AI-Powered Collaborative Win/Loss Analysis from Shamaym Accelerates Sales Team Learning, When They Need It Most

New Shamaym Feature Automates Deal Analysis and Sharing of Insights to Empower Smarter Selling

Shamaym, a leading provider of collaborative real-time learning solutions, today announced the addition of a new feature that, for the first time, automates the process of a win/loss analysis for its sales team platform.

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Sales teams often conduct a win/loss analysis after deals are closed, ostensibly to share information with other sales team members about what worked, what needs to be improved, and how the information learned should be applied to future deals. When a salesperson now changes the status of an opportunity (in Salesforce, for example), Shamaym will automatically generate a deal analysis report, and prompt the salesperson to add their insights and create a win/loss debrief. These takeaways are shared with team members, empowering them to tap into the lessons learned in relevant situations and increase their success rate in future deals.

“Automating the win/loss analysis process ensures it gets done every time and gives the team the tools they need to be successful for the next deal,” said Ofir Paldi, CEO of Shamaym. “It also makes sure salespeople have the information of what works and doesn’t work in the sales process, improving closing rates by continuously updating the team in real-time.”

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Eliminating Missed Opportunities to Close Deals

The Shamaym sales team platform efficiently integrates learning from past experiences into the day-to-day work process of its customers. The automated win/loss analysis adds immediate feedback and creates valuable opportunities to learn at the moment of need. It will improve an important sales process and the opportunities to close deals successfully. Powered by AI, the platform integrates with Salesforce and other CRM systems to deliver real-time sales guidance, increase visibility for managers, and foster strong team collaboration.

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AI-Powered CollaborativeNewsreal-time learning solutionsShamaym
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