Gen AI-Driven Decision Engine brings Innovations to Consumer Product Testing

At NextGen Invent, we developed a transformative Gen AI-enabled decision engine that revolutionized the product testing platform, enhancing its performance and user satisfaction to new heights. By automating complex feedback analysis, we achieved a remarkable 97% reduction in manual processing time, unlocking significant labor savings for product analysts. The AI-driven system empowered teams to swiftly prioritize actions based on feature impact and sentiment analysis, providing precise, data-backed insights that directly influenced product direction.

The client is a trailblazer in delivering best-in-class customer insight solutions, seamlessly integrating the valuable voice of customer feedback into every phase of product development and driving innovation without compromising timelines.

100+ Healthcare Facilities Transformed

95% Customer Satisfaction Rate

50% Reduction in Documentation Time

Industry

Retail

The Gen AI-driven decision support engine transforming consumer product testing by introducing a seamless, intelligent process from ideation to product launch. It integrates feedback channels, customer surveys, activity logs, and performance heatmaps, providing actionable insights that enhance product design and development with precision.

Business Problem

Managing over 700K ongoing product test records, each containing multiple feedback entries, posed a significant challenge for Product Analysts, requiring exhaustive manual filtering and analysis that strained resources and hindered efficiency.

The relentless influx of feedback overwhelmed the analysis process, creating significant operational strain that stretched timelines and escalated costs, making manual handling unsustainable

The delays in analysis postponed critical product refinements, leading to cascading negatives such as missed market opportunities, prolonged development cycles, and reduced user satisfaction. These setbacks risked a decline in product value, potentially eroding the product’s competitive edge and market position.

Solution Approach

Automated Feedback Filtering: The implementation of a Gen AI-enabled decision engine revolutionized the workflow by automating the filtering of feedback data. This innovation not only streamlined the analysis process but also enhanced.

Feature Identification: The Gen AI-enabled decision engine pinpoints key features in feedback, such as identifying a frequently requested ergonomic handle design, which was implemented to enhance user comfort. This actionable insight supported decision-making on produ.

Sentiment Analysis & Tagging: The developed solution analyzes and tags feedback sentiment for each feature, such as categorizing positive responses toward a new design feature, thereby enabling teams to quickly act on user preferences and make data-driven enhancements to the product.

Value Delivered

Our Case Study

Gen AI-Driven Decision Engine brings Innovations to Consumer Product Testing

The capacity to identify potential safety hazards and address them before they become issues is another significant advantage of predictive maintenance in fleet management. To determine what might go wrong, they look at data on historical accidents, driver behavior, and vehicle performance.

→

How Fleets Can Maximize Uptime and Efficiency with Predictive Maintenance?

Maintaining cost-effectiveness and operational efficiency is crucial in the cutthroat field of fleet management. Predictive maintenance has become a game-changing strategy among the numerous others that are accessible. Predictive maintenance has been shown to, boost vehicle availability by 20% , lower maintenance costs by up to 25%

→

How AI in Inventory Management is Redefining Inventory Control?

Modern businesses rely heavily on inventory, which is also may be their most important asset. It can have an impact on consumer satisfaction, turnaround time, sales, production, and even profitability. Therefore, a key component of supply chain management and one of the main objectives of enterprises is the efficient use of AI in inventory management.

→

Gen AI-Driven Decision Engine brings Innovations to Consumer Product Testing

However, 43% of small businesses do not keep an eye on their inventory, and only 6% of companies say they have complete supply chain visibility, which is necessary for efficient inventory management. As global inventory management in supply chain management networks becomes more complex and the need for disruption-immune operations becomes more pressing.

→