How to conduct a product feature analysis

What’s driving customers to purchase and use your product?

Whether you’re launching a new product or improving an existing one, you need to know which features matter most to your audience. When you know which features they value, you can focus your resources on improving them. You can also use this information to discontinue any features that don’t improve your bottom line or that your customers don’t care for.

So, how do you know which features matter the most to users and deliver the most value? The answer is a process called product feature analysis.

Learn how to conduct a comprehensive product feature analysis, the key steps involved, and best practices to follow to ensure your product aligns with customer needs and market demand.

Product feature analysis involves carefully and systematically evaluating each feature within your product based on its performance, relevance, and impact. The analysis is performed using data on how often the feature is used, along with user feedback. The goal is to identify which features have the most significant impact on usability and customer satisfaction.

Ranking your features based on this information can help you make more data-backed decisions about future development. The analysis can help you determine whether to improve or discontinue certain features and reveal what your customers really need from your product. You can then focus your resources on enhancing the features that will help boost customer satisfaction and loyalty—key drivers in business growth.

Understanding which features make your product stand out can help your company stay competitive in an often crowded marketplace. Product feature analysis can also show you potential feature gaps within your product and give you a way to address them.

Not all features are created equal. Some underpin your product’s core purpose and functionality, while others may be there as a bonus for certain users or as a way to make the product easier to use.

Breaking your features into categories can make analyzing and prioritizing them easier.

Here are four types of product features you’ll want to consider in your analysis:

Core features

These are essential features that define the product’s purpose and value. Without these features, the product wouldn’t work or would be unusable.

• Example: word-processing software’s ability to edit text

Niche features

Niche features are specialized features used by specific types of users to address specific needs. They can help differentiate your product from your competitors and attract a different kind of customer.

• Example: video editing software’s special effects and transition templates

Power features

These are advanced functions that offer a lot of value to users. However, using them effectively might require additional resources or knowledge. For example, they might be behind a premium paywall.

• Example: data analysis software that can also perform complex statistical calculations

Usability features

These are features that enhance the user experience and make the product easier to use. These features might improve customer satisfaction, reduce frustrations, and increase product adoption.

• Example: a productivity tool with intuitive navigation and helpful tooltips

Prep work matters when it comes to product feature analysis. Before you start, ensure you have taken the following steps, as they can make a big difference to your final results:

Align on feature definitions

Get your team on the same page about what constitutes a feature. Develop a definition of a feature, including specific criteria for categorizing them. This will make it easier to prioritize features later.

Cluster or group your features

Group your features into logical categories. You can use the categories listed above or create your own based on your product and analysis goals. Grouping your features will make analysis more manageable and give you more insight into how the features work together.

Identify transitional features

Some features evolve over time, and others might serve multiple purposes. Consider these transitional features and determine how you want to categorize and analyze them.

Recognize that features are dynamic

Features often change over time, especially in software as a service (SaaS). They might change because of user feedback, technical updates, or market trends.

You’ll want to change your analysis as your features evolve, so be prepared for this to be an ongoing process.

You can start the analysis process when you have completed your prep work and categorized your features. Here are the six steps you’ll want to take to get the most out of your feature analysis:

1. Define your objective for performing a feature analysis

Consider why you want to perform a feature analysis. Knowing your objectives will guide your research and help you focus on the most relevant data and insights.

Many organizations go through a product feature analysis because they want to:

• Identify underused features

• Prioritize future feature development

• Optimize existing feature performance

• Measure the return on investment (ROI) of specific features

• Gain an understanding of user behaviors

Take time to understand why you are going through this process and what your goals are for it. With that information, you’ll be better equipped to answer specific questions and create insights from your analysis.

2. Specify the metrics to track

Once you know your objectives, you can determine which key metrics will help you measure those goals. Which metrics you track and analyze will depend on the product and your objectives. However, there are a few standard metrics often used in product feature analysis, including the following:

• Frequency of feature usage

• Feature adoption rates

• User retention rates

• User engagement time

• Customer satisfaction

• Customer acquisition cost

• Customer lifetime value

• Conversion rate

Carefully consider which metrics you want to measure. The data you gather will help you assess feature performance and help you make future development decisions.

3. Tag key features and events with a product analytics tool

Once you know what metrics you need, you’ll need to gather data on them.

Product analytics tools can be extremely helpful for this task. These tools allow you to tag key features and events within your product to easily collect and analyze data on user behavior.

You might want to tag specific actions, individual features, or certain events. Whatever you choose to track, be clear and consistent with how you name your tags for more accurate data collection. This data allows you to analyze user behavior, trends, and feature performance.

