Gen AI-Driven Decision Engine brings Innovations to Consumer Product Testing
Previously, product analysts faced challenges with the manual processing of vast user and tester feedback, leading to delays in product refinements and potential risks to product value. The implementation of the Gen AI-enabled decision engine resolved these inefficiencies, automating feedback analysis and empowering teams to make data-driven decisions quickly and effectively. This innovation has set a new standard for consumer product testing, ensuring faster turnarounds and optimized outcomes.
Technology Used: Gen AI Engine (Llama 3), Groq
About the client
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.
Business Challenge
- 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.
- Identifying valuable features and accurately interpreting the sentiment in each feedback was challenging, which directly impacted the product’s market readiness and hindered its adoption by delaying necessary enhancements and alignment with user expectations.
- 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 decision-making capabilities, enabling teams to focus on strategic refinements and accelerate time-to-market.
- 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 product features, leading to improved usability and customer satisfaction.
- 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
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.
Product managers were equipped with dynamic performance ``tags`` that enabled timely, impactful decisions. This innovation not only streamlined operations but also enhanced product value by up to 20%, setting a new benchmark for excellence in consumer product testing.
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