FRAME AI SOLUTIONS > Product Solutions

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.

“Frame AI's STAG architecture and real-time natural language processing has empowered our customers to unlock the full potential of their unstructured data. The automation and insights powered by Frame AI are transforming operations, improving customer experiences, and ultimately achieving superior business outcomes. It's a game-changer for our customers.”

Matt Davey
MD Technology, Gitlab

“Frame AI has enabled us to address customer needs more swiftly and efficiently, resulting in quicker response times and increased satisfaction rates. Monitoring our customer communication in real-time has allowed us to deliver outstanding customer experiences more consistently and effectively, while also recognizing when our team is delivering exemplary customer service.”

Matt Davey
MD Technology, Gitlab

“Frame AI has been instrumental in helping us prioritize resources and optimize operational expenses. We’ve been able to improve customer experiences and improve efficiency at the same time— exactly what we were hoping to achieve.”

Matt Davey
MD Technology, Gitlab

“Frame AI’s STAG architecture seamlessly integrates into our workflows, allowing us to analyze and prioritize issues in real-time, which means we can resolve problems faster and keep our users happy.”

Matt Davey
MD Technology, Gitlab

“As an AWS customer, we’re happy to see we can use our credits to leverage Frame AI’s predictive automation capabilities to anticipate our customers' needs before they even ask. This proactive approach has not only improved our responsiveness but has also enabled us to build stronger, more trusting relationships with our clients.”

Matt Davey
MD Technology, Gitlab

PROACTIVE TOOLS FOR
accelerated resolution

Leverage real-time data, predictive insights, and automated workflows to consistently enhance product quality and customer satisfaction.

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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.

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What is Deep Personalization?

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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.

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Deep Dive: Automated QA

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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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