Outbound from buying signals
Each morning, companies with a new stack or hiring signal are scored on your rubric, checked against the CRM and live sequences, and given one opener per buyer.
- Starts
- Daily schedule
- Steps
- 7
- Checks and gates
- 0
- A person decides
- Never, runs alone
Trigger · Schedule
Daily schedule
Each morning the run opens on the signals of the day before, so a company that adopted the tool you plug into on Tuesday is in sequence on Wednesday.
Claude runs the rest autonomously
- 1
AI builds the universe on stack and hiring.
TheirStackTheirStack
Companies that started running the tools you plug into, backed by more than one posting, and companies hiring for the pain you solve come back as one list with the detections behind it.
Apollo.ioApollo.io
- 2
AI scores on your rubric.
JevJev
Every company is scored on your profile written as closed questions, with a probability next to each answer, and the middle band goes to a person instead of a label.
- 3
AI drops what the CRM or a sequence holds.
HubSpotHubSpot
A customer, an open deal, another rep's claim, a company inside the cool-off or a person already in any sequence leaves the list with its reason, before anything is bought.
LemlistLemlist
- 4
AI reads why now, matches the buyer.
TheirStackTheirStack
Each company's postings and news come back as signals with the exact sentence behind them, and the signal names which of your buyer roles to write to.
SerperSerper
- 5
AI finds the buyers, enriches their emails.
Apollo.ioApollo.io
Two people per company come back with a verified work email, false affiliations purged, and anyone already in a sequence stopped.
FullEnrichFullEnrich
- 6
AI picks the play, writes each opener.
Your outbound playbook decides how many people to write to and in what order, and one opener per person is written from the signal, with only citable figures.
- 7
AI fills the campaign, updates the CRM.
LemlistLemlist
Everyone with an email joins the paused campaign with their opener, each company gets one note with its signal and score, and the team gets the recap with every company that stopped and why.
HubSpotHubSpot
SlackSlack
The companies most likely to buy this quarter said so yesterday, without meaning to. One started running the tool your product plugs into. One opened three postings for the role your product exists for. Someone on the team reads a newsletter, notices one of them, looks it up in the CRM, finds the right person on LinkedIn, writes a note, and does this for one company a day when the list had forty. By the time the sequence starts, the signal is three weeks old, two of the companies were already customers, and one was being worked by a colleague.
Each half of this is already a system. The signals are published, by the tools companies run and the jobs they post. The CRM knows who is a customer and who has a deal open. The outreach tool knows who is already being written to. Your profile of a good customer can be written as questions a model answers with a probability, and your playbook for working an account is written down. The run is the join, done every morning on yesterday's signals, with every company it drops named and the reason beside it.
What you get
Every company that showed a buying signal yesterday is scored on your rubric with a probability next to the score, checked against the CRM, every running sequence and every rep's claims, mapped to its buyers with a verified email each, and in a paused campaign with one opener per person by the time the team sits down, with every company it dropped named and the reason beside it.
Where the buying signals come from, and how they are scored
Two sources, read for the day before and merged on the company's domain:
- The stack, from TheirStack: companies that started running the tools yours plugs into, or their rivals, read at company level and kept only when more than one posting backs the detection. An agency or consultancy tagged with the tool because it sells work on it leaves here.
- Hiring, from the same source: postings opened for the roles that mean a company needs what you sell. One posting is a signal; three for the same role is a stronger one.
Every company is resolved in Apollo for its description, headcount and ownership, then scored by Jev on one rubric: your ideal customer profile written as closed questions, answered with a probability rather than a paragraph. The run keeps what is clearly in, parks what is clearly out and sends the band between to a person. The score, the probability and the model's name stay on the company, which is what makes the threshold mean the same thing tomorrow.
The buyers are found in Apollo and their emails come back from the FullEnrich waterfall; the reason to write now comes from the postings read in full and from a news search through Serper. The CRM is HubSpot, the campaign lives in Lemlist, and the team hears about it in Slack.
What makes signal-based outbound hold up
The CRM is read before anything is bought, and not once but four times. A customer, by lifecycle stage on the domain and never the display name. An open deal, by pipeline and stage identifier and never a label that gets renamed. A company another rep has claimed, or that anyone touched inside the cool-off, from the team's own register. And, once people are found, a person already in any sequence in the workspace or sitting on an open deal as a CRM contact. A company that passes is claimed with the date, so the next morning and the next rep find it held. Two correct processes writing to the same person in one week, or two reps paying twice for the same company, are the failures this exists to prevent, and the recap names every company it stopped and why.
