Growth Edge
AI Client Brief
AI GENERATED60-Second Brief
Growth Edge is exploring AI-driven initiatives to improve lead nurturing, call center performance, conversion rates, and customer retention. Current momentum centers on two parallel tracks: (1) operational reporting and workflow automation for missed calls, callbacks, and lead response times across clinics (PMP), and (2) an AI proof-of-concept to score fitness instructors from audio recordings using a defined rubric. Immediate next steps are to align stakeholders on the call center/lead nurturing automation proposal, deliver key demo assets and datasets, and provide a pricing estimate plus build plan for the instructor scoring POC.
Communication Style
Best handled with concise, action-oriented updates: bullet-point status, clear owners, deadlines, and explicit asks (e.g., required audio files, approval decisions). Use short written recaps after meetings and attach/linked artifacts (reports, spreadsheets, demo videos) for quick review.
Decision Makers
Taylor, Judith
Key Contacts
Haris (Agency lead / primary point of contact (BrandRap)): Owns project coordination and delivery; keep updates structured with clear next steps, dependencies, and timelines. Jeremy Wright (Client contact (Growth Edge)): Engaged in performance improvement discussions; responds well to practical recommendations tied to conversion/retention impact and clinic-level reporting. Taylor (Client stakeholder (implementation reviewer for proposal)): Needs proposal review/approval; provide concise implementation plan, scope boundaries, and expected operational impact. Judith (Client stakeholder (implementation reviewer for proposal)): Needs proposal review/approval; align on workflow automation details, reporting cadence, and accountability owners.
Active Projects
Recent Wins
Current Challenges
Churn Risk Assessment
72% RISKRisk Factors
- ⚠Only 1 total meeting to date, indicating limited ongoing engagement history
- ⚠26 days since last meeting, suggesting a lapse in regular cadence
- ⚠No action items logged (0 total), limiting visibility into progress and next steps
- ⚠No recent meeting sentiment data, preventing detection of satisfaction trends
Retention Recommendations
- ★Schedule the next recurring meeting cadence (e.g., weekly/biweekly) and confirm it on the calendar to reduce the 26-day gap going forward.
- ★Implement action item tracking immediately: capture at least 3-5 concrete next steps after the next meeting with owners and due dates, then review completion each meeting.
- ★Add a lightweight sentiment capture after each meeting (e.g., 1–5 satisfaction rating + notes) to establish a baseline and trend over time.
- ★Send a short recap email after each touchpoint with decisions, action items, and timelines to improve alignment and create measurable engagement signals.
- ★If the client is unresponsive or scheduling is difficult, escalate internally to define an outreach plan (multiple channels, clear agenda/value) and set a deadline for re-engagement.
Health Score Breakdown
Growth Edge shows low observable engagement: only 1 total meeting and 26 days since the last meeting. There are no tracked action items (0 total), which prevents measuring progress and accountability. Sentiment data is missing, so satisfaction cannot be validated from recent interactions; the satisfaction score is therefore conservative and driven by lack of evidence rather than negative signals. Overall health is low primarily due to limited touchpoints and missing operational signals (action items and sentiment), which increases churn/at-risk uncertainty.
Brief generated: Dec 29, 2025, 12:00 AM
Contact Information
General (No Specific Website)
Meetings (1)
Action Items (9)
Prepare and send pricing estimate for the AI instructor scoring proof-of-concept model
Develop a proof-of-concept AI model to score fitness instructors based on audio recordings using an initial rubric
Send the video link demonstrating AI-powered golf putting analysis (01:03:58)
Provide necessary recorded instructor session audio files for AI scoring model training
Review missed calls and callback performance reports by clinic to identify operational improvements