Scope and descriptive statistics
Restaurant data analytics is the process of analyzing every data point related to a business and converting them into meaningful insights, which can help improve everything from menus and staff straining to restaurant policies and marketing campaigns. Larger restaurants may even have 8 or more technology vendors on their payroll, which highlights the need to invest in a reliable analytics solution. Restaurants that operate on this scale, think McDonalds scale, may be looking at big solutions to understand and make use of the huge amount of data they generate.
Objective
The main objective of this research is to undertake data analysis in order to:
I. Understand whether the current expansion criteria can be improved.
II. evaluate the effectiveness of the Loyalty Card marketing strategy
III. identify feasible, actionable opportunities for improvement
The variables that were used in the analysis include the size of the restaurant in square feet, the average spending of an individual in a restaurant, the sales growth over the previous years, the loyalty card percentage of the net sales, annual sales per sq. ft., median income and median age.
The descriptive analysis
| Column1 | Obs | SqFt | Sales/Person | Sales Growth% | LoyaltyCard% | Sales/SqFt | BachDeg% |
| Mean | 37.5 | 2580.473 | 7.044054054 | 7.4140541 | 2.026486 | 420.3054054 | 26.31081081 |
| Standard Error | 2.5 | 43.58345 | 0.034555901 | 0.7701093 | 0.064212 | 15.95377053 | 0.814285102 |
| Median | 37.5 | 2500 | 7 | 7.03 | 2.075 | 396.01 | 26.5 |
| Mode | #N/A | 2500 | 7.03 | 4.05 | 2.04 | #N/A | 29 |
| Standard Deviation | 21.50581 | 374.919 | 0.2972611 | 6.6247303 | 0.552371 | 137.2395233 | 7.004745311 |
| Sample Variance | 462.5 | 140564.3 | 0.088364161 | 43.887052 | 0.305114 | 18834.68676 | 49.06645687 |
| Kurtosis | -1.2 | 3.760921 | 0.85439895 | 1.146166 | 1.4536 | 2.880513142 | -0.937297935 |
| Skewness | 1E-16 | 0.527171 | 0.903631503 | 0.4937475 | -0.756891 | 1.23589655 | 0.140544196 |
| Range | 73 | 2548 | 1.43 | 37.12 | 3.09 | 808.56 | 26 |
| Minimum | 1 | 1251 | 6.54 | -8.31 | 0.29 | 178.56 | 14 |
| Maximum | 74 | 3799 | 7.97 | 28.81 | 3.38 | 987.12 | 40 |
| Sum | 2775 | 190955 | 521.26 | 548.64 | 149.96 | 31102.6 | 1947 |
| Count | 74 | 74 | 74 | 74 | 74 | 74 | 74 |
The total count of the data that were used in this case was 74 as indicated from the descriptive analysis table above. Most of the sizes of the restaurants are around 2580 square feet and the sales percentage growth mean is 7.4 while the mean for sales per person is 7.0. The mean for the company sales per square is 420.30.
Analysis
Scatter plot of BachDeg% versus Sales/SqFt
The type of relationship that exist in this case is a positive relationship. This is because as the  X-values increase (move right), the  Y-values tend to increase (move up). excluding outliers, we can see that the X axis increases as the Y axis increases. The sales per size of the restaurant increases as the BachDeg increases.
Scatter plot for Med Income versus Sales/SqFt
The type of relationship that exist in this case is a positive relationship. This is because as the  X-values increase (move right), the  Y-values tend to increase (move up). excluding outliers. However, the data are scattered at the center and there is no huge increase on the X axis. This means the med income the increases steadily against the sales per square
Scatter Plot MedAge versus Sales/SqFt
In this case there is no relationship that exist.
LoyaltyCard (%) versus SalesGrowth (%)
The type of relationship that exist in this case is a positive relationship. This is because as the  X-values increase (move right), the  Y-values tend to increase (move up). excluding outliers
Recommendations and implementation
Based on the assessment above BachDeg% versus Sales/SqFt correlates and it is more effective. It shows that as the med income increases the size of the restaurant increases. Additionally, according to Scatter Plot MedAge versus Sales/SqFt, it shows that there is identified relationship between median age and the sales square per feet. It can be justified through use of line graph
The median age remains constant as the sales per square feet rise and fall which is a clear indication that there is no statistical relationship between the two. The loyalty card and the sales growth correlates.
Recommendations
The company should change the marketing strategy basing on % w/ Bachelor’s Degree (3 Miles) and the sales per square feet. Just like the loyalty card and the sales per square feet are correlated they should invest on the marketing strategies to increase the income of the restaurant
Instead of the company targeting the entire market they should focus on young people having the age of 35 years old. Since most of them having the age of 34 prefer having their services within the restaurant. The company implementing this strategy and committing their energy with this specific defined group with the market will help in improving their sales.
In a restaurant, collecting data is a bit easy as compared to other places. The most important thing to consider is identification cards. Identification may be a passport or a national identity card. Apart from acquiring the phone number and their address. Having this information will provide an endless opportunity for targeted marketing. Some of the POS systems allows the restaurant to access the demographic data of their customers and if they find missing data they can be filled using the public records.
References
Loeb, S., Dynarski, S., McFarland, D., Morris, P., Reardon, S., & Reber, S. (2017). Descriptive Analysis in Education: A Guide for Researchers. NCEE 2017-4023.  National Center for Education Evaluation and Regional Assistance.
Mavridou, A. M., Bergmans, L., Barendregt, D., & Lambrechts, P. (2017). Descriptive analysis of factors associated with external cervical resorption.  Journal of endodontics,  43(10), 1602-1610.
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