Feature Adoption Metrics: Top Benchmarks for 2026

• Average Core Feature Adoption Rate: 24.5% (Median: 16.5%)
• Top Quartile Core Feature Adoption Rate: >45%
• Time to Adopt (First Use): <24 hours for 60% of users
• Frequency of Use (Core Features): 3+ times per week
• Breadth of Adoption (Multiple Features): 40% of MAUs use 3+ features regularly

By Industry:

• HR Tech: Higher adoption for compliance features (35-50%), lower for performance management (15-25%).
• FinTech: High adoption for core transaction features (50-70%), lower for secondary financial planning tools (10-20%).
• Project Management: Power users show broad adoption (5-7 features), while the majority stick to 2-3 core features.

By Company Size:

• SMBs (<100 employees): Faster initial adoption but higher churn if value isn't immediate.
• Mid-Market (100-1000 employees): Slower, more deliberate adoption, often driven by internal champions.
• Enterprise (>1000 employees): Longest adoption cycles, but highest stickiness once a feature is embedded in workflows.

Key Levers to Improve Feature Adoption:

• In-App Guidance: Contextual tooltips, interactive walkthroughs, and checklists.
• Lifecycle Marketing: Email and in-app campaigns triggered by user behavior (or lack thereof).
• Customer Success: Proactive outreach to accounts showing low adoption of relevant features.
• Product Marketing: Clear communication of new feature value through release notes, webinars, and case studies.

Actionable Insights:

• A low adoption rate for a new feature isn't a failure if the users who do adopt it have a significantly higher retention rate.
• Benchmark your adoption rates against yourself first. A 10% month-over-month improvement is a strong signal of progress.
• Focus on the "why" behind the numbers. Use session recordings and user interviews to understand the friction points for non-adopters.

Key Takeaways:

Industries:

• HR Software: 31%
• AI/ML Solutions: 24.8%
• Insurance: 22.8%
• FinTech: 22.6%

Company Size Trends:

• Small (<$5M): Lower adoption due to limited resources.
• Mid-market ($5–10M): Highest adoption (30.4%) due to balanced resources and agility.
• Enterprise (>$10M): Slower adoption due to complexity.

Feature Usage Frequency:

• Power Users: >40% weekly usage.
• Regular Users: 15–40% weekly usage.
• Occasional Users: <15% weekly usage.

Onboarding Success:

• Interactive walkthroughs drive higher adoption (31%) compared to traditional documentation (16.5%).

Quick Comparison Table:

Category Top Performer Adoption Rate

Industry HR Software 31%

Company Size Mid-market ($5–10M) 30.4%

Onboarding Method Interactive Walkthroughs 31%

To improve feature adoption, focus on customized onboarding, user behavior tracking, and simplifying workflows. High adoption rates (28%+) are linked to better customer retention and premium upgrades.

Dive deeper into 7 Customer Activation Metrics Every SaaS Must Track.

The Future of Feature Adoption: What to Expect Beyond 2025

As technology evolves, so will the strategies for encouraging feature adoption. Key trends to watch include:

• AI-Driven Onboarding: Expect hyper-personalized onboarding flows that adapt in real-time to user behavior, guiding them to the most relevant features.
• Predictive Analytics: Tools will increasingly predict which users are at risk of low adoption and trigger proactive interventions.
• In-App Gamification: More sophisticated gamification techniques will be used to reward feature discovery and mastery, boosting engagement.

Feature Adoption Metrics That Every PM Should Track & 5 Strategies To Improve Them

1. Core Feature Usage Rates

On average, the industry sees a 24.5% adoption rate for core features. Hitting or exceeding 28% is a strong indicator of healthy feature engagement, giving companies a clear benchmark to aim for when refining their strategies.

Adoption rates are also shaped by go-to-market strategies. Sales-led companies report a slightly higher rate of 26.7%, compared to 24.3% for product-led companies. This difference highlights how the choice of strategy can impact feature adoption.

