signal-outbound

Signal Outbound — master

Classic outbound looks for companies that resemble your customers and tells them about a service. This runs the other way: find the companies that already described their own problem in public, and open with their words.

The richest source of those words is job postings. A company that writes "our application is a majestic monolith" paid to publish that sentence and will not walk it back. That is not a guess about pain. It is pain confirmed by a hiring budget.

Everything downstream follows from one split: the event tells you when to write, the data point tells you what to say.

Locating the caller

Ask at most three questions, and stop as soon as the answer is determined.

1. What artifact do you already hold? Nothing / an ICP / a list of companies / a scored list / a sequence / a live campaign / replies coming in.
2. Has anything been sent from these domains before? Never / warmed but not sent / sending now.
3. What is the actual complaint? Only when something is running: no opens, no replies, replies that go nowhere, or good replies that die later.

Do not ask for a strategy deck or a budget. If they had those they would not be asking where to start.

The gates, in one place

Every step below depends on one condition. Route past a failed gate and the work after it is wasted, so name the gate out loud and say what skipping it costs.

Gate	Condition	If it fails
G1 — infrastructure	domains authenticated, mailboxes warmed, send caps set	deliverability-audit. With broken sending you cannot tell weak copy from a blocked domain, so every later measurement is unreadable.
G2 — a hypothesis exists	you can say who, on what trigger, with what offer	hypothesis-builder. A campaign without a stated hypothesis cannot be judged later, only argued about.
G3 — volume	300 accounts per event-signal hypothesis, 500 per data-point one	bundle related signals, or widen the category. Report the shortfall rather than running a test that cannot produce a readable result.
G4 — the list is really the ICP	90% spot-check passes	back to account-sourcing. Two thirds of raw results are agencies, government and universities.
G5 — a reason to write now	rows carry a dated signal or a data point with a source	signal-research. Without it, the no-signal queue has nothing to open with and the campaign is a mass mailing wearing a first name.
G6 — contactable	verified addresses, or the LinkedIn route confirmed	waterfall-enrichment. Enrich only what already passed — it is the expensive step.
G7 — no meeting ask	every touch ends on an interest question	back to sequence-writer.
G8 — the file is clean	final CSV passes the seven-layer check: no suppressed contacts, no invalid addresses, every variable rendered	pre-launch-data-check. One current client or one broken {{first_line}} in the upload costs more than a day's delay.

The path

Ten steps. Each ends in an artifact, and four of them end in a gate that stops the run.

#	Step	Route to	Ends with
1	ICP and tiers	gtm-market-icp-persona ⧉	tier matrix + personas + anti-ICP
2	Offer and entry rung	offer-factory ⧉	5–6 scored bets, entry rung chosen
3	Signal catalog	signal-catalog	50 triggers, scored, bundled
4	Hypotheses	hypothesis-builder	10 scored, three picked · GATE: volume
5	Account list	account-sourcing, then signal-research over it	scored CSV with dated evidence · GATE: 90% ICP spot-check
6	People and email	waterfall-enrichment	contacts with verified addresses
7	Sequence	sequence-writer	8 touches, both personas · GATE: no meeting ask
8	Personalization	personalization-pipeline	two generated fields + confidence gate
9	Base check	pre-launch-data-check	GO verdict + rows-to-fix file · GATE: clean file
10	Launch	deliverability-audit	SPF/DKIM/DMARC, warm-up, send caps

Running later: weekly-outreach-report for the weekly read, reply-audit when replies accumulate, ab-test-analyzer for angle tests.

⧉ = lives in a different plugin. gtm-market-icp-persona is in gtm-strategy-skills, offer-factory in gtm-skills. Without them installed, run steps 1–2 by hand — the path still works, it just loses the scaffolding for those two artifacts.

The four rules that carry the whole thing

A state signal does not work alone. "Your framework is out of support" earns "we know, thanks." Pair it with an event — "you raised in March, that framework lost support in March" — and it becomes a conversation. Step 3 forces this distinction; do not let it collapse.

