Collecting information about the market is quite difficult. This problem has become especially complicated in connection with the transition to a market economy, since many trade and industry enterprises keep commercial secrets. A nationwide market data bank does not yet exist. Therefore, the necessary information has to be collected “bit by bit”, creating a more or less objective picture.
There are two methods for collecting such information - continuous observation, when all units of the general population are examined, and selective, in which information is obtained from only a part of the units of this population. Continuous observations are used relatively rarely, since they are cumbersome and rather expensive. For example, the last complete census of the population required the involvement of about 2 million registrars. Its results were processed using electronic computers for more than a year. However, continuous observations in our country are still sometimes carried out (population censuses, inventories at industrial and trade enterprises, certification of shops, etc.). These data can be used to assess the state and prospects for the development of the market.
More common in marketing research is the selective method of collecting information. It has a number of advantages over solid. First, information can be obtained much more quickly from sample observation, which is important given the timeliness requirement for market information. Secondly, data obtained by sampling are usually much more complete, since there is a good opportunity to characterize each unit of observation from a larger number of sides. Thirdly, the data of selective observation can be more accurate. This advantage looks somewhat paradoxical, but it is true. The fact is that the most significant and unexpected are registration errors, the so-called “misses”, when the actual and registered data can differ by an order of magnitude or even more. The probability of such errors increases in proportion to the number of registrars, which are dozens of times more under continuous observation. With selective observation, there are relatively few registrars, it is possible to better prepare them, instruct them, and control them more often. These measures drastically reduce the likelihood of "misses" during registration. Fourth, the data obtained by choosing
monitoring, much cheaper due to the involvement of a smaller number of workers, lower processing costs. Fifth, selective observation can be applied in those cases where continuous observation is devoid of common sense. For example, when studying the quality level of some goods, their destruction or even complete destruction is required.
However, these advantages of the sampling method can only be realized if certain rules are strictly observed in the organization and conduct of sampling. These primarily include ensuring the quantitative and qualitative representativeness (representativeness) of the sample.
Quantitative representativeness is understood as the provision in the sample of such a number of units, in which it is possible to fairly reasonably judge the magnitude of the studied characteristics. For example, salespeople in a community need to know how many men in that city use electric shavers. It is hardly possible to interview all men. Therefore, it is better to conduct a random survey. But how many people to ask? If too much, then the cost of the survey may exceed the expected benefit, and if too little, then data with a large error can be obtained.
If nothing is known about the general population (for example, we do not even know how many shaving men live in the city), then the calculation of the required sample size is carried out according to the formula
where n is the required (sufficient, representative) sample size;
p is the proportion of men using electric shavers;
q - the proportion of men who do not use electric shavers (q = 1 - p);
AR - the sampling error allowed by us for a share (given accuracy);
t is a coefficient depending on the probability with which the given sampling accuracy is guaranteed.
In this case, the product pq = 0.25, i.e. its maximum level is taken. The reasoning here is as follows. If men who shave are equally divided, i.e. exactly half use electric shavers (p = 0.5) and the other half do not use them (q = 0.5), then the largest sample is needed to determine this ratio. And if this sample is sufficient for such a ratio, then for any other ratio it will be all the more sufficient.
Assume that we can neglect the ±5% error. Then Dr = 0.05. Coefficient 1 tabular. Its value depends on the probability with which it is guaranteed that the value of the sampling error will not go beyond ±5%. Usually in marketing research, a probability of 0.954 is considered quite acceptable. This probability value in special tables corresponds to t = 2. If we wanted to provide a higher probability (for example, 0.997), then this value would correspond to t = 3, etc.
Thus, in our example, the required sample size (the number of interviewed men) is 400 people. 
If something is known about the general population, then the calculations are carried out differently. For example, it is known from past surveys that 80,000 men shaving in the city, 80% of them have previously used electric shavers, so the required sample size is calculated by the formula 
where N is the volume of the general population, and the remaining designations are similar to the previous formula.
If it is necessary to determine the average value of the general population (for example, the average service life of electric shavers), then the sample size is calculated by the formula 
where a2 is the dispersion characterizing the level of variation of the trait under study;
Dx is the maximum allowable sampling error for the mean;
the rest of the designations are given above.
