Christian layers hiring signals for sourcing

1/ Christian’s sourcing stack is a lesson in sequencing, not just tooling. The workflow starts with account selection, adds live intent-like signals, then filters for fit before anyone writes a cold email. The point is to make outbound lists narrower and more defensible, not bigger. (x.com) 2/ The first layer is Ocean.io for funded-company discovery. In practice, that means starting with companies that already match a financing profile — here, Series A through F SaaS — instead of beginning from a generic industry list. That changes the job from “find anyone” to “rank likely buyers inside a known band.” (x.com) 3/ The second layer is Trigify for engagement signals. That adds evidence that a company or its people are already interacting with relevant topics, creators, or conversations. For outbound operators, this is useful because it gives a reason for inclusion beyond firmographics alone. (x.com) 4/ The third layer is the one people in the replies seemed to care about most: hiring signals, especially SDR and BDR openings. That signal is simple but specific. If a SaaS company is hiring sales development reps, it may be expanding pipeline coverage, building outbound capacity, or investing in top-of-funnel motion. Respondents described that layer as a way to improve precision. (x.com) 5/ That matters because hiring signals are different from broad “intent” data. A job post is an operational event. It does not say a company will buy your product, but it does show the company is allocating budget and attention around a function your product may support. (x.com) 6/ Christian’s added recommendation was Clay enrichment for revenue filtering. This is the cleanup step that stops the list from drifting too wide. Once funded accounts and signal-bearing accounts are identified, revenue data helps sort which ones look commercially viable for the offer being sold. (x.com) 7/ Put together, the stack works like a funnel: - Ocean.io finds the funded universe - Trigify adds engagement context - hiring signals flag active buildout - Clay filters by revenue fit Each step removes noise from the step before it. (x.com) 8/ The practical takeaway for B2B SaaS teams is that this is less a “growth hack” than a list-construction method. It favors a smaller list with multiple confirming signals over a large TAM scrape. That can help early outbound teams decide who gets researched, personalized, and contacted first. (x.com) 9/ It also shows how operators are treating hiring data: not as a standalone trigger, but as a layer. On its own, an SDR/BDR opening is noisy. Combined with funding stage, engagement signals, and revenue filtering, it becomes a stronger ranking input for account prioritization. (x.com) 10/ The broader story is about outbound discipline. Christian’s framework suggests that better sourcing now comes from combining company-stage data, behavior signals, org-building signals, and enrichment — then using that stack to decide who is worth the first email. (x.com) 11/ If you’re building from this playbook, the operational question is straightforward: which signals in your stack indicate “possible buyer,” and which indicate “buyer worth contacting now”? Christian’s post argues hiring signals belong in the second bucket when paired with fit filters. (x.com)