Sales & Conversion
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Picture this: You're celebrating because your sign-up conversions are through the roof. Marketing is high-fiving each other, the CEO is happy, and everyone thinks the growth engine is finally working. Then reality hits—90% of those users vanish after day one, and your trial-to-paid conversion rate is absolutely terrible.
Sound familiar? This exact scenario landed on my desk when a B2B SaaS client called me in desperation. They had tons of signups but zero meaningful adoption. Their beautiful funnel was optimized for all the wrong things.
What I discovered completely flipped my understanding of user adoption. Sometimes the best way to improve adoption isn't making things easier—it's making them intentionally harder. I know, it sounds counterintuitive. But stick with me, because the results speak for themselves.
Here's what you'll learn from this real-world experiment:
Why optimizing for signups actually kills user adoption
The psychological principle that makes "friction" increase commitment
How to design qualifying steps that filter for serious users
Real metrics from adding "barriers" to the signup process
When to use this approach (and when to avoid it completely)
This isn't another "optimize your onboarding" guide. This is about fundamentally rethinking what successful user adoption actually looks like.
Industry Reality
What every startup founder believes about user adoption
If you've read any growth blog in the last five years, you've heard the same advice repeated everywhere: "Reduce friction at all costs." Remove form fields, eliminate steps, make everything one-click, and streamline the user journey until it's frictionless.
The conventional wisdom goes like this:
More signups = more success (optimize for volume)
Friction is the enemy (remove every possible barrier)
Speed is everything (get users to "aha moment" instantly)
Simplify, simplify, simplify (complexity kills conversion)
A/B test your way to perfection (incrementally optimize each step)
This advice exists because it works—for certain metrics. You absolutely will get more signups by removing form fields. You definitely will see higher conversion rates by eliminating steps. The data doesn't lie about that.
But here's where the conventional wisdom falls apart: it optimizes for the wrong outcome. Most companies obsess over signup rates while completely ignoring the quality of those signups. They celebrate vanity metrics while their actual business metrics—engagement, retention, trial-to-paid conversion—suffer.
The reality is that sustainable growth doesn't come from maximizing the number of people who try your product. It comes from maximizing the number of people who actually adopt and stick with your product. And those are two completely different problems that require completely different solutions.
The industry has confused "getting people in the door" with "getting the right people in the door." That's a costly mistake.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When this B2B SaaS client reached out, their problem seemed straightforward on the surface. They had a decent product, solid marketing, and signups were coming in consistently. From the outside, everything looked like it was working.
But when we dug into their analytics, the story was completely different. Sure, people were signing up—but they weren't sticking around. Most users would log in once, maybe twice, then disappear forever. Their trial-to-paid conversion rate was embarrassingly low.
The client was a project management SaaS targeting marketing agencies. Their signup flow was "optimized" based on all the best practices: minimal form fields, instant access, no credit card required. Marketing was driving traffic from cold sources—paid ads, SEO, content marketing—and funneling everyone through the same frictionless signup process.
Here's what I observed: The people signing up had no skin in the game. They were tire-kickers, comparison shoppers, and people who stumbled across the product without any real intent to use it. The ease of signup attracted everyone, including people who had zero intention of actually adopting the product.
My first instinct was to follow the playbook—improve the onboarding, add more tooltips, create better tutorials, send more email sequences. We tried all of that. It helped a little, but it didn't solve the core problem.
That's when I had a realization: What if the problem wasn't that our onboarding was too hard? What if the problem was that our signup was too easy? What if we were attracting the wrong people in the first place?
The client thought I was crazy when I suggested we make signup harder, not easier. But they were desperate enough to try anything at that point.
Here's my playbook
What I ended up doing and the results.
Here's exactly what we implemented, step by step:
Step 1: Added Credit Card Requirement Upfront
Instead of "no credit card required," we required a credit card for the trial. This wasn't about charging people—it was about signaling commitment. People who are willing to enter their payment info are demonstrating they're serious about potentially using the product.
Step 2: Extended the Qualification Process
We added specific qualifying questions during signup:
- What type of agency do you run? (with specific options)
- How many team members will use this?
- What's your current project management process?