For example, past surveys show that a2, which characterizes the variation in the service life of electric shavers, is 2.25 years. Acceptable accuracy for us is ±0.3 years. Then
Having calculated the required sample size according to the above formulas, they provide quantitative representativeness
samples, i.e., the minimum number of population units that must be examined in order to obtain a sufficiently accurate result.
Qualitative representativeness is understood as the provision in the sample of the maximum possible number of groups in the general population. In our example, the sample should include young, middle-aged and elderly people, rich and poor, with different levels of education, different professions, etc. The fact is that each of these groups has its own characteristics in the use of electric shavers (some shave more often, others less often, some use an electric razor daily, others alternate shaving with an electric razor and safety blades, etc.).
The best qualitatively representative sample would be one in which the study groups would be represented in proportion to their share in the general population. 
Rice. 7. Qualitatively representative sample
Rice. 8. Qualitatively unrepresentative sample
Shifts in the sample are especially dangerous, since they can give very large errors.
If we neglect the requirement to ensure qualitative representativeness and examine a sufficiently large number of men, but only young and middle-aged men (see Fig. 8), then the results of the survey will be very inaccurate. For example, in reality, only 10% of young people use electric shavers, 40% of middle-aged people, and 90% of the elderly. If the sample were representative (Fig. 7), then the estimated share of those using electric shavers would be 
If there was a shift in the sample (Fig. 8), then the estimated share will be 
i.e. sample data will be obtained with an error of 88%. In the practice of marketing surveys, shifts in the sample can lead to a 5-10-fold error (the author is aware of many such examples).
The best way to avoid such errors is to use an appropriate selection of sampling units. The small volume of the textbook makes it impossible to consider each of them. Let us dwell on the most commonly used in market research random-mechanical selection. Its essence lies in the fact that random people are examined at a certain interval. For example, if there are 80,000 men who shave in a city, and 400 people are scheduled to be examined, then every 200 person should be interviewed (80,000/400). Such selection will ensure the presence in the sample of representatives of almost all groups of the general population.
After conducting a sample survey and counting the results, the representativeness of this survey is assessed by calculating the actual error and determining confidence intervals for the results obtained. Sampling errors are calculated using the formula 
For example, as a result of a sample survey of men in the city, it was found that 47% of them use electric shavers. A total of 250 people were examined. Then the marginal sampling error is 
Therefore, the confidence interval for the proportion of men using electric shavers is
from 0.47-0.06 to 0.47+0.06, i.e. from 41 to 53%.
In other words, it can be assumed that 41 to 53% of men in the city use electric shavers, and based on these data, build their commercial policy.
There are many different ways to collect market information. They depend on the purpose of the survey, the level of detail of information, the capabilities of the company, etc. These include interview surveys, questionnaire surveys, cross-sectional observations, panel surveys, inventories
trade enterprises, sales of experimental batches of goods, exhibitions-sales, exhibitions-views, etc. Some of them will be discussed in this tutorial, others are mentioned only in passing due to the limitations of the scope of this tutorial.
Methods of collecting information about the market. Sampling method and its advantages
There is no nationwide market data bank in Russia yet, so the necessary information has to be collected bit by bit, creating a more or less objective picture.
There are two methods for collecting such information - continuous observation, when all units of the general population are surveyed, and selectively, in which information is obtained from only a part of the units of this population. More common in marketing research is the selective method of collecting information, which has the following advantages:
1 - information can be obtained much faster, which ensures the timeliness of information;
2 - the data obtained by sampling is much more complete, because it is possible to characterize each unit of observation much more fully;
3 - information is more complete, because the number of collected information is less, and therefore the number of possible errors is less.
However, the advantages of the sampling method can only be realized if certain rules are strictly observed in the organization and conduct of sampling. These primarily include ensuring the quantitative and qualitative representativeness (representativeness) of the sample.
Quantitative representativeness is understood as the provision in the sample of such a number of units, in which it is possible to fairly reasonably judge the magnitude of the studied characteristics.
If nothing is known about the general population, then the calculation of the required sample size is carried out according to the formula:
where n is the required sample size;
D p is the sampling error we allow for the proportion (given precision);
t is a coefficient depending on the probability with which the given sampling accuracy is guaranteed;
p, q are the shares of opposite events (p + q = 1).
