Data-Driven Retention.
Engineered Growth.
50% Higher ROAS.
I bridge the gap between technical data engineering and commercial marketing strategy — owning the full growth loop across attribution, segmentation, and lifecycle automation. I don't just build reports; I engineer actions that scale retention and boost acquisition efficiency.
Fluent across the modern growth stack
Value Pillars
Three systems. One compounding revenue engine.
Acquisition efficiency and retention scale aren't separate problems — they share one data foundation. Here is how I engineer it.
Behavioral Data Enrichment
I enrich raw user schemas with the traits your campaigns are missing: Predictive Affinity Scores, Churn Risk flags, and dynamic RFM properties (Recency, Frequency, Monetary) that update as behavior changes — so every audience you target is built on signal, not guesswork.
MMP & Attribution Architecture
Unified tracking loops across AppsFlyer, Adjust, and Branch that combat ad fraud, map complex multi-touch customer journeys, and accurately isolate true organic lift — so budget decisions are made on attribution you can actually trust.
Automated Lifecycle Ops
I build the data pipelines feeding automated win-back sequences and hyper-personalized push and email orchestration engines inside CleverTap, Braze, and MoEngage — retention loops that run, learn, and compound without manual pulls.
Case Studies
Proof, rebuilt as live blueprints.
Client dashboards are confidential — so these are faithful, sanitized reconstructions of the systems and the numbers they produced.
The 50% ROAS Lift Engine
Blended CAC
90-Day LTV
Overall ROAS
Blended ROAS — 12 weeks around enrichment rollout
The Problem
Paid channels reported inflated, overlapping conversions. Ad networks claimed credit for organic installs, budget was allocated on last-click fiction, and blended ROAS sat stuck under 2.9x.
The Technical Data Solution
Re-architected MMP postbacks and aligned AppsFlyer attribution windows with GA4 data blended in BigQuery. Enriched user profiles with predictive affinity and RFM traits, then synced high-intent segments back to ad platforms as seed audiences.
The Commercial Outcome
Overall ROAS climbed +50% to 4.2x while blended CAC fell 31%. Budget shifted from fraud-inflated channels into segments with proven LTV — the same spend, engineered to buy better customers.
Dynamic RFM & Retention Cohort Heatmap
Monthly cohort retention (%)
M1 retention climbed from 58% → 76% after dynamic RFM triggers went live in March — each new cohort enters a lifecycle engine that reacts to behavior in near-real-time instead of static blasts.
Live RFM segment explorer
Select a segment to see its playbook.
Champions — playbook
Recent, frequent, high-spend buyers. Fed into VIP early-access flows and referral loops — protected from generic discount campaigns that erode margin.
The Problem
Retention was reported as one blended number. CRM sends were batch-and-blast, win-back timing was guessed, and the business could not see which behaviors predicted churn until users were already gone.
The Technical Data Solution
Built SQL pipelines in BigQuery computing dynamic RFM scores and churn-risk flags nightly, synced as user properties into CleverTap — powering cohort heatmaps and auto-enrolling users into segment-specific journeys the moment their status shifts.
The Commercial Outcome
M1 retention lifted 18 points across new cohorts, win-back sequences recovered revenue on autopilot, and retargeting spend on 'Lost' users was cut — funding the segments that actually convert.
Technical Stack
The full pipeline, one operator.
From raw event ingestion to the campaign that converts — no hand-offs, no translation loss between data and marketing teams.
Languages & Cloud
MMPs & Product Analytics
Lifecycle & CRM Platforms
BI Tools
Experience
A track record measured in revenue, not reports.
Senior Data Analyst
Boutiqaat
Own the analytics layer where paid acquisition, CRM retention, and executive reporting converge — the bridge between BI, IT, Data Engineering, and Commercial Marketing.
- Optimized overall campaign ROI and marketing budget allocation through comprehensive performance analysis across every acquisition and retention channel.
- Architected automated Power BI dashboards for executive stakeholders — eliminating reporting latency and giving leadership real-time visibility into CRM and marketing KPIs.
- Mitigated churn and strengthened lifetime value by mapping complex behavioral patterns in CRM data into growth recommendations marketing teams actually executed.
- Scaled core analytics infrastructure by integrating fragmented data sources under rigorous validation protocols, alongside BI, IT, and Data Engineering teams.
Data Analyst
Boutiqaat
Promoted to Senior in under two years by proving analytics could drive revenue decisions, not just describe them.
- Delivered daily KPI insights and recommendations that steered live campaign optimization across channels.
- Partnered directly with the digital marketing team to personalize campaigns using customer behavior data.
- Built and maintained the dashboard layer stakeholders relied on as the single view of marketing performance.
Digital Marketing Analyst
DigiTell (Agency)
Agency-side start: multi-client campaign analytics on fast turnarounds — where the marketing instincts were built before the deep data engineering.
- Analyzed social and CRM campaign data across client accounts, turning weekly and monthly reporting into optimization recommendations clients acted on.
- Built interactive dashboards that made campaign performance legible to non-technical stakeholders.
B.Sc. Production & Industrial Engineering
Faculty of Engineering, Alexandria University
Systems thinking, process optimization, and statistical quality control — now applied to funnels, budgets, and retention loops.