MoreYeahs unified siloed store data and marketing execution onto a single Power Apps and Power BI platform for a multi-store Indian retail chain.
The client is an Indian retail chain operating multiple stores across the country, managing a diverse product portfolio and customer base without a unified platform to consolidate operations.
Siloed sales data, inconsistent processes, and limited cross-store visibility prompted the organization to engage MoreYeahs to connect sales operations, marketing execution, and performance reporting on a single platform.
Multiple stores operated in isolation with siloed sales data and inconsistent processes, making it impossible to achieve a consolidated view of performance across the chain.
Siloed Store Data — Each store operated in isolation with inconsistent processes, blocking a consolidated performance view.
Poorly Targeted Marketing — Limited visibility into store performance and customer preferences meant marketing efforts were poorly targeted.
Fragmented Campaign Management — Marketing campaigns had to be managed separately per store or region rather than from a single interface.
No Standardized Reporting — Leadership could not reliably compare store performance or identify underperforming locations and categories.
MoreYeahs built a unified shop-chain management interface on Power Apps using a model-driven approach, providing a single platform for managing sales operations and store performance across all locations.
Unified Management Interface — A model-driven Power Apps platform gave a single view of sales operations and store performance across all locations.
Targeted Marketing — Scheduled marketing workflows and customer wish-tracking improved segmentation and campaign relevance.
Standardized Reporting — Power BI dashboards delivered consistent store, product, and regional performance reporting.
Automated Coordination — Power Automate managed approvals and notifications, reducing manual coordination between stores and head office.
The delivery team conducted store visits and stakeholder workshops across multiple locations to understand operational differences and reporting requirements specific to the retail model.
Store-Level Discovery — Store visits and stakeholder workshops surfaced operational differences and reporting requirements across locations.
Unified Data Model — A single Dataverse model consolidated store, product, customer, and sales data from across the chain.
Role-Based Apps — Power Apps provided role-appropriate interfaces for store managers, marketing teams, and operations leaders.
Iterative BI Development — Power BI reports were developed with leadership to ensure the regional and product-level breakdowns needed for strategy.
The solution was built on Power Apps (model-driven) with Dataverse serving as the central data model and business rules engine for all store and customer data.
A single source of truth was established for sales and customer engagement data across all stores, eliminating the reporting fragmentation that previously hindered decision-making.
Single Source of Truth — Sales and customer engagement data across all stores now live on one governed platform.
Improved Marketing Execution — Better customer segmentation and the ability to schedule and monitor campaigns from a centralized interface.
Faster Decision-Making — Unified dashboards gave leadership consistent, near-real-time performance data across stores, regions, and products.
The platform gives the organization a scalable retail management foundation capable of supporting new store openings and expanded marketing capabilities.
Scalable Retail Foundation — Built to support new store openings and expanded marketing capabilities.
Store-Level Adoption — Role-appropriate tooling and hands-on training helped store staff embed the new processes.
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