If nothing is known about the general population, then take
p = 0.5 and q = 0.5, and the sample size calculated for these values will be sufficient for any other "p" and "q" ratios.
In marketing research, the probability of an event equal to 0.954 is usually considered quite acceptable, at which t = 2 (from the table at p = 0.997, t = 3, etc.).
Example . Traders who sell agricultural machinery need to know how many farms use hay mowers. It is hardly possible to survey all households, so it is better to conduct a selective survey. But how many farms to interview?
For the example in question:
p – share of farms using hay mowers;
q – share of farms not using hay-mowers;
If we can allow a sampling error of ± 5%, then D p = 0.05 and thus have a sample size
farms.
If something is known about the population (for example, it is known from past studies that in the area 800 farms of which 80% used mowers), then the sample size is calculated by the formula:
,
where N - the volume of the general population.
For the example in question
farms.
If it is necessary to determine the average value of the general population (for example, the average service life of an electric mower), then the sample size is calculated using the formula:
,
where s2 – variance characterizing the variations of the trait under study;
Dx – marginal sampling error for the mean.
For example, past research has shown thats2 is±2.25 of the year. Then, with acceptable accuracy, we have±0.3 of the year.
farms.
The sample must be representative (Figure 1.4), i.e. should be represented by the maximum possible number of groups in the general population.
Figure 1.4 - Qualitatively representative sample
Figure 1.5 - Qualitatively unrepresentative sample
To avoid unrepresentativeness (Figure 1.5, random mechanical selection is used in market research. Its essence is that random objects are examined at a certain interval.
There is no nationwide market data bank in Russia yet, so the necessary information has to be collected bit by bit, creating a more or less objective picture.
There are two methods for collecting such information - continuous observation, when all units of the general population are surveyed, and selectively, in which information is obtained from only a part of the units of this population. More common in marketing research is the selective method of collecting information, which has the following advantages:
1 - information can be obtained much faster, which ensures the timeliness of information;
2 - the data obtained by sampling is much more complete, because it is possible to characterize each unit of observation much more fully;
3 - information is more complete, because the number of collected information is less, and therefore the number of possible errors is less.
However, the advantages of the sampling method can only be realized if certain rules are strictly observed in the organization and conduct of sampling. These primarily include ensuring the quantitative and qualitative representativeness (representativeness) of the sample.
Quantitative representativeness is understood as the provision in the sample of such a number of units, in which it is possible to fairly reasonably judge the magnitude of the studied characteristics.
If nothing is known about the general population, then the calculation of the required sample size is carried out according to the formula:
where n is the required sample size;
D p is the sampling error we allow for the proportion (given precision);
t is a coefficient depending on the probability with which the given sampling accuracy is guaranteed;
p, q are the shares of opposite events (p + q = 1).
If nothing is known about the general population, then take
p = 0.5 and q = 0.5, and the sample size calculated for these values will be sufficient for any other "p" and "q" ratios.
In marketing research, the probability of an event equal to 0.954 is usually considered quite acceptable, at which t = 2 (from the table at p = 0.997, t = 3, etc.).
Example . Traders who sell agricultural machinery need to know how many farms use hay mowers. It is hardly possible to survey all households, so it is better to conduct a selective survey. But how many farms to interview?
For the example in question:
p – share of farms using hay mowers;
q – share of farms not using hay-mowers;
If we can allow a sampling error of ± 5%, then D p = 0.05 and thus have a sample size
farms.
If something is known about the population (for example, it is known from past studies that in the area 800 farms of which 80% used mowers), then the sample size is calculated by the formula:
,
where N - the volume of the general population.
For the example in question
farms.
If it is necessary to determine the average value of the general population (for example, the average service life of an electric mower), then the sample size is calculated using the formula:
,
where s2 – variance characterizing the variations of the trait under study;
Dx – marginal sampling error for the mean.
For example, past research has shown thats2 is±2.25 of the year. Then, with acceptable accuracy, we have±0.3 of the year.
farms.
The sample must be representative (Figure 1.4), i.e. should be represented by the maximum possible number of groups in the general population.
