Tune matching to your workspace
LeadSponsor's recommendations and matching scores adapt to your workspace profile — who you are, your audience, and your sponsorship strategy. The richer that profile, the more relevant the matches and the sharper the attack angles.
What powers the matching
Every workspace carries a memory profile with four fields:
| Field | What it captures |
|---|---|
institutionInfo | Who you are — your organization, sport, teams, and assets |
fanbaseInfo | Your audience — size, demographics, geography, engagement |
sponsoringStrategy | What you're after — sponsor types, deal formats, goals |
digitalEngagement | Your digital footprint — channels, reach, content |
get_recommendations, generate_matching, and get_hot_brands all read this profile to score brands against your context and produce tailored rationale.
Step 1 — Fill in your profile
Ask the assistant to build (or refresh) your profile from your LinkedIn page and the web:
"Generate my workspace memory from this LinkedIn: https://www.linkedin.com/company/your-org"
Uses generate_memory(workspace_name=…, linkedin_url=…, language=…) — takes 8–15 seconds and populates the four fields above.
Matching is only as good as your profile. After a rebrand, a new audience segment, or a strategy shift, regenerate your memory so recommendations stay accurate.
Step 2 — Get matched
Once your profile is in place, the matching is ready:
"What are my sponsor recommendations this week, with the match angles?"
Uses get_recommendations — your current targets with the rationale for each.
"Score the fit between my workspace and Decathlon, with attack angles."
Uses generate_matching(entity_name="Decathlon") — a tailored fit score plus how to approach them, grounded in your profile.
"What are my hot brands right now, and why are they relevant to me?"
Uses get_hot_brands — brands active in recent signals, ranked for your workspace.