数据收集方法：8 种类型及示例
Posted: Wed Dec 04, 2024 4:01 am
在商业领域，数据就是一切。数据用确定性取代怀疑，用事实取代猜测。做出基于数据的商业决策的第一步是收集优质数据。
数据收集，简单来说就是如何收集数据。只有拥有有效的数据，才能做出有效的决策。
两种常见的数据收集方法是：
- 原始（第一手）数据收集。
- 二手（现有）数据收集。
您还可以将数据分类为定量（用数字表示）和定性（主观经验数据） - 稍后会详细介绍！
在此博客中，我们将帮助您：
- 选择正确的收集流程。
- 了解主要数据收集与次要数据收集。
- 了解五种主要收集方法的优缺点。
- 了解三种次要数据收集方法的优缺点。
- 探索有效数据收集的最佳实践。
-数据跟踪，这对于企业在当今竞争激烈的环境中蓬勃发 巴拉圭电子邮件列表 230751 联系人线索 展至关重要。通过准确监控和分析数据，公司可以获得有关其运营的宝贵见解，识别趋势并做出推动增长的明智决策
继续阅读以获取一些有用的见解。
为什么公司需要有效的数据收集
公司根据数据做出各种决策。
例如，了解买家行为、预测产品性能和规划营销活动。世界上许多（或许所有）顶级公司都是利用数据重要性的案例研究。
公司规模越大，仅凭经验和直觉做出决策就越困难。组织只能依靠广泛而准确的数据做出有效决策。
选择最有效的方法
有 8 种常见的数据收集方法，分为两类。
主要和次要数据收集方法有不同的用途。您选择的方法将取决于您想要的结果。
让我们深入研究不同的方法。
主要数据
您可以使用此数据类型来解决问题或研究与您的业务相关的内容。它可以包括：
- 您的销售和营销策略有多成功。
- 您的客户行为如何。
- 您的运营表现如何。
原始数据可以是定量的（可使用数字衡量），也可以是定性的（基于人类观点或客户意见的主观数据）。
次要数据
此数据类型包括对您的业务有用的现有数据，例如有关您的市场、目标人群和风险环境的数据。
次要数据可以包括报告和出版物。它通常提供有关外部环境的启发性信息。与原始数据一样，次要数据可以是定量的，也可以是定性的。
简而言之，如果你想了解你的业务，就收集原始数据。如果你想了解业务之外的事情，就收集次要数据。
(来源：MarketResearch.com )
了解你的目标
在认真开始收集过程之前，您需要清楚了解要解决的问题和想要产生的结果。
尝试预测哪些类型的数据将帮助您做出明智的决定。例如，营销团队应该了解这10 个 B2B 定性营销指标和 KPI。业务的每个方面都有类似的指标需要跟踪和优化 - 确保您了解自己的指标！
如果您的目标是了解一些最能通过统计数据表达的内容，那么定量数据收集方法可能是您的首选方法。如果您想了解人们对您业务的某个方面的反应，那么定性数据收集方法更合适。
定量数据与定性数据
那么我们之前谈到的这些收集方法呢？定量方法和定性方法有什么区别？
定量数据代表可以用数字衡量的事物。当人们想到数据时，他们通常会想到定量数据。数据驱动型公司旨在用数字来描述其多样化的运营。
而定性数据则代表主观体验。它通过访谈、焦点小组和观察收集，并探索感受、行为和动机。定性方法对于预测消费者对新产品或设计变化的反应特别有用。
但要小心！不要陷入寻找支持你假设的数据的陷阱。这被称为确认偏差，它会把你引向错误的道路。你需要的是能够提供真实情况的数据，而不是仅仅支持你先入之见的数据。
还值得考虑的是，这是否是一次性活动，或者您的数据收集方法是否将成为长期监测计划的一部分。长期监测对于定性数据来说更耗费资源，因为它是一个手动过程。
现在，让我们了解不同的收集技术及其优缺点。
(Source: CareerFoundry)
Primary Data Collection Methods
Primary data collection is the gathering of data firsthand. Some common types include:
1. Surveys and Questionnaires
Advantages:
Online surveys and questionnaires let you reach a large number of people relatively easily. With large sample sizes, outliers are less prominent, making data more accurate and better for your analysis process.
