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Market research involves gathering and analysing data from the marketplace (i.e. from consumers and potential consumers) in order to provide goods and services that meet their needs.
This is research designed to gather primary data, that is, information which is obtained specifically for the study in question. It can be gathered in three main ways - observation, questionnaires and experimentation.
Observation involves watching people and monitoring and recording their behaviour (e.g. television viewing patterns, cameras which monitor traffic flows, retail audits which measure which brands of product consumers are purchasing).
Questionnaires are a means of direct contact with consumers and can take a variety of forms. Personal questionnaires (such as door-to-door interviewing), postal questionnaires, telephone questionnaires and group questionnaires (such as asking for the attitudes of a group of consumers towards a new product). Questionnaires can be a very expensive and time-consuming process and it can be very difficult to eliminate the element of bias in the way that they are carried out. It is important that every respondent must be asked the same questions in the same order, with no help or emphasis being placed on certain questions / responses.
Experimentation involves the introduction of a variety of marketing activities into the marketplace and then measuring the effect of each of these on consumers. For example, test marketing, where a new product is launched in a small, geographical area and then the response of consumers towards it will dictate whether or not the product is launched nationally.
This is the collection of secondary data, which has previously been collected by others and is not designed specifically for the study in question, but is nevertheless relevant. Secondary data is far cheaper and quicker to gather than primary data, but it can be out-of-date by the time that it is researched. The main sources of secondary data are reference books, government publications and company reports.
The primary and the secondary research will provide the business with much data relating to its markets and its consumers. This data can then be used to describe the current situation in the marketplace, to try to predict what will happen in the future in the marketplace, and to explain the trends that have occurred.
The business may also use the market research data to segment the market. This involves breaking the market down into distinct groups of consumers who have similar characteristics, so as to offer each group a product which best meets their needs. The main ways of segmenting a market are:
By consumer characteristics: this involves investigating their attitudes, hobbies, interests, and lifestyles.
By demographics: their age, sex, income, type of house, and socio-economic group.
By location: the region of the country, urban -v- rural, etc.
Effective segmentation of the market can lead to new opportunities being identified (i.e. gaps in the market for a product), sales potential for products being realised and increased market share, revenue and profitability.
Quantitative research involves carrying out market research by taking a sample of the population and asking them pre-set questions via a questionnaire (normally 200+ respondents) in order to discover the likely levels of demand at different price levels, estimated sales of a new product, and the 'typical' purchaser of the company's products. The data is numerical and can be analysed graphically and statistically. There are several types of sample that can be used to gather quantitative data:
Random sampling - this gives each member of the public an equal chance of being used in the sample. The respondents are often chosen by computer from a telephone directory of from the Electoral Register.
Quota sampling - this method involves the consumers being grouped into segments which share certain characteristics (e.g. age or gender). The interviewers are then told to choose a certain number of respondents from each segment. However, the numbers of people interviewed in each segment are not usually representative of the population as a whole.
Cluster sampling - this normally involves the consumers being grouped into geographical groups (or 'clusters') and then a random sample being carried out within each location.
Stratified sampling - the consumers are grouped into segments again (or 'strata') based upon some previous knowledge of how the population is divided up. The number of people chosen to be interviewed from each 'strata' is proportional to the population as a whole.
Qualitative research attempts to gain an insight into the motivations that drive a consumer to behave in a particular way. It is usually conducted through group discussions (often called focus groups) in order to discover the rationale behind consumers' purchases. The group discussion is often chaired by a psychologist in a relaxed manner, which should encourage the consumers to discuss their shopping habits and pre-conceptions concerning certain products and brands.
This involves attempting to estimate future outcomes (e.g. the level of sales). Forecasting can be done in a number of ways:
Extrapolation - this involves identifying the trend that existed in past data and then continuing this into the future. This is often done by using a software package to establish a line of best fit for past data, and then simply extending this line into the future.
The Delphi Technique - this involves using a panel of business and forecast 'experts' who discuss and agree long-range forecasting for important issues and events.
Market research - this can be used to try and establish the purchasing intentions of consumers.
Time Series analysis - this also attempts to predict future levels from past data. There are 4 main components of time-series data : the trend, cyclical fluctuations (due to the economic cycles of recessions and booms), seasonal fluctuations and random fluctuations.
Clearly, trying to predict and forecast what will happen in the future is not easy and many variables will change in both the short-term and in the long-term which will affect the accuracy of forecasts. It is always advisable for businesses to use a variety of forecasting techniques to arrive at suitable and acceptable figures for the future (e.g. costs, revenues, sales levels, profits, etc).
There are a variety of techniques that a business can use to analyse the data that it collects through its market research methods.
The mean - this is the sum of the items divided by the number of items.
The median - this is the middle number in a set of data.
The mode - this is the number, or value, that occurs most frequently in a set of data.
The range - this is the difference between the highest value and the lowest value in a set of data.
The interquartile range - this considers the range within the central 50% of a set of data. It therefore ignores the top 25% and the bottom 25% and is less prone to distortion by extreme values.
The standard deviation - this is a measure of the deviation from the mean value in a set of data.
Confidence Interval - this is a measure of the likely accuracy of the results of a sample. With a 95% confidence interval, there is a 0.95 probability that the true average will be where the sample believes it will lie (in other words, the results of the sample will be correct 19 times out of 20).
Index numbers - this is a statistical measure which is designed to make changes in a set of data (such as sales figures) easier to manage and interpret. It involves giving one item of data a value of 100 (the base period), and adjusting the other items of data in proportion to it.
For example, if the sales for a particular business are £200,000 in year 1, £220,000 in year 2 and £270,000 in year 3, then index numbers can be used to help identify the trend within the data. The sales in year 1 will be given an index number of 100 (this is known as the base-year). Year 2 has £20,000 more sales than in year 1 - this is a 10% rise, so the index number in year 2 will be 110. Year 3 has £70,000 more sales than year 1 - this is a 35% rise, so the index number in year 3 will be 135.
Moving average - this is another way of identifying the trend in a set of data. It allows extreme values to be glossed over, so as to show the underlying pattern in a set of data. For example, consider the following data referring to sales over a 5 year period for a business :
|Year 3||£ 65,000|
The mean value of sales over this 5 year period is found by adding all 5 values together, and dividing the resulting answer by 5 (£563,000 / 5 = £112,600).
However, a 3-year moving average can give a more realistic indication of the changes in the trend over the 5 years. This is calculated by adding together the first three year's data, and dividing the resulting figure by 3 (£285,000 / 3 = £95,000).
This process is then repeated for the next 3-year period (i.e. years 2, 3 and 4). This gives a figure of £317,000 / 3 = £105,667.
The next 3-year period covers years 3, 4 and 5. This gives an answer of £343,000 / 3 = £114,333.
These figures show how the trend has moved within the data over the 5 year period.
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