Why Most Discovery Calls Fail
Most AI consultants walk into discovery calls hoping to impress. Wrong frame.
The goal of a discovery call isn't to convince them to hire you. It's to qualify whether they're worth hiring.
When you flip that dynamic, everything changes. You ask harder questions. You walk away from bad fits. And prospects respect you more, because you're not desperate.
The 10-Question Qualification Scorecard
Score each answer 1-3. Max score: 30. Don't take projects under 20.
Budget & Authority:
- Who signs the contract? Are they on this call? (3 = decision-maker present)
- Is there an allocated budget? (3 = yes and it's confirmed)
- Have they used consultants before? (3 = yes, paid premium)
Problem Clarity:
- Can they describe the problem in one sentence? (3 = crystal clear)
- Do they know what success looks like? (3 = specific measurable outcome)
- What have they already tried? (3 = shows genuine effort, not looking for magic)
AI Readiness:
- Do they have clean, accessible data? (3 = yes, confirmed)
- Is there technical staff to maintain after delivery? (3 = yes)
- Are stakeholders aligned on AI adoption? (3 = yes, no internal resistance)
Timeline & Urgency:
- What happens if this doesn't get solved? (3 = real consequence, not vague)
Scores 25-30: Priority close. 20-24: Proceed with scope limits. Under 20: Pass.
The One Question That Screens Out 80% of Bad Clients
"What does failure look like for this project?"
Good clients answer specifically: "We'd still be processing claims manually, costing us $40K/month."
Bad clients answer vaguely: "It just... doesn't work out."
The full Discovery Call Scorecard with all 10 questions and a client intake form template is at wedgemethod.gumroad.com. Takes 10 minutes per prospect, saves 40 hours of bad projects.
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