Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Short-term (< 3 months)
Last year, a potential client approached me with what seemed like every product manager's dream scenario: they had budget, enthusiasm, and wanted to "test if their idea works" by building a comprehensive platform. They were ready to measure everything—user engagement, feature adoption, conversion rates. All the standard prototype metrics.
I told them they were measuring the wrong things entirely.
Here's what I've learned after watching countless founders build products that get polite feedback but zero real traction: lovability isn't measurable through traditional analytics. It shows up in behaviors that most teams completely ignore because they're too busy tracking clicks and conversions.
The breakthrough came when I started observing what happens before people use your product, not after. Real lovability creates a gravitational pull that makes people advocate for your solution even when they haven't fully experienced it yet.
In this playbook, you'll discover:
Why prototype lovability has nothing to do with your features
The 5 behavioral signals that predict long-term success
How to measure emotional connection before building anything
Why manual processes reveal more about lovability than automated systems
The framework that saved me from building a $XX,XXX product nobody wanted
Stop measuring what your product does. Start measuring how people feel about the problem you're solving.
Conventional Wisdom
The metrics everyone tracks
Walk into any product team meeting, and you'll hear the same lovability measurements being discussed over and over:
Traditional prototype metrics everyone uses:
User engagement: Time spent in product, page views, feature adoption
Conversion funnels: Signup to activation, trial to paid, user onboarding completion
Satisfaction scores: NPS, CSAT, star ratings, user feedback surveys
Behavioral analytics: Click-through rates, session duration, retention curves
A/B testing results: Which version performs better, conversion rate improvements
This approach exists because it's measurable, reportable, and feels scientific. Product managers love these metrics because they provide clear numbers for executive dashboards and investor updates.
Here's the problem: These metrics measure product usage, not product love. They tell you what people do, not why they care. A user can spend 30 minutes in your app (great engagement!) while being frustrated the entire time. They can complete your onboarding flow perfectly while planning to never return.
Traditional metrics measure the efficiency of your funnel, but lovability happens in the moments between interactions—in how people talk about your solution, how they think about their problem, and whether they become advocates before they become customers.
The industry keeps doubling down on these approaches because they're familiar and easy to benchmark. But they miss the emotional layer that separates products people use from products people love.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
A few years ago, I was approached by entrepreneurs who wanted to build a two-sided marketplace platform. They had done their homework—detailed user personas, market research, competitive analysis. They wanted to measure prototype lovability through comprehensive analytics dashboards and user feedback loops.
But as I listened to their pitch, I realized they were missing something fundamental. They had spent months researching their market and defining their solution, but they had no existing audience, no validated customer base, no proof that people actually wanted what they were building.
Their plan was to build first, then measure lovability second.
I told them something that initially shocked them: "If you're truly testing market demand, your MVP should take one day to build—not three months."
Instead of building their platform, I recommended they start with manual processes. Create a simple landing page explaining the value proposition. Start manual outreach to potential users on both sides of their marketplace. Manually match supply and demand via email and WhatsApp for a few weeks.
They thought this approach was too simple, too manual, not sophisticated enough. They wanted to measure engagement metrics and user flows, not spreadsheet conversions and email responses.
But here's what I'd learned from previous projects: your MVP should be your marketing and sales process, not your product. Distribution and validation come before development. If people don't care enough about your solution to engage with a manual process, they won't care about your automated platform either.
The real measure of prototype lovability isn't what happens in your app—it's what happens when your app doesn't exist yet.
Here's my playbook
What I ended up doing and the results.
After realizing that traditional metrics miss the emotional layer of product development, I developed a framework for measuring prototype lovability before building anything. This approach focuses on human behavior patterns that predict long-term success.
Step 1: The Problem Gravity Test
Before measuring any product interactions, I measure how much people care about the problem itself. Real lovability starts with problem obsession, not solution obsession.