Figure 1.4 - Qualitatively representative sample
Figure 1.5 - Qualitatively unrepresentative sample
To avoid unrepresentativeness (Figure 1.5, random mechanical selection is used in market research. Its essence is that random objects are examined at a certain interval.
After counting the results of the sample, the performance is evaluated by calculating the actual error
a) for the average b) for the proportion
; 
.
Example. As a result of a sample survey of farms, it was found that47 % of them use hay-mowers. A total of 194 farms were surveyed.
.
Therefore, the confidence interval for farms purchasing mowers is from 0.47-0.06 to 0.47+0.06 i.e. from 41% to 53%.
Based on these data, you can build your commercial policy.
The most common method of collecting information about the market is the questionnaire method.
Sampling method - a statistical method for studying the general properties of a set of any objects based on the study of the properties of only a part of these objects taken in the sample.
A well-studied example of the use of dependent observations is the estimation of an empirical distribution or its parameters in "general population" from N objects by the derived from it "sample" containing n< N объектов.
An example of the application of the sampling method is the following. Let there be L defective items in a batch of N items. n is randomly selected from the batch< N изделий. Вероятность того, что число l дефектных изделий в выборке будет равно m, равна
.
Sampling method(method of sampling) - a statistical method for studying the general properties of a set of any objects based on the study of the properties of only a part of these objects. The totality of the studied objects that are of interest to the researcher is called the general population. And part of the objects to be studied is called the sampling set or sample.
The need for a sampling method can be caused by objective reasons:
The object of research is very extensive, for example, the study of consumer preferences in the product market, the forecast of voting results in elections, etc.
The need to collect primary information in "pilot" studies.
Key questions of the sample survey:
Quantitative characterization of the sample or determination of the minimum number of observations (sample size) for the study;
Qualitative characteristics of the sample or methods and methods of forming a sample.
The main task of a sample survey is to obtain, with a minimum sample size, the most accurate description of the population of interest on the basis of sample data. This can be achieved only on the basis of a representative sample, i.e. sampling objectively reflecting the properties of the general population.
The accuracy of the results of sample surveys is achieved through the use of complex sampling methods (cluster sampling, stratification, the use of probability-proportional sampling, simple random or random sampling, repeated or non-repeated sampling).
The minimum sample size depends on many parameters of the study (the estimated indicator or system of indicators, the method and methods of sampling, the variation of the studied data, the given reliability of the results obtained, the maximum allowable error in the assessment of indicators) and is determined based on the formulas of mathematical statistics or by expert means.
The sampling method is used primarily in sociology, marketing, and clinical research. But in fact, in the statistical analysis of data in any field, the researcher, as a rule, works not with the general population, but with the sample. The mistake of many researchers is that they do not attach importance to this, they do not think about what methods the analyzed information was obtained and how the methodology of the sample survey was observed. Because of this, the results obtained do not correspond to really objectively existing patterns, because an unrepresentative sample is analyzed.
In the theory of the sampling method, various methods of selection and types of sampling have been developed to ensure representativeness. Under selection method understand the procedure for selecting units from the general population. There are two methods of selection: repeated and non-repeated. At repeated In the selection process, each randomly selected unit is returned to the general population after its examination and, during subsequent selection, may again fall into the sample.
This selection method is built according to the “returned ball” scheme: the probability of getting into the sample for each unit of the general population does not change regardless of the number of selected units. At non-repetitive selection, each unit selected at random, after its examination, is not returned to the general population. This method of selection is built according to the “unreturned ball” scheme: the probability of getting into the sample for each unit of the general population increases as the selection is made.
Selective observation applies when applying continuous observation physically impossible due to a large amount of data or economically impractical. Physical impossibility occurs, for example, when studying passenger flows, market prices, family budgets. Economic inexpediency occurs when assessing the quality of goods associated with their destruction, for example, tasting, testing bricks for strength, etc.
Statistical units selected for observation make up a sample or sample, and their entire array - the general population (GS). The number of units in the sample is denoted n, and in the entire HS - N. Attitude n/n called the relative size or proportion of the sample.
