How a Certification School Rebuilt RevOps Around AI

A $10M certification school was bottlenecked on RevOps — doubling acquisition cost and a black-box lead score. Casper rebuilt it around an AI lead-scoring engine and call intelligence.

~50%

Potential lead-volume lift

Implementation Time

Jay Singh

CEO & Founder

Casper Studios

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The Challenge

A $10M coach-certification school had a RevOps bottleneck: cost per acquisition had nearly doubled, lead conversion was low, no-show rates were high, lead scoring was a static black box, and ownership was fragmented across marketing and sales.

What They Built

Casper acted as an interim RevOps team and rebuilt the engine around AI: a continuously tuned lead-scoring model replacing static rules, sales-call intelligence that analyzes transcripts for patterns and rep coaching, redesigned application forms, automated nurturing workflows, and a CRM governance framework.

Casper embedded as an interim RevOps team and replaced guesswork with models. A continuously tuned lead-scoring engine took over from the static, black-box rules, giving sales a defensible read on which leads to chase. Transcript analysis of sales calls surfaced patterns and rep-level coaching signals. Around the models, they redesigned application forms to qualify better, automated nurturing to cut no-shows, and put a CRM governance framework in place so ownership stopped being fragmented across marketing and sales. The school unlocked an estimated ~50% lift in qualified lead volume and clearer separation of won-versus-lost deals. [Outcome metrics are stated as potential on the source page — to be confirmed.]

AI Role

AI replaces black-box guesswork in the funnel. A continuously tuned lead-scoring model takes over from static rules to tell sales which leads to chase, while call-transcript analysis surfaces patterns and rep-level coaching signals.

Infrastructure

Integration Points

CRM (lead scoring and governance); call-transcript analysis pipeline; redesigned application/web forms; automated nurturing workflows.

Impact

~50% Lead-Volume Lift

Estimated, qualified leads (stated as potential — confirm).

AI Lead Scoring

Continuously tuned model replaced static black-box rules.

Call Intelligence

Transcript analysis for patterns and rep coaching.

Technology Utilized

Implementation Complexity

Revenue Growth

Customer Experience

Best Fit For

Education, coaching and high-ticket services businesses with a RevOps bottleneck — static lead scoring, rising CPA, fragmented marketing/sales ownership — that want AI lead scoring and call intelligence wrapped in real operating discipline.

Jay Singh

CEO & Founder

Casper Studios

CEO and co-founder of Casper Studios, a product studio helping companies design, build, and integrate AI-powered products.

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Industry:

Education & EdTech

Business Function:

Sales & Revenue

Marketing

Company Size:

Project Cost:

Cost not disclosed

Ownership:

Organization Type:

AI Pattern:

Decision Support & Scoring

Data Synthesis & Reporting

Value Type:

Revenue Growth

Customer Experience

AI Model:

Frequently Asked Questions

How did an education company fix its RevOps bottleneck with AI lead scoring?

The experts embedded as an interim RevOps team and replaced static, black-box rules with a continuously tuned AI lead-scoring model, added call-transcript analysis for rep coaching, and redesigned application forms, nurturing, and CRM governance. Together this is credited with an estimated ~50% lift in qualified lead volume (stated as potential on the source).

What AI approach was used in this education RevOps project?

The work centered on decision support and scoring plus data synthesis: a continuously tuned lead-scoring model that replaced static rules, and transcript analysis of sales calls to surface patterns and rep-level coaching signals. No specific AI model or platform was named in this engagement.

What results did the education company achieve?

Three outcomes: an AI lead-scoring model that replaced static black-box rules, call intelligence that analyzed transcripts for patterns and rep coaching, and an estimated ~50% lift in qualified lead volume (described as potential, to be confirmed).

How long did the AI RevOps engagement take?

The source does not state a fixed timeline. The work was delivered through an embedded, interim RevOps engagement that rebuilt scoring, forms, nurturing, and CRM governance in sequence rather than as a one-off build.

Who is this AI lead-scoring approach best for?

Education, coaching, and high-ticket services businesses with a RevOps bottleneck — static lead scoring, rising acquisition cost, and fragmented marketing/sales ownership — that want AI lead scoring and call intelligence wrapped in real operating discipline.