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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

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..

Quarter Sales ($000s) Moving average trend ($000s) Sales - trend = seasonal variation ($000s)
1 240
2 224
3 204 227.5 - 23.5
4 240 229.5 + 10.5
1 244 233.0 + 11
2 236 237.75 - 1.75
3 220 242.5 - 22.5
4 262 246.75 + 15.25
1 260 250.25 + 9.75
2 254 254.4 - 0.4
3 230
4 286


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

Quarter Calculation Average seasonal variation
1 (11 + 9.75) / 2 10.375
2 ( - 1.75 + - 0.4) / 2 - 1.075
3 (- 23.5 + - 22.5) / 2 - 23
4 (10.5 + 15.25) / 2 12.875


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.

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