Most founders obsess over product, fundraising, and growth. They track revenue, CAC, conversion rates, and maybe retention. But according to Attila Tóth, co-founder and chief strategist of Cognitive Creators, one of the biggest risks in a startup is often hiding somewhere less obvious: inside its digital strategy and data infrastructure. Attila’s path into marketing data started with a teenage side project. As a young cyclist, he built a basic webshop for his father’s business. When the first sale came in, his first reaction was not celebration. It was curiosity: why only one? That question pushed him into analytics, consumer behavior, conversion, and eventually digital due diligence. Today, Attila helps companies, investors, and acquirers understand the hidden risks inside digital businesses—from marketing inefficiency to messy data systems to cloud infrastructure mistakes. In one M&A audit, his team uncovered roughly €2.5 million in risk inside an €80 million deal. The lesson: digital risk is not theoretical. It can directly change valuation, negotiation, and outcomes. The Paid Marketing Treadmill One of Attila’s sharpest arguments is that many companies are trapped in a paid marketing system they don’t fully understand. The trap starts simply. A company spends money on Google, Meta, TikTok, or another paid channel. The campaign works. Revenue grows. So the company spends more. But then competitors enter the same auction. Costs rise. The company has to spend more just to achieve the same results. Over time, the business becomes dependent on platforms where it does not control the rules. Attila compares this to a bakery bidding on search terms like “fresh sourdough bread.” If one advertiser pays $0.50 per click, another may bid $0.51. Then a larger competitor enters and pushes the price to $1. Smaller players either raise their spend or disappear from that digital market. That is the treadmill: you keep running, but the economics do not necessarily improve. For startups, this matters because early CAC can be misleading. A company may look efficient in its first niche or first geography, but that does not mean the same economics will hold when it expands. Attila has seen startups celebrate strong CAC, only to discover that the next market—such as moving from the UK to the US—is dramatically more expensive. First-Party Data Is the Escape Hatch Attila does not argue that companies should abandon paid marketing. That is unrealistic. His point is that companies need more control, and the best source of control is often their own first-party data. Most companies already have useful data sitting inside their business. The problem is that they do not use it well. His tire example makes the point clearly. If a customer buys summer tires today, that customer probably does not need to see tire ads from the same company for the next several weeks—or maybe even years. Yet many companies keep retargeting people who already purchased, wasting budget and creating a bad customer experience. The same problem shows up in banking. Attila described receiving loan offers from a bank despite never taking personal loans and consistently using investment products instead. The bank likely had enough data to understand his behavior, but its marketing system was still blasting irrelevant campaigns. This is not just a marketing mistake. It is an operating problem. Data often sits in silos. It is messy, incomplete, duplicated, or missing key context like dates and behavioral signals. Without clean, centralized, usable data, personalization becomes impossible. The Cloud Credit Trap Attila also warns founders about another hidden startup risk: free software and cloud credits. Startup programs from major cloud providers and software companies can be helpful. Free credits make it easier to launch, test, and scale early. But they can also create bad habits. Founders may build on infrastructure that is oversized, poorly configured, or unnecessarily expensive because the bill is hidden by credits. When the credits expire, the company suddenly faces costs it never designed around. This is especially dangerous because early technical decisions often compound. A stack that looks “free” at seed stage can become expensive technical debt by Series A or Series B. The question founders should ask is not just: Can we get this tool for free? It is: Will this still make sense when we are paying real money for it? What VCs Miss in Digital Due Diligence For investors, Attila argues that digital strategy deserves more scrutiny. Traditional diligence often looks at market size, revenue growth, customer concentration, product differentiation, and team quality. Those matter. But Attila believes investors often miss the market’s digital footprint. That means understanding how customers actually search, compare, discuss, and signal demand online. Search behavior, sentiment, category growth, geography-specific