4. Collect and review feature usage data and behavior analytics

With the tagging done in your product analytics tool, you can start collecting and reviewing feature data. The data will show how users interact with your product and which features bring the most value.

When looking at your feature data, you’ll want to examine the following:

• How often features are used and any patterns in their usage

• How long users spend using each feature

• Customer feedback and support tickets to see how users feel about different features

The first two items involve quantitative data, which is relatively straightforward to gather and analyze. However, the third item involves collecting and analyzing qualitative data, which can be more involved.

Dovetail’s tagging system makes categorizing and analyzing user feedback related to specific features easier. Tags can help you organize and filter that feedback to make it easier to spot trends and patterns. You can use the tagging system for:

• Feature tags: tag feedback related to specific features. You can group the feedback by feature and identify common themes or pain points.

• Sentiment tags: tag feedback with positive, neutral, or negative sentiment. This makes identifying areas where users are satisfied or unsatisfied easier, helping you gauge reactions to different features. It can also help you prioritize resources for feature improvements.

• User segments: tag feedback based on user persona, industry, or other segments. This makes it easy to identify feature needs based on user type and gives insight into how different user groups interact with and value each feature.

Organizing your data like this will make analysis easier and give you clearer, actionable insights at the end of the process.

You can start analyzing behavior with tools such as:

• Heatmaps: visual representation of where users click, hover, or scroll most, revealing areas of high and low engagement

• Session recordings: real-time recordings of user interactions with a feature, displaying the exact behavior in each session

• Funnel analysis: visualizes the steps users take to complete a specific task (such as sign-up and purchase) and highlights where they drop off

• Usage distribution graphs: visualizes the distribution of feature usage across users (for example, daily active users (DAU), weekly active users (WAU), monthly active users (MAU))

• Retention chart: line or bar charts tracking user retention over a period (for example, day 1, day 7, or day 30 retention).

5. Analyze the data to extract new feature development insights

Now, you can start extracting insights from your data. Take the following steps:

• Highlighting patterns: use Dovetail’s visualization features to identify patterns in the feedback. You can search for specific tags and view all related insights simultaneously, helping you identify recurring themes and trends.

• Identifying the most requested features: filter by tags to see which features are frequently mentioned in user feedback. This can help you prioritize development for features that are in high demand and will have the biggest impact on user satisfaction scores.

• Analyzing sentiment: review positive or negative comments about each feature to understand user satisfaction scores. This is helpful for identifying areas where features excel or fall short.

• Showing usage trends: identify how different user segments interact with features and their unique needs. This can help you tailor features to specific user groups and improve the overall user experience.

6. Implement changes and monitor impact

With your insights, you can implement changes and see how they impact your key metrics over time. You might want to enhance existing features based on user feedback and data analysis. You may also develop and launch new features that address user needs. If certain features aren’t providing enough value, you might want to sunset them.

Once you make changes to your features, monitor how they impact your tracked metrics. You can do this by continuing to collect feature usage data, user feedback, or key performance indicators (KPIs). By monitoring the changes, you can refine your strategy and align your features with user needs.

Your product feature analysis is only beneficial if you put it to work. You need to turn that analysis into actionable steps that improve your product, enhance customer satisfaction, and drive you closer to your organizational goals.

Here are some of the things you can do to help turn all that data into action:

• Create reports. Take the data and bring it together into actionable summaries. For example, create a report on the three features users love most, the three features causing friction, and the three most requested features. These reports can be shared with your stakeholders to help allocate resources.

• Feature prioritization. Use the insights from your analysis to prioritize product features. Based on user demand and pain points, identify which feature updates or new developments the team should take on first.

• Sunset unpopular and low-ROI features. Identify features that are underused and provide a minimal return on investment. Create a plan to phase out these features, ensuring you clearly communicate your decision to customers and explain how it will benefit them. This allows the team to redirect resources to high-impact developments that enhance the overall user experience.

• Share and collaborate with stakeholders. Use Dovetail’s collaboration tools to share your research findings with your product and development teams. You can also create shareable reports or visuals highlighting user needs and the reasoning behind your feature recommendations.

• Iterate on features. Based on the analysis, suggest new iterations or feature improvements, then monitor user feedback over time to see how these changes impact satisfaction.

A successful product meets your customers’ needs and delivers value. Product feature analysis can be a powerful process that helps you understand your customers’ needs and informs the development of your product.

When you carefully analyze each feature, you can determine which delivers the most value to your users and which requires improvement. The data you gather in the process can help you make more informed decisions about your product’s future. With product feature analysis, you can make sure you’ve put your product on the path to success.