Perplexity
GrokThe verified result was a clean action package, not a claimed lift. The client now had a baseline, a priority list, and deployment-ready visibility assets.
Back to case studiesEvidence-backed operational readiness
Leadership coaching brand: from invisible in AI answers to a clear action plan
This coaching brand was not showing up in the AI answer checks we measured. New Reward turned that blank starting point into a clear work plan with buyer questions, competitors, gaps, recommendations, and ready-to-use visibility assets.
Coaching visibility workshopThe brand started at zero visibility; the work became buyer questions, competitor gaps, recommendations, and a usable handoff plan.
Visual boundary: New case-specific illustration, not a private client screenshot and not proof of revenue, ranking, or AI-citation lift.
Revenue, lead, ranking, citation, or ROI claims need separate source-backed outcome evidence.
Baseline/current lift is shown only when both sides of the measurement are source-backed.
The journey
Problem to proof.
01
Problem
The brand had a 0/100 AI visibility score. In plain English: the measured AI tools were not naming the business when buyers asked relevant questions.
02
Action
New Reward tested 50 buyer-style questions, mapped competitors and content gaps, and built a package of recommendations and machine-readable assets.
03
Result
The client moved from an unknown AI visibility problem to a documented action package with 23 readiness asset groups and 8 recommendations.
04
Why it matters
A buyer cannot choose a business they never see. The package gave the client a clear path to make the brand easier for search engines, AI tools, and prospects to understand.
Sales use
How to use this proof in a buyer conversation.
Buyer question
What happens when a service brand is invisible in AI answers?
Use this for professional-service buyers who need a plain baseline and a prioritized action package before they invest in content.
Objection handled: The buyer does not need a magic AI claim; they need to see the exact missing questions, competitors, gaps, and readiness assets.
Best fit
Next proof needed before stronger claims
- Post-implementation answer-engine scan
- Approved client naming or anonymized proof path
Client context
Anonymized professional coaching client
- Industry
- Professional coaching and leadership development
- Timeframe
- February 2026 package audit
- Starting point
- The measured AI visibility score was 0/100 across ChatGPT, Grok, Perplexity, Google AI, and Claude.
Proof boundary
This proves baseline measurement and package readiness. It does not claim revenue lift, ranking lift, or AI citation lift.
Verified resultThe verified result was a clean action package, not a claimed lift. The client now had a baseline, a priority list, and deployment-ready visibility assets.
Inspectable work
What shipped and where the proof comes from.
What shipped
- Tested 50 buyer-style AI visibility questions.
- Mapped 5 competitors and 9 content gaps.
- Prepared 8 recommendations and 23 readiness asset groups.
- Checked package files, JSON validity, client scoping, and placeholder cleanup before handoff.
Source notes
Deep package audit
Internal package audit dated 2026-02-25
Package audit data
Internal deployment-package audit data dated 2026-02-25
Next step
Turn this proof into the right offer lane.
Start from the evidence, then choose the work that matches the buyer path.