Volume gate: 300 accounts per event-signal hypothesis, 500 per data-point hypothesis. Under that, the test cannot produce a readable result. Bundle related signals under one email theme, or park it. If no bundle clears the gate, the niche was drawn too narrowly — turn the vertical from a targeting filter into a proof selector and widen.

No meeting ask anywhere. Not in email one, not in the breakup, not on LinkedIn. The only job of a cold touch is a reply.

Two generated fields, never a generated letter. A fully generated email drifts to the mean: correct, smooth, faceless. A fixed skeleton holds the voice while the model does the one thing a template cannot — read someone else's document and form a thought about it.

Where runs actually fail

The vertical was used as a filter when it should have been the proof. A niche with strong case studies but only a few hundred companies is an ABM target, not a campaign. Detect the signal across the wider category and show the case study that matches the reader's vertical. Catch this at step 4, not after the list comes back empty.

Two thirds of raw sourcing results are noise — agencies, government contractors, universities. No vendor flag catches them. Budget time for an explicit exclusion pass at step 5, and diff what got dropped: over-filtering quietly removes real accounts.

The quote was never read by a person. Roughly one keyword match in seven is a false positive — "building a legendary legacy" is not a modernization signal. Ten seconds per account before enrichment.

Personalization was attempted inside the sequencer. It cannot be done there. If step 7 produced a first line that carries a thought, step 8 is mandatory, not optional.

The list was enriched before it was filtered. Enrichment is the expensive step. Spend it only on accounts that already passed.

When a live campaign is underperforming, route by symptom

The complaint points at a stage. Do not restart from step 1.

Symptom	Most likely stage	Route
Almost nothing opens	infrastructure, not copy	deliverability-audit
Opens fine, no replies	the opener has no reason to exist	signal-research, then rewrite the no-signal queue on data points
Replies, but all "not now"	targeting is right, timing is not	reply-audit, then revisit signals at step 3
Replies, but all "tell me more" that die	the copy is vague — they are curious about you, not about their own problem	reply-objection-handler (read the tier mix), then the sequence
Good replies that go nowhere later	the handoff after the reply	lead-scoring, then reply-objection-handler
Numbers look fine, nothing closes	the offer, not the outbound	say so plainly and stop routing — this bundle cannot fix an offer

That last row matters. A router that always finds an outbound answer is useless, because sometimes the honest answer is that outbound is not the broken part.

Reading the results

State	Condition	Action
Kill	replies under 1.5% or interest under 17%	change the signal or the angle, not the copy
Optimize	interest 17–30%	new angles, tighter filters
Scale	interest above 30%	add a channel, raise volume

Measure per hypothesis, never per campaign. A campaign mixing two signals reports an average that describes nothing.

Working ceiling on a signal campaign is around 10% positive replies. Vendor-published figures of 35–40% are marketing.

Cost, so nobody has to guess

Roughly 2.5 credits per send-ready lead plus pennies per posting scanned. A 300-lead batch lands near 750 credits and a few dollars of scraping. Say this early — teams routinely assume an order of magnitude more and scope down for no reason.

Enterprise intent platforms starting at $30k/year do not pay back at this volume. Name them, price them, move on.

What never enters the machine

The top 20–30 accounts by score. A person writes those. Automation takes the middle, not the peak.

When someone arrives mid-path

Ask what artifact they already hold, then enter at the next step. Do not restart at step 1 to be thorough — check the existing artifact against its own gate and move forward. A list with no proof quotes goes back to step 5; a sequence with a calendar link goes back to step 7.

Hand off properly

End every run with three lines, no more:

Where you are: [step]
Gate: [met / failed — which one, and what skipping it costs]
Next: run `[skill]` — [one line on what it produces]

Then stop. Do not pre-empt the skill's own questions or summarise what it will say. When someone returns with the same complaint twice, do not route them to the same skill twice — name the assumption that is probably wrong instead.