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 AI implementation is a successful one. And getting it wrong can have dire consequences when it comes to your brand and customer satisfaction.
Here's a snapshot of what's at stake when considering how you can use AI in your business:
Why AI is Important for Business
Up until recently, you could argue that your industry—whatever it may be—didn't need AI. That's no longer the case. AI is important for your business, no matter what your business is, because it can give you game-changing insights about your customers. What's more - it's incredibly easy to start using off-the-shelf, general-purpose AI tools to unlock these insights.
To illustrate just why AI is important for business, let's use a simple example of AI-powered speech to text transcription. If you turn on transcription of your phone calls, you'll have an auto-generated, searchable record of every phone interaction between you and your customers. This opens the door to all kinds of insights. You can find out what your customers are saying about a certain product, feature or service. You can find calls that contain certain phrases to help train the rest of your team. You can track down that super-important detail your customer shared on that last call, all in a matter of seconds.
6 Things to Consider for AI Implementation
"AI Implementation" is a scary phrase. Just reading it probably makes you think about expensive software engineers, complex topics like machine learning or recursive neural networks, and a whole lot of work. It's not surprising that implementation worries are the thing that discourages so many businesses from using AI tools.
But here's the thing: AI implementation shouldn't be hard. Once you consider some key points, it's an easy problem to solve. So easy, in fact, that we implemented AI in a live demo of our very own in less than five minutes.
Here are some simple steps to implement AI. If you consider these six factors, you'll be set up to choose and implement the right tool in no time.
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.
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.
Speech to text transcription (sometimes abbreviated to STT) is one of the most common ways to use AI in your business. It's built on speech recognition AI, which itself is a form of Natural Language Processing (NLP), an advanced field of machine learning. Luckily, communications platforms like Telnyx allow you to stand on the shoulder of giants, and use pre-built NLP tools to transcribe speech to text directly from your phone calls in real-time.
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.
4. Natural Language Processing
If you'd like to take the leap and build your own Natural Language Processing, you can have more flexibility and control over how your customers' voices are processed and used to make decisions.
The challenge with NLP 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.
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.
How to Use AI in Your Business
Once you've considered all of the factors and benefits laid out above, you're probably left asking, "How can I use AI in my business?"
The answer is surprisingly simple. There are a huge number of tools that you can use to unlock AI-powered insights in every facet of your business. These tools can help you automate repetitive tasks like responding to customer emails and chats, recording expenses and invoices, and tracking time spent on projects. What's more - these tools can often plug-and-play with your existing tools, so you don't need to worry about complex AI implementation strategy.
But there's one application in particular that has an even higher impact. Like we mentioned earlier, transcribing phone calls using speech to text has an outsized impact on your business because it gives you a searchable record of everything that's said on the phone between you and your customers.
If you want a simple way to use AI in your business to reveal insights, follow along with our 5-minute demo and turn on transcription for your phone calls.
If you're interested in other ways that you can use AI to learn more about your customers, your phone calls and text messages with your customers are the richest sources of data that you're not yet using. To start using them, talk to our experts about using AI tools in your customer communications.
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