The stakes are high. According to recent industry data, the average SaaS free trial converts less than 25% of users to paying customers. That means roughly two-thirds to three-quarters of your trial users are walking away without ever becoming customers.

But the good news is that trial cancellations aren’t random. They follow patterns. Users drop off at predictable moments in their journey and struggle with the same features or tasks. Once you identify these patterns, you can systematically address them through trial optimization.

Understanding why trial optimization matters for reducing cancellations

Before diving into how to reduce cancellations, let’s be clear about what we mean by trial optimization and why it deserves your attention.

Trial optimization is the systematic process of improving every touchpoint in your free trial or freemium experience to increase the likelihood that users will see value, engage consistently, and ultimately convert to paying customers. It’s not about manipulation or dark patterns. It’s about removing unnecessary friction, clarifying value, and helping users succeed with your product.

The impact of effective trial optimization extends beyond conversion rates. When you optimize the trial experience, you also reduce customer acquisition costs, improve customer lifetime value, and build a stronger foundation for retention.

Understanding your specific trial model is the first step toward optimization. Different trial structures create different challenges and opportunities.

What is a freemium model?

The freemium model offers perpetual access to a restricted version of your product, either by limiting features or placing caps on usage. Think Spotify’s free tier with ads, or Canva’s basic design tools. The challenge with freemium is that users can stay indefinitely without converting. Your optimization goal is building reliance while strategically gating features that create urgency to upgrade.

What is a reverse trial?

In a reverse trial, users start with full access to all features for a limited time, then get moved to a freemium plan with limited capabilities. This approach, coined by growth leader Elena Verna, prioritizes maximum value upfront. Users experience everything your product can do, making the subsequent feature restrictions feel more pronounced. Trial optimization here focuses on ensuring users activate on premium features during that full-access window.

What is trial with payment?

This model requires payment information up front for full product access during a limited period. Users are charged automatically after the trial unless they cancel. The friction of providing credit card details means fewer signups but typically higher conversion rates, with opt-out trials converting at 49-60% compared to opt-in trials at 18-25%. Optimization here balances making signup worthwhile despite the friction while ensuring the experience justifies the automatic charge.

Five steps to audit and optimize your trial experience

Trial optimization looks different in each of these trial models, but one thing is true across the board: reducing cancellations requires a systematic approach.

You can’t fix what you don’t measure, and you can’t optimize what you don’t understand.

Here is a summary of the five-step framework for auditing your trial experience. For a detailed walkthrough, including specific templates and decision trees, see our article on auditing free user experiences.

Step 1: Identify drop-off points with data analysis

Examine your product analytics to pinpoint exactly where users abandon their trial journey.

• Track activation drop-offs in your onboarding flow
• Monitor which features users engage with versus ignore
• Calculate time-to-value and compare against churn timing
• Segment data by acquisition channel, trial type, and user cohort
• Layer in session recordings to see what users actually do before leaving

Step 2: Conduct user interviews to understand the “why”

Numbers show where users leave. Conversations reveal why.

• Interview 10-15 users, split between active trial users and those who churned
• Ask what value they found, what confused them, and what would make them pay
• Listen for the exact language they use to describe their experience
• Note any competitors or alternatives they mention for market context

Step 3: Benchmark your experience against market standards

Your users compare you to every tool they’ve used. Conduct some competitive analysis to gauge where you fall in the market.

• Document how competitors structure their trial experiences
• Screenshot monetization touchpoints, upgrade prompts, and limit notifications
• Study products your users mention in interviews, even if indirect competitors
• Identify where your experience creates more or less friction than market norms

Step 4: Map user actions with verb scoring

Break down every meaningful action in your product and score the friction required by running a verb scoring exercise.

• List discrete actions users can take (create, share, export, invite, etc.)
• Assign each a verb score from Anonymous to Gated
• Look for inconsistencies in how similar actions are gated
• Identify if you’re giving away too much or asking too soon

Step 5: Connect insights to create an optimization roadmap

Synthesize your findings to prioritize what to fix first.

• Friction without reason: unnecessary barriers compared to competitors
• Value leaks: popular free features that don’t drive conversion
• Invisible gates: paywalls users hit without understanding why
• Poorly timed friction: asking users to pay before they’ve seen value

Prioritize optimizations by impact (users affected), confidence (data supports it), effort (time to implement), and market alignment (are you an outlier).

Six strategies for reducing trial cancellations

Once you’ve audited your trial experience and identified optimization opportunities, you will have a clear roadmap for addressing issues.

Plenty of strategies might arise in your research. Here are a few themes we see often.

Accelerate time-to-first-value

The faster users experience value, the less likely they are to cancel. Industry benchmarks suggest that users should reach their first “aha moment” within 48 hours of signup.

Design your onboarding to guide users directly toward the action that delivers value. Use progress bars and checklists to create clear paths forward.

Remove any friction between signup and first value. If users need to integrate other tools, fill out profiles, or configure settings before experiencing core benefits, you’re creating opportunities for abandonment. Save non-essential setup for after users have seen value.

Provide personalized onboarding experiences

Companies using personalized experiences see conversion rates improve by up to 67%. Generic onboarding treats all users the same, but different user segments have different needs, different technical sophistication, and different use cases.

Segment users based on their role, company size, or stated goals during signup. A solo entrepreneur using your project management tool has different needs than a project manager at a 100-person company. Your onboarding should reflect these differences.

Use progressive disclosure to reveal features as they become relevant. Don’t overwhelm new users with every capability on day one. Instead, introduce advanced features once users have mastered the basics.

Implement strategic reminder systems

Trials between 7-14 days convert better than longer trials because they create urgency. But urgency only works if users remember they’re on a trial.

Send regular emails and in-app notifications informing users about remaining trial time. These reminders should do more than count down days. Each one should emphasize value, highlight features users haven’t explored, or address specific pain points.

Gate features strategically based on usage patterns

In our experience optimizing for SaaS, offering too many free features can actually hurt conversion rates. Users need to experience value from free features while simultaneously understanding what they’re missing from paid capabilities.

Place prompts for premium features adjacent to free ones. PDF Converter, for example, offers free file conversion but positions the premium, higher-quality option nearby. This ensures users understand the upgrade path without being pushy.

Use clear visual cues like lock icons, “Pro” badges, or color contrasts to differentiate free from paid features.

Provide proactive support during critical moments

Customer support engagement during trial periods can significantly boost conversion rates.

Don’t wait for users to ask for help. Implement triggered messages based on behavior patterns. If a user hasn’t logged in for three days, send a helpful email with tips. If someone tries to use a gated feature multiple times, offer a personalized demo or support call.

For high-value potential customers, consider human touchpoints. A quick call from customer success at day three of a 14-day trial can answer questions, provide personalized guidance, and significantly increase conversion likelihood.

Design thoughtful cancellation flows

Not every cancellation is preventable, but many are. When users attempt to cancel, use that moment as an opportunity to understand why and potentially offer alternatives.

Implement exit surveys that capture cancellation reasons. According to data on subscription churn, understanding why users leave is critical for preventing future cancellations. Are they leaving because of the price? Missing features? Poor onboarding? Bugs?

Based on cancellation reasons, offer segment-specific alternatives. If someone is canceling due to price, offer a discount or payment plan. If they barely used the product after the trial, extend the trial. If they’re leaving due to missing features, ask which features would keep them.

Common mistakes that increase trial cancellations

Even well-intentioned optimization efforts can backfire. Avoid these common mistakes that actually increase cancellation rates.

Making cancellation difficult

Some SaaS companies deliberately make cancellation difficult, requiring users to call or email rather than cancel with a simple click. This dark pattern might delay cancellations temporarily, but it can destroy trust and create negative word-of-mouth.

Make cancellation simple. The goal isn’t to trap users; it’s to create such a good experience that they don’t want to leave.

Gating core value too aggressively

If users can’t experience your product’s core value without upgrading, they’ll cancel before converting. The free version should deliver genuine utility while creating a desire for premium features.

Neglecting mobile trial experiences

With increasing mobile usage, trial experiences must work seamlessly across devices.

If your onboarding is desktop-optimized but breaks on mobile, you’re creating cancellations for a substantial user segment.

Sending generic email communications

Automated email sequences that ignore user behavior feel impersonal and often go unread. According to research on trial optimization, personalized communication based on user activity significantly outperforms generic campaigns.

If a user hasn’t logged in since signing up, an email about advanced features is irrelevant. If they’re actively using the product daily, countdown reminders may feel pushy. Segment communications based on engagement levels.

Trial optimization frequently asked questions

What’s the ideal trial length to minimize cancellations?

The optimal length depends on your product’s complexity and how quickly users can experience value. Simple products often perform better with 7-14 day trials that create urgency.

Complex B2B tools may need 30-60 days for users to properly evaluate capabilities. If you are completely lost, start with 14 days and adjust based on your activation data and time-to-value metrics.

Should I require a credit card for trial signup?

This decision significantly impacts both signup volume and conversion rates.

Opt-out trials (credit card required) convert higher but generate fewer signups. Opt-in trials (no credit card) convert lower but attract more users.

The right choice depends on whether you prioritize higher conversion rates per trial or a larger volume of trials and how much more utility the full tier offers versus a free trial.

Most product-led companies start with opt-in trials to maximize exposure, then consider opt-out trials once they’ve optimized the trial experience.

How can I tell if my trial cancellations are normal or problematic?

Track cohort-specific metrics. If certain user segments, acquisition channels, or trial lengths show notably different cancellation patterns, those differences reveal opportunities for targeted optimization.

What’s the most important metric to track for trial optimization?

While trial-to-paid conversion rate matters, activation rate is often more predictive.

Activation measures whether users complete key actions that indicate they’ve experienced value. Research shows users who reach activation are significantly more likely to convert.

Define your activation criteria based on behaviors that correlate with conversion, then optimize to increase the percentage of trial users who activate.

How often should I test and iterate on my trial experience?

Trial optimization is continuous, not a one-time project.

High-performing SaaS companies test constantly. Start with your highest-impact opportunities identified during your audit, then implement a regular testing cadence.

Track results for statistical significance before making changes permanent. Plan quarterly reviews of your trial metrics to identify new optimization opportunities as your product and market evolve.

Can I reduce trial cancellations without changing my product?

Yes. Many cancellations stem from poor onboarding, unclear value communication, or inadequate support rather than product deficiencies.

You can significantly reduce cancellations by improving onboarding sequences, providing better in-app guidance, personalizing the trial experience, implementing proactive support, and strategically positioning upgrade prompts.