Company size plays a big role too, with usage patterns varying widely across organizations of different scales. This underscores the need for tailored approaches that align with the specific needs of each company.

Engaging users early with core features boosts satisfaction and retention over time. Focusing on better onboarding experiences and improving user interactions early on can make a big difference in keeping users engaged.

2. Adoption Rates by Industry

Adoption rates differ significantly across industries. HR software leads with a 31% adoption rate, largely because of its importance in daily operations. Technology sectors, including AI and Machine Learning SaaS, align closely with the overall average of 24.5%. On the other hand, FinTech and Insurance lag behind at 22.6% and 22.8%, respectively, due to hurdles like strict security requirements and regulatory complexities.

Industry Sector Feature Adoption Rate

HR Software 31.0%

AI & ML SaaS 24.8%

Insurance 22.8%

FinTech 22.6%

SaaS providers aiming to increase adoption rates need to tackle challenges specific to each industry. For instance, in financial sectors, simplifying compliance workflows and improving onboarding processes could make a big difference.

3. Usage Patterns by Company Size

Companies with annual revenue between $5-10M lead the way in feature adoption, achieving a 30.4% adoption rate - higher than both smaller and larger organizations.

Mid-market businesses strike a balance between having enough resources and staying agile, making them particularly effective at rolling out new features.

Here’s how feature adoption varies by company size:

Company Size Feature Adoption Trend Key Characteristics

Small (<$5M) Lower than mid-market Agile but resource-constrained

Mid-Market ($5-10M) Highest (30.4%) Balanced resources and flexibility

Enterprise (>$10M) Lower than mid-market Abundant resources but slowed by complexity

While enterprises have plenty of resources, they often struggle with complicated implementations and slower feedback cycles, which can drag down feature adoption rates.

Industry-specific trends shed more light on this dynamic. For example, HR software tends to see steady adoption across all company sizes. On the other hand, industries like FinTech and Insurance show sharper contrasts, with mid-market companies often outperforming their larger peers in adoption rates.

To boost feature adoption across different company sizes, SaaS providers should focus on:

Learn more in our guide: How to do conversion rate optimization for ecommerce.

• Customizing onboarding experiences to suit each company size
• Tracking user behavior to address barriers
• Streamlining workflows to minimize complexity

4. Feature Usage Frequency

Feature usage frequency measures how often users engage with specific features over time, offering insights into their ongoing involvement. Unlike initial adoption, this metric focuses on sustained interaction. Recent benchmarks indicate an average feature engagement rate of 28%.

Frequent usage often aligns with stronger customer retention. Users typically fall into these categories based on weekly interaction rates:

Usage Pattern Frequency Rate

Power Users More than 40% weekly usage

Regular Users 15–40% weekly usage

Occasional Users Less than 15% weekly usage

To better understand engagement, companies often rely on specific metrics like Monthly Active Feature Usage (MAFR), calculated as:

MAFR = (Monthly Active Feature Users / Total Monthly Logins) × 100

Data shows that usage rates vary across industries. For example, HR Software averages 31%, while FinTech and Insurance sectors see lower rates, around 22-23%.

Why do these differences exist? Several factors play a role, including:

• Complexity of the user interface
• How easy it is to discover features
• Integration with existing workflows
• Clear communication of the feature's value
• Quality of onboarding experiences

According to Artisan Strategies, interactive walkthroughs have proven more effective at boosting engagement compared to static documentation.

Here are three key metrics to monitor:

• Time to First Value: How quickly users see the benefit of a feature.
• Usage Consistency: How regularly users interact with it.
• Feature Stickiness: How often users return to the feature.

Companies that focus on simplifying the user experience and offering contextual guidance during critical moments are better equipped to boost feature engagement and keep customers coming back.

5. Feature Drop-off Metrics

Feature drop-off can significantly affect how well users adopt and stick with a product. Keeping an eye on when and why users stop engaging - whether early on, midway, or gradually over time - can uncover important insights.

