7 – Secondary Data

Introduction

During the study, a person other than the researcher may collect and process secondary data. Censuses, significant surveys, and organisational records are familiar secondary data sources in social research. Primary data in sociology is data you have collected yourself, whereas secondary data is data you have received from primary sources to develop a new study. These two concepts have various connotations in historical research. A book or group of archival materials is a primary source. A secondary source is a synopsis of a book or collection of records.

7.1 Secondary Information

Secondary data are pre-existing statistics. They were not gathered for immediate use. This might be defined as “data compiled by a party other than the user.” Secondary data is classified as follows:

1. Internal secondary data

2. External secondary data

7.1.1 Internal secondary data

Internal secondary data is part of the company’s record and has already been researched. Internal data are those found within an organisation.

Sales in units, credit outstanding, salesperson call reports, daily production reports, monthly collection reports, etc.

7.1.2 External Secondary Data

The researcher’s data was gathered from sources outside the company. This is broken into four sections:

• Census information
• Publication of individual project reports
• Syndicated data is data acquired for commercial selling.
• Miscellaneous information

7.1.3 Benefits and Limitations of Secondary Data

Gathering secondary data is significantly less expensive than obtaining primary data. A careful review of secondary sources can provide far more information than a primary data-gathering operation for the same research budget.

The time required to search secondary sources is significantly shorter than that needed to collect primary data.

Secondary sources of information can provide more reliable data than primary research. This is not always the case, but when a government or international agency conducts a large-scale survey or even a census, the results will likely be far more accurate than when custom-designed and executed surveys are based on relatively small sample sizes.

It should not be overlooked that secondary data can play an essential role in the exploratory research phase when the goal is to identify the study problem and create hypotheses. Secondary data collection and analysis almost always improves the researcher’s grasp of the marketing problem, the many lines of investigation that may or should be pursued, and the alternative courses of action that could be taken.

Secondary sources aid in the definition of the population. Secondary data can be beneficial in characterising the population and structuring the sample. For example, government information on a country’s agriculture will help determine how to stratify a sample. Once sample estimates have been derived, these can be projected to the population.

Limitations

1. Definition: When using secondary data, the researcher might draw the wrong conclusions because of how the people who prepared it used certain terminology.

2. Measurement error: When a researcher undertakes fieldwork, he or she may be able to determine measurement imperfections using the standard deviation and standard error, but these are not continuously published in secondary sources. The problem is not always “mistake” but rather variations in the levels of accuracy that decision-makers demand.

3. Source bias: When using secondary sources, researchers encounter the issue of vested interests. Those in charge of compiling them may be incentivised to offer a more optimistic or pessimistic set of results for their organisation; for example, exaggerated figures or inflated estimates may be given.

4. Reliability: The dependability of reported statistics varies over time. Because data collection systems, geographical or administrative boundaries, or the foundation for stratifying a sample may have changed, other study methods that influence the dependability of secondary data include sample size, response rate, questionnaire design, and modalities of analysis, which are not disclosed to the reader of published statistics.

5. Time scale: The period in which secondary data was first compiled may significantly impact its nature. For example, because most censuses are held every 10 years, data from this and other published sources may be outdated by the time the researcher intends to use the numbers.

7.2 Market Research Techniques or Syndicated Data

These strategies involve commercial data collection, i.e., data obtained by this method is sold to interested clients in exchange for payment.

Example: A.C. Nielson, ORG Marg, IMRB, and others collect syndicated data. They offer a business relationship survey known as the BRS, which estimates the following:

1. Rating

2. The company’s profile, for example.

3. these persons regularly supply TRP ratings or television rating points.

This includes:

• Figures for viewership
• Duplication of programmes, etc.

SNAP—Study of Nations Attitude and Awareness Programme is one of the noteworthy studies conducted by IMRB. This study explored the diverse groups of India’s population, their lifestyles, and the attitudes of Indian housewives.

There is also the FSRP study, which involves children aged 10 to 19. Aside from demographics and psychographics, the study delves into topics such as Children as decision-makers, Role models of Indian children, Pocket money and its use in Media evaluations, favourite personalities and attributes, and Brand recognition and advertising recall.

Market research organisations that provide syndicated services are examples of syndicated sources. These market research firms collect and update data constantly. Because data is syndicated, its cost is divided among many client organisations, making it less expensive.

For example, a client firm can request that specific questions be included in the questionnaire frequently used to collect syndicated data. These will incur additional costs for the client. The data created by extra questions and analysis will be available exclusively to the companies that submitted the queries.

As a result, we may argue that secondary data can be customised. Newspapers, periodical readership, TV channel popularity, and so on are examples of syndicated services. Data from syndicated sources is made available weekly or monthly.

Syndicated data can be divided into three categories:

(a) consumer purchase data,

(b) retailer and wholesaler data, and

(c) advertising data.

Most of the data mentioned above collection methods are also called syndicated data. Syndicated data is classified as follows:

7.2.1 Consumer Purchase Data or Panel Type Data

This is a subset of syndicated data. There are consumer panels in this system. Members of this panel will be drawn from a cross-section of the population. Panel members carry notebooks in which they keep track of all purchases they make. Purchased items range from packaged food to personal care items. Members submit their diaries to the organisations for which they are compensated once a month. This panel data can be used to determine the product’s sales. These panel statistics also include information on repeat purchases, the impact of free samples, coupon redemption, and so on.

