ROLE SUMMARY
As Manager, Post-Delivery Experience within talabat’s Customer Experience team, you will own the end-to-end customer experience after an order is delivered. You will lead high-impact programs that improve both customer outcomes (satisfaction, effort) and business outcomes (contact rate, cost-to-serve, retention).
This is a hands-on role that blends strategy and execution. You will define problems using customer and operational data, design and test solutions, pilot at scale across markets, and drive sustained impact through continuous optimization and rigorous performance tracking.
You will work cross-functionally with Product, Tech, Data Science, and Operations to translate insights into shipped changes and measurable results, and to ensure initiatives land consistently across markets.
WHAT’S ON YOUR PLATE?
1) Data-driven problem definition and insight generation
Identify the highest-impact post-delivery pain points using customer, operational, and financial signals.
Run structured analyses (cohorts, funnel diagnostics, segmentation, root-cause deep dives) to isolate drivers and quantify opportunity size.
Define clear success metrics and guardrails for every initiative, including pre/post impact measurement and sustainability checks.
2) End-to-end program ownership and scaled execution
Own the full lifecycle of initiatives: problem statement, solution design, stakeholder alignment, pilot delivery, rollout plan, and iteration.
Drive iterative scaling: continuously optimize programs against defined outcomes
Build repeatable playbooks so programs can be adopted consistently across markets and teams.
3) Measurement, experimentation, and performance governance
Apply hypothesis-led decisioning: choose the right validation method for the change (A/B test where needed or pre/post designs where appropriate).
Ensure every rollout includes measurement design, monitoring cadence, and clear decision thresholds (scale, iterate, or stop).
Partner with Data Science and Performance management to ensure data availability, metric integrity, and dashboard readiness.
4) Data tool fluency and analytics operating model
Fluency with tools such as Looker and Google Sheets to build/maintain dashboards and monitor program health continuously.
When deeper analytics are required, engage Data Science with a crisp brief: problem statement, hypotheses, key questions, required cuts, and expected decisions.
5) Cross-functional leadership and proactive communication
Align Product, Tech, Ops, and Leadership on priorities, scope, trade-offs, and delivery plans for customer-impacting initiatives.
Provide Product (talabat and DeliveryHero) the context and evidence needed to prioritize effectively, and drive accountability through clear milestones and regular check-ins.
Communicate decisions and changes to markets proactively with complete details to minimize reactive follow-ups and ensure smooth execution.
Present data-backed recommendations to senior stakeholders in a clear, persuasive narrative.
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