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

Identifying the seasonal variation

If we used our original sales series there would not be enough data to allow us to identify seasonal variations, so we are going to use the sales figures from our worked example above.

Looking at the original sales figures we can see not only an upward trend in sales, but also a consistent seasonal pattern. Sales in quarter 1 and quarter 4 are higher than the trend sales, and sales in quarter 2 and quarter 3 are lower than the trend sales. We can calculate an average variation from the trend for each of these quarters, which will allow us to adjust the extrapolated trend sales for each quarter to take account of the recognised seasonal pattern of the past. In other words, the trend line and the extrapolated trend smooth out seasonal variations - what we need to do to forecast future actual sales per quarter is to recreate these variations around the extended trend..

The figures in the last column show the seasonal variation for each quarter and confirm that sales in quarters 1 and 4 are higher than trend sales and sales in quarters 2 and 3 are lower than trend sales. We can use these seasonal variations to calculate the average seasonal variations, but it is important to note than from the limited sales data available these variations are based on such a small number of observations that they are unlikely to be very accurate and, therefore, should be used with caution. Firms that have been operating for many years are likely to have

The average seasonal variations can be used with the extrapolated trend to produce a more accurate forecast. Where there is negative result the actual forecast sales can be established by taking the sales variation away from the trend sales figures. So for quarters 2 and 3, the predicted actual sales will be below the trend sales, although quarter 2 is very close to the trend sales. The average seasonal variations for quarters 1 and 4 should be added to the trend sales figure to produce more accurate sales figures.

In other words if the projected sales for the first quarter of year 4 is $140,000, this figure would need to be increased by $10.375 to provide a more accurate prediction.

Trend Analysis Summary Method

• Plot the actual sales
• Work out the trend by using 8 quarter moving averages
• Add the trend to the original graph
• Extend (extrapolate) the trend (using other data for its angle)
• Calculate average seasonal variations for each quarter
• Predict actual future by recreating the shape of the seasonal variations around the extrapolated trend
• Read off the predicted actual sales for the future period required.