How to Do Line-by-Line Coding in Qualitative Research

 
 

Line-by-line coding applies the "devil is in the details" approach to your qualitative research. It’s for when you have dozens or hundreds of interview transcripts to get through, and you’re tempted to just code broad themes and move on. But doing this often means missing subtle insights and nuances hidden in your participants' exact words.

It’s those seemingly minor comments—a hesitation, a metaphor, a casual aside— that often contain the most telling, unfiltered details about their experiences. Line-by-line coding slows you down and focuses your attention on each individual sentence. Like trading binoculars for a microscope, you see less of the landscape at once but discover an entirely new world of meaning in the details.

This guide walks you through line-by-line coding from start to finish. We'll show you when this detailed approach works best, how to apply it successfully, and strategies for high-quality analysis without getting lost in every single detail along the way — with help from qualitative coding tools like Delve.

📘 New to qualitative coding?

If you're just getting started or want a refresher, our free coding course walks you through the basics. For a deeper dive, check out the qualitative coding guide for hands-on tips and best practices.

Finding meaning in every line: What is line-by-line coding

Line-by-line coding is the qualitative research equivalent of reading between the lines – except you're coding every single sentence, so nothing goes unnoticed. Unlike structural coding (where you assign codes to paragraphs or larger chunks of data based on research questions) or selective coding (where you only code what immediately supports your core category), this detailed approach examines each line individually.

As one of your initial coding phases, line-by-line coding is especially valuable for methods like grounded theory where capturing subtle meanings in participants' exact words creates a stronger foundation for your later analysis.

When you’re research participants describe their first-hand experiences, every sentence contains potential insights to help you answer your research question(s). Getting granular with your data makes sure you don’t miss key insights along the way. Consider an interview with a healthcare worker named Kara who says:

📋 Single-code application example

"I'm constantly juggling patient care with documentation. Some days I feel like I'm drowning in paperwork rather than helping people. Then occasionally, a patient says something that reminds me why I got into this field."1

Code key:

  1. Work stress – The general emotional and cognitive load of navigating clinical responsibilities, paperwork, and emotional motivation.

Reference: Delve Qualitative Data Analysis Software

If you code this whole paragraph "workplace stress," you miss or gloss over the tension between care and administration, the emotional toll, and those meaningful moments that make it worth it. Line-by-line coding helps you catch these nuances by examining each sentence as its own data point. Rather than skimming the surface with broad codes, you create a detailed map where nothing falls through the cracks.

🗒️ Line-by-line coding example

"I'm constantly juggling patient care with documentation."1    "Some days I feel like I'm drowning in paperwork rather than helping people."2    "Then occasionally, a patient says something that reminds me why I got into this field."3

Code key:

  1. Work role conflict – Tension between responsibilities like patient care and administrative demands.
  2. Administrative burden overwhelm – Emotional fatigue caused by excessive non-clinical work.
  3. Meaningful patient interactions – Moments that reconnect the participant to their purpose or motivation.

Reference: Delve Qualitative Data Analysis Software

As you go line by line, you're working inductively to develop these codes directly from your data. There are no predetermined categories. This makes it particularly valuable for grounded theory research and thematic analysis, where you build insights from participants' actual words. Your analysis stays anchored in their experiences because you're paying attention to exactly what they've shared, one line at a time.

💡 Get set up before you code

If you're working manually, numbering each line can save time later when you're referencing quotes. In Delve, coding starts at the sentence level by default—just click to highlight and apply your code without extra formatting.

Adding code in Delve

When to use line-by-line coding

Think of line-by-line coding like using a microscope on your data. It reveals details invisible to the naked eye. It works with various types of qualitative data beyond just interview transcripts, though those are common. You can apply line-by-line coding to open-ended survey responses, news articles, qualitative observation, and case studies. Any textual data that contains rich, narrative content can provide helpful information.

