What is grounded theory?

Today's companies are always looking for immediate competitive advantage. They'll seek to develop better tools and methods of understanding their core audiences and improve their products and services. 

Are you looking for a better approach to research, understanding the customer experience, or effective product design? Keep reading. Grounded theory may be the concept your brand needs.

Even if you're familiar with grounded theory, it's best to begin with core definitions. Grounded theory, as the name implies, is the method to discover emerging patterns and form theories rooted in data and metrics. 

Sociologists Anselm Strauss and Barney Glaser originally articulated the principles of grounded theory in 1967 in their book, The Discovery of Grounded Theory. The concept creates theories based on metrics that contradict previous, more traditional methods that presented theories first, then data collection.

It's the process companies leverage when reviewing any customer data. It's effective for any researcher looking to explore trends in the behaviors and experiences of others. Similarly, you can use it when reviewing in-app user behavioral trends. In any scenario where data collection is prominent, the grounded theory discerns applicable theories and processes from those metrics.

Since grounded theory is a data process based entirely on metrics and analytics, conclusions drawn from that data will allow you to develop new theories that are more grounded and effective. These analytically rooted hypotheses are fundamental when additional deeper dives are necessary into various topics. 

Your data collection will come in layers, first scratching the surface. The more focused initiatives that follow are the deductive phase of the grounded theory process. And that's where the goldmine lies, where you can discover new ideas, key advantages, and brilliant insights.

In addition to the three core steps, consider separating your grounded theory strategy into four stages:

1. Collecting the data

2. Coding: Pattern finding 

3. Theoretical sampling: Analyzing and trying theories 

4. Theory: Establishing one winning theory

Separating your ground theory process into these stages, either as your method or with the help of analytic tools, you can further understand, interpret, and organize the data you need to form new theories. And the continuous application of grounded theory methods can lead to a more intuitive, diverse, and deeper understanding of any analytics you collect.

Any scenario where you need to spot emerging trends or be more precise in predicting behaviors is an excellent opportunity to use grounded theory. 

When you need to assign structure and processes to research, consider grounded theory as the best method. You'll maintain an apples-to-apples data collection when you adhere to the pre-strategized method with your research approach. 

From there, you can produce data-grounded conclusions and assumptions that allow you to structure new procedures and initiatives effectively.

Here are some examples where grounded theory makes sense:

• Companies exploring new product designs to resonate with customer pain points or needs

• Businesses looking to stay relevant with products and features that fit the preferences of their audiences

• Researchers interested in innovation or a deeper understanding of datasets to effect change in processes, methods, or behaviors

Grounded theory can assist any time you experience a phenomenon without an existing theory or precedent. It's also revolutionary for completing incomplete theories or exchanging current strategies for new ones.

In research and business, the most common unknown constants are social behavior, human emotional connections, and preferences in decision-making. No predetermined methods can predict these elements. Ongoing research and data collection are mission-critical to effectively engage in these arenas. 

The grounded theory provides the methodology needed to better understand these unknowns' ever-changing complexities.

Other key advantages of properly executing a grounded theory method of research include the ability to:

• Identify an occurrence within a situation 

• Identify the contingent nature of the general practice

• Produce a data-rooted description that identifies contradiction or conflict

• Better determine what's actually happening beyond surface interpretations

• Adapt quickly to diverse phenomena

• Respond to change based on emerging behaviors and preferences

In short, grounded theory is pivotal for connecting data to behavior and processes. It's the way forward in making discoveries and creating more effective strategies. It streamlines how you manage and leverage your analytics. Most importantly, it reduces the confirmation bias that often taints other metric analysis methods.

Sure, there are plenty of inherent benefits to leveraging the grounded theory. But every pro list has a flip side, so there are cons to consider. 

For example, the grounded theory method produces copious amounts of raw data, which can be challenging to manage if you're not prepared with experienced staff and the right tools to sort and disseminate data.

