Ingredients

OrderGroove, Salesforce Service Cloud, and Kodif.

What are AI Policies?

At Kodif, we’re excited to announce the launch of Policies—a powerful, dynamic solution designed to revolutionize the way CX managers handle customer support. Unlike traditional flows, which are rigid and complex, Policies empower non-technical users to create and manage customer interactions with ease. Written in natural language, Policies make it simple to define and refine customer experiences without needing to rely on complicated flowcharts or scripting. This approach is not only user-friendly but also self-serve, enabling CX teams to quickly translate existing Standard Operating Procedures (SOPs) into automation, saving valuable time and resources.

The flexibility of Kodif Policies ensures that businesses can offer personalized, context-driven support while continuously improving customer experiences. With Policies, you can experiment with different strategies to optimize outcomes such as CSAT, revenue, and retention—all without the need to rebuild complex workflows. Whether it’s automating routine interactions or testing new approaches for high-stakes scenarios, Policies provide a scalable, adaptable solution that aligns with your business goals. While flows still have their place in sensitive, high-risk situations, Policies offer an agile alternative that helps businesses innovate faster and deliver exceptional, tailored experiences at scale.

“Cancel subscription” ticket type explained

In customer support, a “Cancel subscription” ticket type refers to requests from customers who wish to terminate their subscription services. These requests often involve managing customer accounts, processing cancellations, and ensuring that the cancellation is completed smoothly without any errors. Efficient handling of such tickets is crucial as it can impact customer satisfaction and retention rates. By understanding the reasons behind cancellations, businesses can also gather valuable feedback to improve their offerings and potentially retain customers through tailored retention strategies.

Which Platforms does this AI policy work on?

This AI policy works seamlessly on OrderGroove, Salesforce Service Cloud, and Kodif. Kodif is designed to integrate with all other major platforms, ensuring wide-ranging compatibility and flexibility for businesses looking to automate their customer support processes.

When should I use this policy?

Use this policy when customers want to cancel orders and the process requires a retention step. The policy logic involves offering alternatives to cancellation to retain the customer.

1. When a customer wants to proceed with the cancellation in the #Single_order_cancellation_policy, provide cancellation alternatives:
2. Discount Offer: Use @set_discount_to_order to offer a discount (e.g., 10% or 15%) on the current order if the user chooses to retain it.
3. Shipping Upgrade: Offer an expedited shipping upgrade free of charge to incentivize the user to keep their order.
4. Product Swap: Offer the option to swap the item for another product of the same or higher value at no extra cost.

5. Future Discount: Offer a discount for a future purchase, e.g., a 20% coupon for their next order, if they keep the current order.

6. Confirm Retention Decision:

7. Ask the user if they are interested in one of the retention options.
8. If the user accepts:
   • Apply the agreed-upon retention offer using the relevant tools (@set_discount_to_order, @upgrade_shipping, or other applicable retention tools).
   • Inform the user that the order has been updated, and provide them with the relevant details (e.g., new discount, shipping upgrade, etc.).
   • Use @send_async_message(message: str) to notify the user that their order has been successfully updated with the retention offer.

9. If the user declines:

   • Proceed with the order cancellation as described in the #Single_order_cancellation_policy.

10. Post-Retention Follow-up:

11. If the user accepts the retention offer, thank them for choosing to keep their order and reiterate any benefits or bonuses (e.g., a future discount).

12. Ensure the user receives a follow-up message confirming that their retention offer has been applied.

13. Escalation:

14. If the user has any additional concerns or issues regarding the retention offer, route the case to an agent for further assistance.
15. In cases where the user insists on canceling despite the retention offers, proceed with cancellation as outlined in the cancellation policy.

Policy logic

The policy logic involves offering alternatives to prevent order cancellation and applying those offers if accepted by the customer. It ensures that customers have options that may lead to retention, but also respects their decision if they choose to proceed with the cancellation.

Example policy

The example policy follows the logic of providing retention alternatives when a customer initiates a cancellation:

1. Customer wants to proceed with the cancellation in the #Single_order_cancellation_policy:

2. Provide Cancellation Alternatives:

   • Discount Offer: Use @ordergroove_set_discount_to_order to offer a discount on the current order if the user chooses to retain it.
   • Shipping Upgrade: Offer an expedited shipping upgrade free of charge.
   • Product Swap: Offer the option to swap the item for another product of the same or higher value.
   • Future Discount: Offer a discount for a future purchase if they keep the current order.

3. Confirm Retention Decision:

4. Ask the user if they are interested in one of the retention options.
5. If the user accepts:
   • Apply the agreed-upon retention offer using the relevant tools (@ordergroove_set_discount_to_order, @ordergroove_upgrade_shipping).
   • Notify the user via @send_async_message(message: str).

6. If the user declines, proceed with the cancellation as outlined in the #Single_order_cancellation_policy.

7. Post-Retention Follow-up and Escalation:

8. Thank the user if they accept the retention offer, and ensure they receive confirmation of the applied offer.
9. Route any additional concerns to an agent if necessary.

Explore more AI policies