15 User Research Methods for SaaS Companies

Why is user research important for SaaS?

User research is a cornerstone of successful SaaS sales and marketing plans. It provides invaluable insights that drive product development, enhance user experience, and ultimately increase customer satisfaction and retention.

Here’s why:

User research helps you step into your users' shoes, understanding their motivations, frustrations, and the problems they're trying to solve.

User research enables you to discover how your customers perceive your product or service: 

• What is in it for them? 
• Why do they give you their time and money?

User research is also a great opportunity to gather feedback on early-stage concepts to identify potential issues and make necessary adjustments. It reveals usability issues.

This way, you can identify interested users who want to develop the product with you and tap into new use cases or market segments.

When to conduct user research

User research should be an ongoing process throughout the entire lifecycle of a SaaS product. 

However, there are specific times when it's particularly crucial:

Product Design

Before investing heavily in development, you can conduct user research to determine which features are most valuable to users and allocate resources accordingly.

You can use the data to create detailed user personas based on your ideal customer's demographics and behaviors to ensure you build a product that resonates with them.

One way to collect data is through surveys. You can design and distribute surveys to collect quantitative data about user preferences.

Or you can launch one-on-one user interviews and incentivize participants with gift cards or discounts to gain deeper insights into user motivations, challenges, and experiences.

If you don’t have enough users to use these ideas, you can wear your detective hat and explore the depths of the internet. 

Look at how users interact with similar products. 

• What do they complain the most about? 
• What do they want to solve by using that specific product? 
• Do they enjoy a certain feature? 

Product Launch

The earlier you spot improvements, the better. 

That is why user research is useful for obtaining feedback on the design of your product, the functionality of your features, and the overall user experience.

You can examine initial customer support tickets and interactions to see how your product is performing during launch. 

See if there are any patterns where users might need additional guidance. 

For example, imagine a customer complaining about a bug in the product on launch day. 

You can either ignore it and celebrate this special day or use it as an opportunity to identify and fix the issue and gather feedback on its impact on their experience. 

It is also important to check your analytics regularly during this stage. 

If, for instance, you notice that a particular feature is not being used as frequently as you expected, sit down with your team and understand why this is happening. 

Product Redesign

Your product’s journey doesn’t end with the launch. In fact, it is only the beginning of a long marathon that requires you to learn, grow, and adapt to deliver the best results to your customers.

Maybe your product struggled to gain traction. This is not the end of the world, but it certainly can be a giant blow to your business. 

You should use the product redesign process to work closely with your product design team, test the redesign, and adapt your marketing strategy to highlight the changes made.

Ongoing Product Updates

You designed, launched, and redesigned your SaaS product. All of these changes might be hard to keep up with for your users.

Important updates might slip under the rug, or a big feature announcement can go unnoticed. To prevent that from happening, you should integrate user research into your schedule.

It ensures that your product remains aligned with user needs and preferences as it evolves. 

It also allows you to try different research methods, such as customer success stories, A/B testing, and others, throughout the process to see what the users respond to the most.

15 User Research Methods for SaaS

User Interviews

What: One-on-one conversations with users to gather in-depth insights into their needs, behaviors, and motivations.

How:

• Structured interviews: Use a predetermined set of questions to guide the conversation and ensure consistency across interviews like "What are your top three priorities when choosing a SaaS solution for [specific task]?
• Semi-structured interviews: Use a general outline of questions, allowing for flexibility and exploration of unexpected topics. For example, you can ask, "Can you tell me about your experience using our SaaS product, specifically [feature]?”
• Unstructured interviews: Have a general topic in mind but allow the conversation to flow naturally, guided by the user's responses. For example, you could ask, “What do you think about the new pricing model we recently introduced?”

Focus Groups

What: Group discussions with multiple users to explore a specific topic or product feature.