That said, if users consistently cancel, citing missing features or bugs, product improvements may be necessary alongside trial optimization.

Build a systematic approach to trial optimization

Reducing SaaS trial cancellations isn’t about quick fixes or growth hacks. It requires systematic analysis of your trial experience, a deep understanding of user behavior and needs, and continuous optimization based on data.

The five-step audit framework provides a structured approach: analyze data to find drop-off points, interview users to understand why they leave, benchmark against market expectations, map actions with verb scoring, and synthesize insights into a prioritized roadmap. Each step builds on the previous one to create a picture of optimization opportunities.

Implementation matters as much as analysis. Accelerate time-to-value, personalize onboarding, implement strategic reminders, gate features based on usage patterns, provide proactive support, and design thoughtful cancellation flows. These six strategies address the most common causes of trial cancellations, but keep in mind that your analysis will likely surface other unique issues.

Most importantly, treat trial optimization as an ongoing discipline rather than a one-time project. User expectations evolve, competitors improve their experiences, and your product adds features. Regular review and iteration ensure your trial experience continues performing as your business grows.

At The Good, we’ve helped SaaS companies reduce trial cancellations and improve conversion rates through our Digital Experience Optimization Program. We conduct comprehensive audits using heatmaps, session recordings, and user research to identify exactly where trial users encounter friction. Then we build custom optimization roadmaps and validate improvements through experimentation.

Ready to reduce your trial cancellations and accelerate growth? Schedule an introductory call to discuss how we can optimize your trial experience for better conversion and retention.

The post How Do You Reduce Cancellations During SaaS Free Trials? appeared first on The Good.

Fritz O’Connor, former VP of Marketing at Ironman 4×4 America, exemplifies this approach. With over two decades of experience spanning manufacturing, sales, and marketing leadership, Fritz has developed a methodology for building high-performing organizations that deliver results consistently, even in challenging circumstances.

A marketing leader built for manufacturing

Fritz’s career journey reads like a masterclass in understanding customers across different industries. Starting in the printing and paper industry, he cut his teeth in structured sales training programs that taught him the fundamentals of professional sales and business operations.

“I’ve spent my entire career in sales and marketing roles. Almost exclusively in the manufacturing sector for companies that make stuff,” Fritz explains. This foundation in manufacturing would prove invaluable throughout his career, giving him deep insight into the complexity of bringing physical products to market.

His two-decade tenure at GE further refined his skills across diverse business environments. “We always used to say we can work in any industry, anywhere in the world, and still get paid by the same company,” he recalls. This experience working across plastics, appliances, and GE Corporate gave him a unique perspective on how great companies operate at scale.

But it was during his time at GE Corporate that Fritz discovered what would become his career-defining framework: differential value proposition (DVP). Working in a marketing consulting role with virtually every business in GE’s global portfolio, he helped launch this customer-centric approach to messaging and positioning throughout the organization.

This systematic approach to understanding and serving customers became foundational to Fritz’s ongoing success.

Implementing systems and frameworks that take teams from features to solutions

Originally coined by the founder of Valkre Solutions, Jerry Alderman, the DVP framework transforms how companies think about customer messaging and competitive positioning. Fritz became a master at implementing this methodology across diverse organizations.

“What are you offering? Be it a product or service that is better than the customer’s next best alternative,” Fritz explains. This might seem simple, but the implications are profound. Rather than competing on features or price, DVP focuses on solving customer problems in ways that competitors simply cannot match.

The challenge, as Fritz learned during his GE implementation, is that DVP represents a fundamental shift in thinking. "Every business, product, or service has a value proposition, but not every value proposition is differential. So many companies have the same value proposition. The white space is that differential part."

"It's about switching thinking from a feature to a benefit. For example, a blue appliance is not a differential value proposition. It's a feature."

Fritz teaches teams to make this shift by leading with problems and solutions.

"It's how it makes the consumer or customer's life better, how it solves that problem. You have to identify what the problem is. You have to articulate how you can fix that problem in a different way, better than anybody else."

This shift from features to solutions requires teams to understand their customers' actual problems, not just their stated needs.

For leaders, this translates directly into more effective product messaging, clearer value propositions, and ultimately, higher conversion rates.

Overcoming the "this is how we've always done it" challenge

One of Fritz's biggest career wins (and ongoing challenges) centers around implementing the Differential Value Proposition (DVP) methodology across organizations. The implementation at GE became both a success story and a learning experience in change management.

"As you can imagine, anytime you try and launch a new process in a company the size of GE, you can be met with resistance. Especially when you're coming out of corporate."

This resistance taught Fritz a crucial lesson about implementing change: "I don't view that as a challenge or a stumbling block, but as a fantastic and wonderful opportunity because when you flip those people, they become your biggest proponents."

His approach centers on listening first, then demonstrating value in the stakeholder's own language. "It's a listening journey. You've gotta understand what the challenges are that of the people with whom you're working, whether it's an external customer or an internal customer."

"Proactively listen and walk in the shoes of the people I'm working with. When I'm trying to introduce something as significant as DVP or other business tools."

This listening approach helps identify the real challenges and resistance points, making it possible to address them effectively.

The foundation: accountability, responsibility, and challenge

But having the right frameworks isn't enough. Fritz learned that execution depends on creating the right team culture. He is quick to credit his teams as the backbone of his successful projects, and one of the ways he supports them is with clear organizational principles.

"I have a few underlying business principles that I've gained along the way that are the foundational threads for me," Fritz explains. "One is, any team I work with or works for me, my job is to make them as successful as possible."

This people-first approach manifests through three guiding principles:

• Accountability: Holding yourself and your team responsible for deliverables and outcomes
• Responsibility: Taking ownership of significant business challenges
• Challenge: Embracing difficult problems that create meaningful business impact

"The way I do that is through three guiding principles, which are accountability, responsibility, and challenge," Fritz notes. "I want to be entrusted with significant responsibility that is helping to solve a significant business challenge."

These principles translate into a simple but powerful operational mantra: deliver on time, complete with excellence.

"I know those all sound like buzzwords, but they're not meant to be. And we don't treat them as such. We treat them as very simple guiding principles to keep us focused."

Putting it all together at Ironman 4x4

When Fritz joined Ironman 4x4 America, he found the perfect opportunity to apply all of these frameworks.

Ironman 4x4 is a global company that sells off-road parts and accessories for 4x4 vehicles (lift kits, suspension parts, bumpers, etc.). They have been around since the 1950s, but were new to the United States, so Fritz had the opportunity to find new ways to market their complex "fitment" products, or parts that must work with specific vehicle makes and models. This complexity creates both technical and marketing challenges that Fritz's team had to solve systematically.

His sales background gave him an invaluable perspective on marketing effectiveness. "If you spend any time in sales, that means you're around customers, whether those are B2B or B2C customers. And you learn what's important to them."

This customer proximity taught him the critical principle of "show me, don't tell me." Rather than relying on feature lists or industry awards, effective marketing demonstrates value through customer experiences and outcomes.

"We always, in both sales and marketing, it's easy to get into the trap of just talking, talking, talking, describing stuff, talking about features and benefits. Talking about the industry's best. Nobody cares about your industry. They care about how your product or service is going to impact them."

The key to marketing complex products, Fritz knew, is understanding how customers think about their problems. Rather than leading with technical specifications, the focus should be on the customer's end goal and the emotional drivers behind their purchase decisions.

Fritz emphasizes the importance of demonstrating value rather than just describing it: "Really, visual storytelling, video storytelling, placing the customer in the scene so they understand your value. That ability comes from firsthand experience of seeing that happen in the sales arena."

A data-driven website replatforming

His POV shaped everything he was involved in at Ironman 4x4 America, from new product introduction processes to website optimization. Fritz implemented structured new product integration toll gates with clear deliverables and cross-functional accountability, ensuring every product launch was executed with precision across creative, digital, and channel marketing.

His customer-centered thinking and frameworks proved essential when his team tackled a complex website migration from an outdated platform to Shopify. The project was based on their understanding that a website change was necessary to better serve their audience and increase ecommerce sales.

Working with The Good on a DXO Program, the Ironman 4x4 team executed the redesign and replatforming with data-driven methodology. Rather than relying on opinions about what the site should look like, they embraced rapid prototyping and continuous testing.

"Any decision made without data is just an opinion, right?" Fritz notes, referencing CEO Luke Schnacke's philosophy.

"We try to be very data-driven, which is why it was so important for us to work with The Good, to get that data and share it with the team managing the website replatforming so that they were making data-driven decisions on design and functionality."

They didn’t wait for a “perfect website” to figure out what customers wanted. They tested and got feedback throughout the entire process to make sure they were developing the right ideas.

"I realized we were never going to do it perfectly," Fritz recalls. The team was getting bogged down in opinions about checkout processes, product customizers, and overall site design. "We could end up using half our development budget on building something that doesn't perform."

"Ultimately, we agreed to launch and then test the heck out of it. We didn't want to overburden the development pipeline with projects that don't have a financial impact."

This represents a fundamental shift in thinking. They went from trying to build the perfect site to building a testable foundation for continuous improvement.

The beauty of working with The Good in this situation, Fritz explains, was "the rapid prototyping, the test and learn. We could very quickly get feedback and iterate and then test and learn again."

Multiplying results through partnership

Leveraging an external partnership accelerated progress beyond what internal resources could achieve alone and held the team accountable to the frameworks and goals of staying user-centered and data-driven.

"If you're not an expert, I would recommend doing a website project with a company like The Good. It wasn't a cost, it was an investment," Fritz emphasizes. "And I think that Ironman 4x4 is the beneficiary of the investment that they made with The Good as they migrated over to Shopify and learned about what customers would like."

The partnership enabled intentional, studied testing with proper dependencies and measurable results tracking.

"That whole test and learn methodology is done in a very structured, deliberate way. Making changes in a waterfall, with the proper dependencies articulated, and then tracking the measurable benefits of changes, and then tweaking accordingly from there."

This approach breeds confidence because it's entirely data-driven, removing guesswork from critical business decisions.

Lessons for marketing and sales leaders

For marketing and sales leaders looking to build similar operational excellence, Fritz's approach provides a roadmap: start with principles, understand your customers deeply, make decisions based on data, and never underestimate the power of strategic partnerships to unlock potential.

Start with principles, not tactics

Before implementing any marketing or optimization program, establish clear guiding principles. Fritz's framework of accountability, responsibility, and challenge provided a foundation that influenced every decision and created lasting organizational change.

Understand your customer's next best alternative

Move beyond feature-benefit messaging to understand what your customers would do if your solution didn't exist. This "next best alternative" thinking is the foundation of truly differential value propositions.