Individual surveys are cost-effective thanks to minimal marginal costs. That means sending 1,000 surveys might not cost much more than sending one.
They’re also well-suited to being repeated at regular intervals, such as annually, biennially or another increment of time. By repeating surveys, you can build up a picture of changing circumstances.
Disadvantages:
Surveys and questionnaires have downsides, including low response rates and inconsistencies in how respondents interpret questions. Answers can change based on how someone is feeling that day, making comparisons and analysis more difficult.
2. Interviews
Advantages:
One-on-one interviews are a way to obtain in-depth insights from a select group of people. The interview method has many advantages over surveys, such as greater depth of answers. They can also provide data that other methods can’t, such as seeing how someone actually interacts with a product.
Disadvantages:
In-person interviews are time-consuming and expensive. And while they allow for depth of answers, they don’t provide much breadth. This limits use cases.
3. Observations
Advantages:
Observation is a data collection method where you watch testers interact with your website or product. It offers a firsthand and genuine view of how people use your product.
You can record the sessions using video and data capture. This guarantees data accuracy. You can also ask your testers to narrate their actions, which provides another type of valuable insight.
Disadvantages:
Observation data collection presents a technical challenge.
While observation sessions can be carried out concurrently by one of two team members, like interviews, they’re hard to scale. And how a tester approaches a product can depend on their feelings on a particular day.
4. Focus Groups
Advantages:
Focus groups offer the chance to speak to multiple people at once. A group setting also allows people to share and build on each other’s perspectives, which can produce more thought-out answers. A diverse group of people provide a broader perspective.
Disadvantages:
Focus groups have a few disadvantages. They can be affected by dominant personalities taking charge of the conversation or groupthink. Groupthink happens when a group’s desire for harmony or conformity leads to irrational thinking.
Focus groups are also harder to coordinate, requiring multiple availabilities for any time slot. Lastly, focus groups aren’t suited to the quantitative data collection method.
5. Experiments
Advantages:
Conducting experiments allows you to collect cause-and-effect data. Tests such as an A/B test isolate variables and tell you exactly what impact each change can have.
A/B testing is a core practice for digital businesses. Many common web and marketing tools have native A/B testing, making it relatively easy to do.
Disadvantages:
Experiments are intensive activities that only answer one question. A business will need to conduct many experiments and collect a lot of data to achieve the same results as other methods.
Secondary Data Collection Methods
Secondary data collection involves using existing data sets. It consists of third-party data research, financial statements, and census data.
Advantages:
Secondary data can be cheaper than first-party data collection. A lot of data is publicly available at no cost. Company financial filings, taxpayer-funded data and reports from consultancy firms are often free.
Secondary data is also immediately available; it’s often easily downloaded and well-formatted. It can form the basis for quick decision-making.
Disadvantages:
Some secondary data is expensive. Research companies charge a high price for data. You are also at the mercy of how often reports are published so relevant data might be several years old.
Let’s look at three common types of second-party data collection:
6. Online Sources
Online sources of second-party data include government reports and industry publications. Governments produce white papers, statistics and annual reports, which can all be used in data collection.
Industry reports and publications provide in-depth business data. The internet is full of reports on almost any aspect of any industry you can think of!
7. Public Databases
Open data sources, such as the datasets accessed via data.gov.uk, can hold an immense amount of valuable data.
These datasets can help you understand your market, find investment opportunities and learn about potential customers.
8. Internal Data
Internal data is another type of secondary data. It includes customer records and sales figures, among other things. It can be used to highlight a company’s capabilities and product success.
Secondary data often provides a solid foundation for decision-making.
