Consulting-Style Case Study
Real-world systems designed to identify risk, drive decisions, and improve business outcomes.
Each project is structured as a consulting-style engagement, highlighting problem-solving, analytics, and execution.
Select a project to explore the full engagement breakdown.
Driving proactive retention through data and operational visibility
+19 pts
SLA improvement
-25%
Escalations
Improved
Risk visibility
Designed a centralized system to track customer health, identify risk signals, and enable proactive intervention.
Improving SLA performance and operational efficiency through data-driven insights
68%→94%
SLA Compliance
-30%
Resolution Time
-40%
Ticket Backlog
Built a data-driven dashboard to analyze support operations, track SLA performance, and identify bottlenecks affecting efficiency and customer satisfaction.
Operational analytics and customer health scoring to improve retention visibility and executive decision-making
42%→89%
Health Visibility
-28%
Escalations
+65%
Revenue Risk Visibility
Unified support, engagement, and SLA signals into an executive-grade platform for churn risk, revenue-at-risk modeling, and retention prioritization.
Featured Case Study
End-to-end system for identifying customer risk and driving proactive retention strategies
Customer data was scattered across disconnected tools, limiting the team's ability to identify at-risk accounts. This project delivered a unified command center that consolidated health scores, ticket analytics, and SLA tracking — resulting in a 19-point SLA improvement and 25% reduction in escalations.
Built a multi-layered system combining automated health scoring, ticket sentiment analytics, and real-time SLA dashboards. Designed intake workflows to centralize reporting and enable cross-functional decision-making.
Enabled proactive outreach for at-risk accounts, restructured escalation workflows, and introduced weekly health review cadences that improved cross-team alignment on retention strategy.
SLA Compliance
72% → 91%
+19 percentage points
Escalations
-25%
Reduced high-risk cases
At-Risk Accounts
18% → 13.5%
Improved retention outlook
Business Outcome Summary
Problem
Fragmented customer data prevented the CS team from identifying churn risk early.
Solution
Unified health scoring, ticket analytics, and SLA tracking into a single command center.
Operational Impact
Proactive outreach for at-risk accounts and weekly health review cadences.
Result
+19 pt SLA improvement and 25% reduction in escalations.
Case Study #2
Improving SLA performance and operational efficiency through data-driven insights
Built a data-driven dashboard to analyze support operations, track SLA performance, and identify bottlenecks affecting efficiency and customer satisfaction.
SLA Compliance
68% → 94%
+26 percentage points
Avg Resolution Time
-30%
Faster ticket closure
Ticket Backlog
-40%
Reduced queue buildup
Reporting Visibility
Significantly Improved
Executive-level dashboards
Business Outcome Summary
Problem
Support leadership lacked visibility into SLA breaches and bottlenecks.
Solution
Built a KPI dashboard tracking volume, SLA compliance, and resolution time with category drilldowns.
Operational Impact
Reallocated peak-hour resources and prioritized high-impact ticket categories.
Result
SLA compliance 68% → 94%, resolution time -30%, backlog -40%.
Case Study #3
Using operational analytics and customer health scoring to improve retention visibility and executive decision-making
Built a centralized customer intelligence platform that identifies churn risk, tracks SLA performance, monitors engagement, and improves operational visibility for leadership. Combines support operations, customer success metrics, and executive reporting into a unified workflow that strengthens retention prioritization and revenue-risk awareness.
Customer Health Visibility
42% → 89%
+47 percentage points
Escalation Reduction
-28%
Fewer high-severity cases
SLA Compliance
71% → 93%
+22 percentage points
Revenue Risk Visibility
+65%
Surfaced at-risk ARR
Business Outcome Summary
Problem
Leadership had no unified view of churn risk or revenue-at-risk across accounts.
Solution
Centralized health scoring, executive KPI dashboards, and revenue risk modeling.
Operational Impact
Prioritized high-risk accounts, improved escalation routing, and tightened SLA monitoring.