Consider using line-by-line coding when your research calls for:

  • Noticing subtle distinctions in how participants express their experiences, picking up on emotional undertones, hesitations, and emphases that broader coding might miss.

  • Examining every line makes you less likely to cherry-pick evidence that supports your preconceptions and more likely to encounter unexpected insights.

  • Building a solid foundation for theory development. Line-by-line codes are reliable building blocks for more abstract concepts that are fully grounded in your data.

  • Revealing connections between seemingly unrelated ideas. Participants can make important conceptual links in passing comments that would be overlooked in paragraph-level coding.

These are situations where line-by-line coding comes in handy, but what about where line-by-line coding happens within your broader qualitative research process?

Where line-by-line coding fits in your qualitative research

When you're doing inductive qualitative analysis, line-by-line coding happens during the initial or open coding phase. It helps break down data into discrete parts after you've collected and prepared your materials, including transcribing your interviews. This detailed coding forms the foundation for all your analytical work that comes later:

  1. Initial/Open Coding: Line-by-line coding is one of several “first-cycle” coding techniques, identifying key concepts in each line

  2. Focused/Axial Coding: Next, you'll segue to “second-cycle” methods that identify relationships between your initial codes and create categories

  3. Theoretical Coding/Theme Development: Finally, you'll build higher-level concepts from these categories

If line-by-line coding is all about breaking your data apart, axial coding is focused on putting it back together in meaningful ways. The quality of your line-by-line coding directly impacts how effectively you can perform these later coding and analytical steps.

For even deeper analysis, line-by-line coding works well alongside other first-cycle approaches. You can combine it with in vivo coding (using participants' exact words as codes) or descriptive coding (summarizing content with topic-based codes) to examine your data from multiple perspectives.

🔎 Coding progression in qualitative research

Qualitative coding often starts with line-by-line coding as part of open coding. From there, researchers move to axial coding to explore relationships between codes, and then to selective or theoretical coding to build broader themes and insights. This flow helps you move from specific observations to more abstract understanding while staying grounded in your data. Learn more about open, axial, and selective coding.

Deep in detail: Line-by-line coding example

Let's look at a real research example to see how line-by-line coding works in practice. James & Johnson (1997) used this approach to study how dramatherapy leads to positive changes for combat veterans with PTSD. Their meticulous line-by-line analysis uncovered connections that might have been missed with broader coding methods.

Real world line-by-line analysis in practice

The researchers analyzed therapy sessions where veterans engaged in physical movement exercises. Instead of simply coding these activities as "therapy exercises," they examined each specific action and response:

 

Image 1: Sample of line-by-line coding in qualitative analysis. (James & Johnson, 1997 pg. 383-395)

The physical actions described as "punches, kicks, a grinding movement with the hands" weren't just lumped together as "physical movements." Instead, they were carefully coded as "Making choices" and "Getting involved" – recognizing the agency and engagement behind each motion. 

Similarly, the "grunts, growls and percussive 'huh' sounds" revealed emotional processing, coded as "Expressing emotion" and "Responding in the moment."

Going from detailed codes to theory

Getting granular allowed the researchers to notice patterns they might otherwise have missed. By connecting these detailed codes, they developed second-order themes like "Choice and control" and "Being actively involved" that explained how the therapy actually worked. Their final theory wasn't built on assumptions about dramatherapy, but on concrete, line-by-line evidence from their observations.

This shows why researchers choose line-by-line coding: it keeps your analysis firmly anchored in what's actually happening in your data rather than what you think might be happening. The detailed codes become building blocks for more abstract concepts, creating a clear trail from raw data to new theory. 

🔎 From lines to patterns: building your analysis

Line-by-line analysis helps sharpen your focus across different research methodologies.

Line-by-line coding in thematic analysis: Helps identify subtle patterns and variations that become the foundation for strong themes—preventing premature or surface-level categorization.

For grounded theory: It's a core part of open coding, making sure your theoretical development stays grounded in participants’ real experiences.

