AIMultiple ResearchAIMultiple Research

Quick Guide to Qualitative Data Collection in 2024

The amount of data that businesses gather and use is increasing1 every day. While some rely mostly on numbers and figures, others rely data on customer experience, behavior analysis, etc. Quantitative and qualitative data are like two sides of a paddle that are equally important2 to steer the business. However, qualitative data collection can sometimes be more difficult than quantitative data, especially for large organizations and brands. 

Keep reading if you plan to start collecting and using qualitative data or improving your existing qualitative data collection process. In this article, we explain what qualitative data collection is, why it’s important for your business and what are the methods of collecting it.

What is qualitative data?

We have explained the difference between qualitative and quantitative data before. In a nutshell, qualitative data is non-numerical data, while quantitative data is numerical. Qualitative data is descriptive and is expressed in terms of feelings rather than numerical values such as amounts, etc. Businesses collect qualitative data to answer the whys and hows of their processes. Such data can not be counted or measured. 

Why is it important for your business?

In the current environment, businesses must scratch the surface and look beyond the things that have worked for them in the past. As customers demand personalized services, business managers need to dive deeper into their world to know them better, and collecting qualitative data is a way of achieving that.


  • Achieving a wider view: Collecting qualitative data can give a wider view of customer needs by covering the gray area questions that can’t be answered through a normal survey or other quantitative methods. For instance, if a customer wants to communicate a specific issue about a product, doing it through quantitative questions can take time and effort.
  • Better understanding attitude: Qualitative data collection can help understand customers’ perspectives from a specific target market and how it changes. For instance, data regarding people’s attitudes towards brands using recycled fabric for clothing production. Additionally, gathering qualitative data can help HR personnel understand employees’ attitudes toward their jobs and help improve their overall employee experience.
  • More flexibility: Qualitative data collection is much more flexible than quantitative. If the answers are not helpful, the data collector can change the setting or modify the questions to adjust the outcome. This is not possible in quantitative data collection since, no matter the situation, the answer to a numerical question will remain more or less the same.


  • More time-consuming and costly: Qualitative data is more time-consuming since it requires answers in paragraphs rather than numerical values. For instance, a quantitative survey will usually have yes-no, true-false questions or questions that need you to add value. On the other hand, conducting a qualitative survey will take much more time since the participant will have to explain the answer in multiple sentences.
  • Complex analysis: Quantitative data can be managed and analyzed much faster than qualitative data. You can use tools such as SPSS to import and analyze large quantities of data in significantly less time. However, analyzing qualitative data takes a lot more time since it requires hours of reading and transcription.
  • Sample bias: Collecting qualitative data can also add bias to the concoction. For instance, while conducting an internal survey in a company with 5000 employees. Not all of them can be interviewed individually since that would take an eternity. In such cases, the sample of employees selected for the survey can provide biased or incomplete information which is not representative of the workforce. 

What are qualitative data collection methods, and how to choose the right one?

This section identifies some popular qualitative data collection methods businesses can use to fulfill their data needs.

1. In-house interviews, surveys, or focus groups

This method involves dedicating a team from within the organization which conducts interviews or surveys from the participants or organizes focus groups. This method can be used to collect qualitative data from a sample of the total population. The team recruits participants who are the representatives of the total population and asks them questions that require descriptive answers. The data collection team can also observe participants’ behavior as they interact with the products/services.

1.1. Recommendations

This method is suitable for collecting small/medium quantities of qualitative data. If a company caters to thousands of customers, they can not interview each customer to get their detailed descriptive views on launching a new product, for instance. However, if the brand does not wish to disclose the details of the product to the public and needs to gather the views from a small/medium-sized sample, in-house qualitative data collection would be suitable.

2. Crowdsourcing

More3 companies leverage crowdsourcing to fulfill various tasks as they realize the benefits. Crowdsourcing qualitative data means fragmenting the data collection tasks to a large crowd through an online platform. Companies can set up their own crowdsourcing platform or outsource the process to a third-party service. This method is suitable for collecting large quantities of qualitative data in a limited amount of time. Crowdsourcing can also be good for brands with a multilingual customer base and international operations. 

2.1. Recommendations

Crowdsourcing is a suitable method for companies with a large and international customer base. For instance, the crowd can gather customer insights from other parts of the world regarding your products and share their analysis with you in large quantities.

3. Leverage conversational commerce

Conversational commerce allows the collection of both qualitative and quantitative data by enabling communication directly with the customer. This method is useful for collecting qualitative data regarding customer feedback. This can be executed by using messaging services like WhatsApp, WeChat, Messenger, etc., to communicate with the customers and gather their data. Since billions4 of customers are using such platforms, it can be beneficial to use them to collect qualitative data from the source.

3.1. Recommendations

This method can especially be beneficial for gathering customer feedback. For instance, a customer can use a messaging platform to provide feedback regarding a service the company provides (See the image below). You can check out this article to learn more about the conversational commerce landscape.

4. Automated qualitative data collection

Data collection automation can also be applied to qualitative data. With solutions such as chatbots, sentiment analysis, or NLP, companies can automate the process of gathering qualitative data, such as customer feedback. For instance, a brand can leverage automated sentiment analysis tools to gather data regarding the customer’s opinions, thoughts, and impressions about a product or service.

4.1. Recommendations

This method is suitable for companies with a large customer base. We recommend using a messaging service that combines the previously mentioned solutions with a human-in-the-loop approach to compile qualitative data from customers. The reason for this is that automated solutions such as chatbots and sentiment analysis still are not advanced enough to operate autonomously. Therefore, if the data is detailed and involves complex conversations, then a human is required to step in.

For more in-depth knowledge on data collection, feel free to download our whitepaper:

Get Data Collection Whitepaper

Further reading

If you need help finding a vendor, or have any questions, feel free to contact us:

Find the Right Vendors


  1. Jackson, Jarret. (Jul 15, 2020). “Businesses Have More Data Than Ever Before, But Do They Measure What They Manage?”. Forbes. Retrieved: Dec 02, 2022.
  2. Christopher, Eric ‘ERock’. (Dec 24, 2020). Why Both Quantitative and Qualitative Data Are Vital for Results-Driven Businesses. Entrepreneur. Retrieved: Dec 02, 2022.
  3. The three billion Enterprise crowdsourcing and the growing fragmentation of work”. Deloitte. Retrieved: Dec 02, 2022.
  4. Dixon, S. (Jul 27, 2022). “Most popular global mobile messenger apps as of January 2022, based on number of monthly active users”. Statista. Retrieved: Dec 02, 2022.
Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
Follow on

Shehmir Javaid
Shehmir Javaid is an industry analyst in AIMultiple. He has a background in logistics and supply chain technology research. He completed his MSc in logistics and operations management and Bachelor's in international business administration From Cardiff University UK.

Next to Read


Your email address will not be published. All fields are required.