The quality of sampling results depends on sample representativeness, that is, on how representative it is in the GS. To ensure the representativeness of the sample, it is necessary to observe principle of random selection of units, which assumes that the inclusion of a HS unit in the sample cannot be influenced by any other factor than chance.
There are 4 ways to randomly select a sample:
1. Actually random selection or "lotto method", when serial numbers are assigned to statistical values, entered on certain objects (for example, kegs), which are then mixed in a certain container (for example, in a bag) and selected at random. In practice, this method is carried out using a random number generator or mathematical tables of random numbers.
2. Mechanical selection, according to which each ( N/n)-th value of the general population. For example, if it contains 100,000 values, and you want to select 1,000, then every 100,000 / 1000 = 100th value will fall into the sample. Moreover, if they are not ranked, then the first one is chosen at random from the first hundred, and the numbers of the others will be one hundred more. For example, if unit number 19 was the first, then number 119 should be next, then number 219, then number 319, and so on. If the population units are ranked, then #50 is selected first, then #150, then #250, and so on.
3. The selection of values from a heterogeneous data array is carried out stratified(stratified) method, when the general population is previously divided into homogeneous groups, to which random or mechanical selection is applied.
4. A special sampling method is serial selection, in which not individual quantities are randomly or mechanically chosen, but their series (sequences from some number to some in a row), within which continuous observation is carried out.
The quality of sample observations also depends on sampling type: repeated or non-repetitive.
At re-selection the statistical values or their series that fell into the sample are returned to the general population after use, having a chance to get into a new sample. At the same time, all values of the general population have the same probability of being included in the sample.
Non-repeating selection means that the statistical values or their series included in the sample are not returned to the general population after use, and therefore the probability of getting into the next sample increases for the remaining values of the latter.
Non-repetitive sampling gives more accurate results, so it is used more often. But there are situations when it cannot be applied (study of passenger flows, consumer demand, etc.) and then a re-selection is carried out.
Index Methods in Statistical Research
Index- this is a generalizing relative indicator that characterizes the change in the level of a social phenomenon over time, compared with a development program, plan, forecast, or its relationship in space.
The most common comparative characteristic in time. In this case, the indices act as relative values of the dynamics.
Index Method is also the most important analytical tool for identifying relationships between phenomena. In this case, not individual indices are used, but their systems.
In statistical practice, indices are used in the analysis of the development of all sectors of the economy, at all stages of economic work. In a market economy, the role of price indices, household incomes, the stock market and territorial indices has especially increased.
Statistics classifies indices according to the following criteria:
1. Depending on the object of study:
Indices of volume (quantitative) indicators (indices of physical volume: turnover, production, consumption)
Indices of quality indicators (indices of prices, costs, wages)
The indexes of volume indicators include indices of physical volume: commodity circulation, production, consumption of material goods and services; as well as other indicators of a quantitative nature: the number of employees, acreage, etc. Indexes of qualitative indicators include indices of: prices, production costs, wages, labor productivity, productivity, etc.;
2. By the degree of coverage of the elements of the population:
Individual indices (give a comparative description of the individual elements of the phenomenon)
General indices (characterize the change in the totality of elements or the whole phenomenon as a whole)
3. Depending on the calculation methodology, general indices are divided into:
Aggregate (aggregate indices are the main form of indices and are built as aggregates by weighting the indexed indicator using the constant value of another indicator interconnected with it).
Average (derived from aggregate)
4. Depending on the basis of comparison, there are:
Basic (if the comparison base remains constant when calculating indices for several periods of time)
Chained (if the base of comparison is constantly changing)
Visit to the consumer. The first thing a market research firm should do is send members of the cross-functional team to the customer. Face-to-face communication with the customer seems to be the most natural method of obtaining data, and yet some firms delve into the most complex customer research, preferring to keep the latter at a distance. As a result, too long a chain of value judgments is stretched between the consumer and the decision maker. Trade shows provide merchants with the opportunity to promote the latest products and services to consumers and distributors. They allow you to collect significant amounts of information not only about new products, but also about how consumers and distributors are interested in them. Annual reports of competitors. Despite the fact that the annual reports are more like a covert self-promotion, growing | calculated on shareholders, valuable information can be gleaned from them regarding trends in the development of the company's mission, its goals and financial condition, comparing reports for the last four to five years. Government and industry reports. Newsletters. The US Census Bureau, the world's largest market research organization, has a wealth of data on American family trends. Nearly every public library receives reports prepared by it, and in every major city there are offices of the Bureau, to which businessmen turn for information of interest to them. Computer databases All interactive databases allow the user to search for relevant articles, newsletters and other data by keywords. Focus groups are made up of carefully selected six to twelve people for a casual one or two hour discussion of a particular issue. An experienced facilitator skillfully guides the discussion, while members of the cross-functional decision-making team watch it through a translucent mirror or on a local television network.
