This workflow is intended for customer success and marketing teams looking to leverage satisfied, long-term customers by requesting referrals. It identifies customers with high satisfaction and extended tenure as ideal candidates for providing referrals.
The process begins with analyzing customer data to detect those who have been with the company for 12+ months and have demonstrated high satisfaction. Once these candidates are identified, the workflow uses AI to draft a warm, appreciative referral request email that thanks the customer and inquires if they know anyone who might benefit from your product.
After drafting, the email is personalized with specific customer details and then dispatched via an email automation platform. The workflow also tracks responses and referrals, enabling teams to follow up and further nurture valuable customer relationships.
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 Advocacy stage in your daily job and want to find ways for Ai to help you do more with less.
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.
Using customer data from {customerData}, draft a warm and appreciative referral request email that thanks the customer for their loyalty and asks if they know anyone who could benefit from our product. The tone should be friendly, sincere, and encouraging.
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