You care about improving the entire lifecycle of buyer and customer journeys. And you want inspiration for areas where Ai may help.
You want inspiration for real-world ways to help people as you're building your Ai product.
You're focused on the Decision stage in your daily job and want to find ways for Ai to help you do more with less.
On a regular schedule, this workflow uses AI to analyze all open sales opportunities. It predicts each deal's likelihood of closing (either as Won or Lost) and identifies stalled deals with little recent activity. The findings are compiled into a Deal Health Scorecard summarizing win probabilities, risk factors, and signs of stalling. This scorecard is delivered to the sales rep, providing clear insights into which deals need attention. For stalled or at-risk opportunities, the workflow also drafts a personalized re-engagement email using AI. The rep can review and edit this draft before sending, ensuring they reach out with the right message to revive the deal.
Does this AI agent workflow rely too much on AI and not enough on human know-how? Or the reverse? Is it missing steps or tools?
Note that this Ai workflow is presented as inspiration for what's possible. Adjust the amount, type and quality of the data inputs. Adjust how much or how little your human team mates (or you), AI and fully autonomous agents contribute.
And test it! Learn what works and what doesn't.
Don't forget! In the end, it's not just about efficiency. It's about delivering great experiences for your customers and customers-to-be.
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