Convert resistance through understanding

When facing organizational resistance to change, focus on understanding stakeholder concerns rather than pushing solutions. Meet people where they are and demonstrate value in their language.

Embrace data-driven decision making

Resist the temptation to rely on opinions or best practices. Instead, create structured testing methodologies that let customer behavior guide optimization decisions.

Invest in external partnerships strategically

Recognize when external expertise can accelerate progress. The right partnerships provide capabilities and perspectives that internal teams may not possess, ultimately delivering better results faster.

Starting an optimization journey

Fritz's approach to building and scaling teams, including Ironman 4x4's US marketing operations, demonstrates how principled leadership, customer-centric thinking, and strategic partnerships can create sustainable competitive advantages.

"There's no obstacle too big that can't be overcome with data and optimization, right?" Fritz states emphatically. "The whole point of being data-driven and optimizing is to get time back and to become more efficient."

His advice for other leaders facing similar challenges?

"Get to yes. Figure out how to do it. Don't say, this is why I can't do it. Say this is how I'm going to do it. Here are things I need to do in order to do it. Then hold yourself accountable. Make it happen. Do it."

The secret, according to Fritz, lies in celebrating small wins that compound over time: "Little steps, I always like to say, celebrate the little wins. Go after the little wins because they compound on one another and then all of a sudden you're gonna look back and go, holy mackerel, I can't believe I am where I am."

The secret is consistency: "And it starts with data as your foundation and optimization as the accelerator."

For ecommerce leaders looking to build similar operational excellence, Fritz's framework provides a proven template: establish clear principles, understand customer problems deeply, make data-driven decisions, and never underestimate the power of strategic partnerships to accelerate growth.

Ready to optimize your ecommerce experience with data-driven methodology? Learn more about The Good's Digital Experience Optimization Program and discover how strategic partnerships can unlock your growth potential.

The Good helps ecommerce brands like Ironman 4x4 optimize their digital experiences through research-backed testing and strategic partnerships. Our team combines deep technical expertise with proven methodologies to deliver measurable results for growing brands.

The post Fritz O’Connor Stays User-Centered and Leads with Data During Uncertain Times appeared first on The Good.

Healthcare software companies can’t freely experiment with patient data. Financial technology firms face strict compliance requirements that limit onsite testing capabilities. Government contractors operate under security clearances that restrict user research. Insurance platforms must navigate complex regulatory frameworks. HR and ATS software handle sensitive employee data that requires careful privacy protection.

Experimentation seems nearly impossible under these circumstances, and the product-led growth strategies these teams see working for companies riding exponential growth waves like Linktree or Lovable can’t work for them.

These regulated SaaS companies still need to grow. They have the same fundamental challenges as any SaaS business: converting leads, reducing churn, and improving user experience. But the traditional growth toolkit doesn’t fit their reality, so let’s explore what can work.

The problem with product-led growth in regulated industries

Product-led growth has become the gold standard for SaaS success.

Companies like Canva, Grammarly, and Spotify have proven that letting users experience your product before purchasing leads to higher conversion rates, lower customer acquisition costs, and sustainable growth.

The strategy is to remove obstacles to product adoption, offer free trials or freemium versions, and let the product sell itself. These companies often move quickly and test new features relentlessly as a way to “hack” growth.

The product-led growth playbook includes:

• Free trials and freemium models that give users immediate product access
• Continuous A/B testing on live user experiences
• Extensive user tracking and behavioral analytics to optimize conversion funnels
• Rapid iteration based on user feedback and behavior data
• Self-service onboarding that guides users to their “aha moment“
• Viral growth loop, where users invite others or share content

And it works…for many. But regulated SaaS companies see these success stories and struggle to replicate them.

How do you offer a free trial for an HR tool that has to be rolled out across an entire organization to be useful? How do you minimize sign-up friction for a fintech software that requires bank information to function?

Experimenting with new features is too risky when system failure or emergency calling disruptions in telecommunications could result in massive fines.

Sometimes the stakes are too high for the product-led growth best practices that we see working in less-restrictive industries.

Regulated SaaS challenges are unique, and their growth solutions should be too

The challenges for this subset of SaaS companies are real and varied.

Compliance and privacy restrictions: Healthcare companies can’t freely test with patient data. Financial services face strict data handling requirements. Government contractors operate under security clearances.

Low traffic volume: Many regulated SaaS companies serve niche markets with limited user bases, making traditional A/B testing statistically impossible.

Long testing cycles: By the time regulated companies collect enough data from different regions and customer segments, it can take years to reach statistical significance. Different customers use different features across various geographical locations, making it difficult to design meaningful experiments that won’t disrupt service.

Risk-averse customers: Enterprise clients in regulated industries don’t want to be testing subjects for new features or experiences.

Resource constraints: Many regulated SaaS companies are highly technical but lack dedicated growth or UX teams.

Unique challenges require unique solutions, and that is what The Good can provide.

The alternative: off-site experiment-led growth

The solution isn’t to abandon growth optimization. It’s to use different methods that work within regulatory constraints.

This is where off-site experiment-led growth becomes the game-changer.

Experiment-led growth is a strategic approach that relies on continuous research, experimentation, and data-driven decision-making to drive business improvements. It allows teams to rapidly iterate on ideas that improve UX, marketing, and more.

Regulated SaaS can add an extra layer to experiment-led growth by taking things off-site or out of the product experience. Moving the growth tactics and experimentation away from the regulated environment and live user base gives teams the chance to make changes freely and quickly, gauge user reaction to those changes, and either launch with confidence or kill the ideas.

While product-led growth relies on in-product experimentation with real users, off-site experiment-led growth validates hypotheses and optimizes experiences before they ever touch your production environment. Instead of letting users test drive your product to discover value, you test drive your assumptions about users to deliver value immediately.

This approach flips the model to accommodate some of the restraints that regulated SaaS companies face. It’s no longer required to iterate on live systems with real customer data. There is an option to conduct experiments in controlled environments that don’t compromise compliance or risk customer relationships. You gather similar insights that drive product-led growth success, but through methods that work within constraints.

The result is a growth strategy that’s both data-driven and compliant, giving regulated SaaS companies access to the same optimization advantages that unrestricted companies enjoy, just through different means.

Off-site experiment-led growth tactics

Here are a few of the methods we use to deliver optimization outcomes for companies with the challenges and constraints outlined earlier in the article.

User testing

Because of the difficulty in getting customer data, there can be a disconnect between product teams and users.

Lookalike user testing solves this by bringing external participants who match the ideal customer profiles through your live experience. They complete tasks while thinking out loud, revealing friction points and confusion without exposing any sensitive data or requiring system changes.

This helps understand user behavior patterns, identify conversion barriers, and validate solutions, all without touching your production environment or compromising compliance.

AI-powered heatmaps and analytics

AI-generated heatmaps can predict user behavior with 92% accuracy without requiring any actual user data. These tools can analyze your interface and predict where users will look, what they’ll miss, and how long they’ll engage with different elements.

This is particularly valuable for regulated companies because you can understand user attention patterns and optimize layouts before the system is used.

Rapid testing

Experimentation is a proven way to get essential feedback on new features or website changes. And with A/B testing off the table in many regulated industries, rapid testing can fill in the gaps.

Unlike traditional A/B testing, rapid testing doesn’t require code changes, live traffic, or long research cycles. Instead, it uses a combination of techniques to validate hypotheses and inform decisions before anything goes live.

Rapid experimentation is not a one-size-fits-all process. Different scenarios call for different types of tests. Here are some common methods:

• First-click tests: First-click tests evaluate whether users can intuitively find the primary action or information on a page.
• Tree tests: Tree testing is a usability technique that helps you understand how users navigate through your website or app’s structure.
• 5-second tests: 5-second tests assess a user’s immediate impression of a design or message.
• Design surveys: Design surveys collect qualitative feedback on wireframes or mockups.
• Preference tests: This test involves showing users two or more design variations and asking which they prefer and why. It’s perfect for narrowing down visual or messaging options before launching a formal test.
• Card sorting: Card sorting is a research technique used to understand how users organize and categorize information.

These are just six of the many types of rapid experimentation.

While none deliver a 1:1 result when compared to A/B or multivariate testing, rapid experimentation offers a way for regulated SaaS companies to focus their development resources on work that has already shown positive signals from users.

For a tangible example, imagine a company struggling with positioning (a common challenge in technical, regulated industries). Five-second testing provides immediate feedback on messaging effectiveness. Users see your page for five seconds, then recall what they remember.

Competitive intelligence and market research

Structured competitive analysis and market research don’t require access to your own user base.

Understanding how competitors position themselves, what messaging resonates in your industry, and what user expectations exist can inform optimization decisions.

Also, gathering growth strategies from businesses in a similar industry with compliance or other restraints will offer a starting point to come up with new ideas that you can rapid test later on.

Getting started with optimization

Optimization can be intimidating and complex for regulated SaaS companies. Based on experiences working with teams like yours, here’s how to get started implementing growth optimization within your constraints.

1. Start with an audit or assessment of your current situation

Before making any changes, conduct a comprehensive audit of your current digital experience. This includes:

• Technical tracking setup to understand what data you can legally collect
• User journey mapping to identify critical conversion points
• Competitive analysis to understand industry standards and opportunities
• Stakeholder interviews to align on growth priorities and compliance requirements

2. Implement the methodologies we covered

Focus on techniques that provide insights without requiring on-site or in-product experimentation:

• User testing with 5-7 participants per user type (you’ll get 80% of insights from this small sample)
• Message testing to validate positioning and value propositions
• Prototype testing for new features or flows before development
• Heat mapping to understand attention patterns and interaction likelihood

3. Prioritize based on impact and compliance

Create a roadmap that balances growth potential with regulatory requirements. Focus on:

• High-impact, low-risk optimizations that don’t require system changes
• Messaging and positioning improvements that can be implemented quickly
• User experience enhancements that reduce friction without compromising security
• Qualification improvements to ensure you’re attracting the right prospects

4. Build your internal capabilities and outsource what you can’t

Many regulated SaaS companies lack dedicated growth resources. Consider:

• Training technical teams on user experience principles
• Establishing research processes that work within compliance frameworks
• Creating feedback loops between customer-facing teams and product development
• Implementing regular optimization cycles that don’t disrupt core operations
• Outsourcing what you just can’t manage internally

Growth within constraints isn’t impossible

Regulated SaaS companies don’t need to accept mediocre growth because of their constraints. They need different approaches that work within their reality.