- What's your biggest challenge with project management?
These weren't just form fields—they were commitment devices. Each question required thought and investment from the user.
Step 3: Introduced a "Setup Investment"
Instead of dropping users into an empty dashboard, we required them to complete a meaningful setup process: import their first project, invite team members, and define their workflow. This took 10-15 minutes of genuine work.
Step 4: Segmented Based on Responses
The qualifying questions weren't just for show—we used them to customize the entire experience. Different agency types got different onboarding flows, different templates, and different email sequences.
The Psychology Behind It:
We were leveraging what behavioral economists call the "effort justification effect." When people invest effort into something, they value it more highly. By requiring meaningful investment upfront, we were actually increasing perceived value and commitment.
But here's the key: we weren't adding meaningless friction. Every "barrier" we added served a purpose—it either qualified the user, customized their experience, or required them to take a meaningful action that would improve their likelihood of success.
The results were immediate and dramatic. Yes, our signup rate dropped—but our engagement rate skyrocketed. More importantly, the people who did sign up were the right people. They were qualified, motivated, and actually needed what we were offering.
This approach works because it solves the fundamental misalignment in most SaaS funnels: marketing optimizes for quantity while the business needs quality. By adding intentional friction, we aligned the incentives and attracted users who were more likely to adopt and convert.
Effort Justification
When users invest effort upfront, they're psychologically committed to getting value from that effort. This creates a self-selection mechanism for serious users.
Setup Investment
Requiring meaningful setup work (importing data, configuring workflows) ensures users have skin in the game and are more likely to see initial value.
Quality Over Quantity
A smaller number of highly-qualified users will always outperform a large number of unqualified users in terms of business outcomes.
Segmentation Power
Using qualification data to customize the experience makes every subsequent interaction more relevant and valuable to the user.
The transformation was remarkable. Signups dropped by about 40%, which initially made the marketing team nervous. But every other metric improved dramatically:
Trial Engagement: Users who completed the new signup process were 3x more likely to log in during their second week. They weren't just creating accounts—they were actually using the product.
Feature Adoption: Because we segmented users based on their responses, we could guide them to the features most relevant to their specific situation. Feature adoption rates increased across the board.
Trial-to-Paid Conversion: This was the big one. Our trial-to-paid conversion rate more than doubled. Yes, we had fewer trials, but a much higher percentage converted to paying customers.
Most importantly, the quality of feedback improved. Instead of generic "this is confusing" complaints, we started getting specific feature requests and meaningful usage insights. These users were engaged enough to actually think about how the product could work better for them.
The unexpected benefit was that it made our entire go-to-market more efficient. Sales conversations were easier because prospects were already qualified. Customer success had fewer "why did I sign up for this?" conversations. The entire funnel became more aligned.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons I learned from this experiment:
Optimize for the right metric: Signup rate is a vanity metric. User engagement and trial conversion are business metrics. Always optimize for business outcomes, not vanity metrics.
Friction can be your friend: Not all friction is bad. Meaningful friction that serves a purpose can actually improve outcomes by filtering for serious users.
Self-selection works: Let users self-select based on their willingness to invest effort. The ones who invest effort are the ones most likely to succeed.
Qualification enables personalization: The data you collect during qualification becomes the foundation for personalizing the entire experience.
Marketing and product must align: If marketing is optimized for volume but product success requires quality, you have a fundamental misalignment that will hurt your business.
Context matters: This approach works best for products that require real commitment or behavior change. It's less effective for simple, transactional products.
Test thoughtfully: Don't just A/B test individual elements. Sometimes you need to test fundamentally different approaches to the entire user journey.
The biggest mistake I see companies make is treating all users the same. Not everyone who can sign up should sign up. Your job isn't to maximize signups—it's to maximize successful outcomes for the right users.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups, implement this approach by:
Adding credit card requirements for trials
Creating meaningful qualification questions
Requiring setup investment before first use
Segmenting users based on qualification data
For your Ecommerce store
For ecommerce stores, apply this by:
Using progressive profiling for account creation
Requiring wishlist setup or preference selection
Creating tiered access based on engagement
Qualifying email subscribers with specific interests