Additionally, it’s imperative to train and educate others if you assign them to use grounded theory. Researchers using grounded theory must be skilled in these methods to be effective. 

Another caveat is that there isn't a rulebook for identifying categories for your datasets. You'll need to develop those based on your unique situation, application, and intended goals.

Another consideration involves the researcher reviewing the data. They may introduce bias in interpretation and data constructions, which can skew results. Sometimes, you’ll only know what you're studying once you've finalized a substantial amount of analysis. 

For example, a core category may only present itself once you've collected other concept metrics. Once you identify that core category, which should correspond to all other concepts in your model, you can then take that as a signal that you've satisfied the first coding stage of grounded theory.

So, what separates a great grounded theory execution from a poor one? It starts with the data you're collecting. Throw all preconceived notions out the window to remove any bias sensitivity.

From there, you or your designated researcher can spot emergent themes, keywords, phrases, and similarities that you can group as codes and assign to a concept hierarchy. Categorizing those concepts through relationships will help you develop your finalized grounded theories. 

Let's break it down into steps before coming to the result of establishing a winning theory.

Planning with metrics

Before we get started with grounded theory, effective planning is critical to the success of any project. You may already be collecting data, whether you're prepared to do anything with it or not. 

Your digital presence online, customer interactions, and conversions or engagements automatically create a pool of valuable data. The grounded theory will work best if you can get strategic about what data you plan to track and analyze amid all those details you're already assembling.

Consider creating goal metrics that outline what key goals are most important to your short and long-term objectives. Separate the metrics into priorities, so you can follow through with a grounded theory analysis on specific concepts at a time. 

When brainstorming the metrics you need to hit, consider your company's financial needs. You may also consider the numbers you promised investors or the numbers you need to hit to stay ahead of competitors. Plan your strategy and include a timeline.

Defining metrics sets your entire company up for success. It defines a finish line for everyone on your team to collectively strive towards, including your researchers. Knowing your goals establishes where gaps are and refines hypotheses. 

In addition, since you’ve established your metrics based on where data is already coming in, researchers can use the same approach in their strategy and planning phase.

Collecting the data

Now you’ve properly established your metrics, it should now be clear what data you need to collect and even some good starting points where you may already be collecting it. However, take into account that metrics are quantitatively based, so they’re limited to telling you what happened and when.

To know what to do and offer actionable insights, you may want to consider how you’ll answer why and how things are happening in more qualitative forms, like interviews. 

Once you’ve thought this over, forming a strategy for data collection is useful. Write out problem statements, and explain the strategy of whatever data collection you plan to use before initiating data collection. This helps gain trust, insight, and confidence across teams and is sometimes mandatory, depending on circumstances.

From here, design your data-gathering methods, such as survey design or writing qualitative scripts. Once you’re sure these will capture the data you seek, it’s time to send them out and start collecting your data. 

Coding

Codes create an order of operations. During the "open coding" stage, you'll review data and assign names based on concepts. 

These codes should be easy to identify and understand, rooted in keywords or titles. Next is "selective coding," where you'll prioritize all those data codes in order of importance. You'll likely have a series of higher and lower-level codes representing your datasets.

When assigning varying levels of importance, you can create hierarchies to outline parent codes and subcodes. For example:

• Problems or pain points

  • Cost

  • Time

  • Location 

• Checkout experience

  • Positive

  • Negative

This more in-depth categorization will help you quickly identify data points and analyze them within their parameters. There are no limitations on the number of codes you create, and lumping too many concepts into one category won't give you the clarity you need in the results.

Once you are confident you have a well-sorted map of data coding, you can begin analyzing. This is the exciting phase of the grounded theory process because the relationships between those codes will begin to emerge. 

To look for patterns, it can help to put each finding onto post-its and move them around as you start to visualize those trends. 

