneurs like me who share the same story as mine. They have that big idea in their minds but are confused about where to start. Interviewing User 2, who has family-run restaurant business in Philadelphia for more than 10 years, helped me understand the pain points that a restaurant owner faces over the years. A few of the pain points discussed were deciding competitive prices, choice of location, cuisine popularity, and top competitors in the vicinity. He mentioned how making the mistake of acquiring cheaper land to set up a restaurant which was not in the heart of the city turned out to be less rewarding. User 3, who worked in other startup industries, mentioned how the concept of the 4 Ps “Product, Price, Place, and Promotion” helps decide the sustainability of the business.
For my current dataset, I have restricted the audience to aspiring real estate entrepreneurs of Pittsburgh, who want to foray into the restaurant industry. Additionally, I am working on this same project in my Capstone course at CMU. I am taking a few advanced steps where I will be widening the audience reach to the state of Pennsylvania, and then to all other states in the US. My final targeted audience will be aspiring entrepreneurs across all industries of real estate. Data accessed from Yelp and Google My Business APIs and providing easy-to-understand Tableau Visualizations will help my audience take calculated risks and smartly approach their ventures. Finally, I added links to public data repositories and guidebooks that entrepreneurs can refer to for their personal research.
To avoid any copyright violations, I made sure to cite all the sources (MLA Format) in the storyboard created on Shorthand. I have added all the sources below for the convenience of readers.
“How Much Does It Cost to Start a Restaurant Business?” CloudKitchens, https://cloudkitchens.com/blog/how-much-does-it-cost-to-start-restaurant-business/. Accessed 21 Feb. 2024.
Bellini, Jarrett. “The No. 1 Thing to Consider before Opening a Restaurant.” CNBC, 15 Mar. 2016, https://www.cnbc.com/2016/01/20/heres-the-real-reason-why-most-restaurants-fail.html.
Claire. “Restaurant Failure Rate Statistics for 2024.” MENU TIGER, 22 Jan. 2024, https://menu.qrcode-tiger.com/blog/restaurant-failure-rate-statistics/.
I thoroughly enjoyed working on this project because it relates to something that has been in my family over the years. I had a practical understanding of the concepts but deeper insights on data and playing around with numbers gave me a broader understanding of how one can gain an edge over their competitors in the market just by doing simple research. This project and the course have really been a learning curve for me. The concepts that I learned here were very useful which inspired me to implement similar concepts in my capstone project. I still remember how amazed my clients were when they saw all the restaurants marked on one of the restaurant density visualizations I created. To further amaze them I made the visualization dynamic, interactive, and visually appealing. I am thankful to my Professor for making us aware of multiple tools to generate really cool visualizations. Since, my project talks about geospatial locations, the 3D visualizations on Kepler.gl blew away my mind. I am currently working on replacing the existing 2D visualization with the 3D.
Researching data was a bit challenging as there were only a few resources that were free and publicly available. Also, extensive research had to be done on gathering data to support why restaurants without a data-driven approach have a high chances of failure. In other words, there are a lot of resources that talk about the solution without actually talking about the real problem. The most fun part of the project was interviewing the users and getting my work reviewed by them. In the past, I had similar creative work ideas that I didn’t bring into action because I was hesitant about user acceptance. However, getting a positive response from the users encouraged me to bring in more creative aspects to the project. I really liked comments from users like “Navigating through the presentation was like a breeze” and “Was very visually appealing. Felt like I was reading a comic book.”
To conclude, I am very fortunate to have taken this course, the learnings and takeaways were immense. In my career as a Data Analyst working through my future projects successfully, I will always be reminded of the “Telling Stories With Data” class and my Professor.