Development of a Mobile Data Collection App for Retail Price Monitoring

The client faces difficulties in gathering accurate competitive pricing information on the sales floor efficiently and discreetly. Existing manual processes are time-consuming, prone to errors, and poorly suited to operations where staff may be hesitant to record competitor prices directly, leading to delays and data inaccuracies.

A mid-sized retail chain seeking to enhance its competitive intelligence by rapidly and accurately collecting competitor pricing data from store locations.

• Develop a mobile solution to enable field staff to collect and upload price data five times faster than previous methods.
• Ensure high data accuracy through integrated error detection and correction features.
• Minimize staff disturbance and maintain discretion during data collection on retail floors.
• Facilitate offline data entry with batch synchronization capabilities.
• Support location-based shop identification and category/subcategory product data management.

• Location detection using device GPS to identify the nearest retail outlets.
• Server integration for retrieving store-specific product categories and subcategories.
• Offline mode for category browsing and price entry, enabling field data collection without network dependency.
• Integration with Bluetooth-enabled portable barcode scanners for quick barcode input.
• Batch data synchronization mechanism for uploading collected data to a central database.
• Error detection for invalid codes, significant price anomalies prompting photo evidence, and consistency checks for data correctness.
• Iterative user interface design involving field testing and continuous feedback.
• Role-based access for staff, with simplified data entry workflows for speed.

• Mapping and location services for identifying nearby stores
• Barcode scanner hardware via Bluetooth
• Central server/database for product categories, price data, and synchronization
• Photo storage or management system for proof images when price anomalies are detected

• System should support high concurrency, with at least 10,000 data entries per day.
• Data accuracy rate should be above 99%, with real-time validation.
• Application must operate smoothly in offline mode with seamless sync once online.
• Secure data transmission with encryption standards.
• User interface should be intuitive, minimizing training time and user errors.

The implementation of this mobile data collection system is expected to significantly accelerate retail price data gathering, increasing collection speed by up to 5 times and reducing errors through validation features. By enabling more comprehensive and timely competitive intelligence, the client can better respond to market pricing strategies, leading to improved pricing competitiveness and increased revenue opportunities. Over six months, operational efficiency improvements are projected to expand the volume of collected data, with potential for continuous process optimization and actionable insights.