Whatagraph has evolved from a bootstrap marketing reporting tool to a comprehensive marketing intelligence platform processing data from 12+ sources for marketing teams globally. With over $10 million in funding and a decade of iteration, the Lithuania-based company recently launched "Whatagraph 3.0"—a fundamental shift from pure sales-led to hybrid PLG motion. In this episode of Category Visionaries, Justas Malinauskas shares the technical and strategic decisions behind their transformation from agency tool to enterprise marketing intelligence platform, including their multi-agentic AI implementation and the SEO strategy that generates 500+ MQLs monthly.

Topics Discussed:

Technical architecture evolution from reporting automation to full-stack marketing intelligence
Strategic pivot from sales-led to hybrid PLG/sales-led motion triggered by mission misalignment
Advanced SEO methodology using competitor pain point analysis and search behavior reverse engineering
AI implementation using multi-agentic systems rather than simple LLM integration
Lithuania's bootstrap-first ecosystem and knowledge-sharing networks among unicorn companies
Go-to-market evolution across three distinct phases over 10 years

GTM Lessons For B2B Founders:

Engineer time-to-value as your primary PLG enabler, not feature breadth: Whatagraph achieved 5-minute time-to-value from data connection to dashboard generation—versus the industry standard of hours—by rebuilding their onboarding around AI-powered automation rather than manual drag-and-drop configuration. Justas notes this wasn't just UI optimization but fundamental product architecture changes: "It's basically a lot of knowledge from our last 10 years...we're able to build it like really multi-agentic platform which helps to build those things in steps, not just like drop something randomly." For PLG success, optimize your technical stack for immediate value delivery, not comprehensive feature exposure.
Weaponize competitor technical limitations through content strategy: Rather than competing on generic "best marketing tool" keywords, Whatagraph dominated by creating authoritative content around specific competitor pain points. Their "Looker Studio being slow" content strategy captured high-volume searches from frustrated users by actually helping solve the problem while positioning their technical advantages. Justas explains: "The biggest problem was it's actually very slow...when we have everything in house we can make things like very quick and speedy compared to there." Target technical pain points your architecture inherently solves rather than fighting brand-to-brand keyword battles.
Align your ICP strategy with your actual technical capabilities, not market perception: Whatagraph's shift to hybrid PLG wasn't market-driven but mission-driven. Justas realized their technical product could serve smaller organizations, but their sales-led approach artificially excluded them: "We were not empowering in the first place people, everyone to make those data driven decisions fast...we were not allowing everyone into the product even if our product was allowing to." Audit whether your go-to-market motion matches your product's actual technical capabilities and addressable market, not just your current revenue optimization.
Build SEO moats through search behavior psychology, not keyword tools: Whatagraph's SEO dominance came from Justas thinking like customers in problem-solving mode rather than using standard keyword research. He reverse-engineered the complete buyer journey: "People go through a very much regular process...they search for a problem...find a blog post...find a product...competition...pricing...reviews...then actually buy the product." They attempted to own multiple touchpoints in this journey through strategic content placement across different domains. Map your customer's actual research psychology, not just search volumes.
Implement freemium with full core functionality, not feature limitations: Whatagraph's new freemium tier includes their complete AI-powered report generation ("Whatagraph IQ") with only data source limitations, not feature restrictions. This approach lets small users experience the full product value while creating natural upgrade triggers as they grow. Justas notes: "All the core functionality...you're able to talk with your data within AI capabilities and ask questions about your data as you would pay a couple of thousands a month." Design freemium around usage scaling, not capability restrictions, to demonstrate full product value.

Sponsors:

Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership.

www.FrontLines.io

The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.

www.GlobalTalent.co

Don't Miss: New Podcast Series — How I Hire

Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.

Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

792: The 4 Essential Building Blocks of Selling Remote, with David Kreiger