Automate a Sales Meeting Request with AI Missions

What if your AI assistant could handle leads just like your best sales rep? Asking the right questions, gathering key details, and guiding them to the next step automatically. Stick around because today I'll show you how to set that up with AI missions and conversation properties. All right. All right. This is where your AI assistant stops being just a chatbot and becomes a real sales asset. To do this, we will define the mission goal. the AI's playbook and set up properties to guide it. Let's dive in. Okay, now we already added a six in for this kind of chat flow. You can go to plus and you will find if you scroll down a template to to manage sales demos.

Okay, when you click it, this will open up and as you can see over here, this is a triggered event of type of AI recognized intent is going to trigger onto anyone and the name is sales meeting and of course there would be a few descriptions and examples. So whenever a lead want to speak with a sales rep and this might be the kind of variation they will be aware of. Now we are going into mission mode. So here what you would do is as you would train your SDR to ask the questions that you would do in order to qualify them. So for example here we've been asking gather sales information from the lead that are important to understand if they qualify for a sales meeting.

Now this is prompt engineering. Okay. So this has been covered in the very first module and if you haven't watched the video I suggest you to go back and watch the video on how conversational AI works. But basically this is the way you prompt the AI to do a very specific task. This is the prompting that you're doing with your AI to achieve a very specific goal. So Aura over here gets into this mission and start asking them their work emails and of course you can provide more details. for example do not accept free emails if someone is providing their Gmail account then or I will say no I would need a work email for this reason and of course here we're asking company sites whatever fits you the best so you need to describe to the prompting what you're expecting to collect and then of course you can

do way much more you can prompt the AI to extract the domain from the work email and store it in the domain attributes okay now we'll talk about it later how you can uh fit the conversation properties and store them or pass it to any different solutions. Okay, but here's the great things about mission goals. It can also provide logic to your prompt. Basically over here for sales purposes let's say you want to focus only on people that got a budget that is more than 10k or that handle more than uh 2,000 tickets a month then redirect them to this page otherwise they can watch a live demo over here now this would be the prompting and you can also prompt aura to complete the mission over here saying our sales team will be reached out to you and that would be it.

So how the mission goal collaborate with the properties. Now we ask the AI to gather this information. Okay. Now you can also not have the properties of course and this will be just ask to the customer and that would be it. If you define the type of the properties as text or if say for example you accept only specific values you can do so. And this description is actually very important to give the AI the context of what to expect from that kind of value. Okay. So this will be matched easily whenever you know the aurora is asking for that kind of information. And as you can see over here we saved a lot of different information in the conversation properties.

Let's try this out shall we? So let's save this. As you can see, whenever the AI mission is being completed, so Ara collected all the data for you at the success, she's going to pass this data to a rested, which means that basically you can connect Slack to send a message with the new lead with the information she gathered and send it to a very specific channel. Now you can create any integration you want and pass this information to pipe drives appspot or Salesforce whatever CRM are you using right now. So basically you're polishing up a new conversation that is coming through the chat with the information you might need and pass it to the sales team whenever is ready to be passed.

Okay. Now we need to assign this to sales for example because of course all this intent is uh about sales. It's either a success or failure of this call or there is an escalation for the animation everything will be assigned to the sales team. So now we can publish this chat flow. And if we go back to our tri page, let's try to open a new conversation asking I want to pick with a sales agent says right. Now if we go to our inboxes, this has already triggered the sales automator. Now she's going into intent mode again. Okay. She's going to ask the questions that she's prompted for.

Okay. So, as you can see, could you tell me your company size and your role? So, let's continue this conversation, shall we? Uh, we are team of 10 people. Actually, let's let's write it in a dumb way. Okay, I'll show you the power of this. And, um, company size on my role, the co-ounder. That's it. Now she's going to check against her mission again and see if there's something missing that I didn't tell her. And as you can see, she's asking, "How many support tickets do you handle per month or what's the budget for automating them with AI?" Now, I handle roughly 10k a month.

Now, I'm not sharing the budget yet. Okay? Something that of course that that's something uh usual that happened. Now, she's asking again, what's the budget to automating these support tickets? If I say 5K a month, I'm really dumb over here, but I'll show you how that will translate into proper data that Cora is collecting for you. Here we go. As you can see, she provided book sales because if we go back to the conversation and also she started that API request, send a message to Slack with all the information. And if you can see, she shared the actual data. Okay, the email wasn't asked because the user already had an email on file on customary.

So there wasn't a need for such a thing because she already had the context of the user email and the username for example. But if I was a lead, she were going to ask that as well. So if you scroll down, you will be able to see conversation properties. Now remember I put down 10 people and she provided that information in such a way that now can be stored as a number. Now ro is co-founder and put it down there. Montific volume 10k and again it's a number. Meeting reason uh now this is a fairly um stupid reason but probably the mission wasn't there and budget is 5k.

Now, if we go back to the sales automator chat flow, we'll see that the logic brought her to send her to the book demo rather than going to the live demo. Why? Because well, it's handing more than 2,000 tickets a month even though the budget is uh lesser than 10k. So, this logic actually worked and this handled perfectly the conversation uh with this with this person. Now some of the inquiries will already have a lot of information at the first message. Okay. So if I start the information already requested by the AI mission such as either we have a we are a company of 50 people and we are looking to replace Zesk.

We manage 40,000 tickets a month and I want to understand with your sales team what could be the price for managing AI. Now this is a different message but still this will trigger the sales meeting. Okay, if we go over here we'll see what Ora would do. Again she triggered the sales automator. Now she already got all that piece of information right the kind of information she was prompt to access to ask in this case she already managed to extract that information from the very first message rather than asking again as a traditional chatbot would do okay now she's asking what is missing and that's right because some of the things that you can do is re requiring those property to be required so if something is important for you you can mark them as required and Orura will continuously ask for that information in a polite way of

course until he gets it. Okay, this is simple enough to set it up and it's crazy good to streamline processes and in this case a sales meeting, but it can do way way much more. Once you learn how to prompt your AI missions goal, you understand how Aura and the AI assistant works. You can actually gather more information and achieve almost 80% of your incoming support tickets completely automated. I'm not kidding. With the mix of REST API, intents, missions, and REST APIs, this will be mindblowing once you see all of this in action. Aura uses the mission goal and properties to deliver a seamless professional experience while collecting structured data your team can act on.

Now it's your turn. Define the mission goal. Set up your properties with descriptions and validation rules and let Aura do the heavy lifting for you. Got any questions or ideas? Drop them in the comment below. I can't wait to see how you use this to transform your sales processes. See you in the next lesson.