B2B data vendor RevenueBase closed a $6 million seed round led by Bessemer Venture Partners.  Additional investors include 2 Lanterns, Argon Ventures, Converge, Feldsmith Capital, Good Friends, Graph Ventures, Gutbrain Ventures, KOA Labs, PBJ Capital, and Service Provider Capital.  The round was oversubscribed as RevenueBase enjoyed significant investor interest.

As part of the round, RevenueBase named three Directors to its Board:

• Kent Bennett, Partner at Bessemer Venture Partners
• Bob Davoli, Founder and Managing Director of GutBrain
• Jude McColgan, former CEO of Localytics

RevenueBase launched last spring looking to solve issues in the B2B data market, including difficulty in identifying and engaging with Ideal Customer Profile (ICP) prospects and marketing’s reliance upon spammy demand generation instead of well-targeted messages.  RevenueBase trebled its revenue over the past year and expects to do the same this year.  It has already onboarded twenty customers, with a focus on selling data as a strategic asset to the CMO or CRO.

RevenueBase was founded by industry veterans Mark Feldman, the VP of Marketing at NetProspex before its acquisition by Dun & Bradstreet, and Milenko Beslic, who built Cheapflights, the travel industry’s first metasearch engine.  As a marketing head at Backupify, Motion Recruitment, and Localytics, Feldman became frustrated with B2B data issues, including misalignment with the sales and marketing team’s go-to-market strategy, data decay, difficulty acquiring data, and managing disparate vendors and formats.  His stint as a B2B data customer led him to return to the B2B data space and create a product that broadly aggregates company, contact, and custom customer-specific insight data that aligns 1:1 with each customers’ go-to-market strategies.

Custom insights can be any variable that enables targeting of the right businesses.  For example,

• Does the company offer a mobile app?
• Are they a managed service provider?
• Do they have a call center?
• Do they sell perishable food products?

RevenueBase then builds a custom database for clients that it calls a Revenue Database, which is updated on an ongoing basis.

“We saw a whitespace for a company like RevenueBase, especially given that we’ve seen little real innovation or change in this market over the past decade leading businesspeople to be bombarded with impersonal and poorly targeted messages multiple times a day.  This situation has been made worse by ‘The Great Resignation,’ during which so many people have left their positions, and the data hasn’t kept up with those changes. Milenko and I knew that we could build a better solution to make it easier for companies to access more buyers in order to increase revenue.  We’re excited to have the support of great investors who are on board with our vision.”

CEO Mark Feldman

RevenueBase will deploy its funds towards building a customer UX and a set of enterprise software integrations for CRMs and MAPs.  It is also looking to grow its headcount from twelve to twenty before the end of the year.

“We think the opportunity to be the B2B data refinement layer powering growth-oriented companies is massive,” said Bennett.  “We are impressed with RevenueBase’s early traction and Mark’s and Milenko’s appetite to transform the B2B data industry.” 

Feldman argues that RevenueBase is distinguished across three dimensions: “completeness of data, data accuracy at scale, and ease.”  RevenueBase offers a high-touch, white-glove offering customized to each of its clients.  It begins with customer alignment, holding a set of discovery workshops that identify each customer’s “revenue archetype.”  RevenueBase then queries its 700 million global contacts database to build tailored databases for its clients.

Revenue Archetypes consist of an ICP, market segmentation, pains addressed, buyer personas, sales showstoppers, and custom insights that enable buyers to be engaged more personally. 

“A revenue archetype is a model of what your ideal customer looks like, i.e., one you can derive revenue from,” Feldman explained to GZ Consulting.  “It’s where there is a mutual benefit.  They need your product/service and will pay a fair price for it.  They also will favor you over the competition because your solution will result in the best cost-benefit tradeoff for the customer.“

Conversely, the Revenue Archetype also defines companies that are not good fits such as industries or geographies that require a standard not met by a firm’s offerings (e.g., HIPAA or GDPR requirements).  It also identifies roles not involved in purchasing a company’s products or services.  These individuals may be too junior in the organization or may not work in functions that use a company’s products or services.

RevenueBase argues that its knowledge graph technology improves the set of discoverable relationships, including the “longtail of customer-specific insights,” stated Feldman.  For example, RevenueBase can identify partners, investors, technologies in use, revenue streams, business models, key resources, and modern industries (such as Fintech and SaaS) that do not fall into standard industry classifications.

Conventional firmographics vendors must have a product manager pre-define the company attributes to be collected and then build these definitions into its data collection methodology and structure.  Because RevenueBase employs a graph database, it is not subject to these structural limitations and can identify uncommon or industry-specific elements that define the ICP.  The data structure also supports multi-point verification and data attribution.  In addition, data fields with high probabilities of changing, such as email addresses, job titles, and current employers, are re-verified at least four times per year.

RevenueBase promises to “replace all of your data vendors with one solution” that “reaches every company and decision-maker across the globe that will benefit from your unique offering.”  By delivering high-quality, targeted data directly to sales and marketing systems, revenue teams avoid time-consuming sales rep data research and managing databases. Data quality steps include custom research, quarterly email re-verification, and annual phone checks.  Data is delivered via a quarterly secure CSV file transfer with a 90% accuracy SLA.