How: 

• Moderator-led groups: A moderator guides the discussion, ensuring that all participants have a chance to contribute and that the conversation stays on topic.
• Facilitated groups: A facilitator creates a supportive and inclusive environment for participants to share their thoughts and ideas.

Usability Testing

What: Observing users as they interact with a product to identify usability issues and areas for improvement.

How: 

• In-person testing: Conduct usability testing in a controlled environment where you can observe users' actions and ask follow-up questions.
• Remote testing: Use screen-sharing tools and video conferencing to conduct usability testing remotely, allowing you to reach a wider audience.

First Click Testing

What: Observing users’ initial actions when presented with a product or interface to understand their thought processes.

How:

• Think-aloud protocol: Ask users to think aloud as they interact with the product, sharing their thoughts and reasoning.
• Eye-tracking: Use eye-tracking technology to measure where users are looking on the screen and how long they focus on different elements.

Card Sorting

What: Asking users to categorize product features or content to understand their mental models and information organization.

How:

• Open card sorting: Allow users to create their own categories and assign items to them. You can prompt them by saying, "Sort these cards into categories that make sense to you based on how you would expect to find them in our product."
• Closed card sorting: Provide users with pre-defined categories and ask them to assign items to them. 

Diary Studies

What: Tracking user behavior and interactions over time to gain insights into daily routines and product usage.

How:

• Daily or weekly logs: Ask users to record their interactions with the product on a daily or weekly basis.
• Prompt-based diaries: Provide users with specific prompts or questions to guide their observations.

Surveys

What: Collecting quantitative and qualitative data from users through questionnaires or online surveys. 

How: Different survey types, such as NPS, customer satisfaction score (CSAT), open-ended, star scale, and thumbs-up-and-down surveys, can help you collect feedback at the right spot in your user’s journey.

💡If you’re interested in reading more about surveys, check out our article on the subject here. 

A/B Testing

What: A comparison of two or more versions of a product or feature to determine which performs better.

How:

• Randomized assignment: Assign users to different versions of the product or feature randomly to ensure that the groups are comparable. For instance, you can assign users to either Group A or Group B to receive different versions of your product.
• Statistical analysis: Use statistical analysis to determine if the differences between the groups are statistically significant. For this, you can try a t-test to determine if there are statistically significant differences in user behavior between the two groups.

Heatmaps and Click Maps

What: Visual representations of user interactions on a webpage or app to identify areas of high and low engagement.

How: 

• Color-coded heatmaps: Use color-coded heatmaps to visualize where users are clicking or hovering on a page. Use a color-coded heatmap to visualize where users are clicking on your product's dashboard to see if users can find what they are looking for easily.
• Click maps: Show the exact locations of user clicks on a page. Try overlaying a click map on your product's interface to see the exact locations of user clicks.

Customer Feedback Analysis

What: Analysis of customer feedback from reviews, support tickets, and social media to identify trends and areas for improvement.

How: 

• Sentiment analysis: Use natural language processing to analyze the sentiment of customer feedback. Categorize sentiments into positive, neutral, and negative groups to detect patterns in user behavior.
• Topic modeling: Identify common themes and topics in customer feedback to understand the most frequently discussed issues.

User Analytics

What: Tracking and analyzing user behavior data to understand user engagement, conversion rates, and other key metrics.

How:

• Web analytics: Use tools like Google Analytics to track website traffic, user behavior, and conversion rates.
• App analytics: Use tools like Firebase or App Annie to track mobile app usage, user engagement, and in-app purchases.

Competitor Analysis

What: Studying competitors' products and strategies to identify opportunities for differentiation. 

How:

• Benchmarking: Compare your product to competitors on key metrics like user satisfaction, market share, and revenue.
• SWOT analysis: Conduct a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) to identify your competitive advantages and disadvantages.

Session Replays

What: Recording user sessions to analyze their interactions with a product in detail.

How: 

• User behavior analysis: Use session replays to understand how users navigate your product, identify pain points, and optimize the user experience.
• Error tracking: Identify errors and bugs that users encounter during their sessions.