(Source: Future Processing)
Best Practices for Data Collection
Here are some tips to get the highest-quality data from your data collection.
Craft Effective Surveys and Questionnaires
A good survey comes down to reaching the right people and writing a good series of questions.
The right people could mean a broad cross-section of society or a tighter focus on specific groups. Scale is vital due to low response rates.
Use open-ended questions to get more information out of your respondents.
A good tip is to test your questions on your internal staff. Then, you’ll know if the questions are producing good data.
Conducting Ethical and Unbiased Interviews
Avoiding bias in interviews means avoiding any language that will trigger emotions or narrow the answers the interviewee might give.
For example, if you say, “I hope you like it,” your interviewee might feel pressure to like it or feel annoyed at an expectation to like something. It also defines the question in terms of like or don’t like, when there could be a wide range of other thoughts one might have.
Ethical standards in interviews is a complex subject but you should abide by a few key tenets:
- Informed consent - Interviewees should fully understand what they’re agreeing to.
- Privacy and confidentiality - Interviewees’ participation, data and answers should be safeguarded and disposed of carefully.
- No pressure - Interviewees should not be coerced into saying or doing something they don’t want to.
Ensuring Accurate and Reliable Observations
If you’re observing interactions with a prototype or MVP, you must be happy that it has the features or design elements you need.
Equally, you must avoid having your tester get distracted by aspects of the product that aren’t part of the study.
Managing Focus Groups for Productive Discussions
The success of a focus group depends on the steady hand of a facilitator. The facilitator creates a comfortable environment, welcomes the guests, encourages introductions, and establishes ground rules.
The facilitator also guides the session through each point of discussion, keeping the conversation on track, defusing any tension should it arise, and making sure everyone has their say.
Designing Controlled and Relevant Experiments
You must approach your experiments with a scientific mindset. You need a hypothesis, a control group and a method.
Don’t be tempted to test too many things at once - in fact, you should just be testing one thing at a time. That’s the best way of uncovering major challenges and how to fix them.
Evaluating the Credibility of Secondary Data Sources
Poor data quality is rife! Evaluate a data source against these five considerations:
1. Reputation - is the source known for being reliable?
2. Author - what profile does the author have?
3. Methodology - does the source have a clear methodology?
4. Bias - is the source compromised by an agenda, such as commercial intent?
5. Currency - are the source’s conclusions likely to be inaccurate due to the passage of time?
None of these alone are sufficient to base an evaluation on. Score a source across each for a complete evaluation.
Key Takeaways
With data guiding decisions across every industry and corporate function, data collection methods are becoming ever more important.
To choose the right data collection method, you need to understand two concepts: primary and secondary data and quantitative and qualitative data. Data can be a combination of primary and secondary and quantitative and qualitative.
