What are the 4 best information collecting methods?
What are the 4 best information collecting methods? Any research is only as good as the data that drives it, so choosing the right technique of data collection can make all the difference. In this article, we will look at four different data collection techniques – observation, questionnaire, interview and focus group discussion – and evaluate their suitability under different circumstances. The 4 methods of collecting information are very important.
Data collection is a method by which companies collect and measure information from various sources to obtain a complete picture, answer important questions, evaluate their results, and anticipate future trends. This process seeks to gather and measure information from different sources to obtain a complete and accurate visualization about a topic, area or situation of interest. In other words: evaluate results for better decision making.
Data is one of the most precious resources in today’s business landscape. The more information you have about your customers, the better you can understand their interests, wants and needs. This enhanced understanding helps you meet and exceed your customers’ expectations and allows you to create messaging and products that appeal to them.
But here’s the question — how do you collect this data? This is where a data management platform (DMP) and a customer data platform (CDP) come into play.
While both CDPs and DMPs contribute to data collection, they have different data collection mechanisms and objectives. A CDP collects individual-level customer data for a comprehensive understanding, while a DMP collects aggregated data for audience segmentation and targeted advertising.
In some cases, organizations may choose to integrate both a CDP and a DMP to leverage the strengths of each platform and create more effective marketing strategies. By leveraging these techniques, you can gain deeper insights into your customers and unlock opportunities for growth.
Below, we explore the various ways to collect data using your DMP, the uses of data collection and the most common methods of data collection. So, whether you’re a seasoned marketer or just starting out, get ready to broaden your horizons and take your data-driven initiatives to new heights.
Research Methods
Data collection can be carried out through 4 research methods:
- Analytical method . Review each data in depth and in an orderly manner; goes from the general to the particular to obtain conclusions.
- synthetic method . Analyzes and summarizes information; Through logical reasoning he arrives at new knowledge.
- Deductive method . Starting from general knowledge to reach singular knowledge.
- Inductive method . From the analysis of particular data, he reaches general conclusions.
What is data collection for?
- It allows you to analyze quantitative or qualitative data in a simple way to understand the context in which the object of study develops.
- The company can store and classify the data according to the characteristics of a specific audience, so that it can later carry out marketing efforts aimed especially at it (which translate into sales).
- Helps identify business opportunities.
- Shows in which processes there is an opportunity for optimization to prevent friction in the buyer’s journey.
- It provides data for businesses to better understand the behaviors of their customers and leads by collecting information about the sites they visit, the posts they interact with, and the actions they complete.
What are the 4 methods of collecting information?
Primary Data Collection Definition
When it comes to data collection methods, understanding the concept of primary data is essential. So, what exactly is primary data collection?
The term “primary data” refers to data you collect yourself rather than data you gather after another party initially recorded it. Primary data is information obtained directly from the source. You will be the first party to use this exact set of data. As the first party to utilize this specific set of data, you have full control over its collection and use.
When it comes to data businesses collect about their customers, primary data is also typically first-party data. First-party data is the information you gather directly from your audience. It could include data you gathered from online properties, data in your customer relationship management system or non-online data you collect from your customers through surveys and various other sources.
Because first-party data comes directly from your audience, you can have high confidence in its accuracy, as well as its relevance to your business. This data holds great value as it provides insights into the behaviors, preferences and characteristics of your customers.
While first-party data forms the foundation of your data set, it’s important to recognize that different types of data have their own unique advantages and use cases. In some instances, supplementing your first-party data with second-party or third-party data can enhance the scale of your audience or help you reach new target segments.
However, in this article, our focus will be on primary data collection. Why? Because primary data is the data you gather yourself, and it requires a well-defined strategy to ensure its effectiveness and accuracy.
To leverage primary data effectively, you need to consider various methods of data collection. By carefully planning and executing your primary data collection efforts, you can obtain valuable insights that directly align with your marketing objectives.
Secondary Data Collection Definition
Now that we have a better understanding of primary data collection, we can dive deeper into secondary data collection.
Second-party data is the first-party data of another company. You can purchase second-party data directly from the organization that collected it or buy it in a private marketplace. Second-party data has many of the same positive attributes as first-party data. It comes directly from the source, so you can be confident in its accuracy, but it also gives you insights you couldn’t get with your first-party data.
Additionally, second-party data provides you with insights you may not have been able to obtain solely from your first-party data. It offers a fresh perspective and expands your understanding of your target audience.
In comparison, third-party data is information a company has pulled together from numerous sources and consolidated into a comprehensive data set. You can buy and sell this kind of data on a data exchange, and it typically contains a large number of data points.