The key is recognizing that optimization isn’t restricted to product-led strategies or A/B testing. Understanding your users, validating your assumptions, and making data-driven decisions can deliver outcomes that are just as impactful.

Whether you’re in healthcare, financial services, government, or any other regulated industry, growth optimization is possible. It just requires the right toolkit and a willingness to think beyond traditional approaches.

Making off-site experiment-led growth work within your regulatory constraints starts with a conversation. Learn what’s actually possible when you have the right methodology and expertise guiding your optimization efforts by getting in touch with our team.

The post Regulated SaaS Companies Need a Different Approach to Growth. What Actually Works? appeared first on The Good.

Most SaaS companies approach these upgrade opportunities with the same basic playbook: add an “Upgrade Now” button and hope for the best. But the companies exceeding their conversion goals understand something different: every upgrade scenario requires its own conversion-centered design strategy.

What is conversion-centered design?

Conversion-centered design is the practice of building digital experiences by making design decisions that serve a specific conversion goal. Unlike traditional user experience design, which prioritizes general usability and user satisfaction, conversion-centered design focuses on guiding users toward specific actions through strategic design choices.

In the case of SaaS upgrades, it’s about understanding the user behavior behind different types of SaaS upgrade decisions and crafting experiences that remove friction at precisely the right moments.

Beyond free-to-paid: the full spectrum of SaaS upgrades

Before we dive into design principles, let’s map the actual upgrade landscape most SaaS companies navigate:

Free trial to paid subscription

Free trial to paid subscription is the classic conversion challenge, where users evaluate whether your product delivers enough value to justify ongoing payment. Users typically weigh their decision based on factors such as feature completeness, onboarding success, and competitive alternatives.

Freemium to premium plans

In a transition from freemium to premium plans, users already love your basic offering, but need to justify paying for advanced features. This involves different psychology than trial conversions. You’re asking satisfied users to spend money, not preventing churn.

Plan tier upgrades

In tiered pricing plans, existing customers hit limits or need additional capabilities when considering an upgrade. These users are already paying, so the decision typically involves budget approval and feature value demonstration, rather than product evaluation.

Usage-based expansions

When customers exceed included allowances for API calls, storage, or monthly active users, they will often consider a usage-based upgrade. The decision here is often reactive rather than strategic, requiring different messaging and strategy.

Feature unlock purchases

In this scenario, individual premium features are available for one-time purchase rather than as part of a plan upgrade. Examples include advanced reporting, integrations, or compliance features sold separately.

Seat-based growth

In order to get tool access for the whole team, a user may need to purchase additional user licenses or a team account. This decision involves both the original user and new team members, creating complex decision dynamics.

Annual vs. monthly billing

Convincing users to commit to longer-term contracts for discounts is tricky. This upgrade isn’t about features, it’s about cash flow and commitment.

Each of these scenarios requires a different conversion approach because the user psychology, decision-making process, and friction points vary significantly. Let’s explore how conversion-centered design principles adapt to these diverse upgrade contexts.

The 7 principles of conversion-centered design for SaaS upgrades

Principle 1: Context-driven focus

Traditional conversion design emphasizes “creating focus” around the action you are leading users towards. In SaaS applications, that focus must be contextual. A user who has reached their storage limit requires a different focus than someone exploring premium features during onboarding.

How this works in practice:

For usage-based upgrades, focus should be immediate and solution-oriented: “You’re running low on API calls. Upgrade now to avoid service interruption.” Remove all other navigation options and make the upgrade path the primary action.

For feature exploration, focus should demonstrate value: “See how advanced analytics helped Acme Corp increase conversions by 34%.” Here, you can include secondary actions like “Learn More” or “See Example Report” because the user isn’t facing immediate urgency.

The key is recognizing where users are in their usage journey and matching your design focus to their mental state.

Here is a good example from Lovable. After creating a design, when you attempt to share it with your team, you are contextually prompted to “upgrade to collaborate.”

Principle 2: Progressive value architecture

Instead of dumping all premium features on users at once, structure your upgrade experience to build conviction progressively. This principle is especially important for complex SaaS products with multiple upgrade paths.

How this works in practice:

Design upgrade flows that reveal features progressively based on user engagement rather than showing everything upfront. Track which users click “Learn More” vs “Upgrade Now” to understand where additional information helps vs. hurts conversion. To implement, you can consider an upgrade architecture like:

Level 1: Immediate benefit

Lead with the single most compelling reason to upgrade based on the user’s current context. If they’re hitting usage limits, start with expanded capacity. If they’re in a specific workflow, highlight features that enhance that workflow.

Level 2: Supporting benefits

Once users engage with the primary benefit, introduce 2-3 supporting features that reinforce the upgrade decision. These should be directly related to their demonstrated usage patterns.

Level 3: Full feature set

Only after users show continued interest should you present comprehensive feature comparisons. Most users never need to see this level; they convert based on the immediate benefit alone.

Principle 3: Consistency across touchpoints

SaaS upgrades happen across multiple touchpoints, like in-app prompts, email campaigns, billing pages, and feature gates. Consistency across messaging, timing, and value presentation will support upgrade conversions.

How this works in practice:

• In-app feature gates: When users encounter locked features, the messaging should match what they’ll see on upgrade pages. If your feature gate says, “Unlock advanced reporting,” your upgrade page shouldn’t suddenly talk about “premium analytics.”
• Email upgrade campaigns: Match the urgency and tone of in-app experiences. If your app uses gentle nudges, don’t send aggressive “Last Chance!” emails. The psychological approach should feel consistent.
• Billing-triggered upgrades: When users approach usage limits, the upgrade flow should feel like a natural extension of their current experience, not a disruptive sales pitch.

Grammarly excels at this with its “writing update” emails, which share your usage statistics and include personalized upgrade benefits. They also maintain the same helpful, educational tone as their in-app suggestions. Users receive consistent value messaging whether they encounter upgrade opportunities in the app or via email.

Principle 4: Outcome-focused benefits

SaaS users don’t buy features, they buy outcomes. But different upgrade scenarios require different outcome framings. A user exploring premium features during onboarding has different priorities than someone hitting usage limits.

How this works in practice:

Use outcome language that matches your user segmentation research. Different user segments care about different outcomes, even for the same features. Your “productivity tools for SMBs” messaging should differ from “enterprise compliance solutions,” even if you’re selling similar capabilities.

Depending on the upgrade scenario, here are some examples:

• Trial-to-paid: Focus on productivity and competitive advantage outcomes. “Close deals 40% faster with advanced pipeline analytics”
• Freemium-to-premium: Focus on elevated capabilities and professional outcomes. “Transform from good to exceptional with premium design tools.”
• Plan upgrades: Focus on growth and scale outcomes. “Handle 10x more leads without adding headcount”
• Usage expansions: Focus on continuity and momentum outcomes. “Keep your growth trajectory without interruption.”
• Feature unlocks: Focus on specific workflow improvements, “Cut monthly reporting time from 8 hours to 30 minutes.”

Perplexity does this effectively by emphasizing the advanced capabilities you’re missing out on if you run out of your five free pro queries per day.

Principle 5: Friction-aware CTA design

Not every upgrade decision carries the same level of friction. Annual commitments create more friction than monthly upgrades. New feature adoption creates more friction than usage expansion. Your CTA design should account for these friction differences.

How this works in practice:

• Low-friction upgrades (usage expansion, monthly plan changes): Use direct, immediate CTAs. “Upgrade Now,” “Add More Storage,” “Increase Limit”. These can be prominent, high-contrast, and positioned aggressively because user resistance is low.
• Medium-friction upgrades (plan tier changes, feature unlocks): Use value-reinforcing CTAs: “Start Free Trial of Pro Features,” “See Premium Features,” “Try Advanced Tools”. Provide trial options or demos to reduce commitment anxiety.
• High-friction upgrades (annual contracts, major plan changes): Use progression-based CTAs: “See Pricing Options,” “Calculate Savings,” “Talk to Sales”. Focus on information-gathering rather than immediate commitment.
• Advanced CTA strategy: Implement dynamic CTAs that change based on user behavior. First-time feature gate encounters might show “Learn More,” while repeated encounters show “Start Free Trial,” and high-engagement users see “Upgrade Now.”

Principle 6: Social proof and trust building

The social proof that convinces someone to try your free trial won’t necessarily convince them to upgrade to enterprise features. Match your trust-building elements to the specific upgrade decision and user context.

How this works in practice:

• For security-conscious upgrades (compliance features, enterprise plans): Emphasize security certifications, enterprise customer logos, and compliance badges, “Trusted by Fortune 500 companies with the highest security standards”.
• For performance-driven upgrades (advanced features, professional tools): Highlight usage statistics and performance improvements, “Pro users complete projects 3x faster on average”.
• For team-based upgrades (collaboration features, multi-seat plans): Show team success stories and collaboration outcomes, “Marketing teams using our collaboration tools report 50% better campaign coordination”.
• For usage-based upgrades (expanded limits, additional capacity): Display growth-stage social proof, “Over 10,000 scaling companies choose our unlimited plan”.
• Trust-building implementation: Position trust elements where conversion anxiety is highest. For high-commitment upgrades, prominently display customer logos and testimonials. For usage expansions, emphasize reliability and uptime statistics.

Suno, an AI music creation platform, includes new feature upgrade options on the same page as featured creators, so you can see how popular artists are using features.

Principle 7: Conversion path optimization

Remove every unnecessary step between the upgrade decision and upgrade completion. However, “unnecessary” depends on the type of upgrade and user psychology. Some upgrades benefit from additional information, while others suffer from any delay.

How this works in practice:

• Immediate need upgrades (usage limits, access blocks): Minimize to single-click upgrades where possible. Pre-populate billing information, default to current payment methods, and confirm changes without additional steps.
• Exploratory upgrades (feature discovery, plan comparison): Allow for investigation without requiring immediate commitment. Provide detailed feature comparisons, trial options, and clear pricing information before asking for upgrade decisions.
• Team decision upgrades (enterprise features, multi-seat plans): Build in consultation and approval workflows. Provide team trial options, detailed ROI calculators, and easy sharing tools for decision-making groups.
• Budget-conscious upgrades (annual plans, major tier changes): Include savings calculators, payment plan options, and clear cancellation policies to reduce financial anxiety.
• Advanced optimization: Implement progressive profiling where users provide information gradually rather than all at once. For complex upgrades, break the decision into smaller commitment steps rather than requiring full upgrade commitment immediately.

The future of SaaS monetization design

SaaS upgrade optimization requires more than applying basic conversion principles to billing pages. The most successful companies understand that different upgrade scenarios require different psychological approaches, design strategies, and optimization metrics.

