Understanding Data Transcription: Unveiling the Power of Qualitative Data Analysis 

data transcription

Research projects heavily depend on data, but often, the initial data isn’t readily understandable numbers. Qualitative data, essential for advancing research, is frequently sourced from video and audio, necessitating data transcription.

Traditionally, data transcription in research involved the laborious conversion of different media into readable formats, often relying on human transcribers. However, automation has revolutionized this process.

In this article, we address crucial questions, such as “What’s the purpose of data transcription?” and “How can I transcribe qualitative data for my research project?” providing valuable insights and guidance.

What is Data Transcription?

Transcription for data analysis is primarily utilized in qualitative research. Qualitative data, as defined by Macalester College, encompasses the characteristics or qualities of a subject under study. Researchers gather this type of data through methods such as observation, interviews with participants, and administering questionnaires. Transcribing these interactions and observations allows for a thorough analysis of the collected qualitative data.

Unlike quantitative data, you need a way to process your results and convert your subject matter into something meaningful for your research project. But you must begin the transcription process before analyzing audio and video.

Some examples of research material that must be transcribed before it can be reviewed include:

  • Subject interviews
  • Focus groups
  • Court hearings
  • Patient consultations
  • Political speeches
  • Podcasts

The point of qualitative research is to explore characteristics and qualities that cannot be measured by numbers alone. Transcriptions help to provide precise language data to analyze. With an accurate transcription, it can influence your analysis and point you in the right direction.

What’s the Purpose of Data Transcription?

Today, 463 ZB of data will be generated daily by 2025. In other words, the value of big data is what keeps society running. But while big data is often presented in numbers, much of the data generated today comes through transcription.

So, what is the main purpose of data transcription in research?

Transcribed data enables researchers to draw vital conclusions and turn subjective dialogs into critical insights. In practice, you can:

  • Place qualitative data into a text-based format.
  • Make data easy to analyze.
  • Free up your time to focus on your observations.
  • Make patterns easier to uncover.
  • Immerse yourself in the data you collect.

Other benefits of transcription include enhancing the shareability of studies, making data simpler to maintain, and informing future studies. However, transcription isn’t a standardized function. Two different types of transcription exist, with various use cases for each.

Verbatim Transcription

The first type of transcription for data is verbatim transcription. This transcription type involves recording every part of a dialog with no additional editing. Other than a person’s words, this transcription will also include the following:

  • Grammatical errors
  • Pauses
  • Non-verbal communication

Recording a verbatim transcription in research is preferred for subjective qualitative research because of its 100% accuracy rate in recording the speaker’s intention. In other words, readability takes a backseat with this type of transcription.

Situations when researchers may opt for a verbatim transcription include:

  • Group discussions
  • Focus groups
  • Interviews
  • Medical consultations
  • Court narrative transcript documents

The value of these types of transcripts should not be underestimated in research circles. After all, studies conclude that up to 93% of all communication is non-verbal. So, including everything within your data transcription analysis can tell you more than just the words people say.

Intelligent Verbatim Transcription

The second type of transcription you can choose is intelligent verbatim. Also known as a clean or edited transcription, these transcriptions omit repeated words, grammatical errors, and non-verbal communication.

Researchers using these transcriptions concentrate on what the speaker is saying rather than how they communicate. These are among the most common transcriptions, but the risk of these transcriptions is that they can unintentionally eliminate the speaker’s true meaning from their sentences.

So, when are these transcripts useful?

These transcripts are designed for researchers who need to skim through texts quickly. Depending on your current research project, intelligent transcriptions can have far more practical applications than verbatim transcriptions.

Some of the scenarios where researchers may use a clean transcription include:

  • General business purposes
  • Financial reports
  • Patient records
  • Publicly available transcripts
  • Lectures
  • Speeches

Ideally, these transcriptions will be deployed when performing objective qualitative and quantitative research.

How to Transcribe Qualitative Data

Transcribing data for qualitative research is relatively straightforward because only two options exist for creating research transcriptions.

The first is employing a professional human transcriber, ensuring accuracy and attention to detail. Alternatively, you can leverage automated AI-powered platforms such as Sonix AI, offering convenience and speed in transcribing your audio and video files.

Let’s explore the process of utilizing both for research transcription.

Human Transcription Services

So, what is a data transcriber?

A data transcriber specializes in creating 100% accurate transcriptions of your content. They will perform multiple passes to ensure nothing is missed on the final transcription.

