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AI-Powered Customer Relationship Manager

As businesses look to their sales team to scale company growth, they must provide them with AI-powered solutions that connect with existing systems, eliminate tedious tasks, and empower them with the tools they need to succeed.
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Contoso Coffee owns offices in countries across North and South America, Europe, and Asia with over 10,000 employees.  David is a Account Executive at Contoso Coffee. He manages a large pipeline of customers, so he needs to stay on-task to get through his to-do list and maintain strong customer relationships. ​
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spend <30% 
of your time on 
non-sales activities1

Let’s see how an AI-powered CRM eliminates inefficiencies throughout his day:

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9:00

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David signs into the CRM and has the system generate a list of tasks, including email responses and meeting summaries based on the opportunity.

9:30

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David sees he has a new email from a prospect. He asks the system to generate a response using data collected from previous meetings, the prospect’s activities, and third-party applications, like LinkedIn Sales Navigator.

11:00

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Later that day, David has a meeting with a prospect interested in buying Contoso Coffee. He uses the system to prepare a summary of the opportunity, including prospect details, past meeting notes, and emails. After reviewing the summary, he realizes there is a chance to increase the opportunity size and wants to connect with his manager, Sara, who works from home, to discuss how to approach today’s conversation.

11:30

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Before meeting with Sara, David takes some time to do prospect using personalized, AI-generated content based on prospect activity and concerns.

12:30

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Using collaboration tools connected to the CRM, David creates a deal room with Sara using a pre-built template that includes all the opportunity details. He then has a virtual meeting with her to develop a strategy for the call.

2:00

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David presents what he discussed with Sara to the prospect. He can better focus on the meeting as the system records the meeting and writes a transcription highlighting competitor mentions and action items instead of manually taking notes.

2:45

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During the call, the prospect asks a question David doesn’t know how to answer. The system generates a suggested answer, tips, and related information to address the prospect's concerns. 

3:00

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After the meeting ends, the system gives David an analysis of the call. The information includes a customer sentiment analysis and KPIs like talk-to-listen ratio, talking speed, and switches in the conversation.

3:30

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David shares the meeting recap and analysis with Sara using the same deal room he created earlier to update her on how the opportunity progressed.

4:30

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A new lead replies from David’s prospecting session earlier in the day. The system automatically adds details to the CRM and the company’s communication systems.

Ready to make this a reality for your sales team?

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