Analysing markets and marketing

analysing the market

• quantitative analysis examines statistical info in order to draw conclusions about the nature of the market
• qualitative analysis considers the reasons why certain actions take place

reasons for market analysis

• gathering evidence for devising a new stratgey
• identifying significant patterns in sales

the value of market analysis

M A helps a bus to understand its existing markets. the data and info gathered also allow a bus to prepare for the future, by enabling it to forecast sales and other data.

sale forecasting serves a number of purposes:

• measure the performance of an individual or department
• motivate staff by presenting them with a realistic but challenging target
• monitor achievements
• coordinate the acitvities

methods of quantitative forecasting

• test marketing
• analysis of trends/moving averages and extrapolation
• correlation

forecasting by usinf test amrketing

by launching a product in a limited part of a market, usually a geogrphical area, a firm can discover customer opinions. it is also used to predict sales. once test marketing has taken place, the firm will use the results for future sales

+ results are relatively accurate

+ is a useful way of gauging the popularity of the product without incurriing the huge expense of a national laucnh

- fewer firms now employ the techniques because it can lead to copies being produced by rival

- in rapdily changing markets, the delay in launching a product nationally may endanger the chances of making a profit from a new launch

- the 'newness' of the product may encourage people to purchase it once, so the test market may exaggerate its true popularity

analysis of trends and extrapolation

• predicting future sales using extraploation.
• in effect, trend analysis examines the pattern of historic data and assumes that this pattern will continue in future.
• extrapolation can be caried out visually or by calculation, althought the latter method is recommended for greater accuracy.
• where there is a clear pattern of change, it is easy to calculate the trend by calculating the averagechange for a period of time and extrapolating data into the future, on the assumption that this trend will continue

predicting future sales based on moving averages and seasonal varieties

moving averages are calculated by combined data over a period of time in such a way that changes caused by fluctuations are elminated or at least reduced.

3 main typres of fluctuation:

• cyclical
• seasonal
• random

moving averages allow an organisation to calculate a trend scientifically using a series of calculations desined to eliminate fluctuations within a series of data. by predicting trends, firms are able to forecast future sales. this info is invaluable in helping to plan production and draw up HR plans, and is the basis of much financial planning.

in order to predict future sales, it is necessary to calculate

• the trend
• seasonal variations

weakness of extrapolation

• less reliable if there are fluctuations
• it assumes that past changes will continue into the future and thus does not take into account changes in the bus environemtn that will influence sales, incliding changes within the bus itself
• it ignores qualitative factors, such as changes in tastes and fashion

correlation

• can be a useful technique for sales forecasting, as it can show the degree to which factors such as drive, the advertising budget or even external factors , such as the proximity of competitors, are linked to sales of a product.
• graphically, the correlation between two sets of data is shown in a scatter diagram or scatter graph
• once the points have been plotted, a line of best fit is added. the line can be drawn graphically by hand but is more accurate if calculated mathematically
• before drawing any conclusion that there is a link between two sets of info, it is essential that a causal link is discovered.
• once a casual link is discovered, correlation can be useful to identify the extent of the link between the two series of data.
• there is a tendency to assume that a company would prefer a high correlation to a low correlation

limitations of quantitative forecasting

• past trends do not always continue into the future
• correlation changes over time
• external influences, such as competitors actions, consumers tastes or the stages of the business cycle, can vary over time.
• corporate objectives may be amended, so that the sales target becomes more or less important
• internal policies or actions may change
• the market research used for forecasts may lack reliability
• forecasts become more difficult the further they predict into the future
• ignore the special understanding of the market that may be possessed by the staff of the business

methods of qualitative forecasting

• the oracle technique - relies on the firm asking individual experts for their views. these experts opinions are then calated into an overall consensus of future events, allowing a more accurate prediction of future sales to be made
• brainstorming - inolves all individuals concerned with the product or service
• individual launch - a particular manager will be held responsible for product/service being considered

reasons for using qualitative forecasting:

• when theforecast concerns a new product/business, so there is no previous info on which to base predictions
• when there is no clear statistical indication of future sales
• when trends have changed, so that it would be unwise to predict on the basis of past statistics
• when the factors influencing sales are not easy to quantify
• when the character of the invididuals is important

limitations of qualitative forecasting:

• unlikely that experts will understand all aspects of a market
• many trends and relationships are broadly consistent overtime, so forecasts based on quantitative data are more accurate than hunches or opinions
• it is easier to persuade a senior manager if your forecast is based on scientific methods
• ignoring statistical info may have a manager open to criticism if predictions turn out to be incorrect

conclusion

• in general, new businesses and managers in small firms are more likely yo use qualitative forecasting.
• if sales are overstimated, there is likely to be a waste of resources as the firm will produce too much
• the cost of the firm depends on whether the products and perishable and how expensive they are to store
• underestimation also causes problems. the opportunity cost of lost sales is high, especially if customer goodwill is undermined

althought sales forecasts cannot be relied upon, they do give direction and targets for an organisation. ideally, they should arise from a blend of qualitative and quantitative techniques. sale forecasts are likely to be correct when:

• the product is well established and the market known
• external factors are predictable and there is stability in tastes and competitor actions
• the forecasts are made by, and agreed with, those having day-to-day contact with the market
• the organisation has undertaken detailed and reliable market research

the use of IT in analysing markets

• an IT based system can complete quantitative forecasting calculations almso instanteously, saving time and money for a business
• allows a business to compare a number of different strategies thus improving the quality of planning in business
• organsiations able to link their sales records to other databases
• allows a firm to improve both internal and external communication, imrpoving efficiency and the firms understanding of its market
• loyalty cards can accumulate info of buyinh habits
• the internet or company intranet allows more data to be stored cheaply and accessed more quickly by a wide range of individuals