Systematic consumer samplingcarried out on the basis of pre-prepared questionnaires. Consumers who have recently purchased a product (service) are surveyed for satisfaction with the product; contact with them is established through a phone call or a postcard with a paid response.
V. 36 Information collection methods
Despite the huge number of various research methods and techniques, the general scheme of activities implemented in the framework of market research is quite simple and understandable. The main sources of marketing information are:
- Interviews and surveys;
- Registration (observation);
- Experiment;
- Panel;
- Expert review.
Interview (poll)- finding out the position of people or obtaining information from them on any issue.
A survey is the most common and essential form of data collection in marketing. Approximately 90% of studies use this method. The survey can be oral (personal) or written.
Personal (Face-to-face) and telephone surveys are called interviews.
Phone interviews
Face-to-face interviews: formalized and non-formalized.
In a formalized interview, there is a specific survey scheme (usually a questionnaire containing pre-prepared clear wording of questions and well-thought-out models of answers to them)
informal interviews- this is a specific method of collecting information in which there is only a topic and a goal.
In-Depth Interviews
Hall - tests- These are personal semi-formalized interviews in a special room.
Group non-formalized interview (focused interview, focus - group) - is a group discussion of issues of interest to representatives of the target audience.
Observation (registration) is a form of marketing research, with the help of which a systematic, systematic study of the behavior of an object or subject is carried out.
Experiment- this is a study of the influence of one factor on another while controlling extraneous factors.
Panel- this is a repeated collection of data from one group of respondents at regular intervals.
Expert review- this is an assessment of the processes under study by qualified specialists - experts.
Delphi Method- a form of survey of experts, in which their anonymous answers are collected over several rounds and, through familiarization with the intermediate results, they receive a group assessment of the process under study.
brainstorming method consists in uncontrolled generation and spontaneous interweaving of ideas by participants in a group discussion of a problem.
Synectics considered a highly creative method. The idea of the method lies in the gradual alienation of the original problem by building analogies with other areas of knowledge. After multistage analogies, a quick return to the original problem is made.
37 definition of competitors and competition structure.
Porter identified five factors that determine competition: current competitors; the danger of new competitors; the danger of the appearance of substitutes for the product; the consumer's ability to make deals; supplier's ability to make deals. This structure can be simplified to current competitors potential competitors and product substitutes. As we will see later, this is because the ability of consumers to make deals depends largely on how strong the competition between competitors for supplies to these consumers is. . A company's market share can change dramatically depending on whether the market is defined as global, export-specific, US, regional, urban, or user or consumption segment. The scale of the market is usually determined by a realistic assessment of the company's resources and its growth goals.
38 definition of the concept of "product distribution channel". Distribution management
goods.
Distribution channels
A firm operating on the international market must necessarily consider in a comprehensive manner the problems of bringing its goods to end consumers 13 . On fig. 94 shows three main links between the seller and the end buyer. The first link is the headquarters ¾ of the seller's organization, which controls the operation of the distribution channels and at the same time is itself part of these channels. The second link ¾ interstate channels ¾ ensures the delivery of goods to the borders of foreign countries. The third link ¾ domestic channels ¾ ensures the delivery of goods from the border crossing points of a foreign state to end consumers. Too many American manufacturers consider their mission complete once the product is out of their hands. And they should more closely monitor what happens to this product in the process of its movement within a foreign state.
Rice. 94. The general structure of the distribution channel at
international marketing
Intrastate distribution channels of different countries differ in many ways from each other. There are large differences in the number and types of intermediaries serving each individual foreign market.
