The problem this solves
Most sequences are built from static lists, so the first line has nothing to say about timing. The prospect cannot tell why the email came this week rather than any other, because there is no reason - the list was built last quarter. Reply rates follow accordingly.
Intent data fixes the timing problem but usually dies before reaching the sequence tool. The signals live in one platform, the contacts in another, the sequences in a third, and the person who saw the signal is rarely the person loading the sequence. The freshest, most perishable information in outbound routinely expires in the handoff.
The fix is to make the signal travel with the contact: find the companies in motion, find the right people with addresses that verify, and land them in the sequence with the signal attached, all inside the window while the research is still happening.
There is also a compounding effect the manual version never reaches: when every sequence is built from this week's signals, reply data starts teaching you which signals convert. A topic that fills sequences but never books meetings is a topic to drop; one that converts at twice the rate deserves its own dedicated cadence. That feedback loop only exists when the signal rides all the way into the sequence field where reporting can see it, which is precisely what hand-built lists lose in the export step.
How the mission runs
- Sweep the intent signals for your category. The agent queries buyer-intent topics for your category and pulls the companies actively researching it this week - the in-market set, not the total addressable market.
- Find the decision-makers with verified addresses. For each in-motion company, the platform's contact tools locate the right role - the title band you sell to - and verification runs on every address before it counts. No verified address, no row.
- Annotate each row with its reason for being here. Every contact carries the signal that put it on the list: the topic, the intensity, the week observed. This is what powers a first line that reads like relevance instead of a mail merge.
- Push the set into Apollo as a live sequence. The annotated contacts land in a new Apollo sequence through your own connection, with the signal text in a custom field so your copy can reference it directly.
- Report the true numbers. You get the honest count at each gate - companies with signal, contacts found, addresses verified, rows loaded - so the funnel math is real rather than optimistic.
The prompt
This is the exact objective the agent receives. Swap the obvious placeholders for your own domain, segment or channel and run it as-is from the console, Slack, or the API.
What comes back
A signal-annotated Apollo sequence of verified in-market contacts, loaded this week while the research is live, with the gate-by-gate funnel counts.
Make it yours
- Narrow to a named account list: run intent only against your target accounts and sequence just those in motion.
- Route by intensity: high-intensity signals to a fast three-touch sequence, early research to a slower nurture.
- Deliver to a CSV plus Slack summary instead when your sending happens outside Apollo.
Frequently asked questions
How fresh are the intent signals?
The sweep reads current-week research activity. Signals decay fast, which is exactly why the whole path from signal to sequence runs in one mission instead of across a handoff.
Can the first-touch line be written too?
Yes - ask for drafted openers grounded in each signal and the agent writes them per contact; they land in the same custom field for your templates to use.
What if a company has no findable decision-maker?
It is reported in the dropped list with the reason, never padded with a guessed contact. True counts over big counts, always.