Result
Health visibility 42% → 89%, escalations -28%, revenue risk visibility +65%.
Operational Reliability
Production-style retry orchestration, failure recovery, and workflow monitoring built to keep automation reliable under real-world API and data constraints.
Built a durable retry queue to preserve failed AI jobs, track retry attempts, and recover safely from quota or rate-limit issues.
Implemented throttling, exponential backoff, concurrency limits, and queued retries to prevent bulk workflow failures.
Documented common operational issues including OpenAI quota limits, ATS import filtering, routing failures, and SMS validation errors.
Added rejection tracking, queue health monitoring, retry history, and manual review routing to improve explainability and system trust.
0
Lost jobs during quota failures
5
Retry attempts before escalation
15m → 2h
Exponential backoff window
50/day
ATS caps with platform controls
System Architecture
High-level workflow showing how jobs move through imports, filtering, AI processing, retry orchestration, and manual review.
Greenhouse, Ashby, Lever, Workday.
Duplicates, scams, title matching, ATS caps.
Packet generation, enrichment, resume workflows.
Throttle, exponential backoff, durable retry queue.
Health monitoring, logs, retry visibility.
Selected storytelling visuals from the AI recruiting platform — each explains a system in seconds.
ATS Ingestion Flow
Every job is filtered, scored, and matched before it ever reaches a recruiter.
ATS Sources
Greenhouse · Lever · Ashby · Breezy
Job Fetch
14-day freshness
Filtering
Salary confidence
Trust Score
11-factor company trust
Resume Match
Variant optimizer
Review
Manual · Auto
Outcome Learning Loop
Real recruiter signals continuously recalibrate scoring and targeting.
Applications
Recruiter Replies
Response rate
Interviews
Interview conversion
Outcomes
Best resume variant
Recalibrated Scores
Best ATS source
Better Targeting
Smart Apply — Safety Gates
Every automated action passes through explicit safety controls.
No CAPTCHA bypass
No MFA bypass
No login-wall evasion
No bot-detection bypass
Manual fallback
Emergency pause
Daily caps
CommandFlowOS, structured as Problem → Constraints → Solution → Product Decisions → Impact → Roadmap.
Problem
Candidates juggle dozens of job boards with inconsistent data, low-trust companies, stale postings, and no feedback loop between applications and outcomes. Recruiting teams face the mirror image: high-volume pipelines with weak signal and no shared system of record.
Constraints
The platform had to operate inside real recruiting norms — no shortcuts that would compromise safety, trust, or data quality.
Solution
CommandFlowOS combines verified job intelligence, resume optimization, recruiter CRM workflows, outcome learning, and safety-aware automation into a single product — with a public sandbox for storytelling and a private workspace for real operations.
Product Decisions
Each layer exists for a specific reason — to keep the platform trustworthy, measurable, and useful to both candidates and recruiters.
Impact
Roadmap
The next phase deepens the learning loop and makes the platform easier for recruiters to adopt as a system of record.
Download or view consulting-style decks for each engagement.
End-to-end case study on proactive retention and customer health analytics.
Used in interviews to demonstrate real-world decision-making.
I approach problems by combining data, systems thinking, and business strategy to drive measurable outcomes. These case studies reflect how I analyze challenges, design solutions, and deliver impact at an operational and strategic level.
Resume bridge
Every project on this site maps to a real bullet on the resume — built, shipped, and measurable.
Resume tag
SQL · Tableau · 92% SLA · 25% escalation reduction
Resume tag
SQL · Excel · $1.2M+ revenue analyzed
Resume tag
Excel · 92% forecast accuracy · Capacity planning
Visual resume · 1 page · ATS-friendly
Data Analyst & Technical Operations Specialist
10K+
Support cases analyzed
91%
CSAT maintained
25%
Escalation reduction
Target roles
Data Analyst · Operations Analyst · Customer Success Analyst · Technical Operations Specialist
Top skills
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