AI agents, especially voice AI agents are changing the entire landscape of customer service. Artificial intelligence has reached a point where AI conversations are becoming more realistic by the day. No wonder you see so many videos of AI surprising humans with its realism. But having a conversation with AI is only one side of the coin. The other is making that conversation actionable. That’s where call flows come in, because what good is an AI agent that confirms appointments but can’t create a calendar event for you? So let’s get into this guide.

What is an AI Call Flow, and Why Does it Matter?

Call flows by themselves are not a new idea. All competent contact centers have call flows for inbound and outbound calling that tell the agent what they need to say and do throughout a call. 

With an AI agent, this complexity needs to be factored in as well. Building in basic logic with a call flow is key to smooth conversation, quick resolutions, and in the case of Phonely; scheduling real-world tasks. Your AI agent much like your human agents needs to be prepared to handle responses and objections as they come. So nailing this is crucial!

Essential Elements of a High-Converting AI Call Flow

Businesses come in all shapes and sizes, and no one call flow is perfect for every business in that industry. But some key aspects remain the same. 

Clear and Concise Scripts

No caller wants to spend any more time than necessary on the phone. They want to accomplish something with the phone call, and your script needs to flow accordingly. The customer should be able to resolve as quickly and smoothly as possible. Earlier IVRs in conjunction with agent call scripts did this task. They got the caller to the right department, and from there the agent followed a curated script that asked the right follow-up questions. This helped the caller get to the right resolution, fast. 

AI call scripts are also similar, but in this case, we are trying to automate the resolution process without human involvement, so clarity and conciseness are even more important. Especially if you intend to use AI customer support full-time. This means creating a script that factors in all possible scenarios that a call will be about and then building an AI call flow to tackle that. In Phonely we use workflows for this, each workflow in an AI agent is catered to handle a few specific types of inquiries. A call flow, or in this case a workflow takes the caller through key steps of the call. It starts with a “How can I help you?” question which then asks additional questions based on the nature of the request. 

If you are building a call flow, a good idea would be to start by planning around the types of calls you receive. For example, a contractor can receive a call for only a few sets of things, appointments, estimates, and complaints. A call flow for each, and you already have a winner on your hands.

Contextual Understanding

The biggest fear that people have with AI is that it will be too robotic. But I am here to put those feelings to rest. AI is good at understanding context, some of it is intuitive, and some of it needs to be built within the call flow. 

Let’s take our contractor example further. So let’s say an old customer calls in to schedule an appointment. You don’t need to go through the same set of questions as you would for any other appointment. You likely have their data on file, just needs to be looked up. And that’s where AI, automation tools, and APIs join forces to define context. With a simple question like “Are you a new or existing customer”; you can send callers down a different call path. Which in the case of existing customers means that they don’t need to provide all their details again. This speeds up the time it takes to schedule an appointment without a single human in the chain. Thereby cutting on lookup time. With near-instant access to your database or CRM, the AI can book someone in for a service quicker than a human would.

When planning your call flows see where data can help provide context to the caller’s request. With added context, you speed up resolution time which ultimately saves time for both you and your customers. 

Intelligent Routing

We are an AI-first business that creates tools for customer service but we understand that good experiences lie at the intersection of AI and human support. Some humans don’t like to engage with AI agents, others sometimes have queries that the AI can’t resolve (issuing refunds, handling loss or tragedy) in that case intelligent routing is key.

When building a call flow you need to anticipate some of these requests, and have those types of calls transferred to a live agent. This ensures that only the most complex issues make their way to the agents, allowing you to do more with fewer agents. Intelligent routing based on specific conditions is a key part of any call flow, and you should know how this must be handled.

Step-by-Step Guide to Designing an Effective AI Call Flow

Let’s get into the granular steps of building an AI call flow. It's very much like building a customer handling system in a contact center, but here it's all automated.

1. Define Clear Objectives: Start by understanding why you wish to build an AI agent in the first place. Is it for customer support, are you trying to qualify leads or simply re-engaging old ones? This will help you align all the information required to accomplish that one goal. You can have multiple goals as well, but then be crystal clear on what those are. Think of it this way, customer support needs FAQs but lead qualification needs objection handling. Both are types of information, but you need to know the goal, so you can set the AI to do exactly that. 

2. Map the Customer Journey: With the goal squared away, you map the customer journey. This means how the customer will flow through the conversation. This includes mapping the request types first, like customer service requests, accounting, or tech support. This would help you create flows for each possible category.

3. Designing the Conversation Paths: Now the fun part, designing the conversation paths. Each query type will have some specific questions and nuance required by your AI agent to accurately assist the caller. This means changing the responses based on the caller’s answer and then taking certain actions like finding a record in the CRM or pulling order status from the Shipping website. Think of these intuitively and based on the calls you’ve received in the past. If you don’t want to do that, we have premade workflow templates that have this process pre-done for you. You just need to modify them to your use case. We will cover this in a different blog post soon!