Additionally, you'll want to stick to a predetermined timeline for analytics review. Depending on your unique research or company positioning, you might collect ongoing data and analyze the trends daily, weekly, monthly, or quarterly.

Grounded theory analysis memos

Another component of your grounded theory analysis involves memos. When coding for the first time, you can create memos to document your process for categorizing and coding. You can track your thoughts and ideas informally with a memo. 

Be mindful of tracking the "why" behind your thinking as you go, so other researchers who get involved later can track your process. New insights and ideas can grow from a well-documented memo trail of organic reasoning. Those informal memos make great future training material, too.

Theoretical sampling

We mentioned the importance of removing bias or pre-existing notions from your analytics process. Interpreting the data using the grounded theory hierarchy of codes should help you remain objective. However, consider implementing support tools and resources that provide reminders for neutral interpretation. 

When you properly code and categorize the data, it will demonstrate trends from which you can draw conclusions. For example, you may spot improved customer engagements, favorable reactions to new products, or new ideas that you can use for innovation.

You can develop a more in-depth round of question sampling or coding optics using verified analytics. Then, dig deeper by collecting new data and repeating your grounded theory method to find even more intuitive insights. With every fresh round of coded results, you can also make data-driven changes to existing processes, allowing you to leverage those newly spotted trends.

The grounded theory method of collecting data and subsequent analysis is game-changing for companies looking to find emerging markets. Staying ahead of competitors requires continuous innovation and niche specialties. Find your company's competitive advantage using the grounded theory and method of staying on top of your data and ahead of ever-changing dynamics in your industry.

The National Library of Medicine suggests that grounded theory is a flexible and well-known method among seasoned researchers. But UX research methodologies have since borrowed and adopted it, as highlighted by the NNG. 

Knowing how to implement it and form actionable data with suggested courses of action is paramount in keeping data-gathering useful. This can require additional resources, making it challenging for novice grounded theorists. 

Implementing new processes for sifting through, analyzing, and theorizing qualitative and quantitative data is a tall order for any first-time adopter. If the grounded theory is new to you or your organization, consider starting with the right people and tools.

Skilled researchers

Whether you plan to do all the research yourself or bring in others to oversee and manage your data, you'll need skilled professionals. 

First, explore the online resources and guides to create a training platform for your grounded theory process. A rulebook to guide your efforts will ensure a consistent set of methods. 

From there, you can develop training sources to use as you introduce other team members to your grounded theory initiatives.

Grounded theory analytics tools

You don’t need to begin any phase of the grounded theory method alone when there are a host of available software solutions and analytics tools to help you. 

Leverage tools like SmartLook, Hot Jar, or Maze to translate data into actionable findings. Tap into programs developed exclusively for coding and analyzing data as part of the grounded theory model, like Dovetail. 

Tools like these will automate and sort your metrics collection steps for accuracy, efficiency, and consistency every time.

If you're not sure where to begin organizing your data, start by creating initial research questions:

• What metrics will have the greatest impact on your overarching goals?

• What answers do you want to know? 

It's okay to list data points that aren't going to aid in your analysis. Separate what you want to know from what you need to know and begin developing your strategy for grounded theory practices.

The grounded theory excels when you want to make sense of your data and spot emerging trends or track behavioral phenomena.

Imagine an instance when traditional processes begin breaking down. For example, where a customer life-cycle typically lasted a few years, it is now averaging only a month. You need to learn more about why that is happening. 

Additionally, there’s a need to discover what emerging method is taking that defunct procedure's place. The grounded theory of analysis will provide a method to collect and review the data you have to identify those new trends and see what behaviors are contributing to the change. 

With a clear picture of your data, you can draw data-driven conclusions. That's where brilliant innovations come from and where big ideas are born.

Consider adopting the grounded theory if you're researching new features or looking for business model improvements. Gain the competitive edge your company needs and break through the traditional theories or processes with innovative new solutions. It's the data-driven way to grow wherever research is pivotal.