Depending on the length of your content, the transcription process could take a few hours or a few days. On average, a person will spend four to five hours transcribing a single hour of audio. Trained professionals will usually take two hours to transcribe one hour of audio.

Some research companies may even retain multiple in-house data transcribers to manage larger projects.


  • Accuracy – Human transcribers can achieve an accuracy rate of 99-100%, depending on their proficiency.
  • Fast Turnaround – Professional transcribers are highly proficient because they often use specialized tools to reduce errors and increase efficiency.
  • Compliance Standards – Your transcriber likely understands the compliance standards within your industry without any prompting.


  • Expensive – Using a human transcriber means spending thousands of dollars annually. Today’s average transcription rates range from $0.50 to $2.00 per audio minute.
  • Time-Consuming – Even the fastest transcriber will still take many hours to finish a larger project.
  • Consistency – No two transcribers are the same. Performances can vary based on the day, making achieving consistency a problem for a researcher.

Automated Transcription

The U.S. transcription market reached $25.98 billion in 2022, with much of the industry’s growth rate powered by automated platforms that take the hassle and expense out of transcription.

While automated tools have existed for many years, it’s only recently that technology has advanced enough to match and surpass the accuracy and efficiency of professional human transcribers.

Indeed, the best human transcriber can still produce a more accurate transcription than a computer, but the difference is around 2%. With some light editing, you can create the ideal research transcription in a fraction of the time of a human.

And the technology is only getting better.


  • Low-Cost Solution – Automated transcription services are always cheaper than human transcribers. Audio minutes can be as low as $0.15 per minute, with the cost coming down further as industry competition increases.
  • Highly Accurate – AI-powered transcription platforms have achieved remarkable accuracy levels. Sonix, for instance, boasts an impressive average accuracy rate of 97%, ensuring reliable and precise transcriptions.
  • On-Demand – Forget about regular working hours or the schedules of freelancers. Machine-powered transcription is available 24/7 for any project.
  • Functionality – Transcription platforms can do much more than a human transcriber at no additional charge. For example, Sonix offers translation services as part of the same package.


  • Editing – Even with advanced technology, cleaning up transcriptions may require additional time and effort, which can be challenging when managing various research-related tasks simultaneously.
  • Configuration – Prepare to configure your chosen platform to create your desired transcription. For beginners, this can seem confusing.

Data Transcription: FAQs

How is data transcription done?

Transcribing data depends on the method chosen. If you decide to use Sonix, transcribing your content is as simple as uploading your audio or video file and letting the platform do the work.

You’ll receive your completed transcription and can make any edits to rectify speaker labeling or grammar errors.

How long does data transcription take?

Human transcribers will spend two hours of transcription time for every hour of audio. While this might sound fast, this can amount to days and weeks of hard work for researchers participating in larger projects.

Sonix can reach speeds of one minute per one minute of audio time, making us twice as fast as human transcribers. Moreover, as technology advances, these platforms are only getting faster.

Is transcription a data analysis?

No, transcription is the process of converting data into a format that you can then analyze. Without transcription, researchers would be forced to repeatedly listen to audio and take notes to uncover patterns.

What is a narrative transcript?

Narrative transcripts are most commonly found within the legal industry. They are readouts of court hearings from a court reporter. Lawyers use them to analyze cases and build their arguments.

Within the broader industry, narrative transcripts would be equivalent to verbatim transcripts.

What should I look for in a transcription service for researchers?

At Sonix, we take pride in meeting the needs of researchers worldwide by simplifying the transcription process. Based on our experiences, we have come up with several important factors to examine before choosing any AI-based transcription service, including:

  • Accuracy rates
  • Pricing models
  • Data security and privacy
  • Ease-of-use for beginners
  • Turnaround time

In practice, we look to enhance our performance in these five core areas. It’s why Sonix is one of the world’s most highly regarded transcription platforms today.

Transcribe Your Research with Sonix

Transcription is a vital part of qualitative research. By taking advantage of an audio transcription service, you spend less time on transcription and more time on your analysis. Additionally, Sonix can even translate your content into 40 major world languages at the click of a button.

Suppose you’re looking to make your next research project more efficient. In that case, Sonix lets you translate audio, transcribe video, and produce readouts that can be analyzed to help you draw ground-breaking conclusions.

To learn more about how Sonix helps researchers, try Sonix for free now.

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