FinanceInvestor CRM Cross-Sell Recommender
Generate explainable service-gap and cross-sell recommendations for a family-office relationship, with every recommendation traceable to a rule.
PPredictive Labs·Finance
Library skill — the default version is maintained in GitHub; edits you make live in your own clone.
cross-sellfamily officerecommendationsrevenue
How does this work?
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Cross-Sell Recommender
Surface the next-best services to offer a family-office relationship, combining a
deterministic rule layer with an AI re-ranking pass — so every recommendation is
explainable and auditable.
When to use
- Reviewing a relationship for white space and revenue opportunities.
- Preparing an account plan or QBR.
- Feeding a proposal drafting step ([[proposal-generator]]).
Inputs
- A current [[family-office-profile]] (structure, asset mix, jurisdictions, pain points).
- The catalogue of services you can offer and their eligibility criteria.
- Existing services already in place for the relationship.
Steps
- Run the rule set against the profile to find eligible-but-unused services; each hit
carries a
rule_id and the profile facts that triggered it.
- Score candidates by fit, urgency and estimated value.
- Re-rank with an AI pass that weighs qualitative context (stated mandates, timing).
- Attach a plain-language rationale to each recommendation citing the triggering facts.
- Drop any recommendation that cannot be traced back to a rule or profile fact.
Output
A ranked list of recommendations, each with: service, rationale, rule_id/source,
estimated value and suggested next action.
Presenting results
- Present every result as one or more clear Markdown tables — one per section, each with a short heading.
- Keep prose minimal; put the substance in the tables.
- Offer the user a downloadable PDF (formatted) and CSV (the underlying rows), and generate them when asked.
- Never invent figures. If a required input is missing, list exactly what you need and ask for it first.