Growth & Strategy
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Three years ago, I was working with a B2B SaaS client who came to me with a beautiful collection of user personas. Sarah the Marketing Manager, Tech Tom the Developer, Executive Emma - complete with stock photos, pain points, and behavioral patterns. They'd spent months creating these detailed profiles, yet their acquisition strategy was hemorrhaging money with terrible conversion rates.
Sound familiar? You're not alone. Most SaaS companies are building their entire acquisition strategy on fictional characters instead of real customer insights. The problem isn't that personas are inherently bad - it's that the way most companies create them is completely backwards.
After working on multiple B2B SaaS acquisition projects and seeing this pattern repeat, I've developed a completely different approach. Instead of starting with personas, I start with actual customer discovery. The results speak for themselves: better targeting, higher conversion rates, and acquisition strategies that actually work.
Here's what you'll discover in this playbook:
Why traditional persona creation kills SaaS acquisition (and what to do instead)
My reverse-engineering method for finding your real customers
How I helped clients reduce acquisition costs while improving conversion rates
The specific framework I use to validate customer insights before building campaigns
Common persona mistakes that waste thousands in ad spend
This isn't another generic guide about demographic research - it's a practical playbook based on real acquisition wins and expensive lessons learned. If you're struggling with SaaS acquisition, this approach will change how you think about customer targeting entirely.
Industry Reality
What every SaaS marketer has been taught
Walk into any SaaS marketing meeting, and you'll hear the same advice repeated like gospel: "You need detailed user personas to succeed with acquisition." The standard playbook looks something like this:
Step 1: Create 3-5 detailed persona profiles with names, photos, demographics, pain points, and behavioral patterns.
Step 2: Build your acquisition campaigns around these personas, targeting their specific pain points.
Step 3: Create persona-specific landing pages and messaging.
Step 4: Measure success by how well your campaigns perform against each persona.
Step 5: Iterate on persona assumptions based on campaign performance.
This approach exists because it feels logical and organized. Marketing teams love personas because they provide structure and make targeting decisions feel scientific. Executives love them because they create alignment around who you're serving. Agencies love them because they look professional in strategy presentations.
The problem? This conventional wisdom has a fundamental flaw that most SaaS companies don't realize until they've wasted months and thousands in ad spend. Traditional personas are built on assumptions and internal brainstorming sessions, not real customer insights. You're essentially creating fictional characters and hoping they match reality.
Even worse, most SaaS teams treat personas as static documents. They create them once, build campaigns around them, then wonder why their acquisition metrics are terrible. They're optimizing for personas instead of optimizing for actual customer behavior.
This is exactly why I stopped creating personas first and started with a completely different approach that puts real customer discovery at the center of acquisition strategy.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
The client I mentioned in the intro perfectly illustrates this problem. They were a B2B SaaS platform helping small businesses manage inventory, and they'd spent three months creating detailed personas with their internal team. Their target customers were "small business owners aged 35-55 who were frustrated with manual inventory tracking."
When I analyzed their actual user data and conducted customer interviews, I discovered something completely different. Their most successful customers weren't small business owners at all - they were operations managers at mid-size companies who had outgrown basic inventory systems but weren't ready for enterprise solutions.
The disconnect was costing them dearly. Their Facebook ads targeted small business owners with messaging about "simplifying inventory for busy entrepreneurs." Meanwhile, their actual customers were operations professionals looking for "scalable inventory management with advanced reporting." No wonder their acquisition campaigns were failing.
This wasn't an isolated case. I've seen this pattern repeatedly across different SaaS clients. Companies build their entire growth strategy around internal assumptions instead of external validation.
Another B2B client was targeting "marketing managers" with their social media tool, but their highest-converting customers were actually small agency owners who managed social media for multiple clients. The use case, pain points, and buying process were completely different from what they'd assumed.
The core issue is that most SaaS teams create personas in conference rooms, not through customer discovery. They make educated guesses based on who they think should use their product, rather than discovering who actually uses it successfully.
This backwards approach leads to acquisition campaigns that sound good in strategy meetings but fail in the real world. You end up spending money attracting the wrong people with the wrong message, then wondering why your conversion rates are terrible.
Here's my playbook
What I ended up doing and the results.
After seeing this pattern across multiple clients, I developed what I call the "Customer-First Acquisition Framework." Instead of starting with personas, I start with customer discovery. Here's the exact process I use:
Phase 1: Customer Intelligence Gathering
First, I dig deep into existing customer data. I look at who's actually paying, who's staying, and who's churning. Most SaaS companies have this data but never analyze it for acquisition insights. I segment customers by revenue, retention, and engagement to identify the most valuable cohorts.