interest, and platform dynamics can all reveal whether a startup is riding a real market wave or merely selling into a narrow pocket of temporary demand. This is especially important for timing. A startup can have a strong product and team, but if the market is not ready, growth will be harder and more expensive. Conversely, a startup entering a market with rising digital demand can ride a tailwind others have not yet noticed. Brand Is a Resilience Mechanism Attila also pushes back on the shallow definition of brand. Brand is not just a logo, color palette, or tagline. Those things matter, but they are not the core. To Attila, brand is about connection. Real connection with an audience creates resilience. His example: Apple could make unpopular product decisions—like removing ports from MacBooks—and still survive because the brand had deep customer trust. A no-name company making the same mistake might not survive. For startups, this matters because performance marketing alone is fragile. If customers only know you through paid ads, you are vulnerable to rising CAC, copycat competitors, and platform shifts. But if your audience has a real relationship with the brand, you have more room to recover, adapt, and compound. In VC terms, this connects to category creation. The best startups do not just sell into a category. They define one. AI Will Make Marketing Worse Before It Makes It Better One of Attila’s more provocative points is that AI may initially make marketing worse. Why? Because many companies are using tools like ChatGPT and Claude lazily. They ask generic prompts, accept generic outputs, and publish campaigns that sound like everyone else’s campaigns. The result is sameness. As more companies rely on default AI-generated messaging, differentiation may collapse. Ads, emails, landing pages, and brand copy will start to converge. Customers will see more noise, not more relevance. Attila’s view is not anti-AI. The better path is to combine AI with proprietary customer behavior data, market signals, and sharper human judgment. AI can accelerate iteration, personalization, and campaign testing—but only if companies feed it something more distinctive than a generic prompt. The Investor Question Founders Should Be Ready For Near the end of the conversation, Attila offered a question he thinks more investors should ask founders: If a similar company appears in six months, how will you react? It is a deceptively strong question. It tests more than competitive awareness. It reveals whether the founder understands their moat, distribution edge, data advantage, brand position, and speed of execution. A weak founder answers with vague confidence. A strong founder has a specific response. For startups, this is the real challenge. It is not enough to grow while the market is quiet. You need to know what happens when competitors notice the same opportunity. The Bottom Line Attila’s message is blunt: growth is not just about spending more, moving faster, or trusting platform dashboards. Startups need to know where their data lives. Investors need to understand whether CAC is sustainable. Founders need to think beyond the first beachhead market. And everyone needs to be more skeptical of digital strategies that look good only because no one has audited the underlying system. The companies that win will not be the ones that blindly pour money into paid channels. They will be the ones that understand their data, own their audience, define their category, and build growth systems that can survive competition.👂🎧 Watch, listen, and follow on your favorite platform: https://tr.ee/S2ayrbx_fL 🙏 Join the conversation on your favorite social network: https://linktr.ee/theignitepodcast Chapters:00:01 — Intro to Attila Tóth and Cognitive Creators 00:25 — Attila’s origin story 00:29 — From teenage cyclist to accidental web builder 02:54 — The first online sale 03:10 — Discovering analytics, tracking, and consumer behavior 04:29 — Launching Sight Doctor at 18 05:00 — Early startup failure and hard lessons 05:40 — Digital business modeling for traditional industries 06:45 — The M&A audit that exposed €2.5M in risk 08:57 — Writing Hyper and the frustration behind marketing data 11:14 — The rising cost-per-click problem 12:18 — The bakery ad-spend analogy 14:52 — The paid marketing trap 16:43 — The marketing spend treadmill 18:10 — Searching for an escape from platform dependency 20:00 — Turning years of experiments into a book 22:04 — Self-publishing Hyper 22:34 — Defining the marketing data trap 24:00 — First-party data as the escape plan 24:22 — The tire purchase example 26:29 — Banks, bad segmentation, and irrelevant offers 28:26 — Data silos inside large companies 31:00 — B2B marketing stacks and startup tooling 31:40 — Why there is no perfect tool list 32:35 — The hidden cost of startup cloud credits 34:04 — Questioning the tech stack after credits expire 35:3
