Bombora
Eric Matlick brought 15 years of founding and executive experience in advertising technology when he started Bombora, having previously founded Madison Logic, Industry Brains, and Media Brains. The core insight was simple but powerful: B2B companies spend enormous effort trying to find customers, but Matlick realized those customers leave digital signals through their research behavior before they buy.
Over five years, Matlick built what became the company's unfair advantage: a data cooperative with thousands of B2B publishers. About 70% of these relationships are exclusive, meaning Bombora has access to buying signals nowhere else can get them. This includes major publications like Wall Street Journal, Forbes, Bloomberg, and niche industry sites like G2 and Captera—essentially everywhere business professionals research products. The technology backbone includes a custom NLP engine that analyzes 30 billion pages per month, an IP-to-domain identity graph that determines which company employees are doing the research, and a taxonomy of 7,000 granular topics.
Matlick took a different path than most SaaS companies: he bootstrapped Bombora and grew almost exclusively through channel partners rather than raising venture capital. By 2018, the company hit $26 million in revenue. It continued scaling by selling primarily to Fortune 1000 enterprises at ACV of $125-150k. In 2019, revenue reached $30 million. The company had close to 2,000 customers purchasing the data, with about 200 buying directly after recently launching their own sales team.
The channel partner model worked exceptionally well, allowing Bombora to scale without VC pressure or heavy direct sales costs. However, the product was initially locked to enterprise-only. Matlick then shifted strategy to address the mid-market with lower ACVs ($30k range) while maintaining the exclusive data relationships. The COVID-19 crisis actually validated the product's value—in March 2020, the company closed more new logos than ever before. Matlick hypothesized that businesses with tighter budgets needed Bombora's insights more than ever to focus on high-probability prospects. The company didn't lay off or furlough anyone despite the disruption.
By April 2020, Bombora had 130+ employees (50% in R&D including data science and engineering, just under 20 in quota-carrying sales roles). The company was well over $30 million ARR with 65% from subscription revenue. Matlick shifted 2020 budget from canceled events to lead generation while applying for PPP loans to maintain stability. He was monitoring macro trends in real-time—showing that B2B research consumption had actually increased during COVID, and that propensity-to-purchase (not just content consumption) showed signs of stabilization by early April after a dip in mid-February.
- •By solving a problem he personally experienced across three prior founding roles, Matlick built deep conviction in the market need and understood the buyer pain well enough to create a defensible product.
- •The exclusive partnerships with 70% of major B2B publishers created an insurmountable competitive moat that couldn't be replicated by competitors, making the data asset itself the primary value driver.
- •Scaling through channel partners rather than direct sales eliminated the need for VC funding and allowed the company to reach Fortune 1000 enterprises efficiently without the overhead of a large sales organization.
- •The enterprise-first pricing model ($125-150k ACV) generated substantial revenue per customer while the exclusive data made customers dependent on Bombora, enabling predictable subscription retention even during economic uncertainty.
- 1.Spend significant time (ideally years) solving the problem yourself or in a previous role to identify the specific, persistent pain point that justifies building a company around it.
- 2.Secure exclusive, long-term partnerships with the highest-quality data or content sources in your market before building the product, then structure your offering around those proprietary assets.
- 3.Map out channel partners who already have relationships with your target customer segment and design a partner program with clear economics that incentivizes them to sell your solution without requiring you to build a large direct sales team.
- 4.Launch initially at the highest price point the market will bear with your best customers, then create tiered product versions for mid-market segments only after proving the core unit economics at enterprise scale.
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