Marketing

Table of Contents

1. Topic pack - Marketing - introduction
2. 4.1 The role of marketing - notes
3. 4.1 The role of marketing - questions
4. 4.2 Marketing Planning - notes
   1. Marketing planning
   2. The marketing mix
   3. The Total Product Concept
   4. Ethics of marketing
   5. Marketing audit
   6. Porter's five forces
   7. Porter's five forces - activities
   8. Marketing objectives
   9. Market research - introduction
   10. The role of market research
   11. Primary and secondary research
   12. Primary research - information gathering techniques
   13. Observations - case studies
   14. Group-based market research
   15. Market research - summary
   16. Questionnaires
   17. Sampling
   18. Methods of sampling - introduction
   19. Main methods of sampling
   20. Sampling errors
   21. Market segmentation
   22. Consumer Profiles
   23. Types of segments
   24. Demographic segmentation
   25. Psychographic segmentation
   26. Psychographic segmentation - case study
   27. Geographic segmentation
   28. Industrial markets
   29. Targeting
   30. Positioning
   31. Corporate image
   32. Position/perception maps
   33. Unique selling point/proposition USP
   34. Marketing strategies and tactics
   35. Sales forecasting
   36. Qualitative forecasting/data
   37. Forecasting and correlation
   38. Forecasting techniques
   39. Constructing time-series analysis
   40. Moving average
   41. Four point moving average - worked example
   42. Identifying the seasonal variation
5. 4.2 Marketing planning - questions
6. 4.3 Product introduction - notes
7. 4.3 Product - questions
8. 4.3 Product - simulations and activities
9. 4.4 Price - notes
10. 4.4 Price - questions
11. 4.4 Price - simulations and activities
12. 4.4 Promotion - notes
13. 4.5 Promotion - questions
14. 4.6 Place (distribution) - notes
15. 4.7 International marketing - notes
16. 4.7 International marketing - questions
17. 4.8 E-commerce - notes
18. 4.8 E-commerce - questions
19. Printable version

Forecasting and correlation

Correlation describes a relationship between two sets of numbers. A scatter diagram can be used to see if there is a possible correlation between two sets of data. The closer the relationship between the two data sets, the closer the correlation and the higher the 'correlation coefficient'. We can see this from the two scatter graphs shown below - one has a high level of correlation between marketing spending and sales growth, while the other shows a low correlation.

Figure 2 Low correlation - sales growth and marketing spending

Figure 3 High positive correlation - sales growth and marketing spending

Correlation is a tool that is perhaps most used in marketing.

• It can show you the extent of a relationship between the sets of data.
• It can help plan with greater certainty and allocate resources accordingly.

Correlation can be placed alongside forecasting in that extrapolation needs to be considered in relation to other positive or negative variables. Changes in the external environment that are positively or negatively correlated with a firm's sales will have to be factored into any predictions of future sales growth.

Without being too repetitive, it is necessary to treat data with caution ... numbers can often be used to prove opposing points of view - it is a matter of the quality of the data (GIGO) and the nature of the interpretation and tools used.

Note:

• The sample may be too small and therefore not significant
• The industry may be subject to fast technical change
• The external environment can change