Which Of The Following Is True Of Secondary Data Used In Marketing Research?

What is secondary data, and why is it important? Find out in this post.

Within data analytics, in that location are many ways of categorizing data. A common distinction, for instance, is that between qualitative and quantitative data . In add-on, you might also distinguish your information based on factors similar sensitivity. For example, is it publicly available or is it highly confidential?

Probably the most key distinction between different types of data is their source. Namely, are they primary, secondary, or third-party information? Each of these vital data sources supports the data analytics procedure in its ain mode. In this post, we'll focus specifically on secondary data. We'll look at its main characteristics, provide some examples, and highlight the chief pros and cons of using secondary data in your assay.

We'll encompass the post-obit topics:

In a nutshell: What is secondary data?
What'southward the difference between primary, secondary, and third-party data?
What are some examples of secondary data?
What are the advantages and disadvantages of using secondary data?
Wrap-up and further reading

Prepare to larn all nearly secondary data? Then let'south get.

one. In a nutshell: What is secondary information?

Secondary information (as well known equally second-party data) refers to whatsoever dataset nerveless by whatever person other than the one using it.

Secondary data sources are extremely useful. They allow researchers and data analysts to build large, high-quality databases that aid solve business issues. By expanding their datasets with secondary data, analysts can enhance the quality and accuracy of their insights. Most secondary data comes from external organizations. However, secondary data likewise refers to that collected inside an organization and and so repurposed.

Secondary data has various benefits and drawbacks, which we'll explore in detail in department four. First, though, information technology'south essential to contextualize secondary information past understanding its relationship to 2 other sources of data: master and 3rd-party data. Nosotros'll look at these next.

A data analyst in side profile, looking at secondary data on a laptop screen

2. What'due south the difference between main, secondary, and third-political party data?

To best understand secondary information, we need to know how it relates to the other chief data sources: principal and 3rd-party data.

What is master data?

'Master information' (also known as first-party information) are those directly nerveless or obtained by the organisation or individual that intends to utilize them. Chief data are e'er collected for a specific purpose. This could be to inform a divers goal or objective or to address a item business concern problem.

For example, a existent estate arrangement might want to analyze electric current housing market trends. This might involve conducting interviews, collecting facts and figures through surveys and focus groups, or capturing data via electronic forms. Focusing but on the data required to complete the task at hand ensures that master information remain highly relevant. They're also well-structured and of high quality.

What is secondary information?

As explained, 'secondary information' describes those collected for a purpose other than the task at hand. Secondary data can come from within an organization but more normally originate from an external source. If it helps to brand the stardom, secondary data is essentially merely some other organization's primary information.

Secondary information sources are so numerous that they've started playing an increasingly vital role in research and analytics. They are easier to source than primary data and tin can be repurposed to solve many unlike bug. While secondary data may be less relevant for a given task than primary data, they are generally all the same well-structured and highly reliable.

What is 3rd-party data?

'Tertiary-political party data' (sometimes referred to every bit tertiary data) refers to information nerveless and aggregated from numerous discrete sources by third-party organizations. Because third-party information combine data from numerous sources and aren't nerveless with a specific goal in mind, the quality tin exist lower.

Third-party data likewise tend to exist largely unstructured. This means that they're oft beset by errors, duplicates, and and then on, and require more processing to go them into a usable format. Notwithstanding, used appropriately, third-party data are however a useful information analytics resource. You can learn more almost structured vs unstructured data hither .

OK, at present that we've placed secondary information in context, let's explore some mutual sources and types of secondary data.

A laptop screen showing an Excel spreadsheet containing secondary data

3. What are some examples of secondary information?

External secondary data

Before we go to examples of secondary data, we get-go need to understand the types of organizations that mostly provide them. Frequent sources of secondary data include:

Authorities departments
Public sector organizations
Industry associations
Trade and manufacture bodies
Educational institutions
Private companies
Market enquiry providers

While all these organizations provide secondary data, government sources are perhaps the most freely accessible. They are legally obliged to keep records when registering people, providing services, and and so on. This type of secondary information is known as administrative data. It'due south specially useful for creating detailed segment profiles, where analysts hone in on a particular region, trend, market, or other demographic.

Types of secondary data vary. Popular examples of secondary data include:

Tax records and social security data
Demography data
Electoral statistics
Health records
Books, journals, or other print media
Social media monitoring, internet searches, and other online information
Sales figures or other reports from third-political party companies
Libraries and electronic filing systems
App information, due east.g. location information, GPS data, timestamp data, etc.

Internal secondary data

As mentioned, secondary data is not limited to that from a different organisation. It can besides come from inside an system itself.

