Why We Invested in Operator: True Differentiation in Sales Data

Pipeline coverage is the lifeblood of every B2B organization, and the robustness and actionability of a company’s prospect data will make or break their growth strategy.

Almost every B2B company licenses data about their prospective buyers. Sales teams need to know not just the basics about their targets—name, title, phone, email—but also crave contextual data to further qualify an opportunity and ensure that their messaging is as targeted and timely as possible.

In the past sellers were satisfied with information like the prospect’s tech stack or team size but today, even that data is considered obvious. The holy grail has become an insight as rich and specific as, “owners of insurance agencies within two hours of Houston that support Medicare and have hired 10+ new agents in the last 12 months."

But despite this acute market need and established budgets that are actually growing, the status quo is abysmal, and has been for a while. While I was the CRO at Sailthru, we licensed data from multiple providers only to have our own revenue operations team franken-stack their disparate data together to develop a richer understanding of our prospects: BuiltWith data on the prospects’ current tech stacks, information on the size of their CRM teams, an assortment of third-party inputs that provided annual email volume estimates, etc. This stitching work was the bane of our RevOps team’s existence and even when that team delivered, we still faced a host of challenges:

• Data robustness. As previously mentioned, we were forced to invest in multiple tools in order to be able to build a true 360-degree view of the prospect. No single player could offer us a three-dimensional view.
• Cost scalability. Our vendors knew how desperate we were for their data and charged us accordingly; economies of scale were seemingly non-existent. And we were constantly adding new sources.
• Data accuracy. We lived in a world where accuracy rates of 60%+ were considered acceptable and even “good.”
• Feedback vacuum. Even once we realized we had inaccurate data, we endured a painful process to update our CRM system.
• Timeliness and actionability. The data we aggregated was largely static, meaning the sales team still had to manually research more time-sensitive context (e.g. recent leadership changes or new job postings).
• Accessibility of insights. Even with great Franken-stack plumbing in place, most members of the GTM team lacked the technical chops to develop multifaceted insights or pull custom data cuts.

Don’t get me wrong: in more recent years, long-standing incumbents like ZoomInfo have certainly offered some improved integrations, and newer entrants like Apollo and Clay have successfully challenged those incumbents. But even with those advancements, there is still no universal painkiller. To be a truly coordinated, world-class prospector today, you must be a dexterous growth hacker, and that in reality is 1) not achievable for many and 2) not scalable for any.

I haven’t even touched on the resulting implications for buyers, but they are not good. Most platforms are licensing the exact same data (and lackluster insights) to all of their customers, meaning Company X and its direct competitor are often armed with the same intel and their buyers are left struggling to discern signals from noise, which usually results in messages being completely ignored. Sellers invariably wind up abusing the data they do have by inundating buyers with persistent and relentless messaging, and automation capabilities have exacerbated the situation: automated outbound is cheap and easy; throw enough against the wall, and something will stick. The promise of AI-powered BDRs will only make matters worse. I frequently joke that I long for the “Promotions” tab equivalent for AI-generated prospecting messages!

Both revenue teams and their buyers deserve better, which is why we couldn’t be more excited to introduce Operator.ai and to announce its $3.6 million pre-seed round we led alongside GTMfund.

Operator’s Founder and CEO Mark Kosoglow was employee #1 at Outreach, where he grew ARR from $0 to $200MM+ in seven years, making it one of the fastest growing SaaS companies in history. And by scaling one of the most respected category creators in integrated sales automation, Mark has seen how people use it as a “spam cannon” plaguing buyers everywhere. And he’s committed to righting the ship.

Operator was incubated by Max Altschuler at GTMfund and Adam Meyer, Mark’s cofounder and a master 0-1 product and design leader who previously cofounded Monospace and more recently was a founding member of the Amazon Explore team. The combination of Mark’s go-to-market expertise and Adam’s product brain is one for the ages, and GTMfund’s LP network of 350+ go-to-market leaders from companies such as DocuSign, Salesforce, LinkedIn, Snowflake and Okta–or said another way, leaders who understand this problem statement all too well–was certainly an exciting part of the package. My colleague Zach Fredericks likes to preach the gospel of the “$0 CAC CEO;” Mark and Max are two of the most respected and widely-followed thought leaders in the go-to-market world, so their domain expertise and reach certainly fit that bill. We couldn’t imagine a team better suited to disrupt this category.

Operator does more than just stitch together data sources, though: the platform provides rich insights specific to your business and unique ideal customer profile so that prospecting efforts are less about optimizing the volume and “touches” and more about attracting the best possible customers; Operator’s heat map visualization of prospect relevance has been a favorite with early customers. Better yet, Operator offers seamless workflows to make these insights actionable for sellers, whether that is automatically purging bad data from the CRM or enabling sellers to send automated triggers based on real-time insights. And perhaps best yet, they’ve built the solution in a way that democratizes access to these insights: no technical chops required.

The combination of Operator’s developing data advantage and ROI-rich workflows were a perfect match for our GTM SaaS thesis at Primary. Moreover, we have strong conviction that there will be a wave of AI-native companies that manage to completely disrupt established incumbents with lower prices and stronger results, and expect Operator to do just that in the GTM data category. We are excited to build alongside Mark and his team as they revolutionize the way that revenue teams attract new customers and challenge what’s possible for improving the B2B buying experience and eradicating what Operator has dubbed the Great Ignore.

To play your part in challenging what’s possible in the world of GTM data, join Operator’s waitlist here.