How to Select an AI Chatbot for Customer Service

Selecting the right AI chatbot for customer service is crucial for enhancing customer experience and streamlining support processes.

This article outlines key factors to consider when selecting a AI customer service chatbot.

Implementation & Integration

When selecting a customer service chatbot, it's important to consider how long it will take to deploy the chatbot. You should also consider if the chatbot is compatible with your customer service tech stack.

Consider these criteria:

1. Deployment Time: A competent customer support AI chatbot should be up and running within hours, not weeks or months.
2. Knowledge Import: The AI chatbot should be capable of ingesting a proprietary knowledge base from various sources. Those sources could include existing FAQs, product documents, wikis, community discussion boards, and help desk tickets.
3. Knowledge Preparation: Does the chatbot require curated knowledge, like FAQs? Or if it can ingest existing documentation "as is".
4. Language Translation: Does the chatbot need you to translate documents in the knowledge base? Or can it translate knowledge on the fly and automatically help you overcome language barriers?
5. Works with Existing CS Solutions:  The AI customer support chatbot should work with your current help desk and live chat systems. This allows you to leverage existing investments. It also creates a smoother experience for your customers.
6. Configurability:  Can you set up the chatbot to only transfer to live agents at specific times or days?
7. Multi-Channel Support: Ensure the chatbot works across various all your customer support channels, like email, SMS, Slack, and Discord.
8. No Additional Cost across Channels: The chatbot should be deployable across all customer support channels without additional license fees.
9. Customization: Customizing the chatbot to match your brand’s aesthetics and personality is crucial for a consistent brand experience.
10. Enterprise System Integration: The chatbot should integrate with other systems, like order management, payment processing, and CRM.
11. Deployment of Multiple Chatbots: Can you deploy different versions of the chatbot for different audiences?  How easy is it to create different chatbots?

The Customer's Experience

Once you've gotten your chatbot up and running, it's important to evaluate the end user experience. Use these criteria to evaluate how good your chatbot is at actually improving the customer experience:

1. Query Input: The chatbot should allow customers to type in queries and not just choose from preset options.
2. Language Detection: The chatbot should automatically detect and respond in the customer's primary language.
3. Response Time: Assess how quickly the chatbot starts interacting with users.
4. Ability to Converse:  The chatbot should engage with customers in a human-like, empathetic manner.
5. Context Memory: The chatbot remembers the context of the conversation. Customers should not need to repeat themselves. Also, the chatbot should be able to remember
6. Resource Links: The chatbot should provide links to relevant customer documentation.
7. False Negative Rate: Know how often the chatbot fails to answer questions it should be able to answer.
8. Accuracy: Evaluate the frequency of accurate responses to relevant questions.
9. False Positive Rate: Measure the rate at which the chatbot responds to queries completely outside its knowledge base. At Gleen, we call these false positives "ungrounded hallucinations."  Your chatbot's ungrounded hallucination rate should be close to 0%. The chatbot shouldn't provide any answers to questions that aren't part of its knowledge base.

Here's a video of Gleen AI versus an Open AI GPT trained on the same knowledge. The GPT hallucinates, but Gleen AI doesn't.

Feedback & Supervision

Once the chatbot has answered a customer's question, what comes next? Will you actually have visibility into the chatbot's operations? Consider the following criteria:

1. Feedback Mechanism: The chatbot should collect and adapt to feedback from customers and admins.
2. Chatbot analytics:  The chatbot should provide summary analytics:  the number of questions received, average response time, and customer feedback.
3. Question Review: You (and other admins) should be able to review customer queries to the chatbot.
4. Response Review: You should be able to review the chatbot’s responses. Response review is crucial for quality control.
5. Response Improvement: The system should allow you to improve responses for future chatbot interactions.

Maintenance

1. Knowledge Base Ingestion: The chatbot should automatically update its knowledge base.
2. Manual Knowledge Update: There should be an option to manually trigger knowledge base updates.
3. Aging of Knowledge:  Does your chatbot automatically age knowledge?  Is older knowledge considered to be just as important as newer knowledge?  Or do you need to manually remove knowledge from the chatbot?

Other Considerations

1. Uptime and Downtime: Understand the chatbot's reliability and expected downtimes.
2. Downtime User Experience: Evaluate the impact of downtime on end users.
3. Analytics: The chatbot should provide analytics on performance metrics like response time and feedback rates.
4. Data Privacy and Security: Verify if the vendor is SOC 2 Type 2 compliant or has equivalent security measures.
5. Vendor Support: Consider the support and service level agreements provided by the vendor.
6. LLM indifference:  For chatbots using generative AI, what large language model (LLM) does the chatbot use?  Can you change the underlying LLM to a different model?  Given how quickly the LLM industry is changing, a good chatbot should be LLM-agnostic.

Conclusion

Your customers are your most important asset.

Selecting the wrong customer service chatbot can lead to customer frustration and lower customer loyalty.

Selecting the best AI customer service chatbot is important for your business. Use the above criteria to ensure your chatbot is an effective solution for your customers.

Do the criteria make sense to you?  

If so, you should consider Gleen AI. Gleen AI is a generative AI chatbot for customer service teams, and it easily meets all the above criteria.

Create your free generative AI chatbot with Gleen AI or schedule a demo today.