Chatbots can become indispensable tools for businesses looking to streamline operations and enhance customer service. However, creating a chatbot that consistently delivers value requires more than just setting it up and letting it run; it requires ongoing conversation review and content optimization.
I’ve performed conversation review for natural language processing (NLP) chatbots as well as generative AI-powered assistants. What have I learned? It’s a mostly manual effort that not only requires close attention to details, but constant communication with developers and content writers to completely correct the experience.
Understanding the Importance of Conversation Review
Conversation review is the process of analyzing interactions between users and chatbots to identify areas that may need improvement. This analysis can reveal insights into user satisfaction rates, chatbot response accuracy, and opportunities for enhancing your organization’s knowledge base. Regular review ensures your chatbot remains effective, relevant, and capable of delivering a high-quality user experience.
Setting Up Your Conversation Review Process
To begin, identify the team member(s) doing the conversation review. In my experience, it should be the content writer themselves or a designated QA tester with a familiarity of the project. Once you’ve identified your reviewer, establish a process that includes:
- Monitoring Schedule: Schedule daily (ideally) or weekly sessions to examine conversations. This helps in catching issues early.
- Key Metrics: Determine what metrics you’ll use to evaluate the chatbot’s performance. Common metrics include response accuracy, user satisfaction scores, and resolution times.
- Feedback Loop: Implement a mechanism for incorporating findings from reviews back into chatbot training and refinement. Some platforms even incorporate training into their conversation review tools.
Analyzing Chatbot Conversations With Your Customers
You might think that conversation review sounds boring — it is. After a few days of dedicated conversation review under your belt, you will get to know the content in your bot so well it may seep into your subconscious dreams at night (hopefully not). Over time, you will start to get quicker at identifying what and where conversations may go wrong.
When analyzing chatbot conversations for effective conversation review, look closely at:
- User Queries and Chatbot Responses: Look for accuracy in the chatbot’s responses and its ability to understand and process user queries.
- Escalation Points: Identify conversations that required human intervention, and understand why the chatbot couldn’t handle them independently.
- User Satisfaction: Use post-interaction surveys to gauge user satisfaction and note any recurring complaints or suggestions.
- Formatting Errors: Sometimes text may appear one way in the testing environment and another in production. While you should do your best to mirror any test and production environments, visual formatting bugs can happen.
Enhancing Chatbot Performance Over Time
Based on your ongoing analysis, take steps to enhance your chatbot’s performance:
- Expand the Knowledge Base: Add more information to the chatbot’s database to cover gaps identified during the review. Source ideas from customer channels outside of your digital ones if the volume is there.
- Refine AI Models: Use insights from conversation reviews to train your chatbot’s AI models, improving understanding and response generation. This can be done by adding new data, or utterances for intents and tokenizing words as specific entities.
- Personality Enhancements: By analyzing user sentiment at various steps in the flow, you can try to make the chatbot more user-friendly and efficient with copy changes. Botpress has it’s own “personality agent.”
Leveraging Technology for Efficient Conversation Reviews
Today there also analytics tools and AI-powered platforms designed for conversation analysis. These tools can automate aspects of the review process, such as identifying common issues or tracking performance metrics, making your review process more efficient and effective. Tetra, Gong, Chorus, and Avoma are just a few brands that offer industry leading conversational intelligence tools.
Plan Ahead with Proactive Optimization
Proactive optimization involves anticipating changes in user behavior or business operations and updating the chatbot accordingly. This can include adding new functionalities, updating information, or refining conversation flows based on seasonal trends or promotional activities.
Other data from your business may be useful in predicting the content that your users may need in the future. For example, if a certain flavor of sales or transaction volume spikes during a certain time of the year. During my time building chatbots at TD Ameritrade, we often rushed to make content updates before spikes in user activity based on many seasonal occurrences and market events (like tax season or reorganizations).
Cultivating a Culture of Continuous Improvement
Finally, fostering a culture of continuous improvement within your team is essential. Encourage feedback and suggestions from all team members involved in the chatbot’s operation, from developers to customer service representatives. This collective approach not only enhances the chatbot’s performance but also ensures it evolves in line with your business’s changing needs.
Conversation review is not just about maintaining a chatbot; it’s about continually enhancing it to meet and exceed user expectations. By following this comprehensive guide, you can ensure your chatbot remains a valuable asset to your business, providing efficient, accurate, and satisfying interactions that reflect the high standards your customers have come to expect from your two decades of experience in the field.
Need help with chatbot maintenance or training an NLP model? I can provide a comprehensive assessment of your brand’s current conversational experiences and AI workflows. We can help you get the most value out of your platform of choice and apply the tactics described above to your product or experience.