The 7 conversion-centered design principles are a great way to start doing just that.

But it’s not a one-and-done process. Iterate your designs and conduct user testing to figure out which upgrade paths are working and which aren’t.

As SaaS markets mature, upgrade optimization becomes increasingly sophisticated. Successful companies will move beyond the basics and:

• Embrace usage-driven monetization: Move beyond simple tier-based pricing to value-based and usage-responsive pricing models that require more nuanced upgrade design approaches.
• Implement AI-driven personalization: Use behavioral data to personalize upgrade timing, messaging, and pricing presentation for individual users rather than broad segments.
• Develop ecosystem-based upgrades: Create upgrade opportunities that span multiple products or services within a broader platform ecosystem.
• Focus on revenue expansion: Prioritize existing customer upgrade experiences over new customer acquisition as markets become more competitive.

Ready to optimize your SaaS upgrade experiences across every monetization touchpoint? The Good’s Digital Experience Optimization Program specializes in helping product-led companies design sophisticated upgrade experiences. Check it out and learn how you can take your business from product-market fit to sustainable scale with conversion-centered design techniques customized for your business and users.

The post Conversion-Centered Design: 7 Principles That Drive SaaS Upgrades appeared first on The Good.

But then the metrics start to roll in. Conversion rates are flat. Churn is up. Customer satisfaction scores haven’t budged.

Sound familiar? You’re not alone.

Most SaaS companies are stuck in a feature factory, churning out functionality users don’t want, don’t use, or actively avoid. While your competitors are optimizing the core experiences that drive growth, you’re polishing the peripheral features.

Here’s the uncomfortable truth: You’re probably building the wrong things.

The hidden cost of feature bloat

Low-impact features aren’t just harmless additions to your product; they’re silent growth killers. Every hour spent building or optimizing a feature that doesn’t move the needle is an hour stolen from something that could grow your business.

But what exactly makes a feature “low-impact”? It’s not about whether the feature works or whether someone, somewhere, might find it useful. Low-impact features are those that:

• Address edge cases rather than core user needs
• Generate minimal usage after launch
• Don’t correlate with key business metrics like retention or expansion revenue
• Create more complexity than value

According to research by UserPilot, the average core feature adoption rate is 24.5%. That means more than 75% of features might as well not exist from a user perspective.

When a SaaS company prioritizes those extra features, it is likely suffering from feature bloat.

Feature bloat is costly for your team, your users, and your business. An excess of features creates complexity and detracts from your product’s core value. Sometimes, feature bloat can actually prevent your product from doing its main job.

The cost of feature bloat develops quickly. Some examples include:

Development opportunity cost: While your team builds that quirky reporting dashboard that three power users requested, your core onboarding flow continues to hemorrhage trial users.

User experience degradation: Every new feature is another decision your users have to make, another item in the navigation, another potential source of confusion. Research from the Nielson Norman Group shows that feature bloat directly correlates with decreased user satisfaction and other industry experts agree. Jared Spool calls it experience rot and often highlights the inevitable complexity creep and user experience decline that occurs when teams add features without ruthless prioritization.

Technical debt accumulation: Low-impact features still need maintenance, bug fixes, and updates. They create dependencies that slow down future development and increase the risk of breaking changes.

Low-impact features don’t just waste resources; they actively prevent you from building high-impact ones.

Consider a hypothetical case of a B2B SaaS platform that spent six months building an advanced scheduling feature requested by their largest enterprise client. The feature worked beautifully for that one client, but sat unused by 98% of their user base. Meanwhile, their core product suffered a 60% drop-off rate during onboarding. This was a fixable problem that could have doubled their conversion rate.

The real kicker? That scheduling feature became a maintenance burden, requiring updates every time they changed their core platform. What started as a “quick win” became an ongoing resource drain.

Warning signs you’re in the feature bloat trap

It isn’t always easy to identify if and when you’re prioritizing low-impact features. Here are some of the common red flags that might make you think twice about how you’re building your roadmap:

• Lack of data: Decisions based on gut feeling rather than data-driven insights can easily lead to prioritizing the wrong things.
• The squeaky wheel syndrome: Your roadmap is driven by whoever complains loudest, not by what data shows you should build.
• Internal politics: Sometimes, features are prioritized based on the influence of certain stakeholders rather than their actual value to the user or the business.
• Fear of risk: High-impact features often involve more risk and uncertainty. Teams might opt for safer, less impactful options to avoid potential failures.
• Shiny object syndrome: New feature ideas consistently trump optimization of existing functionality, or the allure of new and trendy features can sometimes overshadow the importance of addressing core user needs.
• Short-term focus: A focus on immediate gains can lead to neglecting long-term strategic goals and prioritizing quick wins over sustainable growth.
• The metrics disconnect: You can’t clearly articulate how each planned feature connects to business outcomes like revenue, retention, or user satisfaction.
• Poor prioritization framework: Without a clear and consistent framework for evaluating and prioritizing features, it’s easy to fall into the trap of prioritizing the wrong things.
• The “just one more thing” mentality: Features keep getting added to releases because they seem small and easy.

The longer your team functions in the trap of any of these situations, the harder it is to change the behavior. So, if this resonates, try to get your team on board to shift behavior and implement some of the strategies we outline below.

A better way: Data-driven prioritization

The solution isn’t to stop building features, it’s to build and optimize the right ones. This means establishing clear criteria for what constitutes “high-impact” before you write a single line of code.

Start with the outcome, not the output

Instead of asking “What features should we build?” ask “What user behaviors drive business growth, and how can we encourage more of them?”

Implement continuous user research

Don’t just collect feature requests, use them as an opportunity to understand the underlying problems. Continuous research that includes things like regular user interviews, behavioral analytics, and feedback loops can help you distinguish between what users say they want and what actually drives value.

Continuous research also allows you to test assumptions before implementation. Including rapid testing in your workflow can help you get fast, early feedback on concepts from real users for better direction.

Let the data guide decisions

Base your prioritization decisions on data from user research, analytics, and market analysis so that you can focus on what users truly need and what will drive the most significant impact.

Use prioritization frameworks consistently

Tools like RICE (Reach, Impact, Confidence, Effort) or the ICE (Impact, Confidence, Ease) scoring model help you compare feature ideas objectively. The specific framework matters less than using one consistently.

At The Good, we use the ADVIS’R Prioritization Framework to guide our optimization strategy.

Measure everything

For every feature you build, define success metrics upfront. If you can’t measure whether a feature is working, you can’t determine if it’s worth the investment.

Consider the indirect impact

Sometimes, a feature might not directly impact a North Star metric but could have a significant indirect impact. For example, improving the onboarding experience might not immediately increase conversion rates but could lead to higher user retention and lifetime value in the long run.

Focus on your most valuable users

Part of building and optimizing the right features means understanding your users. If you haven’t, conduct a step-by-step user segmentation study to help identify your highest-value users. Then you can tailor feature prioritization and optimization to their use case before moving on to other segments. A feature that’s high-impact for one segment might be low-impact for another.

Embrace the power of “no”

The most successful product teams are ruthless about saying no to good ideas so they can say yes to great ones. Create explicit criteria for what doesn’t make the cut. It’s okay to say “no” to features that don’t align with your strategic goals or offer significant value.

Moving beyond the feature bloat factory

Breaking free from the low-impact feature trap requires discipline, but the payoff is substantial. Companies that master prioritization don’t just build better products; they build products faster, with fewer resources, and with much better business outcomes.

The goal isn’t to build everything your users request. It’s to understand what truly drives value and relentlessly focus on that.

Your roadmap should be a strategic weapon, not a wishlist. Every feature should earn its place through clear evidence that it will move the metrics that matter.

Stop building features. Start building value.

Struggling to identify which features truly drive growth? Our Digital Experience Optimization Program helps SaaS companies cut through the noise and focus on changes that move the needle.

The post The Biggest Roadmap Mistake: Prioritizing Low-Impact Features appeared first on The Good.

But this episodic style is falling out of favor with forward-thinking teams. The best product organizations are embracing continuous research, an always-on approach to gathering insights that allows for more user-centered, effective products.

In one study, 83% of designers, product managers, and researchers agreed that research should be conducted at every stage of the product development life cycle. But, only 36% of them are conducting research studies after launch.

How can they bridge the gap? With continuous research.

What is continuous research?

Continuous research is an “always-on” style of research, where product teams put practices and systems in place to habitually learn from users. Rather than conducting isolated research studies or sprints, it focuses on integrating regular research activities into the product development cycle.

Why continuous research?

The benefits of continuous research are plentiful. Gathering insights regularly means quickly responding to user needs/wants, making more data-driven decisions, and reducing spend on changes that don’t work.

According to research by McKinsey, there is a direct correlation between financial success and de-risking development by continually listening, testing, and iterating with end-users. Continuous research methods are proven to positively impact the bottom line, and you can feel good knowing that they also make your customers’ lives better.

However, the under-touted benefit of continuous research is that it makes everyone’s job at your company easier. Product teams get their questions answered faster. Developers don’t have to waste time on unfriendly user features. Sales can more easily connect with customers.

No one has to wait to get on a roadmap, because there is a constant cycle of feedback and user connection that is otherwise unattainable.

Continuous research methods

So, what specifically counts as continuous research? Plenty of methods would fall under this umbrella. Here are a few of our favorites to paint a picture of what continuous research looks like in action.

Regular user interviews

Open a time on your calendar to consistently fill with customer interviews. This consistent, lightweight user research can gather immediate feedback on new features or designs.

Regular usability testing

Find time to observe users interacting with your product. Do this often, and you will uncover patterns to improve your UX.

Ongoing collection of CSAT or NPS scores

Keep a record of customer satisfaction scores (CSAT) or Net Promoter Scores (NPS) to understand over time whether users are happy with your product. This consistent record will help you determine if product optimizations have helped or hurt your experience.

Cohort comparison through onboarding surveys

Conduct onboarding surveys and then compare cohorts over time to identify trends that may not be apparent in individual feedback sessions.

Lightweight prototype testing

Get feedback on designs from initial prototype to mid-fidelity to fully mocked up. Use the consistent feedback to iterate quickly and make immediate changes as you go.

Continuous research implementation strategies

With the benefits and methods clear, you might be ready to shift your culture towards continuous research. If so, here are a few implementation strategies to set you off on the right foot.

Start small and build up consistency

Begin with a single recurring research touchpoint, such as weekly user interviews or bi-weekly prototype testing sessions. You don’t need a comprehensive, always-on strategy when you’re just starting out. Starting small will get you into the habit, and then you can find ways to expand your efforts.