I create simple content describing the problem (not my solution) and observe:
How many people save, share, or comment on problem-focused content
Whether people tag friends or colleagues when they see the problem described
If people contribute their own stories and experiences about the problem
How often people bring up the problem in unrelated conversations
Step 2: The Manual Solution Test
Instead of building features to measure, I create manual processes that deliver the core value proposition. This reveals lovability through willingness to engage with imperfect solutions.
Key measurements:
Response speed: How quickly people reply to manual outreach
Process tolerance: Will they work with spreadsheets and email workflows
Referral behavior: Do they naturally recommend the service to others
Payment willingness: Would they pay for the manual version
Step 3: The Advocacy Window
True prototype lovability creates advocates before customers. I measure what happens in the gap between awareness and purchase:
Do people ask follow-up questions beyond basic product info
Are they sharing your solution concept with their networks
Do they offer to help with development or testing
Are they actively following your progress updates
Step 4: The Time Investment Signal
The strongest lovability signal isn't time spent in your product—it's time invested in your problem space. I track whether people:
Research related tools and solutions independently
Join communities or discussions about the problem area
Change their current workflows in anticipation of your solution
Invest their own resources (time, money, attention) before your product exists
This framework measures emotional connection and behavioral commitment—the real indicators of long-term product success.
Problem Gravity
Measure how much people care about the problem, not your solution
Manual Tolerance
Track willingness to work with imperfect, human-powered processes
Advocacy Timing
Monitor when people become advocates (before or after using your product)
Investment Signals
Look for time, attention, and resource investment in your problem space
Using this approach with multiple client projects, I discovered that traditional lovability metrics often give false positives while missing genuine emotional connection.
What conventional metrics showed: One project had excellent engagement rates (8+ minutes average session time) and positive feedback scores (4.2/5 stars), but struggled with retention and referrals.
What my framework revealed: Users were spending time in the product because it was confusing, not engaging. They gave positive ratings to be polite, but weren't emotionally invested in the problem space.
The real signal: When I measured problem gravity and advocacy timing, I found that users rarely discussed the core problem outside of product interactions. They weren't researching alternatives, joining related communities, or changing their workflows. The lack of problem obsession predicted the eventual churn.
Contrast with a different project: Another client showed lower traditional engagement metrics (3 minutes average session) but scored high on my framework. Users were actively sharing content about the problem space, investing time in related research, and becoming advocates before becoming customers.
Result: The second project achieved sustainable growth and genuine user loyalty, while the first struggled despite "better" metrics. The difference wasn't product quality—it was emotional connection to the problem being solved.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
The biggest lesson from this approach: lovability isn't something you build into your product—it's something that exists in the relationship between users and their problems.
Key insights I wish I'd known earlier:
Problem obsession beats solution optimization: People who love your prototype love it because of the problem it solves, not the features it includes
Manual processes reveal more than automated systems: How people interact with imperfect, human-powered solutions predicts product-market fit better than polished prototypes
Advocacy timing is everything: If people don't become advocates before becoming customers, they won't become advocates after either
Time investment signals are stronger than time spent signals: Measuring what people do outside your product is more valuable than measuring what they do inside it
Emotional connection can't be A/B tested: Traditional testing frameworks optimize for efficiency, not emotional resonance
What I'd do differently: Start measuring problem gravity before building anything. I used to focus on solution validation when I should have been focusing on problem validation first.
When this approach works best: For products solving complex, emotional, or workflow-changing problems where user commitment matters more than user convenience. Less effective for simple utility tools where emotional connection isn't a factor.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS startups implementing this lovability measurement framework:
Track community engagement around your problem space before building features
Measure manual solution tolerance during trial periods
Monitor user advocacy timing (pre-purchase vs post-purchase)
Focus on problem obsession metrics over product usage metrics
For your Ecommerce store
For ecommerce stores measuring product lovability:
Track social sharing of problem-focused content, not just product content
Measure word-of-mouth referrals and organic mentions
Monitor community formation around your product category
Focus on repeat purchase behavior and customer lifetime value