unleash the power of your customer data
AI that hears what your customers want
Continuously detect product themes, customer preferences, competitor
considerations and more in every customer engagement.
turn every word into an opportunity
make smarter product decisions
Continuous trait
detection, everywhere
Continuously detect key product signals in every customer engagement, including calls, chats, and more, to prioritize product development and drive timely improvements.
Predictive insights and
customer intelligence
Leverage predictive insights about product usage, customer satisfaction, and purchase considerations to drive strategic decisions and enhance customer experiences.
amplify your existing tools and processes
85%
of product teams experience a reduction in churn rate with Frame AI
30%
increase in feature adoption with Frame AI
integrate with your existing data structure.
Unify
Consolidate unstructured customer data from various sources to create a single, comprehensive view of user interactions and feedback.
Detect
Identify key patterns, trends, and anomalies within the unified data to uncover hidden product-related insights and emerging issues.
Analyze
Utilize advanced analytics to delve deeper into the detected insights, understanding user behavior and pinpointing opportunities for product enhancement.
Activate
Translate analytical insights into actionable strategies, informing the development roadmap and driving impactful product improvements.
Unify
Consolidate unstructured customer data from various sources to create a single, comprehensive view of user interactions and feedback.
Detect
Identify key patterns, trends, and anomalies within the unified data to uncover hidden product-related insights and emerging issues.
Analyze
Utilize advanced analytics to delve deeper into the detected insights, understanding user behavior and pinpointing opportunities for product enhancement.
Activate
Translate analytical insights into actionable strategies, informing the development roadmap and driving impactful product improvements.
your ai pipeline
for customer intelligence
Accelerate and improve decision-making with a robust AI pipeline for customer intelligence. Unlock organic and meaningful insights shared in natural language interactions to drive customer satisfaction and product innovation.
CONTINUOUS DETECTION
Detect key product signals from every customer interaction, including calls and chats, to prioritize development and drive timely improvements.
RISKS AND INTERVENTIONS
Identify product risks and initiate targeted interventions to prioritize fixes and enhance customer satisfaction.
BUILD A FLEXIBLE AI STRATEGY
Build a flexible AI strategy to adapt to evolving product needs and continuously drive better product decisions.
industry
leaders
giving their
data a voice
Frame AI helps the world’s biggest companies stay ahead of risk.
PROACTIVE TOOLS FOR
accelerated resolution
Leverage real-time data, predictive insights, and automated workflows to consistently enhance product quality and customer satisfaction.
Consistent, Actionable Insights
Frame AI unifies and analyzes unstructured customer data, providing deep insights into user behavior and preferences, which drive informed product development decisions.
Optimize Development Resources
By detecting and prioritizing key trends and user needs, Frame AI helps focus development resources on the most impactful features and improvements, accelerating time to market.
Improve the Impact of Iteration
Frame AI activates strategic improvements by continuously testing and refining the product based on user feedback and performance data, ensuring ongoing enhancement and user satisfaction.
Works how you work
Leverage customer support interactions to gather insights that inform product improvements and feature development
Analyze CRM data to uncover product feedback trends and enhance the product roadmap with customer-driven insights
Utilize support data to identify recurring product issues and enhance the user experience through continuous feedback
Unify large datasets to generate actionable product insights, driving data-informed decision-making for product teams
Capture customer feedback to identify key areas for product enhancement and align features with user needs
Analyze customer experience data to inform product decisions, ensuring features align with user expectations and demands
Analyze sales and support conversations to extract actionable insights for product improvements and feature prioritization
Track product usage patterns to drive data-informed product development and prioritize features based on user behavior
Leverage product analytics to identify user behaviors and trends, enabling more informed product decisions and optimizations
Frequently asked
questions
How does Frame AI help product leaders prioritize development and resource allocation?
By analyzing unstructured data in real-time, Frame AI uncovers critical insights and trends that highlight the most impactful areas for improvement. This quantification allows product leaders to make data-driven decisions, ensuring that resources are allocated to high-priority enhancements and optimizations. By focusing on issues that have the most significant cost implications, Frame AI enables product teams to maximize efficiency, streamline development processes, and deliver features and fixes that drive the most value for customers.
