16 GTM plays, with receipts.

Fires when: Someone who used your product at a previous company starts a new role.

1. Sync every closed-won and power-user contact into a watch list.
2. Poll for employer changes weekly, not daily. Nobody buys in week one.
3. Gate on two things: the new company is in ICP, and the person kept or gained seniority.
4. Open with what they already know about the product, never with congratulations.

17% or higher reply rate and a 10% booked-meeting rate, roughly 2x Common Room's cold baseline. Former champions convert about 3x more often than cold prospects.

Source: Common Room, Plays that payfirst-party

Fires when: A known-account visitor hits a high-intent page and never fills in a form.

1. Accept that person-level resolution tops out around 15 to 20% of traffic. Work the account level for the rest.
2. Score by page, not by visit count. Pricing and docs beat the blog.
3. Because you cannot be certain who visited, lead with account research rather than the visit itself.
4. Route to a human within the hour. The window is the whole advantage.

2x reply rate and 2x booked meetings versus cold outbound, at 17%+ reply and 10% meetings. For context, about 98% of site visitors leave without filling anything in.

Source: Common Room · HubSpotfirst-party

Fires when: Any buying signal fires: funding, a new exec, a tool change, a job post.

1. Treat latency as the product. Measure hours from signal to first touch.
2. Hold the record in a delay queue if the signal is noisy on day one, then send inside the window.
3. Never mention the signal itself. Say the consequence.
4. Instrument signal-to-meeting rate per trigger type so you can kill the dead ones.

Signal-triggered campaigns report 3x to 5x higher positive response than static list outbound, and reaching a prospect within 48 hours of the trigger lifts booked meetings by up to 40%.

Source: Vanderbuild, The signal revolution

Fires when: Quarterly review of every trigger you run.

1. Start with three to five trigger types, not fifteen.
2. Run each for a full quarter before judging it.
3. Keep only triggers whose signal-to-meeting rate clears 3%.
4. Expect a wide spread: funding and headcount growth carry most programmes, social engagement carries almost none.

Reported conversion by trigger: funding around 30%, headcount growth 25%, a competitor post about 5%. One team's six-month numbers were 4.57x ROI, 85+ SQLs, 6 closed deals and a 35% CAC reduction.

Source: Reachly, Signal-based outbound playbook

Fires when: Any list leaves research and enters sequencing.

1. Never run a single provider. Coverage caps out around half your list.
2. Chain providers cheapest-first and stop at the first verified hit.
3. Verify before send, not after bounce.
4. Track cost per verified contact, not cost per credit.

Single-provider email coverage runs around 50%. A waterfall takes the same list past 80% coverage, across 50+ Clay deployments.

Source: GTMinds, Clay outbound playbookfirst-party

Fires when: A segment shares one specific, nameable pain.

1. Segment by the pain, not the firmographic.
2. Write one message per pain and refuse to reuse it across segments.
3. Keep volume high enough to read the result, low enough that every message stays unique.

A 1,478-lead campaign built this way returned a 24.2% positive reply rate. A second, aimed at founders and CEOs across 1,798 leads, returned 30% positive replies.

Source: Outbound Republic case studiesfirst-party

Fires when: You are about to put open rate on a dashboard.

1. Apple Mail Privacy Protection and corporate scanners pre-load tracking pixels, so opens are partly machine noise.
2. Report reply, meeting and pipeline instead.
3. If you must keep opens, halve them mentally before drawing a conclusion.

Reported open rates average about 43%, but real human opens sit nearer 25 to 30%. Only 15% of marketers still treat open rate as a primary metric.

Source: Salesmotion, Signal-based outbound metrics

Fires when: Before you claim any campaign worked.

1. Hold out a control group from the same list, every time.
2. Compare against your own cold baseline, not a vendor's published average.
3. Record the hypothesis before the build, so the result can actually falsify it.

Published B2B cold-email baselines cluster between 0.5% and 3.4% reply, and broad sequences to scraped lists sit under 1%. Only 3 to 5% of any addressable market is in an active buying cycle at a given moment.

Source: Growleads, citing Woodpecker and Forrester

Fires when: Any campaign about to leave the building.

1. Automate research, enrichment, drafting and routing.
2. Keep exactly one human gate: a person reads the batch before it sends.
3. The gate is a sample, not every row, or it stops scaling.

One agency runs about 90% of its outbound workflow on automation and still passes every campaign through a human checkpoint before send.

Source: The Playbook Agency, The Clay stackfirst-party

Fires when: You are deciding whether signal-based outbound is worth the build.

1. Run the signal programme and a cold control on the same ICP, same quarter.
2. Measure reply and meeting rate on both.
3. Only then decide what to keep.

Teams running signal-based outbound report 15 to 25% reply rates against roughly 3% for traditional cold email on the same kind of list.

Source: Reachly, citing Unify