Hopefully, you’ve learnt from this blog what they mean, but let’s recap one final time:
- 原始数据是您收集的数据。
- 次要数据是其他人收集的现有数据。
- 定量数据是具有数值的数据。
- 定性数据是人提供的主观数据。
祝您的收藏之旅好运！
分享此文章
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关于作者
作者图片
Jeremy Moser，uSERP 首席执行官兼 Wordable 所有者
Jeremy 是 uSERP 的联合创始人兼首席执行官，uSERP 是一家拥有 50 多名员工、以绩效为导向的 SEO 公司，帮助 Fivetran、Freshworks、ActiveCampaign、monday.com 等数百家高增长科技公司扩大盈利性客户增长。在最初的 3.5 年内，他带领公司实现了每月 50 万美元以上的经常性收入。他还拥有 Wordable 并担任其团队的顾问，Wordable 是一款 SaaS，被 Ahrefs、Kinsta、Stanford EDU 等品牌使用，每周可为他们节省数千美元。
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目录
数据收集方法：8 种类型及示例
为什么公司需要有效的数据收集
选择最有效的方法
主要数据收集方法
二次数据收集方法
数据收集的最佳实践
关键要点
阅读更多
LeadGen 应用横幅 1 - 中
数据收集，简单来说就是如何收集数据。只有拥有有效的数据，才能做出有效的决策。
两种常见的数据收集方法是：
- 原始（第一手）数据收集。
- 二手（现有）数据收集。
您还可以将数据分类为定量（用数字表示）和定性（主观经验数据） - 稍后会详细介绍！
在此博客中，我们将帮助您：
- 选择正确的收集流程。
- 了解主要数据收集与次要数据收集。
- 了解五种主要收集方法的优缺点。
- 了解三种次要数据收集方法的优缺点。
- 探索有效数据收集的最佳实践。
-数据跟踪，这对于企业在当今竞争激烈的环境中蓬勃发 巴拉圭电子邮件列表 230751 联系人线索 展至关重要。通过准确监控和分析数据，公司可以获得有关其运营的宝贵见解，识别趋势并做出推动增长的明智决策
继续阅读以获取一些有用的见解。
为什么公司需要有效的数据收集
公司根据数据做出各种决策。
例如，了解买家行为、预测产品性能和规划营销活动。世界上许多（或许所有）顶级公司都是利用数据重要性的案例研究。
公司规模越大，仅凭经验和直觉做出决策就越困难。组织只能依靠广泛而准确的数据做出有效决策。
选择最有效的方法
有 8 种常见的数据收集方法，分为两类。
主要和次要数据收集方法有不同的用途。您选择的方法将取决于您想要的结果。
让我们深入研究不同的方法。
主要数据
您可以使用此数据类型来解决问题或研究与您的业务相关的内容。它可以包括：
- 您的销售和营销策略有多成功。
- 您的客户行为如何。
- 您的运营表现如何。
原始数据可以是定量的（可使用数字衡量），也可以是定性的（基于人类观点或客户意见的主观数据）。
次要数据
此数据类型包括对您的业务有用的现有数据，例如有关您的市场、目标人群和风险环境的数据。
次要数据可以包括报告和出版物。它通常提供有关外部环境的启发性信息。与原始数据一样，次要数据可以是定量的，也可以是定性的。
简而言之，如果你想了解你的业务，就收集原始数据。如果你想了解业务之外的事情，就收集次要数据。
(来源：MarketResearch.com )
了解你的目标
在认真开始收集过程之前，您需要清楚了解要解决的问题和想要产生的结果。
尝试预测哪些类型的数据将帮助您做出明智的决定。例如，营销团队应该了解这10 个 B2B 定性营销指标和 KPI。业务的每个方面都有类似的指标需要跟踪和优化 - 确保您了解自己的指标！
如果您的目标是了解一些最能通过统计数据表达的内容，那么定量数据收集方法可能是您的首选方法。如果您想了解人们对您业务的某个方面的反应，那么定性数据收集方法更合适。
定量数据与定性数据
那么我们之前谈到的这些收集方法呢？定量方法和定性方法有什么区别？
定量数据代表可以用数字衡量的事物。当人们想到数据时，他们通常会想到定量数据。数据驱动型公司旨在用数字来描述其多样化的运营。
而定性数据则代表主观体验。它通过访谈、焦点小组和观察收集，并探索感受、行为和动机。定性方法对于预测消费者对新产品或设计变化的反应特别有用。
但要小心！不要陷入寻找支持你假设的数据的陷阱。这被称为确认偏差，它会把你引向错误的道路。你需要的是能够提供真实情况的数据，而不是仅仅支持你先入之见的数据。
还值得考虑的是，这是否是一次性活动，或者您的数据收集方法是否将成为长期监测计划的一部分。长期监测对于定性数据来说更耗费资源，因为它是一个手动过程。
现在，让我们了解不同的收集技术及其优缺点。
(Source: CareerFoundry)
Primary Data Collection Methods
Primary data collection is the gathering of data firsthand. Some common types include:
1. Surveys and Questionnaires
Advantages:
Online surveys and questionnaires let you reach a large number of people relatively easily. With large sample sizes, outliers are less prominent, making data more accurate and better for your analysis process.