Put research on the calendar

Blocking time on the calendar for research will get you into the continuous research habit. Consider something like a Friday afternoon standing meeting that you can fill with customer interviews.

Teresa Torres, a well-respected expert and author of Continuous Discovery Habits, suggests you talk to customers every week. “Continuous discovery means weekly touchpoints with customers by the team building the product, where they conduct small research activities in pursuit of a desired outcome.”

The emphasis is on taking research from something you pause to do, into something you always do. Putting it on the calendar in a consistent cadence will help you stick to it.

Get the whole team involved

One of the best parts of continuous research is that it benefits the whole team… and the whole team can be involved! While continuous research may be led by a researcher, it can also be effectively led by product managers who incorporate it into their regular schedule.

Even if other teams don’t lead the process, get them involved by:

• Asking salespeople to ask one specific research question in each call
• Having designers build prototype testing into their workflows
• Sharing research findings across the organization

We have lots of expert insights on how to make B2B research work harder and get your team involved in the process, here.

Complement ongoing feedback with strategic research

Another great recommendation from Teresa Torres is to complement ongoing feedback with occasional deeper discovery work. When you have a higher-risk change or question, take the necessary time to do a deep dive into the data, testing, and analysis.

An always-on research strategy should ensure you’re solving the right problems and that you’re doing it effectively. A combination of lighter, continuous, and deep-dive research will make sure that happens.

Build your toolkit

Tools and technologies that enable continuous feedback will be a lifesaver during busy weeks when it would be easy to let research fall to the wayside. Set up automations and find the tools that make it easier for you to keep users scheduling, data collecting, and insights surfacing.

In the end, the value of continuous research comes from rapidly applying insights. These implementation strategies will create explicit pathways for research findings to influence product decisions within days, not months.

Who should leverage continuous research?

A shift to continuous research represents a cultural shift in product development. It’s not just a changing methodology; it’s a truly user-centered approach where customer feedback continuously shapes product direction. Most product teams would benefit from implementing an always-on research strategy, but it’s particularly valuable in a few circumstances.

Teams with limited resources

It might seem counterintuitive, but it is particularly valuable for teams that don’t have a big research budget. Even without the dollars to fund big studies, teams can leverage continuous research to uncover customer insights that guide development.

Growth-stage startups

It’s ideal for startups that are moving quickly to build and make decisions. They’re mostly throwing things at the wall to see what sticks, but continuous research can act as the safety net or gut check for those ideas. Run it by a customer and get some quick feedback instead of waiting to make mistakes in-market.

Products in rapidly evolving markets

If you’re in a market that is changing quickly, like AI, it’s a good idea to implement continuous research. It helps you adapt to evolving consumer needs more efficiently and to keep up with rapidly developing technological advancements. When you have an always-on research schedule, you can get your questions answered more quickly and implement changes shortly after.

Why “always-on” should be your new normal

Studies show that the compartmentalization of design, development, and research stages of product development “increases the risk of losing the voice of the consumer or of relying too heavily on one iteration of that voice.” Don’t let your organization fall into this trap.

User insights help teams innovate faster and build better products. The best teams today are those that learn from their customers as they build, putting the user experience at the center of product development and optimization. Consistent feedback loops allow them to deliver constant value and effectively respond to market changes.

As competition intensifies in SaaS, continuous research could be the difference between products that thrive and those that die.

If your team sees the value of continuous research but doesn’t have the resources to manage it in-house, The Good can help.

Our team of experts will be an on-demand research (and design and strategy) team that helps you get things done faster. No more waiting months to get your ideas on the roadmap.

The post Continuous Research: The Secret Weapon For Effective Product Teams appeared first on The Good.

What is going wrong? The most common assumption is a poor product experience, but something else could be the culprit: SaaS products take too long to deliver value.

If users don’t quickly experience how software makes their life better, they will delete the app or simply abandon their account.

If you find your users in this position, accelerating time-to-value should be at the top of your priority list. Reducing the time it takes a customer to find value in your product can increase customer satisfaction by 10% to 30%, which will have a direct impact on retention.

In this article, we’ll share how strategies like optimizing onboarding, personalizing the user experience, and implementing quick wins can help you improve time-to-value and reduce churn.

What is time-to-value (TTV)?

Time-to-value is the duration of time it takes a user to experience the value of your SaaS product. It measures the time lapsed from when a user starts engaging with your tool to when they have an ‘Aha!’ moment about the positive impact on their life.

Types of time-to-value:

• Time-to-basic value: A metric measuring the time it takes a customer to see any value from your product.
• Time-to-exceed value: A metric measuring the time it takes to exceed a user’s expectations about your product’s value.
• Long time-to-value SaaS: A product or service that takes a longer duration of time to realize value (sometimes weeks or months). Usually, for SaaS, this is true when it takes time to integrate systems or data. In this case, it’s important to demonstrate incremental value during the journey to full value.
• Short time-to-value SaaS: A product or service that meets an immediate need, such as a transactional software product with a one-time use.
• Immediate time-to-value SaaS: A product or service with an instant reward for customer actions, such as a picture resizing or link shortening software.

How to calculate time-to-value

The simple time-to-value formula is:
TTV = Time that value is realized – Time user starts engaging with your product

But while the concept of time to value is pretty straightforward, how you calculate it will vary.

Your unique product, user, and definition of value will help guide the inputs of your TTV formula. Here is a quick overview of how to calculate time to value for your business:

1. Define value: What does finding value mean in the context of your product? Usually, it is how long it takes a user to complete a specific task that showcases the core function of your product.
2. Define the start time: When do you start measuring the users’ path to value? What is the starting point of their journey? Usually, it’s during the registration or onboarding process.
3. Define the end time: What is the moment a customer realizes value for your product? You’ll likely need to conduct research to pinpoint the ‘Aha!’ moment (more on that later). Typically, it takes the form of achieving a specific outcome, uncovering a benefit, or reaching a milestone.
4. Calculate the duration: Measure the time between the start and end points. This is your time to value.

Source

Some examples of how actual SaaS companies measure time-to-value include: how long it takes for a user to upgrade from free to paid, how quickly users start a new project after onboarding, or how long it takes to get the first ROI from the tool.

Why is time-to-value important?

Time-to-value directly impacts product success. It is an early indicator of retention and churn, and can help uncover areas for optimization.

The metric is especially important for companies with freemium or free trial pricing models. When your monetization happens during the product experience, you need to show your value explicitly and efficiently. Time-to-value is a way to measure if you are doing so successfully.

How to improve time-to-value

Demonstrating your value early on takes your SaaS product from ‘nice-to-have’ to ‘can’t live without.’ Here are a few strategies to help you do it.

Identify your product’s ‘Aha!’ moments

To get to the ‘Aha!’ moments faster, you first need to understand what those eye-opening experiences are. What turns casual users into lifelong customers? What is the first product experience that clearly shows your product’s potential impact on a user’s life?

To identify those ‘Aha!’ moments (or the end time in your formula), there is nothing more effective than talking to and studying the users themselves.

With user research methods like session recordings, usability tests, interviews, and surveys, you can uncover the intrinsic motivations of your users and take stock of their goals. What you find in your UX research process will help identify which product experiences will be most valuable to them and help prioritize which to show off early.

For example, if a new user of your project management tool wants to gain transparency across their team, the product should show them how to do that before it does anything else.

It will be tempting to bombard new users with all the amazing features of your tool, but to provide the quickest route to value for each user, you have to understand their objectives and why they are exploring your tool in the first place.

Personalize the user experience

The meaning of value will vary across your user base and their unique needs. For example, a 10-strong team signing up for an analytics tool may find different early value than a one-person team looking to monitor their small business. Or someone who has less tech know-how might need more hand-holding, while someone already comfortable with complex systems might want to see more intricate aspects upfront.

That’s why it’s important to personalize the user experience to accelerate time-to-value.

It doesn’t have to be 1:1 personalization, though. There’s a good chance there will be groups of users who have similar goals. Gain insight into your users, identify patterns, and create experiences for those groups. Start with a few segments and then continue to add on personalization if you see it’s working.

Optimize the registration and onboarding experiences

One significant lever for accelerating time to value is improving early product experiences.

The ROPES framework, designed to help product-first leaders think about, optimize, and improve the end-to-end customer experience, shows how the R (registration) and O (onboarding) experiences might help or hinder TTV.

While the other elements of the customer journey can play a part, the biggest drivers for reducing TTV lie in those first stages of the product experience.

While there is no exact blueprint for optimization, there are some commonalities you can bear in mind for improving registration and onboarding:

• Take it slowly: The last thing you want to do is dump everything onto new signups. Avoid overwhelming by trickling out information and allowing users to go at their own pace.
• Put the user first: The best experiences focus on the needs of each individual user and what they need to know to get started.
• Leverage novel UI mechanisms: Make use of novel mechanisms like tooltips or a modal window to gently guide users through the registration onboarding process.
• Give clear step-by-step instructions: Clearly guide users through your registration and onboarding step-by-step. Make it straightforward to complete, and be sure to highlight your product’s use cases during the process.
• Follow good form design principles: Show clear progress, give feedback as they go, and group common information to make it easily digestible.
• Collect feedback: Track and measure how successful your process is by asking new signups for their feedback.

Your product experience should be fluid. The needs of your user base will change over time, and you must listen to user feedback if you want to continue to improve the experience and showcase your value more efficiently.

Implement quick wins for users

Quick wins are a great tactic for improving time to value. Get your new users to complete small actions quickly so they start to feel comfortable using your tool ASAP.

Quick wins create initial momentum for users, playing into the psychology that when you feel accomplished or successful, you’re inclined to continue succeeding. This is similar to basketball players who gain confidence as they continue scoring points (hot streak) or that feeling when you have a task list of chores to do and you begin crossing them off one by one. Momentum is something that is built and will carry users forward.

As you build their confidence with your tool, you can use those quick wins to show the valuable features or functionality that is relevant to them.

Measure and iterate

No product experience gets it exactly right the first time, and there are always ways to continue improving your time to value.

Just like your users are learning how to use your product, you’re also learning how they use it. The more clarity you get on challenges, use cases, and goals, the easier it’ll be to create a valuable experience early on.

Continuously test different journeys, tweak steps based on user feedback, and don’t forget to track everything you do to see what works and what doesn’t.

Signs your time-to-value is too slow

It’s true that there is always room for TTV improvement, but how do you know you have a big problem?