Sources of internal secondary data might include:

Sales reports
Hr filings
Annual accounts
Quarterly sales figures
Client relationship management systems
Emails and metadata
Website cookies

In the correct context, we tin can ascertain practically any type of information as secondary data. The key takeaway is that the term 'secondary information' doesn't refer to any inherent quality of the data themselves, only to how they are used. Any data source (external or internal) used for a chore other than that for which information technology was originally collected tin can exist described as secondary information.

A data analyst looking at data visualizations on an iPad

iv. What are the advantages and disadvantages of using secondary data?

Secondary data is suitable for any number of analytics activities. The only limitation is a dataset'south format, structure, and whether or not it relates to the topic or problem at hand.

When analyzing secondary data, the procedure has some small-scale differences, mainly in the preparation stage. Otherwise, it follows much the same path equally any traditional data analytics project. Yous can acquire more about secondary data analysis in this mail.

More than broadly, though, what are the advantages and disadvantages of using secondary data? Let'southward take a look.

Advantages of using secondary data

Information technology'south an economic use of time and resources: Because secondary data take already been collected, cleaned, and stored, this saves analysts much of the hard piece of work that comes from collecting these information firsthand. For instance, for qualitative data, the complex tasks of deciding on appropriate inquiry questions or how best to record the answers have already been completed. Secondary data saves data analysts and data scientists from having to start from scratch.

It provides a unique, detailed picture of a population: Certain types of secondary information, especially government administrative data, tin provide admission to levels of detail that it would otherwise exist extremely hard (or incommunicable) for organizations to collect on their own. Data from public sources, for example, tin provide organizations and individuals with a far greater level of population detail than they could ever hope to gather in-house. You can also obtain data over larger intervals if you need it., e.1000. stock market information which provides decades'-worth of information.

Secondary data can build useful relationships: Acquiring secondary information usually involves making connections with organizations and analysts in fields that share some mutual footing with your own. This opens the door to a cross-pollination of disciplinary knowledge. You lot never know what nuggets of data or additional information resource yous might find past edifice these relationships.

Secondary information tend to be loftier-quality: Unlike some information sources, e.chiliad. third-party information, secondary data tends to be in excellent shape. In general, secondary datasets have already been validated and therefore require minimal checking. Often, such as in the case of government data, datasets are likewise gathered and quality-assured by organizations with much more than time and resources available. This farther benefits the data quality , while benefiting smaller organizations that don't have endless resources available.

It's splendid for both data enrichment and informing primary information collection: Another benefit of secondary information is that they can be used to heighten and expand existing datasets. Secondary data tin also inform master information collection strategies. They can provide analysts or researchers with initial insights into the blazon of data they might want to collect themselves further downwardly the line.

Disadvantages of using secondary data

They aren't e'er complimentary: Sometimes, it's unavoidable—you lot may have to pay for access to secondary data. However, while this can be a financial brunt, in reality, the cost of purchasing a secondary dataset commonly far outweighs the cost of having to program for and collect the data immediate.

The data isn't always suited to the trouble at manus: While secondary data may tick many boxes concerning its relevance to a business problem, this is non always true. For instance, secondary information drove might have been in a geographical location or time menstruation ill-suited to your analysis. Because analysts were non present when the data were initially collected, this may as well limit the insights they can extract.

The information may non exist in the preferred format: Even when a dataset provides the necessary data, that doesn't mean it'south appropriately stored. A basic example: numbers might be stored equally categorical data rather than numerical information. Another issue is that in that location may be gaps in the information. Categories that are too vague may limit the information you tin glean. For example, a dataset of people's hair color that is express to 'brown, blonde and other' will tell you very little about people with auburn, black, white, or grayness hair.

You lot can't be sure how the data were collected: A structured, well-ordered secondary dataset may appear to be in good shape. However, it'south not always possible to know what bug might have occurred during data collection that will impact their quality. For case, poor response rates will provide a limited view. While issues relating to data collection are sometimes fabricated available aslope the datasets (e.g. for government data) this isn't always the instance. You lot should therefore treat secondary data with a reasonable caste of caution.

Existence enlightened of these disadvantages is the first footstep towards mitigating them. While you should be enlightened of the risks associated with using secondary datasets, in general, the benefits far outweigh the drawbacks.

5. Wrap-up and further reading

In this post we've explored secondary information in particular. Equally we've seen, it's non so different from other forms of data. What defines data as secondary data is how information technology is used rather than an inherent characteristic of the information themselves.

To learn more than about information analytics, check out this free, v-day introductory data analytics short course . You can also check out these manufactures to acquire more about the information analytics process: