FAQ for opportunity summary feature in Outlook and Teams
These frequently asked questions (FAQ) describe the AI impact of Microsoft 365 Copilot for Sales's opportunity summary feature in Outlook and Teams.
What is opportunity summary feature in Outlook and Teams?
Leveraging CRM data, Copilot for Sales provides salespeople with a summary of relevant information before a meeting and in Teams chat and channel conversations. By aggregating customer data and insights, it equips sellers with the necessary context and background, enabling them to be well-prepared and engage in more meaningful and productive discussions.
What are the feature's capabilities?
Leveraging its integration with CRM systems and customer databases, Copilot for Sales retrieves relevant customer information such as contact details, past interactions, and preferences. It uses this data to generate a concise summary, providing salespeople with a comprehensive overview of the customer's background, needs, and preferences, enabling more informed and tailored discussions.
What is the feature's intended use?
The intended use of this feature is to provide salespeople with an overview of customer information and insights based on CRM information. By aggregating and analyzing data from CRM systems and customer databases, it aims to equip salespeople with the necessary context, enabling them to have well-informed discussions, build stronger relationships, and increase the chances of successful outcomes when communicating with the customer or collaborating with colleagues.
How was the opportunity summary feature evaluated? What metrics are used to measure performance?
The feature is evaluated through a combination of comparative analysis, human review, and customer engagement metrics. Performance is measured based on criteria such as accuracy, relevance, engagement, and customer satisfaction. The accuracy and usefulness of retrieved customer information in meeting preparation are also used to measure performance.
End-users provide ongoing feedback on each Copilot feature, along with iterative improvements contribute to optimizing the system's performance across all features.
What are the limitations of this feature? How can users minimize the impact of the limitations when using the system?
The retrieved customer information is limited to the data available in the CRM system or external sources, potentially missing recent developments, or contextual nuances.
To minimize the impact, users should supplement the retrieved information with their own knowledge and insights, actively engaging with the customer prior to the meeting to gather up-to-date details and ensure a comprehensive understanding.
What operational factors and settings allow for effective and responsible use of the system?
Data privacy and security: Implement robust data privacy measures to protect customer information and ensure compliance with relevant regulations. Use secure communication channels and encryption methods to safeguard sensitive data.
User training and guidelines: Provide comprehensive training to users on the system's features, capabilities, and limitations. Establish clear guidelines and best practices for responsible and ethical use, emphasizing the importance of accurate representation, respectful communication, and adherence to legal and ethical standards.
User permissions and access control: Implement role-based access control to limit system functionalities and data access based on user roles and responsibilities. Ensure that users have appropriate permissions aligned with their job responsibilities and authorized access to customer data.
Monitoring and auditing: Regularly monitor system usage, interactions, and outcomes to identify any potential issues or concerns. Conduct periodic audits to assess adherence to guidelines, data protection measures, and ethical practices.
Feedback and continuous improvement: Encourage users to provide feedback on system performance, accuracy, and user experience. Actively seek user input to understand their needs and identify areas for improvement. Regularly update the system based on feedback and advancements in technology.
Transparency and explainability: Foster transparency by clearly communicating to users how the system works, the underlying technologies used, and any limitations or potential biases. Ensure that users have a basic understanding of the system's capabilities and are informed about its AI-powered nature.
Accountability and error correction: Establish mechanisms for addressing errors or inaccuracies that may occur in system-generated content. Encourage users to review and correct any inaccuracies, taking responsibility for the final output, and ensuring it aligns with their knowledge and expertise.