Analysing Marketing Data

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In this revision presentation, some core concepts of marketing data analysis are introduced. The presentation introduces topics such as test marketing, calculation of moving averages, extrapolation, correlation and qualitative methods of marketing forecasts (hunch & delphi).

Analysing Marketing Data

  1. 1. AnalysingMarketing Data
  2. 2. What marketing managers want to know• How big is the market? (measured by sales, volume etc)• How fast is the market growing and what is the growth potential?• The key social, economic, political/legal and technological factors that drive change in the market• Who are the existing competitors and their market shares?• Extent of branding and customer loyalty in the market• How the market is segmented to meet different customer needs• Customer preferences in terms of when and where they buy, what prices they pay and which methods of promotion are effective• The potential for developing a competitive position in a market – either through a USP or through effective price competition
  3. 3. Examples of when marketing analysis is really needed• Forecasting sales for new products or investments into new markets• Gathering evidence to support a finance- raising exercise• To support a new marketing strategy or significant changes to the marketing objectives• To help make decisions in relation to significant organisational or operational change
  4. 4. Test marketingTest marketing involves launchingTest marketing involves launchingthe product in small part (usually the product in small part (usually geographic) part of the target geographic) part of the target market in order to gauge the market in order to gauge theviability of a product or service in viability of a product or service inthe target market prior to a main the target market prior to a main roll-out or launch. roll-out or launch.
  5. 5. Aim of test marketing To gather as To gather as Product Product much muchinformation as information as Price Pricepossible about possible about Promotion Promotion the optimum the optimummarketing mix marketing mix Place Place
  6. 6. Benefits and drawbacks of test marketingAdvantages DisadvantagesData provided is from actual customer Danger of the competition learningspending about the product and coming up with a response before the full launchReduces the risk of a full-scale launch Test market may not be– if the product fails a test then representative of the full targetsignificant costs may be saved market, leading to inappropriate decisionsProvides a way to tweak the Delays in full launch may limit themarketing mix before full launch revenue opportunity in markets subject to rapid changeCan create a promotional “buzz” Costly and time-consuming towhich supports the main launch administer
  7. 7. Analysing trends – key topics Moving averages Extrapolation Correlation
  8. 8. A Moving Average A moving average takes a data A moving average takes a data series and “smoothes” the series and “smoothes” the fluctuations in data to show an fluctuations in data to show an average averageThe aim is to take out the extremesThe aim is to take out the extremes of data from period to period of data from period to period
  9. 9. Moving average illustrated The red line shows the quarterly moving average. This is calculated by adding the latest four quarters of sales (e.g. Q1 + Q2 + Q3 + Q4) and then dividing by four.The blue line shows the actual quarterly sales figure which varies quarter by quarter
  10. 10. Moving average to extrapolationThe moving average helps shows the growth trend (expressed as aapercentage The moving average helps shows the growth trend (expressed as percentagegrowth rate), and extrapolation can use this to predict the path of future sales. growth rate), and extrapolation can use this to predict the path of future sales. This could be done mathematically using aaspreadsheet. Alternatively, an This could be done mathematically using spreadsheet. Alternatively, an extrapolated trend can simply be drawn on the chart as aarough estimate, as extrapolated trend can simply be drawn on the chart as rough estimate, as shown below: shown below:
  11. 11. Benefits / drawbacks of using extrapolationAdvantages DisadvantagesA simple method of Unreliable if there areforecasting significant fluctuations in historical dataNot much data required Assumes past trend will continue into the future – unlikely in many competitive business environmentsQuick and cheap Ignores qualitative factors (e.g. changes in tastes & fashions)
  12. 12. Correlation Correlation looks at the strength of arelationship between two variables
  13. 13. Correlation variables Independent Independent Dependent Dependent Variable Variable Variable Variable The factor that The factor that The variable that The variable that causes the causes the is influenced by is influenced by dependent dependent the independent the independentvariable to changevariable to change variable variable
  14. 14. Plotting correlation - example (number per week)Customer Enquiries Advertising per week (£’000)
  15. 15. Explaining the scatter chart (1) Correlation is Correlation is usually measured usually measured by using a scatter by using a scatter diagram, on which diagram, on which data points are data points are plotted. plotted. The dependent variable is normally The dependent variable is normallyplotted on the y-axis: the independentplotted on the y-axis: the independent variable on the x-axis variable on the x-axis
  16. 16. Explaining the scatter chart (2) A “line of best fit” A “line of best fit” (the regression (the regression line) attempts to line) attempts to plot the plot the mathematical mathematical relationship relationship between the between the variables based variables based on the data on the data points. points.
  17. 17. Types of correlationPositive A positive relationship exists where ascorrelation the independent variable increases in value, so does the dependent variableNegative A negative relationship exists where ascorrelation the independent variable increases in value, the dependent variable falls in valueNo correlation There is no discernible relationship between the independent and dependent variable
  18. 18. Positive correlation the UK to FloridaHolidays taken from Pound / $ Dollar Exchange Rate
  19. 19. Negative correlationDemand for new houses Interest rate on mortgages
  20. 20. No correlationand other savoury pastries Demand for sausage rolls Number of weddings per year in the UK
  21. 21. Strong or weak correlation?• The line of best fit indicates the strength of the correlation• Strong correlation means that there is little room between the data points and the line• Weak correlation means that the data points are spread quite wide and far away from the line of best fit• If the data suggests strong correlation, then the relationship might be used to make marketing predictions
  22. 22. Qualitative forecasting – two approaches Delphi Hunch Method An educated An educated Opinion from Opinion from guess guess the experts the experts
  23. 23. Hunch• A forecast based on a hunch is likely to be influenced by the experience of the forecaster, perhaps supported by market research or from discussions with others in the market• An experienced manager will have strong insights into the sales prospects for individual products, business units• The starting point for a hunch forecast is often the previous years’ or period data
  24. 24. Delphi• Involves getting a group of market experts to provide an opinion on the forecasting task – e.g. to estimate future sales growth in a market• Experts first give a confidential individual opinion on the task• Their forecasts then revised based on the submissions of each expert to the group• Ultimately the aim of the Delphi method is to reach a “consensus” forecast
  25. 25. When to use qualitative forecasting• When there is little accurate or predictable historical data available (e.g. in the case of a new product launched into a new market)• Where a market is subject to wide fluctuations in demand (e.g. unexpected surges or shocks)• Where a market experiences significant change (e.g. shortened product life cycles, rapid changes in technology)
  26. 26. Using IT to analyse marketsAlmost every majormarket is analysed using IT
  27. 27. The analysts• Businesses themselves• Competitors• Suppliers• Trade associations• Government• Industry regulators• Industry analysts
  28. 28. Example - retailing• Individual retailers analyse sales using their EPOS terminals and other systems• The Office of National Statistics produces regular data on total retail sales• Specialist market researchers like TNS track retail sales in great detail at the checkout• The British Retail Consortium produces weekly and monthly data for its members (the BRC is the trade association for retailers)
  29. 29. Example – the media market• Thousands of households track radio usage for RAJAR which is used to measure demand and market share• Industry regulator OFCOM produces highly detailed market research on sales, cost and other market information for all consumer media markets
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