Marketing Research

1
Marketing Research
SESSION 7 Preparing Quantitative Data For
Analysis
2
Session Objectives

• the role of editing, coding, counting and
  interpretation of data
• coding a simple questionnaire
• how statistical techniques may be used to
  evaluate the significance of quantitative data
• the features of a good, commercially credible
  marketing research report

3
Analysing Quantitative Data

• Manually
• Counting up answers
• Frequencies and percentages
• Using computer package
• Excel, SPSS, SNAP
• Frequencies and cross-tabulations
• Statistical techniques
• Building up the picture of the data

4
Analysing Quantitative Data

• Prepare the data
• Edit
• Check questionnaires for errors or omissions
• Coding
• Allocating a numerical code for each possible
  answer
• Data Input
• Data Cleansing
• Data Processing
• Data Mining
• Statistical Analysis
• Presentation

5
Questionnaire Coding

• A method of inputting data from a questionnaire
  in the form of numerical codes

6
Coding Single Response Questions

• Q12 To which of the following age groups do you
  belong?
• 18-25 (1)
• 26-34 (2)
• 35-44 (3)
• 45-54 (4)
• 55 (5)

7
Coding Multiple Response Questions

• Q3 Which of the following Supermarkets have you
  visited in the last month in order to purchase
  your main grocery shopping?
• q3a Asda 1 Yes, 2 No
• q3b Tesco 1 Yes, 2 No
• q3c Sainsbury 1 Yes, 2 No
• q3d Morrisons 1 Yes, 2 No

8
Data Input

• Time Consuming
• Human Error
• Build into schedule
• Can pay third party
• OMR (Optical Mark Recognition)
• Using OMR form
• Each questionnaire read in

9
Data Cleansing

• Check for human error
• Computer may identify responses it does not
  recognise
• Time consuming but gets data ready for analysis
• Makes optimum use of all responses gained

10
Data Analysis

• What is the story of the data?
• What comparisons are suggested?
• What trends or relationships are observed?
• How reliable and meaningful is the data?
• Are you interpreting it correctly?

11
Data Analysis

• Frequencies
• Cross Tabulations
• Statistical Significance
• Looking at relationships
• Significance of results

12
Statistical Analysis

• Statistical Analysis
• Descriptive statistics , describing large masses
  of numbers
• Inferential statistics, drawing conclusions

13
Simple Measures

• Frequencies
• Gender of respondents, age of respondents, income
• Numbers of responses against each question
• Compile as a percentage of the whole
• Cross Tabulations
• Table setting out responses to one question
  relative to others
• Cumulative Frequency
• Average
• Arithmetic Mean
• The median
• The mode

14
Are Results Significant?

• Confidence Testing
• How confident are we that our sample results are
  true for the whole population? (95, 99)
• All statistics used with care
• Compare results with known factors about the
  total population

15
Forward Plan

• Week 8 16th March - no lecture go straight to
  209 at 3pm
• Week 9 23rd March - no lecture go straight to
  209 at 3pm
• Easter break (3 weeks)
• Week 10 20th April - Lecture Reports and
  Layout
• Week 11 27th April - no lecture go straight
  to 209 at 3pm I can review submissions for
  pass/fail
• Week 12 4th May - Bank Holiday no
  lecture/workshops
• Week 13 Tuesday 13th May Hand-in date