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Insights from Yasen Lilov on how startups can use data to reach product-market fit faster.
Welcome to another article in our series showcasing our most dedicated mentors and their invaluable wisdom. These are the silent heroes working behind the curtains – the ones who jump in and help our founders when they need it most, but rarely get the spotlight. Get to know the people our founders already swear by and gain access to their knowledge.
The Role of Data in Early-Stage Startup Growth
Startups operate in a high-uncertainty environment where every decision matters. Whether it’s fine-tuning a product, identifying the right audience, or optimizing growth strategies, data is the single most valuable tool for navigating the early stages of scaling. Yet, many founders still rely on gut instinct rather than structured insights.
Yasen Lilov, Partner & Head of Data & Analytics at VertoDigital, has seen firsthand how data transforms guesswork into strategy. With years of experience helping companies turn messy metrics into actionable insights across B2B SaaS, FinTech, and ecommerce, his message to founders is straightforward: the companies that adopt a data-first approach typically reach product-market fit faster than those relying on intuition alone.
Paid advertising offers a perfect example of this data-first approach in action. While some founders see ads as an unnecessary expense too early in the journey, others expect immediate ROI. The reality? Advertising at the pre-PMF stage isn’t about profitability – it’s about validation. When used correctly, data-driven advertising helps startups:
✅ Test and validate demand before scaling development efforts.
✅ Refine messaging and positioning based on real audience reactions.
✅ Acquire early users and measure retention, feeding back into the product roadmap.
Bridging Data and Decision-Making
The focus should be on bridging the gap between raw data and real business impact. VertoDigital’s experience with the global brands they work with shows that AI-enhanced analytics leads to faster insights, smarter decisions, and scalable growth.
The key to success lies in leveraging data, AI, and acquisition strategies to make informed decisions – whether validating a product idea or optimizing a go-to-market strategy. Companies that adopt a data-first approach typically reach PMF faster and more efficiently than those relying on intuition alone.
To break down how startups can use data effectively in their early growth phase, let’s answer some of the most common questions founders have.
Q&A: Navigating Early-Stage Growth with Data and Advertising
Q: How can a startup measure whether they’re on track toward PMF?
The best way to assess PMF is through the Pirate Metrics Framework (AARRR)—a five-stage funnel that tracks user behavior and conversion at key points:
- Acquisition – Where are users coming from? Are they finding your product organically or through paid channels?
- Activation – Are users engaging with your product after signing up?
- Retention – Are they coming back? This is a major PMF indicator.
- Referral – Do users find enough value to recommend your product?
- Revenue – Are users converting to paying customers or generating value for the business?
Startups should track these metrics consistently, identifying bottlenecks and adjusting their strategy to optimize for activation and retention.
Q: Should early-stage startups invest in paid advertising before achieving PMF?
A common myth is that startups should wait until they have a fully optimized product before running ads. In reality, paid advertising can be a powerful validation tool even before PMF. Instead of focusing on profitability, startups should use ads to:
✅ Test different customer segments and identify early adopters.
✅ Experiment with messaging and positioning to see what resonates.
✅ Measure key metrics like activation and retention to refine product-market fit.
However, running ads without a solid analytics foundation is a waste. Tracking tools like GA4, conversion APIs, and event-based measurement are critical for ensuring every marketing dollar provides insights – not just clicks.
Q: What’s the biggest mistake startups make with data in the early stages?
The most common mistake is focusing too much on vanity metrics (e.g., impressions, likes, clicks) instead of tracking meaningful user behaviors that indicate retention and revenue potential.
A startup should ask:
➡ Which acquisition channels bring users that actually stay and engage?
➡ What behaviors correlate with long-term retention and revenue?
➡ What messaging drives the highest activation rates?
By structuring experiments around actionable insights, startups can refine their growth strategy based on real user behavior – not just assumptions.
Q: How can a startup use paid ads to improve retention and referral rates?
While most founders think of paid ads as a pure acquisition channel, they can also be used strategically to boost retention and referrals. Some effective approaches include:
- Retargeting campaigns for user re-engagement – Bringing back users who dropped off during onboarding.
- Lookalike audiences based on high-LTV customers – Targeting new users similar to your best existing customers.
- Referral-based ad incentives – Running ad campaigns that encourage users to invite their network.
Retention-focused advertising is particularly effective when combined with automated email and in-app messaging, ensuring a seamless user journey.
Q: What’s the best way for an early-stage startup to structure its data tracking?
At a minimum, every startup should have:
✅ Google Analytics 4 (GA4) or Segment for event tracking.
✅ A CRM (HubSpot, Marketo, or equivalent) to connect marketing and user data.
✅ Ad platform tracking (Google Ads, Meta Pixel, LinkedIn Insight Tag, etc.) for precise attribution.
✅ Product analytics (Amplitude, Pendo, or similar) to monitor user engagement in-product.
By integrating these tools properly – rather than collecting fragmented data – startups can create a unified view of customer behavior, making data-driven decisions and achieving PMF faster. This approach transforms the founder journey from a series of high-stakes gambles into a structured discovery process. While intuition might spark innovation, it’s methodical testing and validation that turn promising ideas into market-winning products. The most successful founders recognize that data isn’t just about tracking performance – it’s about developing a deeper understanding of customer needs and behaviors that competitors miss. In a world of uncertainty, let your data be your compass.
⚡Quick Fire Questions with Yasen Lilov:
Professional Quick Fires:
1️⃣ One metric founders should track but often ignore?
Activation rate – the % of users who reach a meaningful first step after acquisition. Defining what is the first step is key.
2️⃣ What separates startups that effectively use data from those that don’t?
Those who treat data like a co-founder, not like a monthly report. One asks for feedback constantly, the other just sends you a PDF with graphs you never open.
3️⃣ Quickest way to test if your messaging resonates?
Run a small paid ad campaign with variant messaging. If you’re getting high click-through and engagement from the right audience, it’s working.
4️⃣ One data-related skill every founder should develop?
The ability to ask sharp, structured and meaningful questions. Founders who can frame clear prompts and guide AI to extract insights are already ahead of the curve.
5️⃣ Most effective way to validate customer segments with paid ads?
Build different personas and run targeted campaigns to each. Track cost-per-click, conversion, and retention metrics. Let data tell you where the real traction is.
Personal Quick Fires:
1️⃣ Favorite way to recharge?
Chasing the flow – whether it’s skiing down a slope, riding down a trail, or just slowing things down with a good coffee, a great meal, or a quiet whisky.
2️⃣ Book currently on your nightstand?
Currently on my digital nightstand (aka Audible): Tools of Titans by Tim Ferriss.
3️⃣ Hidden talent?
Translating chaos into clarity – especially when it starts with a whiteboard and ends with a plan.
4️⃣ Favorite productivity hack?
Calendar-blocking with ruthless prioritization. If it’s not on the calendar, it doesn’t get done.
5️⃣ What would you do if not in data analytics?
I’d be running a Counter-Strike bootcamp somewhere in the mountains – teaching strategy, discipline, and the art of the perfectly coordinated round. It’s where I first learned about teamwork, split-second decisions, and the thrill of a well-executed plan. Data just came later.
Enjoyed this data-driven approach? Complement it with storytelling strategies from our mentor Alexei Lazarov in “Tell a Story or Be Ignored: Why Your Marketing Is Failing.”