Third-party data offers much more scale than any other type of data, which is its primary benefit. This expanded scale opens up opportunities to explore new audiences, uncover market trends and identify patterns that can shape your marketing strategies.
When considering your data collection methods, it’s crucial to understand the differences between first-party data, second-party and third-party data. Each type of data brings its own strengths and benefits to the table, depending on your specific goals and requirements.
Data collection techniques
- Observation
- Questionnaires or surveys
- Focus group
- Interviews
- Contact forms
- Open sources
- Social media monitoring
- Website analysis
- Conversation history
1. Observation
If what you want is to know the behavior of your object of study directly, making an observation is one of the best techniques. It is a discreet and simple way to inspect data without relying on a middleman. This method is characterized by being non-intrusive and requires evaluating the behavior of the object of study for a continuous time, without intervening.
To execute it properly, you can record your field observations in notes, recordings or on some online or offline platform (preferably from a mobile device, from where you can easily access the information collected during the observation).
Although this technique is one of the most used, its superficiality usually leaves out some important data to obtain a complete picture in your study. We recommend that you record your information in an orderly manner and try to avoid personal biases or prejudices. This will be of great help when evaluating your results, as you will have clear data that will allow you to make better decisions.
2. Questionnaires or surveys
It consists of obtaining data directly from the study subjects in order to obtain their opinions or suggestions. To achieve the desired results with this technique, it is important to be clear about the objectives of your research.
Questionnaires or surveys provide broader information; however, you must apply them carefully. To do this you have to define what type of questionnaire is most efficient for your purposes. Some of the most popular are:
- Open Questionnaire : Used to gain insight into people’s perspective on a specific topic, analyze their opinions, and obtain more detailed information.
- Closed questionnaire : used to obtain a large amount of information, but people’s responses are limited. They may contain multiple-choice questions or questions that are easily answered with a “yes/no” or “true/false.”
This is one of the most economical and flexible types of data collection, since you can apply it through different channels, such as email, social networks, telephone or face to face, thus obtaining honest information that gives you more results. precise.
Note : Keep in mind that one of the main obstacles in applying surveys or questionnaires is the low response rate, so you should opt for an attractive and simple document. It uses simple language and gives clear instructions when applying it.
3. Focus group
This qualitative method consists of a meeting in which a group of people give their opinion on a specific topic. One of the qualities of this tool is the possibility of obtaining various perspectives on the same topic to reach the most appropriate solution.
If you can create the right environment, you will get honest opinions from your participants and observe reactions and attitudes that cannot be analyzed with another data collection plan.
To do a focus group properly you need a moderator who is an expert on the topic. Like observation, order is essential for evaluating your results. Remember that a debate can always get out of control if it is not carried out in an organized manner.
4. Interviews
This method consists of collecting information by asking questions. Through interpersonal communication, the sender obtains verbal responses from the receiver on a specific topic or problem.
The interview can be carried out in person or by telephone and requires an interviewer and an informant. To conduct an interview effectively, consider what information you want to obtain from the subject under investigation in order to guide the conversation to the topics you need to cover.
Gather enough information on the topic and prepare your interview in advance, listen carefully and generate an atmosphere of cordiality. Remember to approach the interviewee gradually and ask easy-to-understand questions, as you will have the opportunity to capture reactions, gestures and clarify the information in the moment.
There are other very important methods such as:
. Contact forms
A form on a website is a great source of data that users contribute voluntarily. It helps your brand to know their name, email, location, among other relevant data; They also help you segment the market so that you generate better conversion results.
You can obtain this data by offering a special discount, subscribing to your newsletter, ebooks, infographics, videos, tutorials, and more content that may be of interest to your site visitors. If you don’t have one yet, try our free online form builder .
. Open sources
To understand your business even more, turn to open sources to obtain valuable data. Find free and public information on government pages, universities, independent institutions, non-profit organizations, large companies, data analysis platforms, agencies, specialized magazines, among others.
. Social media monitoring
Through social networks it is possible that they collect data about the sector in which your brand operates, your main competitors and, above all, your potential clients. This way you can also communicate with them and get to know your audience more closely.
The best of all is that most of these types of platforms already have integrated performance analysis tools for your profile and your marketing campaigns, for free; including Facebook, Instagram, Twitter and YouTube.
. Website Analysis
Another technique to collect really useful data from visitors to your website is to implement a tracking pixel or cookies. This way you will easily know the user’s location, their behavior patterns within the page, which sections they interact with the most, the keywords they used in the search engine to get there, if they came from another website, among others.