4. Integrate Personalization: Next is personalization, which is a key value add in AI-based systems. Using Caller ID an AI agent can already recognize numbers in your CRM, answer calls with the caller’s name, and guide them based on their preferences. This takes out a lot of friction from the calls making resolutions faster. This is the step that ensures that you save time and money in the long run. While the setup on this may be a little longer, it's worth the time. 

5. Test and Iterate: Creating an AI agent is an iterative process. As you build one out, you will need to test and validate the conversation, the integrations, and the overall conversation quality. With a good operational base, you will be able to launch your AI agent and iterate further based on customer interactions and feedback. Small changes over time can help you build an exceptional call flow that can handle a significant volume of customer calls.
   
   In the Phonely dashboard, you can test your agents over a web call, so build, test, build, test, GO LIVE.

Common Mistakes to Avoid

AI as a technology is quite ripe, and the agents created as a result are extremely competent but there are certain pitfalls that you must keep in mind when designing your call flows. Here’s what to look out for: 

1. Overcomplicating call menus or options: With an AI toolkit it's easy to complicate call flows, trying to anchor the agent down as much as possible making the system clunky and robotic. Remember, when it feels like it's too complicated, it likely is. Call flows should be simple prompt-based instructions with diversions in key decision-making areas. New-age LLMs are more than capable of handling problems with just a little bit of logic in place. 

2. Ignoring conversational nuance and sounding robotic: This brings us to the next point. The goal of AI systems is to be indistinguishable, and even surpass human agents. So you don’t want your scripts to be impersonal and robotic. Try to keep the flow natural and relevant without anchoring it down. “May I please know your age” and “May I know how old you are” don’t make much of a difference. So don’t try to force an output unless necessary.

3. Failing to integrate customer context: Integrations make a big difference to how calls are handled and the overall experience of the customer. Early on, this may not seem necessary but having a fully integrated system eventually should be the goal. That’s AI agents answering calls, providing resolutions, and updating call and customer status in your CRM or Calendar. That’s the only way to maximize the value of a system like this.

4. Neglecting continuous testing and optimization: AI agents at first glance may seem like set-and-forget systems, and while they largely are, as your business evolves, your agent needs to grow with it. Customer queries will change, responses will change and you need to monitor this agent a regular intervals. Like any employee, these agents need training and attention, just not as hands-on. Just make sure that you listen in on a few calls from time to time, and give your agent the most current information possible. 

Measuring Success and Optimizing Your AI Call Flow

That brings us to measuring the success of an AI call flow, and your overall agent performance. It's very similar to how you’d review all your human agents, but the optimization part after will be handled once. 

Monitoring KPIs

Keep an eye on your KPIs like conversion rates, first-call resolution rates, and customer satisfaction levels. With initial testing aside, these will help gauge the real-world performance of your agent. Additionally track call outcomes and sentiment. These KPIs will inform changes that you may need to make to your AI agent. Check out our comprehensive guide on Contact Center KPIs. These will apply to your AI agent as well.

Tools and Methods to Analyze Call Flow Performance 

A lot of the same call-monitoring tools used in contact centers can also gauge the quality of your calls. Software for speech analytics and call transcription is a great place to start. But we also have a bunch of nifty tools inside your Phonely dashboard to make it much simpler to monitor calls and call outcomes. Phonely can track the number of calls, the overall sentiment on those calls, and the resulting outcomes. If you want to dig deeper, you even have transcripts and call recordings to verify customer sentiment. And if that’s not your style, we can respect that. Just use the post-call actions or API connections to see your metrics in a dashboard of your choice.

Points for Refinement

With the KPIs and call data you will see points of refinement within the call flow. Points where the script is a bit confusing, or the logic is not as sound, leading to incorrect routing in certain cases; then take note of that. You can then go into your call flow and make the necessary changes to ensure a seamless flow. Another key consideration is the voice. A lot of people ignore the agent's voice and its effect on the caller. So make sure that you use a good voice, and cycle through them till you find the perfect one!

Conclusion

A well-crafted call flow has been a mainstay at many contact centers, and the same applies to AI agents as well. With AI, that level of finesse and scale is now way more accessible. Take this as an opportunity to scale up your operations and cut costs in the process. It may feel a little daunting at the start, but with a good plan in place, you will be able to create a call flow that works for your business. The best move is to get started right away, test, and iterate as you build your agent out. We recognize that it can be challenging, and that’s why we have a help center that helps you create a call flow on Phonely, helping you take advantage of this. The tech’s ready. The tools are here. You in?