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Customer Experience Specialist — Lost & Bad Orders

Job in Lusail, Al Daayen, Qatar
Listing for: Keka Technologies Private Limited
Full Time position
Listed on 2026-09-13
Job specializations:
  • Business
    Data Analyst
Salary/Wage Range or Industry Benchmark: 90000 - 150000 QAR Yearly QAR 90000.00 150000.00 YEAR
Job Description & How to Apply Below
Location: Lusail

Customer Experience Specialist — Lost & Bad Orders

3-5

Full-Time

Welcome to Your Next Adventure!

We are looking for a Customer Experience Specialist to own and solve two specific problems that directly cost Snoonu orders and revenue:

  • Lost orders — customers who browse, add items to their cart, and never complete checkout, whether due to app friction, bugs, UX gaps, or abandonment.
  • Bad orders — completed orders that receive low ratings without a specific complaint to support, where the root cause is unclear and unaddressed.

This person will not report on these problems. They will reduce them. The measure of success is incremental orders recovered — customers who would have abandoned but didn't, and orders that would have been rated poorly but weren't — because this person found the root cause and drove the fix.

This is a strategic, data-driven role. You will dig into funnels, session data, ratings patterns, and operational signals to understand what is actually going wrong, build hypotheses, work with Product and Engineering to fix it, and measure whether the fix worked. You own the problem end-to-end: from diagnosis through solution through measured impact.

We are looking for a sharp generalist who can deeply own this problem space today while evolving into broader CX strategic initiatives as the organization grows.

What You’ll Get Your Hands On:

Own the Lost Orders Problem
  • Map the full customer funnel from browse to checkout and identify where and why drop-off happens — app errors, UX friction, payment failures, session timeouts, pricing confusion, or pure abandonment.
  • Segment drop-off by stage, device, vertical, time of day, customer cohort, and any other dimension that reveals patterns.
  • Quantify the revenue impact of each drop-off point to prioritize what to fix first.
  • Partner with Product and Engineering to fix the highest-impact drop-off points — write clear problem statements, propose solutions, and stay on it until the fix ships and the numbers move.
  • Design and run experiments (A/B tests, nudges, flow changes) to validate recovery tactics like cart reminders, checkout simplification, or error handling improvements.
  • Track recovery rate as your primary metric: how many previously lost orders are now completing.
Own the Bad Orders Problem
  • Identify the population of orders with low ratings but no specific complaint — the "silent dissatisfaction" segment.
  • Dig into what these orders have in common: merchant, item type, delivery time, packaging, rider, zone, time window, weather, or any other signal that explains the pattern.
  • Build a root cause taxonomy for bad orders that goes beyond surface-level categories and reveals the actual operational or product failures behind them.
  • Propose and drive fixes — whether that's merchant quality interventions, packaging standards, delivery process changes, or product-side improvements — in partnership with the relevant teams.
  • Measure the impact: track whether the fixes reduce the rate of low-rated orders and improve repeat behavior for affected customers.
Drive Cross-Functional Solutions
  • Translate root cause findings into clear, actionable problem statements for Product, Engineering, Operations, and Merchant teams.
  • Build business cases that quantify the order and revenue impact of each fix, so stakeholders prioritize accordingly.
  • Own follow-through: track implementation, measure results post-launch, and iterate if the first fix doesn't move the needle.
  • Drive accountability across teams — this role has no direct authority over Product or Ops, so you need to influence through evidence and persistence.
Measure What Matters
  • Define and own the KPIs for this problem space: checkout conversion rate, cart abandonment rate, bad-order rate, recovery rate, and incremental orders…
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