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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

Four point moving average - worked example

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Worked example using a four-point moving average

Sales of XYZ Ltd.

Sales Revenue ($000s)
Year Quarters
1 2 3 4
1 240 224 204 240
2 244 236 220 262
3 260 254 230 286


A qualitative examination of this data shows that the general trend is one of rising sales. Superimposed on this is an annual cycle with the highest sales in quarter 1 and the lowest in quarter 3 - this is likely to be a seasonal variation. Now let us investigate the figures quantitatively.

Extracting the 'trend'

After calculating an average of year 1, consisting of quarters 1 to 4, we then drop the first quarter's sales value and replace it with that of quarter 1, year 2. The average has, therefore 'moved' forward one quarter.

Periods used (Yr/Qtr) Moving Average Trend
1/1, 1/2, 1/3, 1/4 (240+224+204+240) / 4 = 227
1/2, 1/3, 1/4, 2/1 (224+204+240+244) / 4 = 228
1/3, 1/4, 2/1, 2/2 (204+240+244+236) / 4 = 231
1/4, 2/1, 2/2, 2/3 (240+244+236+220) / 4 = 235
2/1, 2/2, 2/3, 2/4 (244+236+220+262) / 4 = 240.5
2/2, 2/3, 2/4, 3/1 (236+220+262+260) / 4 = 244.5
2/3, 2/4, 3/1, 3/2 (220+262+260+254) / 4 = 249
2/4, 3/1, 3/2, 3/3 (262+260+254+230) / 4 = 251.5
3/1, 3/2, 3/3, 3/4 (260+254+230+286) / 4 = 257.5


The problem with this method is that the resulting trend figures do not fall on a particular quarter, but between quarters (see Figure 1). Since it is necessary to compare the sales trend with actual sales, it is advisable to obtain a trend that falls on a particular quarter. This is achieved by a process called CENTREING, where we add and average pairs of trends. The resulting average is thus based on eight quarter's data (Figure 2).

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Figure 1: Mean of four-quarter sales

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Figure 2: Centreing of two successive four-quarter moving averages

Since the trend average now corresponds with an actual month and we can compared this figure directly with the actual sales of that month. In practice, it is easier to add the two successive 4-period moving totals together and divide the result by 8, as shown below.

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The trend line can be extended to forecast the future trend line on the assumption that the trend of the past will continue in the future. The angle of the extension could be changed according to other data, e.g. economic forecasts that might suggest that the future will be better, worse or similar to now.

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