AI Prospect Discovery Meeting Prep in 10 Minutes

Discovery meetings are where the prospecting funnel converts. The advisors who win them are the ones who walk in feeling like they already know the prospect. AI lets you do that in 10 minutes instead of 60.

Here's the workflow we deploy at advisor firms.

What the AI handles vs what you handle

AI handles:

• Public-record research (LinkedIn, news, public filings, social if available)
• Wealth estimation and signal aggregation (via Catchlight or similar)
• Behavioral and personality inference (via Crystal, Humantic)
• Conversation hook generation
• Risk-of-objection identification
• Prep questions tailored to the prospect

You handle:

• The meeting itself
• The relationship build
• The actual diagnosis of fit and need
• The strategic call on whether to pursue

The AI gets you into the meeting prepared. The meeting still belongs to you.

The data sources

For each prospect, the workflow ideally pulls from:

• LinkedIn (employment history, posts, connections)
• Catchlight or similar (estimated wealth, life-event signals)
• Crystal/Humantic (DISC-style behavioral inference)
• Google/news (recent business activity, articles, quotes)
• The referrer's notes (if introduced) — most valuable input by far

Not every prospect has rich data. The workflow degrades gracefully — pulls what's available, flags what's missing.

The brief the AI produces

10 minutes before the meeting, the advisor opens a one-page brief:

`` PROSPECT: [Name] MEETING TIME: [time] SOURCE: [Referral from X / Inbound / Event]

WHAT THEY DO [2-3 sentence summary of role, company, career arc]

WHAT MATTERS TO THEM (inferred)

• [Likely top concern 1, based on age/career stage/recent signals]
• [Likely top concern 2]
• [Likely top concern 3]

LIKELY WEALTH PROFILE

• Estimated AUM target: $[range]
• Likely account types: [taxable, retirement, equity comp, business equity]
• Estimated complexity: [low/medium/high]

PERSONAL HOOKS

• [Family info if available]
• [Hobbies/interests if found in public data]
• [Recent significant events]

LIKELY OBJECTIONS

• [Objection 1, based on profile]
• [Objection 2]
• [Objection 3]

DISCOVERY QUESTIONS TO ASK

• [Question tailored to their situation 1]
• [Question 2]
• [Question 3]
• [Question 4]
• [Question 5]

WHAT NOT TO LEAD WITH [Things to avoid given their profile]

REFERRER CONTEXT (if applicable) [Notes from the referrer] ``

The workflow steps

Setup (once, ~2-4 hours):

• Connect data sources (Catchlight, Crystal, LinkedIn export)
• Build the prompt scaffold
• Pilot on 3-5 prospects before going live

Per-prospect (10-15 minutes total):

• Workflow auto-triggers 24-48 hours before meeting
• Brief lands in advisor's prep dashboard or email
• Advisor reads brief, customizes 1-2 questions
• Saves brief into CRM for post-meeting reference

Compliance considerations

Public-record research on a prospect is unrestricted. Things to handle carefully:

• Don't share AI-inferred wealth estimates with the prospect. They're directional, not diagnostic, and can be wrong in ways that damage trust.
• Don't reference how you got specific information ("I see you sold your company last quarter"). Use the data to ask better questions, not to perform research.
• Don't store prospect data beyond what's needed. Retention rules apply once a prospect becomes a client; pre-client research should have a defined retention period.

The mistakes to avoid

Mistake 1: Generic prep. "Tell me about yourself" is a wasted question. AI prep should make every discovery question specific to what you already know.

Mistake 2: Showing off the research. Walking into a meeting and citing the prospect's public statements feels invasive. Use what you know to ask better questions, not to demonstrate research depth.

Mistake 3: Trusting AI inference too much. Behavioral inference from public data is directional. The prospect is a real person, not a personality profile.

Mistake 4: Skipping the referrer notes. If you got the prospect from a referral, the referrer's context is the highest-value input. The AI brief should incorporate, not replace, that context.

The measurable impact

At firms running this workflow:

• Discovery meeting conversion lifts 5-12 percentage points (from ~30% to 35-42%)
• Meeting prep time drops from 45-60 minutes to 10-15 minutes
• Advisor confidence in the meeting is materially higher
• Post-meeting follow-up is faster because the AI brief becomes the CRM entry

The conversion lift is the real win. Better-prepared meetings convert better, and at advisor economics, even 5 points of conversion lift on 40 meetings/year produces 2 additional new clients = ~$15k/year in new fees.

Scaling across the firm

For multi-advisor firms, the prep workflow standardizes the firm's discovery process:

• Every prospect gets the same depth of prep
• The brief format becomes a training tool for newer advisors
• Compliance can sample prep briefs as part of supervisory review
• Conversion rate measurement becomes possible because the prep is consistent

Bottom line

Discovery meeting prep is high-leverage work that most advisors compress because it's tedious. AI does the compression for you. The advisor still owns the meeting; the AI just makes sure you walk in prepared.

10 minutes of AI-assisted prep beats 60 minutes of manual prep for most prospects. Use the recovered time for the meeting itself or for more discovery meetings — both compound advisor pipeline.