Dreamdata, a B2B marketing analytics platform, has secured a $55 million Series B round of funding, the company told Crunchbase News exclusively.
PeakSpan Capital led the round, which included participation from InReach Ventures, Angel Invest, Curiosity Venture Capital and Crowberry Capital.
With this latest financing, Dreamdata — which has dual headquarters in Copenhagen, Denmark, and New York — has raised $67 million since its 2018 inception. The company’s last raise was in December 2022 with an $8 million Series A led by Signals Venture Capital. CEO Nick Turner declined to reveal at what valuation Dreamdata raised its latest round, saying only that it was “an incredibly significant increase” when compared to its previous venture funding.
Dreamdata’s goal is to provide “the most complete B2B buyer journey map anywhere by joining ads, website visits, emails, CRM … into one clean timeline per account,” according to Turner. Examples of functions its platform can perform include syncing “high-intent” audiences to ad platforms such as Google or Meta, triggering notifications to a sales team, or running marketing workflows.
“That gives marketers a trustworthy ‘single source of truth’ to see what’s working, prove ROI, and then act on it, with AI assistance,” Turner said. “We do both activation and attribution. We’re not just a reporting tool; we are building the operational infrastructure for the B2B marketer.”
Clio, Finastra, Cognism, Oyster and Turing are among its “thousands” of customers.
AI has had a profound effect on many sectors such as biotech and cybersecurity, as many startups have added the technology to their platforms. Marketing is no exception, as Dreamdata is only the most recent marketing tech startup to get funding.
In February, marketing and personalization startup Hightouch locked up an $80 million Series C led by Sapphire Ventures, minting it as a new unicorn at a $1.2 billion valuation. Also in February, Toronto-based StackAdapt raised a $235 million growth round led by Teachers’ Venture Growth — the late-stage venture and growth investment arm of Ontario Teachers’ Pension Plan. The startup has a multichannel programmatic advertising platform that uses AI and automation to help with digital marketing efforts.
Overall, global venture funding to sales and marketing tech startups totaled $5.9 billion through Oct. 10, 2025, per Crunchbase data. That’s down 11.9% compared to the $6.7 billion raised in the same time period in 2024.
Sustainable growth
Dreamdata operates its business under a SaaS model with a component of usage-based pricing. The company has more than doubled its annual recurring revenue while maintaining the same number of employees it had one year ago (50), according to Turner.
“We are operating with disciplined ambition via sustainable growth,” he said, noting that Dreamdata is focused on growing its business in Europe and North America.
One of Dreamdata’s biggest differentiators from traditional competitors, such as Adobe’s Marketo Measure/Bizible, Turner claims, is that it’s designed for “forward-looking action” as opposed to focusing on what happened in the past.
Matt Melymuka, co-founder and managing partner of PeakSpan Capital, leads the GTM technology investing at the venture firm and said he’s been partnering with companies in the space for over 15 years.
“It is with that long-tenured perspective and context that I have developed a deep appreciation for the problem Dreamdata is solving. Accurate revenue attribution has been a persistent challenge for years and years, and the problem today is complex and multi-faceted,” he told Crunchbase News via email. “The modern customer journey is convoluted, spanning numerous channels and disparate touchpoints, so understanding with high confidence what contributes most to a conversion is incredibly complex.”
In Melymuka’s view, Dreamdata’s offering solves the challenge of revenue attribution while also leveraging signal data and AI to support activation and execution.
“Relative to other solutions in the market, Dreamdata delivers far and away the quickest time to value – despite the complexity underpinning the solution,” he said.
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