This will also help you improve the user experience on your website. One of the most popular tools to perform this task is Google Analytics. It is worth mentioning that the handling of this type of data is legally regulated in each country differently, so you must comply with the guidelines that apply to you.
. Conversation history
Saving the conversations generated in the chat on your website, on social networks, chatbots, emails, even calls and video calls with customers is also an efficient data collection technique. This will give you excellent feedback to optimize your products or services, improve customer service, accelerate the sales cycle, deliver products on time, resolve complaints, etc.
It is very important to ensure that data collection methods are accurate ( reliable ). This means that a method measures the same thing every time it is used. There are many things that can affect the accuracy (reliability) of an instrument or method for collecting information. Some of these things are the form of the instrument (verbal or written), the environment in which it is administered, how it is administered by the team, the difference in participants between one group and another, the time and time in which the instrument is administered. instrument.
The researcher can also affect accuracy (reliability) by flattering or belittling the participant. The principal investigator is responsible for providing appropriate training and doing “checks” on how instruments are being administered or methods applied to ensure that the research study is being conducted accurately.
Research studies are often criticized because they do not use precise methods to gather information. Precision (reliability) helps to do research with greater value, since there is greater confidence that the findings are real.
Example of Precision (Reliability)
A study is designed to see if an antihypertensive drug is effective in lowering blood pressure. Study participants’ blood pressure is measured to see if it is reduced due to the medication. The research design requires that blood pressure be taken when the person is in a quiet place and a digital baumanometer is used.
It is also important to ensure that data collection methods are accurate (valid). Accuracy (validity) refers to whether an instrument or method truly measures what one believes it is measuring. Researchers want exact or valid procedures for a study so that the results of the study are useful and meaningful.
There are many elements that can affect the accuracy (validity) of an instrument or method. Some elements are:
- cultural adaptation,
- the theoretical bases used to develop an instrument or method,
- the appropriateness of the method or form of testing for the capabilities of the participant.
Sometimes, to show that study measurements are accurate, researchers collect different types of data to measure the same thing. They then verify whether all methods or instruments offer the same or similar conclusions. If they do, the researcher can be confident that the findings do in fact represent what they are trying to study.
In addition to lack of precision (reliability), research studies are often criticized due to the use of inaccurate methods to gather information. Measuring accuracy (validity) is essential to ensure the quality and integrity of research findings.
Definition: Accuracy refers to whether the instrument or method actually measures what it is expected to be measured.
Example of Accuracy in Research
In research involving a weight loss program, the researcher weighs the participants to determine if the program is effective. To weigh accurately the scale must be working properly. To verify the accuracy of the scale, a 10 kilo weight is placed on the digital scale three times to ensure that each time the scale reads 10 kilos.
In another study, researchers want to determine whether participants have reduced the number of cigarettes they smoke. For this, the researcher asks the participant a series of questions as a survey about smoking habits in the last two weeks. To verify the accuracy of the answers, the researcher does a saliva analysis to measure certain chemicals that are increased by smoking.
When we measure something or collect information, there are many reasons for our findings to be incorrect. The most obvious reason is that we might have made a mistake when writing something. This type of lack is what we normally know as an error. However, there are other types of errors that we might not see unless we know to look for them. These errors are not failures in the sense that we have done something wrong and may reduce the credibility or accuracy of what we do, but they are errors about things over which we have no control.
An error is considered random if the value of what is measured increases sometimes or decreases in other cases. A very simple example is our blood pressure. It is normal that blood pressure can be different in each measurement even if someone is healthy. If your blood pressure is taken several times, some times it will be higher and other times it will be lower.
This random error is expected due to variation in normal body processes and the way the measuring device works. If the error is truly random and we take enough measurements, we can get a good estimate of what we are measuring. However, if a random error is large then the measurements will be unpredictable, inconsistent and will not be representative of the true value of what we are measuring.
Example of Systematic Error
Systematic Error
In a study about weight loss, researchers determined at the end of the study that the scale they were using to measure participants’ weight was not accurate. The scale added 10 pounds to the person’s actual weight each time the scale was used. Because the researcher realized that the scale consistently added 10 pounds to each participant’s weight, adjustments were made for this issue when analyzing the results.
Random Error
In a study on weight loss, a scale was used that added or subtracted a few grams each time it was used. The researcher was unaware that the scale did not measure the exact weight of the participant. Therefore, the researcher was unable to adjust for this issue when analyzing the results. This causes the study results to include some errors.