Individual surveys are cost-effective thanks to minimal marginal costs. That means sending 1,000 surveys might not cost much more than sending one.
They’re also well-suited to being repeated at regular intervals, such as annually, biennially or another increment of time. By repeating surveys, you can build up a picture of changing circumstances.
Disadvantages:
Surveys and questionnaires have downsides, including low response rates and inconsistencies in how respondents interpret questions. Answers can change based on how someone is feeling that day, making comparisons and analysis more difficult.
2. Interviews
Advantages:
One-on-one interviews are a way to obtain in-depth insights from a select group of people. The interview method has many advantages over surveys, such as greater depth of answers. They can also provide data that other methods can’t, such as seeing how someone actually interacts with a product.
Disadvantages:
In-person interviews are time-consuming and expensive. And while they allow for depth of answers, they don’t provide much breadth. This limits use cases.
3. Observations
Advantages:
Observation is a data collection method where you watch testers interact with your website or product. It offers a firsthand and genuine view of how people use your product.
You can record the sessions using video and data capture. This guarantees data accuracy. You can also ask your testers to narrate their actions, which provides another type of valuable insight.
Disadvantages:
Observation data collection presents a technical challenge.
While observation sessions can be carried out concurrently by one of two team members, like interviews, they’re hard to scale. And how a tester approaches a product can depend on their feelings on a particular day.
4. Focus Groups
Advantages:
Focus groups offer the chance to speak to multiple people at once. A group setting also allows people to share and build on each other’s perspectives, which can produce more thought-out answers. A diverse group of people provide a broader perspective.
Disadvantages:
Focus groups have a few disadvantages. They can be affected by dominant personalities taking charge of the conversation or groupthink. Groupthink happens when a group’s desire for harmony or conformity leads to irrational thinking.
Focus groups are also harder to coordinate, requiring multiple availabilities for any time slot. Lastly, focus groups aren’t suited to the quantitative data collection method.
5. Experiments
Advantages:
Conducting experiments allows you to collect cause-and-effect data. Tests such as an A/B test isolate variables and tell you exactly what impact each change can have.
A/B testing is a core practice for digital businesses. Many common web and marketing tools have native A/B testing, making it relatively easy to do.
Disadvantages:
Experiments are intensive activities that only answer one question. A business will need to conduct many experiments and collect a lot of data to achieve the same results as other methods.
Secondary Data Collection Methods
Secondary data collection involves using existing data sets. It consists of third-party data research, financial statements, and census data.
Advantages:
Secondary data can be cheaper than first-party data collection. A lot of data is publicly available at no cost. Company financial filings, taxpayer-funded data and reports from consultancy firms are often free.
Secondary data is also immediately available; it’s often easily downloaded and well-formatted. It can form the basis for quick decision-making.
Disadvantages:
Some secondary data is expensive. Research companies charge a high price for data. You are also at the mercy of how often reports are published so relevant data might be several years old.
Let’s look at three common types of second-party data collection:
6. Online Sources
Online sources of second-party data include government reports and industry publications. Governments produce white papers, statistics and annual reports, which can all be used in data collection.
Industry reports and publications provide in-depth business data. The internet is full of reports on almost any aspect of any industry you can think of!
7. Public Databases
Open data sources, such as the datasets accessed via data.gov.uk, can hold an immense amount of valuable data.
These datasets can help you understand your market, find investment opportunities and learn about potential customers.
8. Internal Data
Internal data is another type of secondary data. It includes customer records and sales figures, among other things. It can be used to highlight a company’s capabilities and product success.
Secondary data often provides a solid foundation for decision-making.
(Source: Future Processing)
Best Practices for Data Collection
Here are some tips to get the highest-quality data from your data collection.