Here are some red flags to look out for:

• High churn or low retention rates: Customers are leaving your service early in their subscription cycle, usually the first 30, 60, or 90 days.
• Low upgrade rate: Users don’t upgrade on their own, and/or sales teams get resistance to any account expansion or new offering pitches. This means customers are either seeing too much or too little value on their current account level.
• Low engagement with core features: Infrequent logins or low engagement with your core product functions/features means users don’t see the value of your product.
• Poor NPS: The feedback you receive is largely neutral or even negative.
• High customer acquisition costs: When users abandon, and you have to replace lost users, your cost of acquiring new customers will increase.
• Customer success or sales complaints: Your customer success team spends almost all their time resolving issues, or the sales team can’t clearly show the ROI of your product.

If you see one or many of these red flags, it’s time to start a new UX research cycle and dig into where there is room to optimize and show your value earlier on.

To get an expert’s POV on the situation, reach out to The Good. We can help uncover where and why your users are dropping off, and help you fix it.

The post Accelerating Time-to-Value: How SaaS Products Get Users to ‘Aha!’ Moments Faster appeared first on The Good.

But I’m here to tell you that while you might be raring to take action, there is one more key step to ensure success: sharing the roadmap across your organization.

And by this, I don’t mean sending out a single ‘FYI’ Slack message and calling it a day. I mean real communication that fosters understanding and alignment for what you have outlined in your roadmap. The way you communicate your roadmap could make or break all the incredible product optimizations and plans you have in there.

When cross-departmental teams are on board with your roadmap, there is no question about plans or prioritization. The roadmap serves as a shared plan of action and keeps the organization on track for product goals.

Here’s how you do it.

Give your roadmap a home and start building visibility

The first step in communicating a roadmap across the organization is creating a home for it. It needs to be visible and accessible to your team. Ideally, it lives somewhere that is natural to your internal workflows/tooling and is frequently accessed by your team.

This could mean:

• Uploading to Google Drive or Sharepoint
• Pinning to a dedicated Slack channel
• Creating a shared Airtable or Notion base

For the perfectionists out there, there’s no one right or wrong way to store your roadmap. It will depend on your organizational structure, size, and goals.

Once you have a home for your roadmap, start building visibility. While it’s good for you to know your roadmap like the back of your hand, it’s even better for your teammates to get invested.

A siloed roadmap is a debilitated roadmap, so make sure various team leads can access it.

Tailor the messaging based on stakeholders

A good product leader can bridge the gaps and translate messages across teams. This is a skill you’ll need to leverage when communicating the roadmap across your organization.

The best messaging for sharing the roadmap will likely look different based on the stakeholders you’re working with.

Leadership

Generally speaking, organizational leadership prefers to focus on high-level goals and outcomes rather than the specific features you’ll use to achieve those goals. While this isn’t true for every leader, it’s a good place to start.

Focus on themes in your roadmap to explain to your leadership or external stakeholders what you hope to achieve and your expected performance. How you achieve it doesn’t really matter as long as you’re solving the problem.

Outline what you’re trying to achieve and share what this stakeholder audience will find most relevant. For example:

• Themes
• Objectives
• Initiatives
• General timeframes

Individual contributors

When sharing with individual contributors, you’ll likely want to get into more of the “why” and the “how” than you would with leadership. It may spur some debate, but it will allow your team to discuss tactics within the context of the theme and possibly come up with unique ways to achieve your goals.

More specifics will come in handy, including:

• Specific tasks and milestones
• Detailed timelines
• Ownership

Shoulder teams

There is also value in sharing the roadmap with people who might not always be part of the product strategy or executing the roadmap but can offer a lot of valuable input based on their experience in other areas of the company.

Connecting across departments and getting early buy-in makes teams work faster and ship better products.

The most effective products are built with human-centered product management in mind. This ​​approach creates products and makes decisions based on and for the user, and it also prioritizes collaborating with teams outside of the day-to-day work and connecting with them where they are.

Shoulder teams benefit from knowing more theoretical elements like:

• How the roadmap impacts their roles/department
• Overview of projects
• What benefits and value it can drive

In many cases, working with different experts means learning to speak their language and translating between teams. Getting everyone on the same page can be tough, but it is worth the effort.

Pick the right forum and format

“The medium is the message” is a mantra repeated by communications leaders around the world. The forum in which you share a message is equally as important as or even more important than the message itself. This rings true for sharing roadmaps as well.

A roadmap isn’t just a list of priorities; it’s a story of where you’re going and why. Sharing that story in the right forum builds alignment and trust, while sharing it in the wrong one can leave it overlooked.

So, what are some ways to communicate your roadmap beyond typical sharing methods like a presentation or email?

In our conversations with B2B research leaders, René Bastijans gave some tips on how to circulate research that can be applied to roadmap dissemination as well. Visibility is key to making sure that teams reference the roadmap and use it to help make decisions.

He builds alignment and visibility through what he calls “Learning Lunches,” 25-minute presentations with Q&A designed to share insights and keep everyone moving in the same direction. You can apply the same approach to your roadmap by creating an informal, open forum where teams can ask questions and gain clarity on how the roadmap impacts their work.

Get together to present the roadmap and share updates on progress. This more casual approach to a presentation offers learning opportunities for the team, helps them feel ownership over the product, and, in turn, continued buy-in.

Another effective forum for communicating your roadmap is one-on-one conversations with the team. While you may not be able to get to everyone at the organization, finding ways to share your plan in a more intimate environment fosters trust and helps show more individually what impact the roadmap will have on their role.

At your organization, a presentation to each team or even an email might be the right fit. Just be sure to leverage a dedicated time when your audience is focused and invested.

Make sure your roadmap drives growth

Your roadmap is more than a strategic document. It’s a powerful tool to align teams, prioritize efforts, and deliver better user experiences. But even the most thoughtfully crafted roadmap can only reach its full potential if it’s communicated effectively across your organization.

By giving your roadmap a visible home, tailoring your messaging to different stakeholders, and selecting the right forums to share it, you can foster alignment, buy-in, and momentum for your product vision. Thoughtful communication transforms your roadmap from a static plan into a shared mission.

If you’re looking to build a customer-centric roadmap or need help identifying the highest-impact opportunities for your product, The Good can help. Our team of digital experience experts partners with companies to uncover customer insights, prioritize optimizations, and deliver measurable results.

Let’s work together to turn your product roadmap into a growth-driving force.

The post How To Communicate Your Roadmap Across The Organization appeared first on The Good.

So, as a leader, it’s important to adapt. Kalah Arsenault knows this well.

Over the course of her career, she’s been tasked with everything from turning data into actionable insights and advocating for data-driven analysis to building experimentation programs.

Currently, she leads the marketing optimization team at Autodesk, the global leader in 3D design, engineering, and entertainment software.

We had the chance to sit down with her and get the inside scoop on:

• Standing up an A/B testing program
• A simple prioritization model making an impact
• Measuring and circulating optimization learnings

Marketing optimization for a leading software company

As the marketing optimization team lead, Kalah digs into all the nooks and crannies of the company’s marketing efforts to make it more effective and efficient.

The marketing optimization team at Autodesk sits on the operations team at the intersection between marketing operations and technology. Partnering with marketing teams to improve campaign effectiveness, Kalah and the marketing optimization team bridge the gap between data, marketing know-how, and testing expertise.

When shakeups a few years ago halted all A/B testing on the Autodesk website, Kalah was eager to partner with the website team to re-enable experimentation. A self-proclaimed marketing, analytics & optimization enthusiast, Kalah brings a consistent data-backed ethos to her work. And her background tee’d her up for success. Kalah jump-started her professional life in advertising and ecommerce. The experience working in stakeholder-facing roles gave her a unique ability to turn data into stories and prove the value of iterating your way to success.

Standing up an A/B testing program

The challenge was clear. Without an experimentation program in place, the team was left without the data needed to fuel good decision-making.

“The data will tell you what is the right choice and it takes decision-making out of the process,” she said when asked how data plays a role in her decision-making. It can even go so far as to be said that they don’t just affect the process, they are the process. “Experimentation and data can be the decision-making process.”

So, it was crucial to get the A/B testing program back on its feet in order to bring that clarity to the work she was doing day-to-day.

To start, Kalah and her team put their experience into practice, creating an A/B testing roadmap. This was a crucial step, requiring them to define goals, align with stakeholders, and assess priorities and risks of optimization. Because of a new organizational structure, on top of the complexity of rebuilding the A/B testing program, there was an added obstacle to working across different marketing teams.

The optimization and web teams worked together to establish clear parameters, agreements, and definitions of what could or could not be tested. There is now a huge, pre-approved sandbox to play in, allowing optimizers the chance to find iterations that improve UX and marketing KPIs.

Whether you’re a researcher, an analyst, a marketer, or an optimization specialist, a well-made roadmap connects you with the clear steps needed to begin experimenting.

For Kalah, this meant:

• Identifying objectives for the testing program
• Establishing marketing and website challenges
• Isolating testing opportunities
• Formulating testing hypotheses
• Prioritizing testing opportunities

With frameworks in place, they were ready to get back to work.

While other optimization leaders can follow a similar strategy of aligning with stakeholders and building a roadmap, standing up an A/B testing program is no small feat. So, if you don’t have the resources or a dedicated team like Autodesk, she has some advice.

“What I primarily suggest is hiring someone who specializes in the practice. I think the expertise to identify optimization opportunities, design the tests, see it through implementation, measure the results, and provide recommendations and next steps is incredibly impactful.”

And while there are some savvy marketers that can do this, she emphasizes that “it's a separate skill set and expertise.” So whether you hire for that as a full-time role or you look to agencies to bring that expertise, Kalah strongly recommends companies consider experts to lead the charge.

For example, “at a high level, a test may show one version outperforming another,” she says. “But digging deeper often reveals different results by segment, whether by job profile, country, or industry. We aim to look beyond primary KPIs to fully understand what’s driving the outcome.” That level of nuance is hard to find in a busy marketer, so it’s best to have dedicated optimizers around who can take the time to know and understand audiences.

A prioritization model to drive velocity

With the A/B testing program back up and running, Kalah and her team had their plates full finding efficiencies and improvements across Autodesk’s marketing efforts.

Not only were there opportunities identified in their research, but teams across the organization were submitting requests and ideas for their consideration.

The list was long. The optimization team wasn’t sure what the “most important first thing” to work on was, and marketing stakeholders didn’t understand why their projects weren’t top of the list for testing. There was an opportunity to clarify and get more done quickly.

The solution? A prioritization model aimed at:

• Increase testing volume
• Aligning teams
• Saving time

While lots of testing folks would hear “prioritization model” and go straight to the mathematical elements, Kalah needed a model that was simple, easy to calculate, and transparent for all parties.