Product Analytics

What: Analyzing product usage data to understand user behavior, identify trends, and measure the impact of product changes.

How:

• Cohort analysis: Analyze the behavior of specific groups of users (e.g., new users, repeat users) over time. For example, you can track the behaviors of new users, repeat users, and power users to see if your product updates have the results you want.
• Funnel analysis: Track users' progress through the customer journey to identify drop-off points and areas for improvement.

How to Use AI for User Research Methods

Natural Language Processing (NLP)

Natural Language Processing (NLP) is a subfield of artificial intelligence that deals with the interaction between computers and human (natural) languages. 

It's about teaching computers to understand, interpret, and generate human language in a meaningful and useful way.

You can use NLP in sentiment analysis and topic modeling to identify common themes and topics and understand the emotional tone of users’ key concerns and interests.

Machine Learning

Machine learning is also a subfield of artificial intelligence that focuses on developing algorithms that allow computers to learn from data and improve their performance on a specific task without being explicitly programmed. 

Essentially, it's about teaching computers to learn from experience, similar to how humans do.

You can use machine learning in predictive analytics and anomaly detection.

Chatbots and Virtual Assistants

Chatbots and virtual assistants are computer programs designed to simulate human conversation. They can be used to provide information, complete tasks, or engage in casual conversation.

You can use these tools to collect real-time feedback from users and test different product scenarios.

AI-Powered Analytics

AI-powered analytics is the application of artificial intelligence (AI) techniques to analyze data and extract insights that would be difficult or impossible for humans to identify on their own.

You can use AI-powered analytics tools to create visualizations and make complex data more understandable and actionable.

How to Use Third-Party Tools for User Research

Want to level up your user research game?

Third-party tools can be a huge help! They offer organized ways to do things, help you make sense of data, and make it easy to talk to people. 

Check out these popular tools and see how they can work for you:

User Experience Tools

1. Hotjar: Track user behavior with heatmaps, session recordings, and surveys.
2. UsabilityHub: Conduct five-second tests, first-click tests, and card-sorting tasks.
3. UserTesting: Conduct remote user testing sessions with video recordings and transcriptions.
4. UXPressia: Create interactive prototypes and conduct usability testing.
5. Optimal Workshop: Conduct card sorting, tree testing, and first-click tests.

Survey and Feedback Tools

1. SurveyMonkey: Create and distribute online surveys with advanced analysis tools.
2. Typeform: Design beautiful and engaging surveys with conditional logic and integrations.
3. Qualtrics: Conduct surveys, market research, and customer experience programs.
4. Mopinion: Collect feedback through in-page surveys, pop-ups, and feedback widgets.
5. Feedbackify: Gather feedback through in-app surveys, email follow-ups, and live chat.

Analytics Tools

1. UserGuiding: Analyze user behavior and product usage to identify opportunities for improvement.
2. Google Analytics: Track website traffic, user behavior, and conversion rates.
3. Mixpanel: Analyze user behavior and engagement across different channels.
4. Amplitude: Track user journeys and understand key metrics like retention and churn.
5. Heap: Capture all user interactions automatically, without requiring instrumentation.

AI-Powered Tools

1. MonkeyLearn: Analyze text data using natural language processing techniques.
2. Google Cloud Natural Language API: Extract insights from text data, including sentiment analysis and entity recognition.
3. Amazon Comprehend: Analyze text data for sentiment, entities, syntax, and key phrases.

Key Takeaways

User research in SaaS is essential for validating your product concepts, increasing customer satisfaction, and driving product development.

Consider conducting your research during key stages like product design, launch, and updates. Use a variety of methods, including surveys, interviews, usability testing, and analytics, to gather comprehensive insights.

And don’t forget to involve cross-functional teams in the research process to ensure alignment and effective implementation of findings and use third-party tools when needed.