Account scoring without the black box

Specter 1.0

The tribe has spoken and black boxes are so out

Nearly a decade ago, 6sense coined the "dark funnel." They weren't wrong. Buying behavior had shifted from businesses having all the power to individuals researching on their own terms. Account-level scoring based on the singularity of publication-based research intent was novel.

But fast-forward to today, GTM professionals are challenged by an entirely new frontier. AI has (once again) shifted how we buy; agents make up more than 50% of the internet's activity, eating our owned audiences. Simultaneously, decreasing technical moats bring more competition meaning more noise across inbound and outbound.

The legacy playbook doesn't work.

A new bombshell has entered the villa

Introducing Specter 1.0: the world's first purpose-built scoring model for ABM.

It combines powerful machine learning with bleeding-edge large language models. The result? Your rich 1st, 2nd, and 3rd party signals are processed by a model that deeply understands their nuance, ensuring your GTM efforts across paid advertising, marketing campaigns, and sales activations are optimized.

Stop manually weighing signals

In benchmarking, Specter 1.0 outperformed 100% of models hand-weighted by Marketing and RevOps teams (n=63).

GTM professionals have been conditioned: manual scoring = control. Afterall, your business is unique. Will a model really be able to understand that certain nuanced signals make all the difference?

Turns out, the answer is "yes." Across 174 companies, the top 10% of Vector-scored accounts contained ~50% of the next month's new deals, 5× better than working the same list at random. The top 5% held ~40% of deals, nearly 8× lift.

Transparent reasoning & contact-level actionability

Let's face it: we sell to people, not accounts. Most ABM programs fall apart with two simple questions:

• Why is the account "surging"?
• Who should I reach out to?

Specter 1.0 answers them both. Instead of spitting out a meaningless numerical score, it provides a human-readable explanation of its reasoning, ready for human and agent consumption. Finally, Specter leverages Vector Signals and Journeys, suggesting exactly who in the buying committee is in-market and why.