Champion Mapper
Turn a supplied contact CSV into an evidence-led stakeholder map, without treating title-based guesses as confirmed account truth.
Inputs it uses
- The target account name.
- A CSV containing each known contact's name, title, email, and last interaction.
- Equivalent fields such as
last_touch,last_activity_date, orlatest_email. - Optional explicit context such as replies, meetings, introductions, approval responsibility, business pain, budget, or timeline.
Blank, invalid, unknown, and stale interaction dates are preserved as missing or weak evidence rather than filled with a favorable guess.
What the result contains
- An org chart or text tree with unresolved reporting lines grouped under
Unknown / needs discovery. - A score table covering every supplied contact: role, score, influence, engagement, and concise score reason.
- An influence map whose relationships are labeled
likely,possible, orunknown. - A next-action table matched to economic buyer, coach, user, blocker/risk, or unknown status.
How the 0-100 score works
The heuristic combines title seniority, engagement recency, explicit influence signals, and risk penalties or caps. C-level roles keep high influence treatment, but missing or stale engagement prevents an automatic top champion score. Unknown titles, generic inboxes, inactive approval roles, and missing interaction evidence reduce confidence.
Every score includes a short breakdown such as Title: +20 director; engagement: +28 within 30 days; signals: +10 explains process; penalties/caps: none.
Representative output
Boundaries and limitations
The map is only as current and complete as the supplied contacts, titles, interaction dates, and notes. Titles can suggest function and seniority but cannot prove reporting lines, budget ownership, internal support, or account politics. The score is a repeatable prioritization heuristic, not a prediction that a person will champion or approve a purchase.
The package contains no scripts, CRM connector, enrichment service, browser automation, or outreach sender. It does not update records, research people on the web, or contact stakeholders. Review personal data and any eventual outreach under your organization's privacy, consent, and legal requirements.
Map the committee without turning inference into fact
Use the guide to separate role, authority, engagement, and demonstrated influence; label every relationship by confidence; and choose the next evidence-seeking action for each stakeholder.
Read the sales champion mapping guide →Questions
What does Champion Mapper need?
It requires a target account name and a CSV of known contacts with name, title, email, and last interaction. Equivalent last-touch field names are accepted, and explicit notes or CRM context can supply additional influence signals.
What does Champion Mapper return?
It returns an org chart or text tree, a per-contact score table, an influence map with confidence labels, and a role-specific next-action table.
How are champion scores calculated?
The 0-100 heuristic combines title seniority, engagement recency, explicit influence signals, and risk penalties or caps. The score estimates immediate champion usefulness; it is not a measure of personal value or confirmed authority.
Does a C-level title automatically make someone the champion?
No. C-level contacts receive high influence treatment, but stale or missing engagement lowers and caps the champion score. They may be an economic buyer or approver while another stakeholder acts as coach or champion.
Does it confirm reporting lines or account politics?
No. It infers likely functions and influence paths from supplied title and engagement evidence, labels every relationship likely, possible, or unknown, and places unresolved people under needs discovery.
Does it update the CRM or contact stakeholders?
No. The package contains instructions and reference files, not CRM integrations or outreach automation. It analyzes the supplied context and returns Markdown for the user to review.
See the committee, the confidence, and the next move.
Current price and purchase option are shown on Agensi. Champion Mapper works with agents that read SKILL.md and returns a reviewable Markdown analysis.
Get Champion Mapper on Agensi