Breaking it down: How to do line-by-line coding

Let's get practical with a line-by-line coding guide and walk through how to actually implement this technique. Here's a step-by-step approach that balances thoroughness with efficiency:

1. Set the stage: Preparing your materials

Before diving into coding, take a moment to get organized. If you’re working with pen and paper, Excel, or word processors, numbering your lines saves time when you need to find specific passages later. Delve simplifies this preparation process. You can drag and drop a single transcript or batch upload them directly to the platform, where sentences are already set up as your default coding units.

The important part is setting up a reliable system for tracking your code and how it changes over time. Whether it's a dedicated notebook, spreadsheet, or qualitative coding tool like Delve, getting organized before coding begins saves you considerable headaches down the road.

2. The contextual scan: Reading before coding

Resist the urge to jump straight into coding. First, read through your data completely without assigning any codes. You want to do this a couple times to get a strong handle on your data. This initial pass helps you get a feel for the overall narrative and context. You might notice potential patterns or recurring ideas, but hold off on formal coding at this early stage. 

It’s like visiting a museum. Rather than taking an hour to analyze every brushstroke in the first painting you see, you first walk through all the galleries to get your footing. You eventually dig into each brushstroke, but also don’t want to miss the forest for the trees.

3. The detailed pass: Coding line by line

Now comes the core line-by-line coding work. Brushstroke by brushstroke, sentence by sentence, you’re  going through each transcript again:

  • Focus on capturing the essence of what's happening in each line

  • Pay attention to actions, processes, emotions, and meanings

  • Use concise language for your codes (usually 2-5 words)

  • Stay open to what's actually in the data, not just what you expect to find

  • Use memos to track your thinking and the evolution of your codes

Let's see this in action with an interview excerpt. In this example, we hear from a remote worker named Ava discussing her experience during the shift to remote work:

🗒️ Line-by-line coding example

"Working from home has completely changed my routine."1 "I save two hours each day not commuting."2 "But I miss chatting with colleagues by the coffee machine."3 "Sometimes I feel invisible to my manager now."4 "I've had to create a dedicated office space to stay focused."5

Code key:

  1. Working pattern shift – Adjustments in daily structure due to remote work.
  2. Time efficiency – Gaining usable time by removing commute.
  3. Loss of informal interaction – Missing casual conversations with coworkers.
  4. Reduced workplace visibility – Feeling unseen or disconnected from management.
  5. Home workspace adaptation – Creating a physical space to support productivity.

Reference: Delve Qualitative Data Analysis Software

Notice how each line receives its own distinct code, capturing the specific idea expressed. If this were coded at the paragraph level, you might simply label it all as "Remote work experience" – missing the nuanced mix of benefits, challenges, and adaptations described. Just like with your first readings of your data, you want to do a couple coding passes to make sure you aren’t skipping over key details. 

Here, you might consider other coding techniques like in vivo coding, descriptive coding, or emotion coding. Using a medley of qualitative coding approaches enriches your analysis. It taps into the depth and diversity of the data, layering on meaning that a single coding method might miss. But note this does require more time and resources!

💡 Coding tip for new researchers

When you're just starting out, aim for specificity in your codes without overthinking them. It's better to capture what's happening than to get stuck trying to find the “perfect” label. Memos help you return to your ideas later and make it easier to refine your thinking as your analysis evolves.

4. Leave breadcrumbs: Documenting your thinking

Line-by-line coding isn't just about labeling data – it's about developing your thinking. As you code, keep recording detailed memos about your thought process:

  • Why did you choose certain codes over others?

  • What questions or uncertainties arose as you coded?

  • What potential connections are you noticing between different codes?

  • How do your codes relate to your research questions?

These reflexive notes are very helpful during later analysis stages and help create transparency in your research process. Delve's integrated memo feature lets you attach notes directly to codes or data excerpts, creating a rich analytical landscape that evolves with your understanding.

