Market Analysis: The Pizza Study

What is market analysis? How is it done? This article describes how market analysis works using data on a pizza study.

After having defined marketing research in my previous post and giving an example conceptual framework for a pizza study, I decided to get into the details of market analysis using a standard multivariate statistical analysis tool. I saw the need of writing this article upon reading several articles on market analysis. There is a need to demonstrate what is market analysis.

Before everything else, the concept “market analysis” should be defined first.

What is market analysis and how is it used?

Market Analysis Defined

Marketing strategies work best when founded on a systematic evaluation of consumer preferences. What do consumers want? How do they respond to a product or service? Marketing research provides answers to these questions.

Hence, market analysis can be defined as the process of evaluating consumer preferences using a systematic approach such as marketing research, among others. Market analysis is a detailed examination of the elements or structure of the market.

Why is a market analysis done? An analysis is done to draw out important findings for interpretation, discussion and finally, a decision on what steps to make.

The Pizza Study

Once again, the conceptual framework given in the pizza study is given below to serve as a reference in the following discussion.

market analysis of a pizza study
Conceptual framework of the pizza study.

To find out what customers want, let us have a sample data of feedback from 200 pizza shop customers. To understand how analysis works, you need to read the article on variables as these are important units of analysis. If you already understand what variables are, then proceed to read the rest of the discussion.

Coding the Variables for Market Analysis

Let us have the following measures for the variables in this study namely pizza taste, service speed, and waiter courtesy:

Pizza Taste

1 – Very bad
2 – Bad
3 – Moderate
4 – Good
5 – Very good

Service Speed
1 – Satisfied
0 – Not satisfied

Waiter Courtesy
1 – Courteous
0 – Not courteous

Level of Satisfaction
Let us assume that the following Likert scale applies to the customer’s level of satisfaction:

1- Not at all satisfied
2 – Slightly satisfied
3 – Moderately satisfied
4 – Very satisfied
5 – Extremely satisfied

If for example, the customer is satisfied with pizza taste, service speed, and waiter courtesy; he rates everything “5.” If he is not satisfied with courtesy, then he might rate it a “0.”

Multiple Regression Analysis

Below is a data set representing the response of 200 pizza customers that serves as input to multiple regression analysis (you may try the data set if you know how to compute using multiple regression):

You may skip this table by clicking the link below:

Jump to the Results of Analysis.

A table summarizing the results of the pizza survey.

Customer #SatisfactionTasteSpeedCourtesy
15511
25411
34411
44411
54411
63500
75511
84511
95511
104411
114410
124411
134311
145311
154311
163401
174411
185411
195410
205410
214411
223501
234511
244411
253401
264511
275511
285411
294411
303401
313501
323501
333401
344411
354311
364210
375411
385311
395311
404311
414411
425411
434411
445311
454411
465411
474511
485511
494511
505511
514511
525411
534411
545411
554410
565511
573501
583501
593501
604411
614410
624410
634400
645511
655511
665511
675511
685411
695411
705411
714411
724411
734411
745311
754311
765311
774411
784411
794411
804511
814511
824510
835511
844411
854411
864411
874511
884511
894511
903501
914511
924411
934411
945411
954411
964411
974410
983401
993401
1003401
1013401
1024311
1034411
1044411
1054410
1064511
1074511
1084511
1095511
1104511
1114411
1124411
1135411
1144411
1154411
1164411
1175511
1185511
1195510
1205511
1215511
1225411
1235411
1245411
1255411
1265411
1275411
1284411
1294411
1304410
1314411
1324511
1334511
1344511
1354511
1364511
1375411
1385411
1395411
1405311
1414411
1424411
1434411
1444411
1454410
1464411
1474311
1484311
1494311
1503401
1514411
1524411
1534411
1543401
1554411
1564511
1574511
1584511
1595511
1605511
1615510
1625510
1635511
1645511
1654511
1664511
1674510
1684510
1694511
1704411
1715411
1725411
1735411
1745411
1754411
1764511
1774511
1784511
1794511
1804511
1815511
1825511
1835511
1845511
1854511
1864511
1874511
1884411
1893401
1904411
1914411
1924411
1934411
1945411
1955411
1965410
1974511
1984411
1994411
2003401

Result of the Regression Analysis

The following table presents the results of the multiple regression analysis using a simple spreadsheet software application with regression capability – Gnumeric. The first part shows the general relationship between the dependent and independent variables. The second part shows the details of the relationship between satisfaction score and pizza taste, service speed, and waiter courtesy.

Part 1. Regression Statistics
Multiple R0.66
R^20.44
Standard Error0.47
Adjusted R^20.43
Observations200
Part 2. Details
CoefficientsStandard Errort-Statisticsp-Value
Intercept2.91920.269110.84860.0000
Taste0.03260.05260.62080.5355
Speed1.32450.107612.31000.0000
Courtesy−0.01610.1098−0.14690.8834

Notice that the overall relationship has R values. Among these R values, the most important for interpretation is the Adjusted R^2 value. This value represents the relationship between variables of the study. The value obtained here is 0.43. This means 43% of the variation in satisfaction score is accounted for by the three variables.

Closer scrutiny of the details in Part 2 reveals that service speed significantly relates to satisfaction score. The red font indicates this significant relationship (for better understanding, please read the post on how to determine the significance of statistical relationships).

Interpretation of the Results

Based on the results of the statistical analysis, we can say with confidence that among the variables studied, service speed relates significantly to customer satisfaction. If you look closely at the entries in the data set, for every 5 or 4 satisfaction score, a 1 corresponds to service speed, meaning, the customer is satisfied with service speed. Take note, however, that this interpretation holds true only to the particular location where the study transpired.

Given this result, the marketing manager, therefore, should focus on the improvement of service speed to satisfy customers. This simple information can help the pizza business grow and gain a competitive edge. Market analysis guides decision-making and avoids incurring the unnecessary cost associated with the hit-and-miss approach.

Cite this article as: Regoniel, Patrick A. (May 21, 2016). Market Analysis: The Pizza Study. In SimplyEducate.Me. Retrieved from http://simplyeducate.me/2016/05/21/market-analysis-pizza-study/

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