Kalah and her team built out an auto-calculated prioritization model as part of their optimization requests intake process. It involves three elements:

• Business impact: Measured based on whether the request aligns with the marketing plan, which is agreed upon by everyone from CMO to entry-level marketing team member.
• Level of effort: Internal criteria that identify a higher or lower level of effort.
• Urgency: Assess the request with questions like: Does it need to be executed immediately? Does it impact a larger project immediately? Does this effort have backing from a senior leader in marketing?

The intake process asks questions related to the criteria mentioned, and then logic set up in Asana auto-calculates the prioritization of the experiment or optimization. “This is what saves us time and energy,” she says. It eliminates looping conversations and time to manually prioritize things amongst the team.

Kalah emphasizes the power of this setup. “We don't do mathematical calculations to assess the level of business impact or length of time to reach statistical significance. That's too resource-intensive, and we'd be spending all our time assessing and prioritizing. With our automated prioritization model, we can spend our time on launching and analyzing tests and making business impact.”

And it worked.

“We were able to double the amount of tests our team took on within one year. So from this compared to last year we doubled the volume of testing with a new operating and prioritization model.”

Measuring marketing optimization success

The volume of tests is just one of the key metrics Kalah identified for measuring her team’s success.

It can be tough to find just one KPI to prove the value of optimization, given the nature of working across teams, products, and audiences. So, instead of focusing on 1:1 measurement, they look at a variety of metrics, including:

• Volume of tests
• Volume of analyses
• Customer satisfaction score
• How many marketers are seeing/learning from the findings

In the end, her team’s goal is to look at how marketing campaigns are performing and then give advice on how to make them better. So, while each test or optimization has its own KPI related to growth, as a team they are measured more holistically.

With prioritization and test volume locked down, she is ready to move the needle on insights shared.

“I'd really love to put more energy towards amplifying the impact of each test and getting the findings out to as many marketing teams as possible. We've already seen this working through a newsletter that's sharing our testing results and analysis work. We've also been hosting quarterly brown bag style meetings with the most universally applicable test results that marketers could implement themselves.”

This year, Kalah is also hoping to find new ways to turn insights into action. “I am also hoping to dive into data visualizations and figuring out how to make our findings more snackable and basically getting to a place where people want to read them and it's easy and enjoyable.”

These goals directly align with her team’s measurements for success. Other optimization leaders can take a page from Kalah’s playbook here by letting individual tests focus on the marketing metrics and determine departmental success based on insights, experiments, or other relevant measurements.

How can you replicate some of Kalah’s success?

Kalah’s advice to those new to optimization is simple yet impactful: start small, and stay curious. “Get to know your data, experiment with tools, and don’t be afraid to make tweaks,” she says. “You might be surprised at the impact even small changes can have.”

Her overarching message is one of optimism and opportunity. “Optimization is about evolving and improving—for your customers, your organization, and yourself,” she concludes.

Yet, good optimization leaders know that you can’t do it all alone. Internally, Kalah’s team employs a mix of full-time employees, contractors, and agency partners to meet the demands of scaling optimization efforts. “Contractors and agencies can help manage peaks in the workload,” she notes.

“I come from an agency background. I've always been a fan of working with full-time employees, but I realized as we're trying to scale and grow the amount of impact we're making as a team, it's really important to have contractors or agency partners to support higher demand and the peaks and valleys of work.”

By embracing a data-driven mindset, prioritizing strategically, and fostering cross-team collaboration, Kalah exemplifies what it means to lead impactful optimization efforts. If you need an expert partner to help manage a robust roadmap, get to know our Digital Experience Optimization Program.

The post How Kalah Arsenault’s Team Stood Up An A/B Testing Program & Doubled Volume With A New Prioritization Model appeared first on The Good.

Heuristics play a crucial role in how customers navigate and perceive digital experiences. So, we developed a framework called the Heuristics for Digital Experience Optimization to theme common optimization issues and opportunities through the lens of heuristics.

Leveraging the tool keeps users at the center of analyses and, when done correctly, ensures your strategy creates journeys that feel familiar, do what they say, and function intuitively.

One of the six Heuristics for Digital Experience Optimization focuses on incentives. In this article, we’ll explore how SaaS teams can leverage the Incentives Heuristic to build better user experiences and ultimately increase referrals through a well-done SaaS referral program.

How does the Incentives Heuristic work?

The goal of the Incentives Heuristic is to find opportunities for digital experiences to motivate users to take action. For example, sharing promotional offers or guarantees to get a user to register, convert free-to-paid, or make a referral would fall under the Incentives Heuristic.

Instead of relying on discounts, which have historically been the go-to to incentivize an action, digital experiences that adhere to this heuristic typically incentivize with offers that add value for the user and don’t devalue the product, such as bonus features or upgrades.

One great way to leverage the Incentives Heuristic is to build a referral program.

The power of a SaaS referral program

Well-done SaaS referral programs leverage incentives to encourage existing users to promote your tool.

The goal is to harness word-of-mouth referrals and increase product relevance and reach.

SaaS referral programs work well because they systemize the referral process and make it easy for users to share products with their network. And with 86% of B2B buyers saying word-of-mouth is the most influential factor in making purchase decisions, it’s an incredibly important part of the sales cycle.

Referral programs are effective for SaaS companies because of the social nature of tools. Professional peers frequently share their favorite tools and discuss new options in their communities. Incentivizing these conversations makes them mutually beneficial.

It’s a win-win. Your customer receives valuable incentives and trusted recommendations while you generate an organic growth cycle and harness positive network effects.

Viral growth loops

A growth loop is a compounding referral motion that leverages existing users to grow your user base through referrals. Referrals help keep marketing expenses low and increase the potential value of every new user.

Unlike traditional funnel frameworks, growth loops turn each interaction into a chance to draw in new users. When they start spinning on their own, they lead to lower customer acquisition costs and increased loyalty.

Positive network effects

SaaS referral programs that center on user benefits and incentives create positive network effects.

A positive network effect is when the value of a SaaS tool increases as the user base grows. For many companies, this larger user base leads to increased retention, bigger advertising budgets, unique user-generated content, improved user trust, and more.

How the best SaaS referral programs incentivize users

As mentioned, a straight discount or percentage off isn’t always the right way to incentivize referrals. Here are a few ways SaaS tools creatively incentivize users AND show the value of their product.

Service upgrades

Companies can incentivize referrals by offering upgraded account status. For example, Trello rewards referrers with one month of their “Premium” level service for each signup, up to 12 months. This gives users access to a new service level with a variety of new features and member benefits.

Dropbox pioneered the dual-sided incentive model, rewarding both the referrer and the new user with additional storage space. Referrers earn 500 MB for each successful referral, while new users receive 500 MB upon signing up, creating a viral loop that significantly boosts their user base.

Premium features

Some companies offer access to specific features as part of their referral program to add value for users while showing off the capabilities of their products. Evernote uses a points system where users can redeem points to unlock premium features. This tiered reward system encourages multiple referrals and gamifies the process.

Value-based offers

Another way to incentivize users is to offer a product that aligns with your tool’s value proposition. GetResponse combines financial rewards with educational incentives by offering the referrer and the new user a $30 reward alongside a digital marketing certification valued at $200 after three successful referrals. This approach aligns with the professional development goals of many users.

Credits

While we don’t necessarily recommend cash rewards or discounts, credits can be a valuable way to drive referrals. Airtable provides a $10 account credit for each referral, and DigitalOcean offers a $200 credit for new users to explore their services for 60 days. Referrers earn a $25 credit once the referred user spends their first $25, making it attractive for both parties.

Best practices for a SaaS referral program that leverages the incentives heuristic

Once you have the idea to build a SaaS referral program or optimize an existing one, these are a few best practices to keep in mind.

Stay user-centered

The key to building a successful SaaS referral program is to prioritize the user. Conduct research to understand what they want and tailor the program to their needs.

Your rewards structure should be based on what motivates them, and then the UX should be seamless to your digital platform. For example, provide easy-to-share unique referral links and offer in-app dashboards for users to track their referrals and rewards.

Also, make the act of referring intuitive, reminding users when it is natural to the actions they’re already taking. By integrating these incentives directly into their digital experience, SaaS companies make referral programs an engaging and rewarding part of using their products.

Gamify the rewards system

Make your referral process fun, easy, and satisfying to refer users. One way to do this is to gamify the experience. Gamification is the use of game mechanics in nongame contexts, and many SaaS companies do this extremely well in their actual product experience but not necessarily in their referral experience.

Leveraging gamification to find ways to make tasks more engaging and to make the referral process entertaining encourages users to track their success, refer more customers, and unlock rewards.

Align incentives with your value proposition

Incentives work best when they’re aligned with what makes your product compelling, so your first step is to clarify your offer and/or value proposition.

Ask yourself: What core action do users find most valuable? What helps them realize the most value from your product?

Then, incorporate incentives that encourage users to make referrals. These don’t have to be financial rewards. Sometimes, the product’s value is plenty, like in the case of Dropbox where users get more storage (the product’s primary value) for sharing. Closer alignment to the value will encourage more sharing.

Strategically place incentives throughout the user journey

Users love incentives like upgrades, guarantees, and other promises, but can fail to see them when they are in the thick of purchase indecision, comparing a number of other variables.

Placing key incentives near CTAs can increase the visibility of the offer and increase conversion readiness.

Incorporate optimization

There is no one-size-fits-all referral program or incentivization strategy. To find what works for you, test and validate ways to make sharing a natural part of your product experience.

Some tools you can leverage to iterate on the experience include rapid experimentation, user testing, A/B testing, or simply talking to your customers or customer service team to identify pain points.

And if you aren’t sure how to do this on your own, hire an expert for support.

Incentivize referrals to spur SaaS growth

So, now you have a starting point for building a strong referral program with heuristics in mind. But, the Incentives Heuristic is only one of the six Heuristics for Digital Experience Optimization. The full list includes:

• Priming & Expectation Setting
• Trust & Authority
• Ease
• Benefits & Unique Selling Points
• Directional Guidance
• Incentives

Each heuristic can help you identify and theme optimization issues or opportunities. These are the building blocks for a theme-based roadmap and are indispensable for any data-backed product team.

At The Good, we leverage the heuristics and work with your team to implement optimizations and build viral loops that help you scale faster. Learn more about how we increase referrals and get in touch here.

The post Building Viral Growth: Leveraging Incentives in SaaS Referral Programs & Strategies appeared first on The Good.