Autonomous Shopping Solutions Provider Achieves 99% M/L Accuracy Reducing Store Latency with IGT’s Tech-Enabled Retail Optimization Services

Learn how IGT Solutions helped an AI-powered shopping solution provider to reduce store latency, improve machine learning accuracy rate, stabilize critical KPIs, and drive process and efficiency enhancements with content tagging and data annotation services.

About the Client

The largest provider of AI-powered shopping solutions that simplify retail by offering shoppers a convenient, accessible, and personalized camera-first checkout experience, enabling anonymous in-store purchases without the need to wait in line, scan, or pay.

Business Challenges

The client faced several operational issues that delayed their transaction processing efficiency and accuracy.

Higher Store Latency– Delayed receipt generation resulting in revenue loss and customer dissatisfaction
Shortage of Specialists: A shortage of specialized operators proficient in AI/ML-based skill sets for efficient transaction processing using data annotation models.
Inability to meet accuracy targets: The team failed to meet the accuracy targets due to inadequate skilled personnel.
Insufficient data trend analysis – The client’s platform couldn’t leverage in-depth research and industry analysis for a robust ML pipeline owing to a lack of trained analysts.

100% increase in sales conversions. Increase in conversions from 12% to 25%.

Business Solution

With a collaborative and forward-looking strategy, IGT Solutions enabled a multifaceted, tech-enabled solution.

Deployment of Experienced FTEs: Within 45 days, over 100 seasoned Full-Time Equivalents (FTEs) were deployed to conduct real-time video transaction reviews. It ensured expedited transaction processing and minimized store latency.
Content Tagging Enhancement: Implemented enhancements in content tagging (including data annotation and video tagging) to streamline review queue volumes. This optimization resulted in a more efficient and effective transaction processing system.
Scalable Operations Model: Agile model designed to respond to peak periods and deliver consistently during demand spikes.
Optimized Data Annotation Services: Accessing large, diverse annotated datasets markedly sped up the Client's AI algorithm training, overcoming internal dataset limitations and improving machine learning model accuracy. They received actionable insights to enhance and future-proof workflows.

Business Results

The dedicated service desk elevated the merchant experience and the multichannel support for end-consumers enhanced services and experience drastically.

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Accuracy rate of issues for machine learning

Efficiency gains helped enhance profits

Reduced system loading time

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Meta variance translating to world class machine learning pipeline accuracy

Reduced Backlog

Improved response time and customer satisfaction reduced backlog substantially.

Tools Partner

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