Marketing Marker: from a 3-month MSP to a scalable lead-intelligence platform

Marketing Marker is a B2B SaaS product that identifies high-quality, sales-ready leads. It detects early purchase signals at the anonymous stage by analyzing company and individual activity, and optimizes content to engage prospects at the right moment.

It's built for:

• B2B marketers at SaaS companies
• Marketing managers
• Sales teams
• Companies aiming to grow or expand their business

As the lead product designer, my role was to align business objectives with both technical constraints and design requirements, while continuously integrating user feedback. Given the limited resources typical of a new product, we focused on prioritizing key features, making thoughtful trade-offs, and adapting quickly to evolving client needs.

The product was launched within a few months by a lean product team composed of a product manager, one designer, and one developer. The project kicked off in July, with the MVP scope and design finalized by September. Development took place in October, leading to a public launch at the end of November.

As the product evolved, the team expanded to include sales, customer support, additional developers, and QA, enabling more structured collaboration and scaling of the product.

Initial user research surfaced a consistent set of pain points:

• Too many leads, but not the right ones
• Marketing automation tools that were too complex to fully use
• Inefficient lead nurturing
• Inability to prioritize leads correctly

Marketing Marker's answer was to identify and prioritize customers with high interest in real time, instead of relying on outdated lead scores — focusing on recency-based intent (activity in the last 48 hours) rather than accumulated scores, to improve lead quality, sales timing, and conversion rates. It does this by collecting real buyer signals: 1st-party intent data from website behavior (cookies, content views, visit frequency), and 3rd-party intent data at the company level via IP-based identification, which AI then interprets to surface genuine intent.

A lightweight MVP focused on core lead acquisition grew, over the following year, into an advanced lead-management platform.

I closely followed the product's evolution, incorporating weekly feedback from both the sales and business teams. As the team grew from a lean trio into a full cross-functional group — with QA, additional developers, sales, and customer support — we actively evolved our workflows and processes alongside the product itself, gathering and analyzing user feedback throughout.

Numerous features were developed throughout the year, including an intent-analysis screen based on industry segments, letting users target industries by searched keyword or visited page. The on-site tools designed to capture and engage prospects were continuously optimized for performance and usability, and the intent-identification system kept evolving to more precisely understand and target prospect needs.

I learned how to build a product from a business idea, starting with a Minimum Sellable Product developed in a very short timeframe — then helped rapidly evolve it by continuously iterating on real client usage.

Starting within a small product team that gradually scaled, I gained a holistic view of the product, shaped by direct customer feedback, real-time observation of their needs, and close collaboration with sales.