salesauto-generated · unproven

How do I find the three-to-five people at a target company most likely to own the budget for your offer, ranked by buyer likelihood, from public org signals

the agent that answers this

decision-maker finder. find the three-to-five people at a target company most likely to own the budget for your offer, ranked by buyer likelihood, from public org signals.

Updated Jul 12

Cost: Free; on your own plan
Runs: On demand; or scheduled
Built from: 4 steps; 3 verified skills
Runs in: Claude or Codex; as you

what you get

a ranked shortlist of decision-makers with title, why they likely hold budget, and a first-touch angle for each.

buyer_reachedmeeting_booked

example result

illustrative

A finished run delivers: a ranked shortlist of decision-makers with title, why they likely hold budget, and a first-touch angle for each. Each run captures: buyer_reached, meeting_booked.

Example output, to show the shape of the deliverable. It has not run on your data. Build the agent to get this on yours.

the steps

4 steps · 3 from verified skills

Step 1
identify the roles that own budget for this kind of offer
Budget allocation and bidding strategy review across all ad platforms. Evaluates spend distribution, bidding strategy appropriateness, scaling readiness, and…
Budget Allocation & Bidding Strategy Process Collect budget and performance data across all active platforms Read ads/references/budget-allocation.md for allocation framework Read ads/references/bidding-strategies.md for strategy…
Full skill: ads-budget
Step 2
find the named people in those roles from public sources
Research a specific person using Common Room data. Triggers on 'who is [name]', 'look up [email]', 'research [contact]', 'is [name] a warm lead', or any…
Contact Research Retrieve a comprehensive contact profile from Common Room. Supports lookup by email, social handle, or name + company. Returns enriched data including activity history, Spark, scores, website visits, and CRM fields. Step…
Full skill: contact-research
Step 3decision
rank them by likelihood of being the actual buyer
Decision step
Step 4
draft a first-touch angle tailored to each person
Tailor a Commercial Teaching pitch to each stakeholder role using Functional Bias Cards and route the pitch to avoid the C-suite elevation trap. Trigger this...
--- name: tailor-pitch-by-stakeholder description: | Tailor a Commercial Teaching pitch to each stakeholder role using Functional Bias Cards and route the pitch to avoid the C-suite elevation trap. Trigger this skill when you need to: -…
Full skill: Tailor Pitch By Stakeholder

Run this agent in Implexa, on your own Claude or Codex, free

Get the Implexa app (or connect your Claude Code / Codex), then say build the decision-maker finder agent and approve the schedule. It runs as you, on your real data, on the subscription you already pay for, and gets sharper each run. Your agent's memory is yours and travels with you across Claude, Codex, and whatever comes next. About 5 minutes to your first real run.

Run this agent in Implexa →

common questions

How do I find the three-to-five people at a target company most likely to own the budget for your offer, ranked by buyer likelihood, from public org signals?

The decision-maker finder agent. a ranked shortlist of decision-makers with title, why they likely hold budget, and a first-touch angle for each.

Is the decision-maker finder agent free?

Yes. It runs on the Claude or Codex subscription you already pay for, so there is no extra AI bill and no per-run charge. You can build and run unlimited agents on the free plan.

How often does the decision-maker finder agent run?

You choose: run it on demand, or put it on a schedule (hourly, daily, weekly). Once scheduled it runs unattended, as you, on your own machine.

What does the decision-maker finder agent need to run?

Just Implexa installed in your Claude or Codex. There are no fragile integrations to wire up, and Implexa never touches your accounts, passwords, or the contents of your work.

Does the decision-maker finder agent use my data? Is it private?

It runs as you, on your own machine, on your real data. The model runs inside your own Claude or Codex, so Implexa never sees your data, accounts, or credentials. Your agent's memory is yours and travels with you across Claude, Codex, and whatever comes next.

How do I build the decision-maker finder agent?

Install Implexa into your Claude or Codex, then say "build the decision-maker finder agent" and approve the schedule. Implexa assembles the 4 steps (3 from verified skills) and it runs on its own. About 5 minutes to your first real run.

Can I change what the decision-maker finder agent does?

Yes. Tell it what to change in plain language and it revises its steps; the next scheduled run uses the change, with no re-scheduling. Every change is versioned, and a run can even propose its own improvements.