What types of unstructured data does Frame AI analyze to improve product quality and user experience?
Frame AI analyzes support tickets, calls, and emails which provide detailed information on recurring issues and common pain points, helping to identify critical bugs or features that require attention. By synthesizing these data sources, Frame AI identifies key trends and areas for improvement, enabling product teams to make informed decisions that enhance overall product quality and user experience.
How can Frame AI trigger actions based on product feedback and customer sentiment?
Frame AI can trigger actions based on key indicators like predicted CSAT scores, escalation risk, and churn risk. For instance, if the analysis detects a recurring issue with a feature, Frame AI can trigger an alert to the product team to prioritize a bug fix. Similarly, if customer sentiment indicates high satisfaction with a new feature, this feedback can prompt further development or enhancements. By providing real-time insights and alerts, Frame AI ensures that product teams can take targeted actions, such as implementing feature updates, addressing critical bugs, or refining user experience, ultimately leading to a more responsive and customer-focused product development process.
How does Frame AI integrate with existing product management tools?
Frame AI integrates seamlessly with existing product management tools such as Jira, Trello, and Asana. This integration process involves securely linking Frame AI’s advanced analytics capabilities with the product management system, allowing real-time data flow between the two. Frame AI enriches the data within these systems by analyzing unstructured customer interactions, such as support tickets, calls, and emails, and extracting valuable insights related to customer sentiment, recurring issues, and feature requests. These insights are then automatically fed into the product management tools, enhancing the existing data with deeper, context-rich information. This seamless integration enables product teams to have a more holistic view of customer feedback and pain points, leading to more informed decision-making and prioritization of development efforts.
How does Frame AI measure impact and ROI?
Frame AI measures impact and ROI by integrating seamlessly with your existing metrics and performance indicators, eliminating the need for new measurement frameworks. By enhancing your current data with deeper insights and more granular analysis, Frame AI quantifies the cost and benefit of each issue and action through solutions like Dynamic Cost Attribution. This allows businesses to track improvements in key areas such as CSAT scores, escalation reduction, and resource allocation efficiency. By participating in existing ROI measurements, Frame AI ensures that you can clearly see the value added by its advanced analytics and proactive insights, demonstrating tangible improvements in operational performance and customer satisfaction.
THE LATEST
Powering the Middle with AI
Middle managers are crucial to organizational success but often spend a significant amount of time on administrative tasks, which limits their ability to focus on leadership and strategy. AI can alleviate these burdens by automating repetitive tasks and providing real-time insights, enabling managers to concentrate on higher-level responsibilities. Technologies like Frame AI’s STAG architecture go further by continuously analyzing data, proactively identifying risks, and offering performance feedback, which allows managers to take timely action. By empowering middle managers with advanced AI tools, organizations can enhance leadership, team performance, and overall operational success.
What is Deep Personalization?
Personalization has evolved from basic demographic targeting to more complex, individualized experiences, thanks to the rise of AI. Early personalization was limited by structured data, offering shallow insights into customer behavior. However, AI now enables businesses to tap into unstructured data, such as customer interactions and feedback, allowing for deeper, more context-driven personalization. With AI’s ability to understand customer intent and emotions in real time, brands can deliver highly relevant, proactive engagement that enhances customer experiences and builds long-term loyalty.
Deep Dive: Automated QA
AI-driven Automated Quality Assurance (AQA) is revolutionizing the traditional QA process in customer service by making evaluations more efficient and consistent. Traditionally, managers manually reviewed a small percentage of interactions based on rubrics measuring accuracy, empathy, and adherence to procedures, which was time-consuming and left room for inconsistencies. AQA automates much of this process by using AI to analyze entire conversations, pre-fill rubrics, and provide real-time insights into agent performance. This allows managers to focus on high-level feedback, improving scalability and ensuring more comprehensive and accurate evaluations across a larger number of customer interactions.
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