Understanding your business needs, one solution at a time.
Our client was a mid-size omnichannel retailer running over 180 brick-and-mortar stores alongside a growing e-commerce platform. Their brand was well recognized, and their customer base was loyal. Their team was doing everything they could with the tools they had. But those tools were quietly holding them back.
Research. Understood. Proposed.
Our team suggested developing a machine learning forecasting system built to predict demand at an SKU-store level every week so the right stock is always in the right place at the right time.
We also proposed a customer lifetime value model and recommendation engine that can help the team understand who their best customers were and market to them in a way that actually felt personal.
An intelligent labor scheduling tool combined with a conversational AI assistant, which makes staffing predictable and handles routine customer queries automatically, without needing a human every time.
The team mapped the client’s operations across all 180 stores, the e-commerce platform, and marketing and service workflows to identify where data lived, where it broke down, and where the biggest losses occurred.
Each of the four problem areas was scoped into its own workstream, with clear success metrics, data dependencies, and stakeholder alignment defined before development began.
Solutions were built in parallel, starting with the data foundation, followed by forecasting, personalization, scheduling, and the service assistant, each piloted in a controlled environment before scaling.
Every solution was validated through A/B testing and real-world pilots across a subset of stores and customers, with results measured against actual business metrics before wider rollout.
Pilots that hit their targets were scaled across the business over an 18-month program, with continuous iteration based on feedback from buyers, store managers, and service teams.
From nothing to a star!
A unified customer data system that brought together five years of sales, customer, and behavioral data into one connected platform.
AI-based demand forecasting that helped predict store-level inventory needs and improve replenishment decisions.
Customer value and churn tracking models that helped marketing teams focus on the right customers.
Personalized product recommendations integrated into email campaigns and the online shopping experience.
Smarter targeting for paid social and search campaigns based on behavioral data
Two-week-ahead staffing recommendations delivered to store managers, integrated into existing software
Handles order lookups, return initiation, tracking, and store queries across web chat and SMS
Real-time escalation of at-risk conversations to human agents before they become complaints
The measurable impact delivered after deployment.
“I have used Zealous for several of my projects, I have found the team to be very professional yet personable. When I work with Zealous, I know I am getting the best developers who understand my requirements before they start.”
Sales Director at Digital Dilemma
“From day-1 Pranjal and his team have been very good at delivering quality work on time to budget. They are dynamic, if resources need to be shuffled around depending on what work needs to be done.”
Senior Product Manager at Ecentric Payment Systems Driving
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