The Zendesk Community Event on AI Agents highlighted the potential of AI agents to enhance customer service. Attendees learned about best practices, real-world use cases, and received resources to improve their service experiences with AI agents….
Launching an AI agent is a straightforward process that can be done in minutes. Start by setting guardrails with intents, then add personalization and control to your interactions. After deployment, allow a 2-week learning period for your AI agent…
In the first month of AI agent rollout, it's crucial to monitor key metrics via the Insights dashboard. This includes tracking active users, the percentage of transfers to agents, and automated resolutions. These performance metrics provide a…
To prevent your AI agent from giving incorrect answers, ensure your knowledge base content is up-to-date and verified regularly. The quality of information your AI agent provides is directly linked to the accuracy of your knowledge base. Focus on…
Measuring the success of AI agents involves starting slowly and building automation rates over time. Aim for up to 20% automation rates using generative replies and gradually automate more intents. Regularly review AI agent conversation…
Key performance indicators (KPIs) for evaluating AI agent success include self-service rates, bot insights, and CSAT scores. Start by assessing your current self-service rates and use bot insights to track performance over a 7-day period. Identify…
AI agents can potentially integrate with HubSpot to create sales and marketing workflows from support tickets using the Make API call step. This step allows you to configure API calls to external systems. While direct experience with the HubSpot…
To increase chatbot adoption among less tech-savvy customers, start with the basics and ensure your AI agents have access to relevant content and knowledge. This foundation provides immediate value with minimal setup. By focusing on simple and…