When analyzing feature usage, understanding where drop-offs occur helps pinpoint areas that need attention. Here are three common drop-off patterns and their causes:

Drop-off Pattern Likely Cause

Early Abandonment Ineffective onboarding

Mid-term Drop-off Users don’t see enough value

Gradual Decline Complexity or poor workflow fit

The more engaged users are, the less likely they are to drop off. To spot where users lose interest, track these key metrics:

• Feature Abandonment Rate: The percentage of users who start but don’t finish using a feature.
• Depth of Feature Usage: How thoroughly users explore and use a feature's capabilities.
• Time-to-Value: How quickly users achieve their first meaningful success with the feature.

Research by Artisan Strategies highlights that using interactive walkthroughs can significantly lower feature abandonment, especially in complex B2B products. Their findings stress the importance of offering timely, contextual guidance during crucial moments.

Interestingly, mid-market companies tend to experience fewer drop-offs. Sectors like FinTech and Insurance see improvements when they provide extra support, such as interactive onboarding and context-aware help tools.

To combat drop-offs, simplify workflows and make the value of features crystal clear. Removing obstacles and maintaining consistent communication about benefits can go a long way in keeping users engaged.

Check out our comprehensive guide: How to Measure and Improve Time-to-Value (2025 Guide).

6. Onboarding Success Rates

Getting onboarding right is a game-changer for feature adoption. It's the moment where you can go beyond just "okay" results and make a real impact.

Interestingly, company size influences onboarding success. Mid-sized businesses with annual revenues of $5–10M see the best adoption rates at 30.4%. Why? These companies seem to balance resources and flexibility perfectly. This highlights how customized onboarding strategies can lead to better outcomes.

Here’s a quick comparison of how different onboarding methods perform:

Onboarding Approach Average Adoption Rate Key Benefits

Interactive Walkthroughs 31% (HR products) Engages users immediately

Traditional Documentation 16.5% Allows self-paced learning

The HR sector stands out here, achieving a 31% adoption rate with interactive walkthroughs. This success comes from blending guided tutorials with hands-on practice, making it easier for users to understand and use features right away.

To track and improve onboarding outcomes, focus on these metrics:

• Time-to-adopt: How quickly users start using features.
• Feature usage patterns: How often key features are used.
• Post-onboarding retention: How many users stick around after onboarding.
• Tutorial completion rates: How many users finish guided sessions.

The best-performing companies focus on removing early hurdles. By studying user behavior and tweaking onboarding flows, they boost feature adoption significantly.

"The success of SaaS products heavily depends on how well users adopt their features. High feature adoption rates indicate that customers find value in the product, which is essential for satisfaction and long-term retention."

For complex B2B products, personalized guidance that adjusts to user actions works wonders. It provides help exactly when users need it, ensuring they fully understand the features. A well-optimized onboarding process not only smooths the initial learning curve but also keeps users engaged with the product over time.

7. User Behavior Analysis

Now that we've covered core usage, industry variations, and onboarding, it's time to dig into how users interact with your product's features. This step helps identify where users face challenges and uncovers areas to refine their experience.

Break down user behavior into three key areas: initial engagement (how quickly users start using the product), usage depth (how often users engage with features), and long-term adoption (how well users stick around). Focusing on these areas makes it easier to spot friction points in the user journey. For instance, companies in the HR sector often tailor their strategies based on specific user roles to address these issues effectively.

To track these behaviors in real-time, many organizations rely on analytics tools like Userpilot and Pendo. These platforms provide insights into user interactions, with adoption trends varying by industry and company size.

Keep an eye on metrics like time-to-first-use, interaction frequency, and retention rates to identify roadblocks and create targeted solutions. Segmenting users can also help uncover which features resonate most, leading to better engagement strategies. According to Artisan Strategies, using behavioral data to fine-tune conversion funnels can boost user engagement and retention, while also driving growth over time.

Implementation Examples

Several SaaS companies have successfully used feature adoption data to refine their products and boost user engagement. Here are some practical examples from different industries.