 
 

💡 Coding best practices

If you're coding by hand, numbering your transcript lines gives you clear reference points. If you're using Delve, the software automatically links your codes to exact lines. The second approach makes it easier to revisit key excerpts and collaborate with others.

5. Refine and reconsider: The iterative process

After your initial coding pass, step back and review your work:

  • Are you using consistent language for similar concepts?

  • Do your codes truly capture what's happening in the data?

  • Are there places where more precise codes would better reflect the content?

This iterative approach helps you refine your analysis. Don't be afraid to go back and recode sections as your understanding evolves – this is a normal and valuable part of the process. Instead of thinking about this like a linear process, you want to keep iterating throughout all of these steps. 

6. Connect the dots: Moving toward synthesis

As a first-cycle method, line-by-line coding is typically just the beginning. Once you've completed this detailed coding, you'll start identifying patterns and relationships among your codes:

  • Which codes frequently appear together?

  • Are there broader categories that encompass multiple detailed codes?

  • How do these patterns relate to your research questions?

This progression from detailed coding to higher-level analysis helps build robust findings that remain firmly grounded in your data while offering meaningful theoretical insights. Delve's nesting feature makes it easier to spot emerging patterns and make connections between your detailed initial codes.

The microscope vs. the telescope: Overcoming line-by-line Coding challenges

Line-by-line coding uncovers valuable insights, but it's not without its challenges. Most researchers struggle with similar issues as they work through their data:

Managing code overload

The James & Johnson study shows how quickly codes multiply. Even simple physical movements generated multiple analytical codes, and your own research will likely follow the same pattern. Before you know it, you're juggling hundreds of codes.

Solution:

Balancing detail and big picture

When dissecting text line by line, you might lose sight of how individual comments connect to participants' broader experiences. The granular focus can fragment the narrative flow and the cohesive story your participants are telling.

Solution: 

💡 Time-saving tip for new researchers

Skip the repetitive setup. Delve's quick code application and search features save time by making it easy to reuse descriptions and find what you need fast—so you can spend less time organizing and more time analyzing.

Staying consistent with a team

When multiple researchers are coding the same data during collaborative qualitative research, you can expect coding inconsistencies to arise and for team members to view data differently. 

Solution:

Finding the best tool for line-by-line coding

While you can absolutely do line-by-line coding using traditional methods like pen and paper, spreadsheets, or Microsoft Word, specialized qualitative data analysis software like Delve can make for a much smoother and stress-free research experience. 

 
 

Delve addresses these specific challenges by offering:

  • Nested codes to improve rigor: Create code hierarchies and groups that help manage growing code lists without losing their specificity

  • Connected memos to track code development: Attach your analytical thoughts directly to codes or text segments, making it easier to track your thinking

  • Search functionality for quick retrieval: Quickly find related codes or text segments across transcripts, saving considerable time from picking through sticky notes or Excel tabs

  • Smarter collaborative features: Work with team members on a shared codebook all in one place, maintaining consistency while updating your work in real-time

If you find the administrative aspects of line-by-line coding challenging, Delve consistently receives high praise from real researchers for keeping the process focused and methodical without the usual workflow frustrations.

Closing thoughts: The value of details

Line-by-line coding is a commitment to thoroughness where nothing is swept under the rug. While it requires more investment than broader coding approaches, this highly detailed option helps you stay true to what your participants are actually saying rather than what you might expect to find.

Whether you're conducting thematic analysis or building grounded theory, the granular insights from line-by-line coding create a solid foundation that keeps your findings firmly rooted in your data. The investment in detailed coding early on pays dividends in the richness and credibility of your final results.

Ready to try line-by-line coding with a tool designed for simpler coding? Start your free 14-day trial of Delve today and experience how intuitive qualitative analysis can be.

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Cite this article

Coding Qualitative Data, Step by Step GuidesDaniel Politz