Craft Effective Surveys and Questionnaires
A good survey comes down to reaching the right people and writing a good series of questions.
The right people could mean a broad cross-section of society or a tighter focus on specific groups. Scale is vital due to low response rates.
Use open-ended questions to get more information out of your respondents.
A good tip is to test your questions on your internal staff. Then, you’ll know if the questions are producing good data.
Conducting Ethical and Unbiased Interviews
Avoiding bias in interviews means avoiding any language that will trigger emotions or narrow the answers the interviewee might give.
For example, if you say, “I hope you like it,” your interviewee might feel pressure to like it or feel annoyed at an expectation to like something. It also defines the question in terms of like or don’t like, when there could be a wide range of other thoughts one might have.
Ethical standards in interviews is a complex subject but you should abide by a few key tenets:
- Informed consent - Interviewees should fully understand what they’re agreeing to.
- Privacy and confidentiality - Interviewees’ participation, data and answers should be safeguarded and disposed of carefully.
- No pressure - Interviewees should not be coerced into saying or doing something they don’t want to.
Ensuring Accurate and Reliable Observations
If you’re observing interactions with a prototype or MVP, you must be happy that it has the features or design elements you need.
Equally, you must avoid having your tester get distracted by aspects of the product that aren’t part of the study.
Managing Focus Groups for Productive Discussions
The success of a focus group depends on the steady hand of a facilitator. The facilitator creates a comfortable environment, welcomes the guests, encourages introductions, and establishes ground rules.
The facilitator also guides the session through each point of discussion, keeping the conversation on track, defusing any tension should it arise, and making sure everyone has their say.
Designing Controlled and Relevant Experiments
You must approach your experiments with a scientific mindset. You need a hypothesis, a control group and a method.
Don’t be tempted to test too many things at once - in fact, you should just be testing one thing at a time. That’s the best way of uncovering major challenges and how to fix them.
Evaluating the Credibility of Secondary Data Sources
Poor data quality is rife! Evaluate a data source against these five considerations:
1. Reputation - is the source known for being reliable?
2. Author - what profile does the author have?
3. Methodology - does the source have a clear methodology?
4. Bias - is the source compromised by an agenda, such as commercial intent?
5. Currency - are the source’s conclusions likely to be inaccurate due to the passage of time?
None of these alone are sufficient to base an evaluation on. Score a source across each for a complete evaluation.
Key Takeaways
With data guiding decisions across every industry and corporate function, data collection methods are becoming ever more important.
To choose the right data collection method, you need to understand two concepts: primary and secondary data and quantitative and qualitative data. Data can be a combination of primary and secondary and quantitative and qualitative.
Hopefully, you’ve learnt from this blog what they mean, but let’s recap one final time:
- 原始数据是您收集的数据。
- 次要数据是其他人收集的现有数据。
- 定量数据是具有数值的数据。
- 定性数据是人提供的主观数据。
祝您的收藏之旅好运！
分享此文章
Facebook 叽叽喳喳 LinkedIn
关于作者
作者图片
Jeremy Moser，uSERP 首席执行官兼 Wordable 所有者
Jeremy 是 uSERP 的联合创始人兼首席执行官，uSERP 是一家拥有 50 多名员工、以绩效为导向的 SEO 公司，帮助 Fivetran、Freshworks、ActiveCampaign、monday.com 等数百家高增长科技公司扩大盈利性客户增长。在最初的 3.5 年内，他带领公司实现了每月 50 万美元以上的经常性收入。他还拥有 Wordable 并担任其团队的顾问，Wordable 是一款 SaaS，被 Ahrefs、Kinsta、Stanford EDU 等品牌使用，每周可为他们节省数千美元。
领英 叽叽喳喳
目录
数据收集方法：8 种类型及示例
为什么公司需要有效的数据收集
选择最有效的方法
主要数据收集方法
二次数据收集方法
数据收集的最佳实践
关键要点
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LeadGen 应用横幅 1 - 中