The data from the consumer panel also gives a profile of the target audience. In recent years, handheld scanners have mostly replaced diaries.

Limitations

• Limitations include a lack of representation for low-income groups and some people’s unwillingness to keep track of their purchases. As a result, relevant data is unavailable.

Advantages

• Using a scanner linked to the central computer allows panel members to record their purchases early (nearly instantly) and provides dependability and speed.
• The panel could be comprised entirely of senior citizens or children.
• There is also the Consumer Mail Panel (CMP). This group is made up of people who are willing to respond to postal questionnaires. A considerable proportion of these households remain on the panel. This serves as a world in which panels are chosen.

7.2.2 Retail and Wholesale Data

A retail store is used for marketing research. These companies provide ongoing data on supermarket products. The approach does not entail interviewing people or relying on their memories, which necessitates the retailer’s assistance in auditing. In general, retail auditing entails counting stocks between two consecutive visits.

It entails inspecting things provided in between visits. Suppose the stock of any product in the shop is precisely measured during both visits, and data on delivery is accurately gathered from the records. In that case, the collection of sales of a product throughout that period can be accurately determined as follows:

Initial stock + Deliveries between visits – Second-time stock = Sales

If this information is acquired from a representative sample of stores, then accurate estimations of the product’s sales can be made. To do this, certain stores can be viewed as a “Panel of Stores,” symbolising the universe.

Advantages

• It offers information between audits on over-the-counter consumer purchases in individual units, such as KGs, bottles, Nos, etc.
• It gives information on store transactions or purchases the business makes between audits.
• It is a pretty dependable strategy.

Disadvantages

• The market researcher must have experience, and the retail shop must cooperate. It is time demanding.

7.2.3 Advertising Data

Because so much money is spent on advertising, statistics about advertising must be collected. The use of a passive metre is one method of recording. This device, mounted to a television, records when the TV is turned on. It will keep track of “how long a channel is viewed.” Data about audience interest in a channel can be obtained using this method. One thing to note from the above is that it only indicates that someone watches television at home. However, it does not inform “who is watching at home.” A new gadget, the ‘People’s Meter’, is presented to determine “who is viewing.” This is a set of instrument buttons that can be manipulated remotely. Each household is assigned a unique button. When that button is pressed, it alerts the control box to the fact that a particular user is viewing it. This information is electronically recorded and delivered to a computer, which stores and then analyses it.

Secondary Information in Various Forms

This data includes trade associations such as FICCI, CEI, Institution of Engineers, Chamber of Commerce, libraries such as public libraries, university libraries, etc., literature, state and central government publications, private sources such as All India Management Association (AIMA), Financial Express and financial dailies, world bodies and international organisations such as IMF, ADB, and others.

7.3 Secondary Data Advantages  and Disadvantages

 Advantages

• It is cost-effective because there is no need to pay field personnel, and it saves time (usually 2 to 3 months). If the data is readily available, it can be tallied in minutes.
• They provide information that retailers may be unwilling to share with researchers.
• Unlike primary data, no training is required to acquire secondary data.

Disadvantages

• It may not apply to the topic because secondary data was gathered for other projects. The stream is so bad that the data is useless in certain circumstances. It may be unsuitable for the following three reasons:

1. Unit of measurement

2. Definition of a class

3. Recency

1. Unit of measurement:

Secondary data is frequently expressed in units.

For example, the size of a retail establishment can be expressed in terms of total sales, profits, square feet area, and personnel count. Consumer income can be expressed in terms of the individual, family, home, etc. Secondary data that is available may not easily fit in.

Assume that the class intervals are vastly different from those required.

Example: The following data is provided for each age group:

18-year-olds

18–24-year-olds

25–34-year-olds

35–44-year-olds

The aforementioned secondary data classification cannot be applied if the company requires a classification of less than 20, 20-30, or 30-40.

2. Problem of Accuracy

The reliability of accessible secondary data is highly dubious. A variety of errors can occur during data collecting and processing. The accuracy of secondary data is determined by:

• Who gathered the information?
• How is the information gathered?

1. Who gathered the information? The source’s dependability determines the accuracy of the data. Assume a private periodical publisher performs a survey of his readers. The primary goal of the poll is to find out what readers think about the advertising that appears in it. The publisher hopes that other businesses will purchase this information before adding adverts.

Assume a professional MR agency did a comparable poll and sold syndicated data to several journals.

If you want information on a specific periodical, purchase the data from the MR agency rather than the periodical’s publisher. The cause for this is a lack of trust in the MR agency. The following are the grounds for trusting the MR agency:

• There is no bias because the agency is independent. The MR agency will most likely offer unbiased data.
• Because they are professionals, the data quality of the MR agency will be high.

2. How was the information gathered?

• What were the instruments used?
• What kind of sampling was used?
• What was the size of the sample?
• How long did it take to acquire the data, such as days of the week and times of the day?

3. Recency

This relates to the question, “How old was the information?” Information older than five years may be useless, and publication lag is an issue.