In today's customer-centric business world, providing exceptional customer service is crucial to success. Contact centers play a vital role in shaping customer experiences, and analyzing post-call interactions can provide valuable insights to improve agent performance, identify areas for improvement, and improve overall customer satisfaction. customer.
amazon Web Services (AWS) has ai and generative ai solutions that you can integrate into your existing contact centers to improve post-call analysis.
Post Call Analytics (PCA) is a solution that does most of the heavy lifting associated with providing an end-to-end solution that can process call recordings from your existing contact center. PCA provides useful information to detect emerging trends, identify agent training opportunities, and evaluate overall call sentiment.
Complementing PCA, we have Live Call Analytics with Agent Assistance (LCA) for real-time analysis while calls occur, providing ai and generative ai capabilities.
In this post, we show you how to unlock powerful post-call analytics and visualizations, empowering your organization to make data-driven decisions and drive continuous improvement.
Enrich and enhance your post-call recording files with amazon Q and amazon Quicksight
amazon QuickSight is a unified business intelligence (BI) service that provides modern interactive dashboards, natural language queries, paginated reports, machine learning (ML) insights, and integrated analytics at scale.
amazon Q is a powerful new capability in amazon QuickSight that you can use to ask questions about your data using natural language and share presentation-ready data stories to communicate insights to others.
These capabilities can significantly improve your post-call analysis workflow, making it easier to derive insights from your contact center data.
To start using amazon Q in QuickSight, you'll first need Quicksight Enterprise Edition, which you can sign up for by following this process.
amazon Q on QuickSight offers users a set of new generative BI capabilities.
Depending on the user's role, they will have access to different sets of capabilities. For example, a Reader Pro user can create data stories and executive summaries. If the user is an Author Pro user, they will also be able to create themes and dashboards using natural language. The following figure shows the available roles and their capabilities.
Below are some key ways amazon Q in QuickSight can increase your post-call analytical productivity.
- Fast Yonviews– Instead of spending time creating complex visualizations and dashboards, you can let users quickly get answers to their questions about call volumes, agent performance, customer sentiment, and more. amazon Q in QuickSight understands the context of your data and generates relevant visualizations on the fly.
- one time toanalysis: With amazon Q in QuickSight, you can perform a one-time post-call analysis of your data without any prior configuration. Ask your questions using natural language and QuickSight will provide you with relevant information, allowing you to explore your data in new ways and uncover hidden patterns.
- Natural language interface: amazon Q in QuickSight has a natural language interface that makes it accessible to non-technical users. Analysts, managers, and business executives can ask questions about data post-call without needing to learn complex query languages or data visualization tools.
- Contextual rrecommendations: amazon Q in QuickSight can provide contextual recommendations based on your questions and available data. For example, if you ask about customer sentiment, you might suggest analyzing sentiment by agent, call duration, or other relevant dimensions.
- Automated dashtrays: amazon Q can help accelerate the development of dashboards based on your questions, saving you the effort of manually creating and maintaining dashboards for post-call analysis.
By using amazon Q in QuickSight, your organization can streamline post-call analytics, leading to faster insights, better decision-making, and better customer experiences. With its natural language interface and automated visualizations, amazon Q enables users of all levels to explore and understand post-call data more efficiently.
Let's dive into some of the capabilities available to Pro users, such as creating executive summaries and data stories for post-call analysis.
Executive summaries
When a user is just starting to explore a new dashboard that has been shared with them, it often takes time to become familiar with the content of the dashboard and where they should look for key information. Executive summaries are a great way to use ai to highlight key information and draw the user's attention to specific images that contain metrics worth further analysis.
You can create an executive summary in any dashboard you have access to. Like the board shown in the following figure.
As shown in the figure below, you can switch to another sheet or even apply filters and regenerate the summary to get a new set of highlights for the filtered data set.
Key benefits of using executive summaries include:
- Automated Yonviews: amazon Q can automatically extract key insights and trends from your post-call data, allowing you to quickly create executive summaries that highlight the most important information.
- Personalized views: Executives can customize the visualizations and summaries generated by amazon Q to align with their specific requirements and preferences, ensuring that executive summaries are tailored to their needs.
Data Storytelling
After a user has found a trend or interesting information within a panel, they often need to communicate with others to make a decision about what to do next. That decision can be made in a meeting or offline, but a presentation with key metrics and a structured narrative is often the basis for making the argument. This is exactly what data stories are designed to do. Instead of taking screenshots and pasting them into a document or email, at which point all control is lost and the data becomes static, stories in QuickSight are interactive, governed, and can be updated with a click.
To build a story, you always start from a panel. Next, you select visual elements to support your story and enter an indication of what you want the story to be about. In the example, we want to generate a story to obtain information and recommendations to improve call center operations (as shown in the following figure).
As the figure below shows, after a few moments, you will see a fully structured story that includes images and information, including recommendations for next steps.
Key benefits of using data stories:
- Narrative myexploration: With amazon Q, you can explore your post-call data through a narrative approach and ask follow-up questions based on the information generated. This allows you to create a compelling data story that uncovers underlying patterns and trends in your contact center operations.
- Contextual rrecommendations: amazon Q may provide contextual recommendations for additional visualizations or analysis based on your questions and available data. These recommendations can help you discover new insights and enrich your data storytelling.
- Automated northarratives: amazon Q can generate automated narratives that explain visualizations and insights, making it easier to communicate the data story to stakeholders who may not be familiar with the technical details.
- Interactive ppresentations: By integrating amazon Q with QuickSight presentation mode, you can create interactive data storytelling experiences. Executives and stakeholders can ask questions during the presentation, and amazon Q will generate visualizations and insights in real time, enabling a more engaging and dynamic data storytelling experience.
Conclusion
By using amazon Q capabilities in QuickSight, you can uncover valuable insights from your call recordings and post-call analytics data. These insights can then inform data-driven decisions to improve customer experiences, optimize contact center operations, and drive overall business performance.
In the era of customer-centricity, post-call analytics has become a game-changer for contact center operations. By using the power of amazon Q and amazon QuickSight in addition to your PCA data, you can unlock a wealth of valuable insights, optimize agent performance, and deliver exceptional customer experiences. Embrace the future of customer service with cutting-edge ai and analytics solutions from AWS and stay ahead of the competition in today's customer-centric landscape.
About the author
Daniel Martinez is a Solutions Architect at Iberia Enterprise, part of the AWS Worldwide Commercial Sales (WWCS) organization.