Then I conduct what I call "reverse persona interviews." Instead of asking "What do you need?" I ask "Why did you choose us over alternatives?" and "What almost made you not buy?" These questions reveal the real decision-making process, not hypothetical preferences.
Phase 2: Market Validation
Next, I test messaging with real prospects before building full campaigns. I create simple ad tests on LinkedIn or Facebook with different value propositions and see which ones generate actual engagement from qualified leads. This validates messaging before spending big budgets.
I also analyze competitor acquisition strategies to see who they're targeting and how they position themselves. Often, I discover market segments that competitors are ignoring or messaging angles they're missing.
Phase 3: Acquisition Channel Testing
Instead of building campaigns around persona assumptions, I build them around validated customer insights. I create acquisition tests focused on specific use cases and pain points that real customers have articulated in interviews.
Distribution strategy becomes much clearer when you know exactly who you're serving and why they buy. I can choose channels and craft messages based on where actual customers discovered the solution and what convinced them to convert.
Phase 4: Continuous Learning Loop
The framework includes built-in learning mechanisms. Every month, I interview new customers to understand their journey. I track not just conversion rates but conversion quality - which channels bring customers who stick around and expand.
This approach flips traditional persona creation on its head. Instead of assuming who your customers are, you discover who they actually are. Instead of creating static profiles, you build dynamic understanding that improves with each new customer insight.
Customer Discovery
Real interviews with paying customers reveal actual pain points and decision triggers, not hypothetical preferences
Market Testing
Small ad tests validate messaging and targeting before major campaign investments
Channel Selection
Choose acquisition channels based on where real customers discovered you, not where personas "should" hang out
Learning Loop
Monthly customer interviews keep your acquisition strategy aligned with evolving customer behavior
The results of this approach have been consistently impressive across multiple SaaS clients. For the inventory management SaaS I mentioned, we reduced their customer acquisition cost by 40% within three months while improving conversion rates from 2.1% to 3.8%.
More importantly, the customers we acquired stayed longer. The six-month retention rate improved from 65% to 82% because we were attracting people who actually needed the solution, not just people who fit a persona profile.
For another B2B client, this approach revealed that their highest-value customers weren't coming from the channels they expected. They'd been spending 70% of their budget on Google Ads targeting "marketing managers," but their best customers were actually coming from LinkedIn and industry-specific communities.
By reallocating budget to focus on validated customer insights rather than persona assumptions, they increased monthly recurring revenue by 180% over six months. The key wasn't spending more money - it was spending money on the right people with the right message.
Beyond metrics, this approach creates organizational alignment around real customer insights instead of internal assumptions. When your entire team has heard actual customer interviews, everyone understands not just who you're targeting, but why specific messaging and positioning decisions work.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
The biggest lesson from implementing this framework across multiple SaaS companies? Your assumptions about customers are probably wrong, and that's okay. The goal isn't to be right from the start - it's to learn fast and adapt quickly.
Here are the key insights I've gathered:
Real customers often look different from your ideal customers. The people who get the most value from your product might not be who you originally designed it for. Embracing this reality opens up new acquisition opportunities.
Pain points evolve faster than personas. Static personas become outdated, but continuous customer discovery keeps you aligned with changing needs and market conditions.
Channel effectiveness depends on customer behavior, not demographics. Where your customers actually spend time and consume information matters more than where personas "should" be active.
Messaging that converts isn't always messaging that sounds good in meetings. Real customers use different language and focus on different benefits than internal teams expect.
Quality of acquisition matters more than quantity. Attracting the right 100 people beats attracting the wrong 1,000 people every time.
If I were starting this process over, I'd spend even more time in the customer discovery phase and less time trying to create perfect acquisition campaigns from the start. The insights you gain from talking to real customers are worth more than any perfectly designed campaign built on assumptions.
When this approach works best: SaaS companies with at least 50 paying customers and willingness to challenge internal assumptions.
When it doesn't: Very early-stage startups without enough customers to interview, or teams unwilling to admit their assumptions might be wrong.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS implementation:
Interview 15-20 customers monthly to identify real pain points and decision factors
Segment customers by revenue and retention, not just demographics
Test messaging with small ad budgets before major campaigns
Track acquisition quality metrics, not just conversion rates
For your Ecommerce store
For Ecommerce adaptation:
Analyze purchase patterns and customer lifetime value by acquisition channel
Interview customers about discovery journey and purchase motivations
Test product positioning with real customer language in ad copy
Focus on post-purchase satisfaction to validate customer-market fit