Nothing expensive is bought for a company that already failed a cheaper test. Sourcing is almost free, the rubric costs a fraction of a cent per company, the CRM reads are free, and only the companies that pass all of them reach a people search, a reveal or an enrichment credit. A company parked by the rubric or stopped by a check costs nothing further.
A signal is quoted or it is not a signal. Each company's postings are read in full, because the sentence worth quoting lives in the description, and each signal is kept with that sentence and its date. The signal also names the buyer: a company hiring its first sales manager is a message to the founder, a company that just adopted the tool you plug into is a message to whoever runs it.
One opener per person, from the source
Your outbound playbook says how many people to write to in a company of a given size, in what order, with what gap, and which signals warrant the full play. The run decides per company, names the rule, and sends a signal too weak on its own to the watchlist instead of to a sequence. Every opener is written fresh from the signal, two sentences and one question, in the person's language, with nothing the sources did not say, no figure your proof points do not mark citable and no customer not marked citable. A draft that fails either check is not written, and the row says why, which is a finding about your proof points rather than a failure of the run.
People are added to a campaign your team keeps paused, each with their opener, and the campaign's own report proves nothing left. Each company gets one note in the CRM with its signal, its score and the play chosen, and nothing else is written there. The team gets one recap: what each source returned, what passed the rubric, who is in the campaign, and the skipped line, every customer, open deal, claim, cool-off, person already in a sequence and company with no one to reach, each with its reason.
The prompt
The real prompt behind the steps above, detailed enough that an agent with the same tools can run it as written. The Run buttons copy the full version, which also carries the steps for connecting those tools.
# Outbound from buying signals
You have access to a job-posting and tech-stack source, a company and
people database, a scoring model, a CRM, an outreach tool, a web
search tool, an email enrichment waterfall, and a messaging tool. Run
this every morning for **[the signals of the day before]**.
## 1. Build the universe on stack and hiring
Two sources, one list, merged on the company's domain.
- **The stack.** From the tech-stack source, companies that started
running **[the tools yours plugs into, and their rivals]** in the
last week, in **[your countries and headcount band]**, in one call
for the whole category. A detection resting on a single posting is
one job ad, not a stack: keep only companies whose detection rests
on **[at least two]** postings. A company whose industry is an
agency or a consultancy is tagged with the tool because it sells
work on it, and it leaves here.
- **Hiring.** From the same source, companies that opened a posting in
the last day for **[the roles that mean a company needs what you
sell]**. One posting is a signal; three for the same role is a
stronger one, and the count is kept.
Resolve every company in the company database for its description,
headcount, founding year and ownership, ten domains per call. Keep
the record light: domain, name, headcount, industry, what was
detected and the postings behind it. Report the total each source
returned beside what was kept, so the team can see whether the
segment is bigger than the morning.
## 2. Score on your rubric
Send every company to the scoring model with the same rubric, in
batches: **[your ICP written as closed questions, for example: is
this company a buyer of what you sell, yes or no; which segment is it
in, one of your named segments or none; how well does it fit, on a
scale of 0 to 4]**. Send only the fields the judgement needs, never
the whole record.
Each answer comes back with a probability. Read it with two
thresholds: a fit above **[0.8]** is in, below **[0.4]** is parked,
and the band between goes to a person with the reasons, never forced
to a label. Store the score, the probability and the model's name on
the company, so the threshold is reproducible. A company parked here
costs nothing further: no search, no enrichment, no credit.
## 3. Drop what the CRM or a sequence holds
This is where most of the morning's list stops, and it stops before
anything is bought. Four checks, in order, on every company that
passed the rubric:
1. **A customer.** Match the domain against the CRM's companies, on
the domain property and never the display name, and read the
lifecycle stage. A customer leaves the list.
2. **An open deal.** Read the deals associated with each matched
company, by pipeline and stage identifier, never by stage label.
A company with an open deal leaves the list, and its owner gets one
line saying it just showed a signal.
3. **Another rep's claim.** Read **[your claims register]**: a company
claimed by another rep inside **[the claim window]**, on your
exclusion list, or touched by anyone inside **[the cool-off after
a touch]** leaves the list with that reason.
