Insights & Resources2 min read

6 Considerations When Implementing an AI Solution

When they’re done right, conversational AI and chatbots can have huge payoffs for a business in terms of cost, operational efficiencies and customer experience.

Christie Wragg
Telnyx Voice API Call Control: Conversational AI Considerations
When they’re done right, conversational AI and chatbots can have huge payoffs for a business in terms of cost, operational efficiencies and customer experience. However, there are a number of factors to consider in order to make sure your implementation is a successful one. And getting it wrong can have dire consequences when it comes to your brand and customer satisfaction.
Here are our top 6 considerations you’ll need to understand, evaluate and make decisions about when you’re implementing any kind of AI solution.

1. Omnichannel experiences

Whether you’re using conversational AI for voice or text, it’s critical that the experience is consistent from channel to channel. Your conversational AI and chatbots should speak in voice and style that’s congruent with your other branding efforts. And, you need to ensure that information is shared between your various communication channels, so that the transition from channel to channel is seamless for the customer.
That way, if a customer starts a chat on your website, then moves to your mobile app, the chat session can continue. Or, at least any information the customer had entered should be transferred to the new channel.

2. Text-to-speech

Text-to-speech is first an accessibility feature for customers with disabilities which makes your conversational AI usable for more customers. However, even customers who don’t need text-to-speech for accessibility will prefer text-to-speech options so that it’s easier to interact with your automated customer service systems on the go.

3. Natural language processing

Natural language processing is one of the most important aspects of conversational AI. It’s what enables your AI to understand human languages as they’re spoken or in text.
Natural language processing is critical because it enables your customers to interact naturally with your AI system. Rather than being restricted to very specific inputs, like a touchtone menu on a phone, customers can simply speak to your AI, and it will understand them.
The challenge with natural language processing is that it requires very strong underlying infrastructure. Your conversational AI must be connected to a high-reliability network with very low latency. Otherwise, the language processing system will interrupt the natural flow of conversation, and customers will get frustrated with the delays.

4. Human handoff

As we mentioned earlier, your conversational AI systems can’t handle everything. There are some customer service tasks that must be done by humans. Your AI needs to be able to identify when it receives a request that must be handed off to a customer service representative, and the program needs the power to transfer calls and chat sessions to live agents on-demand.
So, your AI applications need a certain level of call control, and connectivity to your live chat programs.

5. Sentiment analysis

The ability to identify attitudes in text may not be mandatory for a chatbot. However, if your chatbot can identify positive, negative, and neutral attitudes in customer interactions, it can tailor its responses accordingly and mitigate situations or identify faster paths to problem resolution.
This is especially useful in situations where customers are handed off to live customer service agents, because customers begin their conversation with the customer service representative in a less agitated state.

6. Talk-time latency

Regardless of whether the communication is through text or voice, talk-time latency may be the most important factor in successfully deploying conversational AI and chatbots. It doesn’t matter how well your conversational AI is built or how well-written the responses are if customers don’t want to interact with your AI. When there’s a long delay between when the customer speaks or types and the response, customers are going to get irritated fast. Then they’ll try to bypass the AI as quickly as possible to get to an actual human, which makes the customer experience worse, and completely defeats the purpose of the AI.

To find out more about how to implement conversational AI successfully, including some common mistakes to avoid, check out our eBook: Your Guide to Better Leveraging Conversational AI.
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