Best practices for commerce agents

Enhance your business with PayPal's new Model Context Protocol (MCP) server and agent toolkit. When you implement AI agents strategically, you can:

• Provide consistent customer support
• Deliver personalized product recommendations
• Create smoother payment processes

The key is finding the right balance between efficient automation and the human touch that customers value.

With PayPal's MCP-powered agent toolkit, you can:

• Automate routine customer interactions
• Streamline your commerce operations
• Improve the overall customer experience

Keep human oversight in critical areas where personal judgment matters most, while letting AI handle repetitive tasks.

Getting started

When you hire an employee, you consider that person’s scope, role, and responsibilities. Similarly, when building an agent, you keep the same things in mind, plus commerce-specific considerations.

Recommended best practices and considerations include:

• Create an organizational chart based on roles and scope of responsibilities for your business.
• Define a clear purpose for each agent and their role.
• Define clear capabilities and responsibilities for each agent.
• Define where an agent should interact with another agent.
• Clearly define edge cases and expectations of how an Agent should handle these.
• Define where an agent hands off to a human.
• Understand where agents need to be integrated to perform effectively, such as with an inventory management system.

Examples of agent types for an online store

These examples are for a fictional online coffee bean store, but they illustrate some of the ways that any seller might use agents. 

Agent type	Purpose	Key capabilities
Customer support	Handle common customer inquiries and support requests.	- Answer product questions, such as coffee origins, roast levels, or flavor profiles. - Process order status inquiries. - Explain shipping policies and timeframes. - Handle basic troubleshooting for website or order issues.
Product recommendation	Help customers discover coffee beans that suit their preferences	- Ask questions about taste preferences, such as acidity, body, and flavor notes. - Consider brewing methods, such as French press, espresso, or pour-over. - Suggest complementary products, such as filters or brewing equipment. - Track and learn from customer patterns.
Order processing	Streamline the purchase process and handle order-related tasks.	- Guide customers through checkout. - Process shipping address validation. - Handle inventory checks and back-order information. - Provide shipping cost estimates and delivery timeframes.
Shipping	Automate processing of end-to-end shipping capabilities.	- Search open orders and generate shipping labels. - Print shipping labels. - Share shipping tracking information with customers and partners. - Interact with a returns agent to generate return shipping labels.
Returns and exchanges	Facilitate smooth return and exchange processes.	- Process return requests and generate return labels. - Explain return policies and eligibility. - Process refunds or store credits. - Gather feedback about reasons for returns.
Subscription management	Handle coffee subscription services and recurring orders.	- Process subscription sign-ups and modifications. - Handle requests to pause or resume a subscription. - Manage delivery frequency changes. - Process subscription cancellations with retention options.

Integration considerations

From the preceding examples, you can see how agents help automate an entire business, but there is still a cost consideration when implementing. Consider the size and scale of your business and your pain points to determine where it makes sense to invest in building an agent. Other cost considerations to factor in are the costs of tokens and how many tokens an AI agent uses to complete its tasks.

If you're thinking about using agents:

• Start with the highest value agents. Begin with agents that address your most frequent customer interactions. 
• Design clear agent boundaries and handoffs between agents and human staff. 
• Develop a knowledge base. Ensure that you have a clearly documented knowledge base on products, FAQ’s, policies around shipping and returns, and so on. This knowledge base helps guide your agents. 
• Test and iterate. Commit the necessary time and resources for testing agents with real-world scenarios before full deployment to ensure accuracy and to allow you to improve the agent and its capabilities. 
• Monitor performance. Track the performance of an agent and your customer satisfaction to understand where agents are most effective and where they can be improved.

Agent-to-agent interactions 

Another area to consider is how an agent interacts with other agents you build. These interactions help scope each agent’s role and prevent duplication or overlap.

Some examples of these interactions might include: 

• Order agent interacting with a shipping agent to quote shipping timelines
• Returns agent interacting with a shipping agent to generate a return shipping label
• Support agent interacting with a return agent to update the status of a return

Other integration considerations

Are your agents able to integrate into your other back-end systems to be effective? Consider how interactions like these might impact your agents and your integration:  

• Inventory management system for real-time stock levels
• Order processing system for status updates
• Customer accounts for personalized experiences
• Shipping partners for tracking information
• CRM system for customer history