AI-Powered Printed Advertisement Processing and Data Extraction System

The client faces significant difficulties in manually collecting and analyzing data from a vast array of printed ads across multiple locations, leading to costly errors, delays, and incomplete data collection that hampers data-driven decision making for promotional strategies.

A large retail chain seeking to automate and enhance the extraction of promotional data from printed advertisements to optimize pricing strategies and marketing efforts.

• Develop an AI-based system capable of accurately detecting and cropping individual ads from printed pages with at least 99.3% accuracy.
• Implement text detection and recognition algorithms to extract key product and offer information with an accuracy approaching 100%.
• Classify advertisement offers into predefined categories such as 'Buy One Get One', 'X for...' deals, etc., achieving at least 93% accuracy in offer type recognition.
• Automate the processing of approximately 20,000 ad blocks daily, automating at least 80% of the manual effort involved.
• Create a scalable, real-time processing pipeline utilizing state-of-the-art neural network models and OCR technologies.

• Neural network-based detection and cropping of individual ad blocks with high accuracy (e.g., YOLO family models).
• Advanced text detection and recognition using models such as CRAFT, spatial transformer networks, bidirectional LSTM, and CTC classifiers, trained on real-world and synthetic datasets.
• Classification modules to identify offer types, including special deals like 'Buy One Get One' and 'X for...' options.
• Generation of structured Offer Tables summarizing identified deals and product details.
• An adaptable training process incorporating new data to enhance accuracy and processing speed over time.

• Database systems for storing extracted ad and offer data
• Input pipelines for scanned printed ads (e.g., image repositories or scanning devices)
• Automation workflows for batch processing and data export

• Processing capacity of approximately 20,000 ad blocks per day
• Accuracy targets: cropping accuracy ≥ 99.3%, text recognition approaching 100%, offer classification ≥ 93%
• Real-time or near-real-time processing performance with minimal latency
• System scalability to handle increasing ad volumes
• Ensuring data security and compliance with relevant data handling standards

The implementation of this AI-powered printed advertisement processing system is expected to significantly reduce manual effort by automating at least 80% of data handling procedures, improve data accuracy to nearly 100%, and enable comprehensive insights into promotional activities—supporting more effective pricing and marketing strategies, and processing up to 20,000 ads daily to maintain competitive intelligence.