HR Software Success

HR software companies have improved user engagement by focusing on onboarding. For instance, a mid-sized HR platform enhanced its onboarding process with interactive walkthroughs and contextual help prompts. This approach led to a noticeable increase in user activity in a relatively short time. FinTech Feature Improvements

With FinTech adoption rates hovering around 22.6%, a growing platform partnered with Artisan Strategies to tackle low feature usage. By identifying drop-off points and simplifying the conversion funnel, they raised core feature adoption from 16.5% to 24.5%. Small Business Solutions

A SaaS company targeting small businesses used AI to personalize its onboarding process. By tailoring feature introductions to individual user behaviors, they achieved consistent improvements in user engagement across their customer base. Enterprise-Level Strategies

Larger organizations often face lower adoption rates, but segmentation and targeted strategies have helped them make progress. Their approach typically includes:

Check out our comprehensive guide: How SaaS Brands Build Long-Term Customer Loyalty.

• Data Collection: Tracking user interactions with key features.
• Analysis: Leveraging analytics tools for actionable insights.
• Optimization: Designing custom user journeys based on roles and behaviors.

These examples highlight how analyzing data, refining strategies, and adapting to user needs can drive feature adoption and engagement.

Conclusion

Analyzing the benchmarks and trends outlined earlier highlights key areas for improving feature adoption. While baseline metrics set the stage, success hinges on strategies customized to fit specific industries and company profiles.

Mid-sized companies with annual revenues of $5–10M stand out, achieving adoption rates of 30.4%. This points to a balance between available resources and operational efficiency. The data also reveals that sales-led companies slightly outperform product-led ones in adoption rates, underlining the role of personal interaction in navigating complex solutions.

Adoption rates between 20–30% are linked to better retention and more premium upgrades. This connection underscores how feature adoption directly impacts customer lifetime value, making targeted improvements critical.

For SaaS companies aiming to boost their adoption metrics, the focus should be on:

• Targeted onboarding: Use interactive walkthroughs and personalized experiences to guide users effectively.
• Continuous tracking: Monitor user behavior and adoption trends to identify opportunities.
• Data-driven improvements: Prioritize updates and feature development based on user insights.

Engaging professional consulting services can provide the expertise and proven methods needed to accelerate these efforts. With developments in AI and edge computing on the horizon, there’s potential for even greater innovation in feature discovery and user engagement.

"The success of SaaS products heavily depends on how well users adopt their features. High feature adoption rates indicate that customers find value in the product, which is essential for satisfaction and long-term retention."

FAQs

Here’s a quick look at common questions about feature adoption rates and what they mean for your product.

What is the average new feature adoption rate?

Based on the Product Metrics Benchmark Report 2024, which analyzed 181 SaaS companies, the average core feature adoption rate stands at 24.5%. However, adoption rates differ across industries:

• HR products typically see a rate of 31%.
• FinTech averages 22.6%.
• Insurance products are close behind at 22.8%.
• Mid-market companies (with annual revenues of $5–10M) tend to perform better, achieving rates around 30.4%.

What is a good feature adoption rate?

A rate of around 28% is often viewed as strong, but this can depend on your industry and how complex your product is. For example:

• HR products average 31%.
• AI & Machine Learning products come in at 24.8%.
• FinTech and Insurance products hover at 22.6% and 22.8%, respectively.

Higher adoption rates generally lead to better customer retention. When users see value in your product, they’re more likely to stay engaged and even explore premium upgrades. To improve adoption rates, consider factors like industry benchmarks, how complex your product is, who your users are, and how long it takes to implement features. Tracking these metrics can help SaaS companies refine their onboarding and engagement strategies to encourage growth.

Related reading

• 7 Customer Activation Metrics Every SaaS Must Track
• How to Build a SaaS Pricing Strategy That Converts
• Freemium vs Premium: Choosing the Right SaaS Model
• How to do conversion rate optimization for ecommerce
• How to hire a growth marketing expert

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