4. **A person already in a sequence.** Once people are found in step
5, look each email up in the outreach tool's whole workspace, not
one campaign, and against the CRM's contacts with their deals. A
person already in a sequence, or a CRM contact on an open deal,
stops.
A company that passes is claimed for this run's owner in the register
with the date, so the next morning and the next rep find it held.
Nothing billable is spent on a company this run has not claimed.
## 4. Read why now, match the buyer
For each claimed company, read its postings of the last **[90 days]**
in full, since the sentence worth quoting lives in the description,
and search the news of the last month for funding, expansion and
leadership changes. Keep each signal with the exact sentence it rests
on and its date. A signal with no quote behind it is not written.
The signal names the buyer: a company hiring its first sales manager
is a message to the founder, a company that just adopted the tool you
plug into is a message to whoever runs it. Write down which of
**[your buyer roles]** each signal points at. A company with no signal
is still worked; it opens on the segment instead of a reason.
## 5. Find the buyers, enrich their emails
Search the people database one domain per call, with the buyer roles
from step 4, the person's country and at most three candidates, and
keep **[two]** per company: the one the signal points at and one
beside them. Reveal each by their identifier, never by name plus
company, and read the contact record as well as the person record: an
address is usable only when both agree.
Send the misses to the enrichment waterfall as one job for the whole
morning, work emails only. Purge false affiliations: the email domain
belongs to the company, the employer returned matches it, and the
same person is not attached to two companies in this run. Then run
check 4 of step 3 on every email. A company where nobody resolves
keeps its claim and is reported for a person to find someone by hand.
## 6. Pick the play, write each opener
Read each company against **[your outbound playbook: how many people
to write to by segment, in what order, with what gap, and which
signals warrant the full play]**. Decide per company: the full
sequence, one person only, or the watchlist for a signal too weak on
its own. Name the rule.
Then write one opener per person: two sentences at most, the signal
first, quoted where it is a quote, and one question. In the person's
language. No pitch, no adjective about the company, nothing the
sources did not say, no figure your proof points do not mark citable,
no customer named that is not marked citable. A draft that fails
either check is not written, and the row says why.
## 7. Fill the campaign, update the CRM
Add each person with an email to **[the campaign your team keeps for
signal-based outbound]**, with their opener as the first-step
variable, deduplicated on email. That campaign is kept paused, and its
reports call proves it: the lead count up by the morning's people, and
nothing reviewed, in sequence or sent. If the campaign is found
running, add nobody and report that it was.
Write one note on each company in the CRM: the signal with its quote,
the score with its probability, the tier and the play chosen. Nothing
else: no property, stage, deal or owner. Create a company only when
the domain search came back empty.
Post one recap to the team: the universe against the total each
source returned, how many passed the rubric, how many were parked, and
every company that stopped with its reason, customers, open deals,
claims, cool-offs, people already in a sequence, unreachable, no
draft. The skipped line is how a rep finds out that half the segment
already belongs to someone else before the next morning repeats it.
## Output
Report: companies from each source against each source's total,
scores with their probabilities and the band sent to a person,
companies stopped at each of the four checks with their reasons,
signals found with their quotes, people found, emails verified and
purged, the play per company, drafts written and withheld, the
campaign and its paused state, and the notes written.
Why run it with Tulina
A prompt helps one person. A process moves a team.
Pasted into a chat, the prompt above works once, for whoever pasted it. In Tulina, "Outbound from buying signals" becomes a process the team shares, that keeps its history, runs on its own, and stays inside the same security perimeter as the tools it calls.
The whole team works on the same one
PersonalTeamOrganisation
A process lives where it belongs: yours, your team's or the whole organisation's. Whoever runs it can improve it, and everyone starts from the best version instead of explaining the job again.
Every edit is a version
v1v2v3
Each change is a new version with the previous one kept, so a bad edit is undone by restoring an earlier one. Every run records the version it followed, and what a run teaches goes back into the process.
It runs without you
schedulewebhookon demand
A hosted agent runs the process on Tulina's own infrastructure, on a schedule or when an event arrives, and keeps going when you close the chat. Nothing to host. Every run is tracked to its outcome.
Inside the same security perimeter
vaultrolesrun log
Credentials stay in the vault, never in the prompt. Roles decide who may run what, every call is logged, and a step a person has to approve waits for that person.
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