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How Calen.ai Won a Google Award for a Chatbot Built With Make

Jun 16, 2021 | 4 minutes
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Appointment scheduling software is a different kind of beast in the realm of digital infrastructure, and figuring out the best options is hard, to say the least. 

The first thing to understand about digital appointments is that different people will go through different channels to get one.  

Some will gladly click on a Calendly link shared via email and snatch a slot in a calendar. 

Others will hit the “Book now” button on a Facebook page, and pick it up from there.

Then, there will be those who will interact with a chatbot on a website to schedule an appointment when given the chance.

In any case, it’s safe to say that providing multiple touchpoints is instrumental to cover the whole spectrum of your audience - and here exactly is where trouble begins, as the quality of each solution can vary greatly. 

Yes, Calendly does an excellent job in getting appointments lined up through the share of a link. But what happens when you need a chatbot on the side to address colder audiences? 

Calen.ai understood this challenge from the get-go and took on the mission to automate all those appointment booking conversations that eat away time every day. 

In this case study, we’ll take a look at their journey, and show you how they used Make to build an appointment funnel solution that got them recognized by Google in the 2021 Build an Agent Contest.

Hop on!  

Improving response times while saving resources

Calen.ai focused on two problems. 

The first one is related to response times. Customers expect to receive personalized replies almost immediately after interacting with support, but this is something most companies simply can’t tackle.  

The average response time hovers around the 12-hour mark, with 62% of companies never responding at all

The second issue has to do with resources spent on repetitive conversations and manual data entry tasks.

Car dealerships, law firms, medical offices, and other businesses that rely on appointments lose a lot of time on them. 

For Calen.ai, this represented an opportunity to relieve companies from the repetitive appointment setting tasks, and also from the need to manually move data between the involved systems. 

Towards frictionless, speedy appointments

The faster a company replies, the higher the chance a prospect converts. 

Even when prospects come across the perfect deal, there is a natural resistance to filling out a form with their data, for example. 

They want to learn more, gain trust, and be guided toward their next decision. 

The traditional way to solve this contingency is to appoint a sales representative to deal with the intricacies of the initial interactions.

Taking into account how time-consuming and unscalable this is, many companies turned to scripted chatbots, but these rarely hit the mark when it comes to actual conversations. 

Humans don’t always talk in a linear fashion, and bots don’t follow the user in a human-like way. 

Taking all these factors into account, Calen.ai turned to conversational AI technology. 

Unlike more primitive chatbots, this technology handles interruptions in the flow, making for a natural progression of the conversation. It also guides users towards converting, just like how an efficient sales rep would. 

This solved the problems of response times and resource allocation, but the path towards attaining a conversational chatbot was dotted with roadblocks and dead-ends.

When custom code is not the answer

Initially, Calen.ai decided to do what felt “natural” to them: code their way towards a solution.

For months, a team of developers worked on the project, but the result didn’t turn out as expected. 

They rotated the team and started the process all over again. Unfortunately, the outcome was the same. 

The high costs of development and unpredictability of the result led Calen.ai to start looking into less-traveled roads. 

And here’s where Make entered the chat.

Speak softly, and carry a great tool

After careful evaluation, Calen.ai picked Make to build their entire application. 

Rather than using Make to automate internal processes, the company took a swing at building apps for their customers - and it worked. 

With Make under the hood, every user request is processed and provided with relevant responses, all while accomplishing key tasks like: 

  • Getting the user’s contact data (name, phone number)

  • Confirming date and time of appointments

  • Setting up the appointments

 https://www.youtube.com/watch?v=9g1h3_xw3tg 

After the initial success, they iterated their first conversational chatbot to work in multiple platforms, including SMS, Facebook Messenger, Telegram, and other texting apps.

Make connects several apps together to create conversational flows, but also to move data into relevant systems (CRMs), create appointments (Google Calendar), and send reminders and notifications to the customer when the appointment is near. 

Below you can see the flow that won them Google’s recognition. As you can see, it’s a complex integration between several apps, and yet, an easier (and more affordable) solution than creating and shipping custom code. 

How automation positively impacted Calen.ai’s business

Leaning on Make, Calen.ai has developed chatbot solutions for over 100 businesses across several industries, including:

  • Car dealerships: to automate test drive bookings and handle up to 75% of routine conversations

  • Medical practices: to filter through routine conversations and let urgent cases pass-through

  • Dental clinics: to automate SMS campaigns for 20+ clinics in 5 countries

In the words of Irakli Beselidze, the company’s founder:

“We automate conversations. We don’t use Make to automate our internal processes but rather to build applications for our clients. We don’t have coders and developers in our team and that is a huge resource saver.”

As a result, clients receive a fully customized solution that can be expanded and adjusted when needed. This allows for a deeper focus on communication and marketing rather than burning through cash on tasks that require dedicated coders.

Conclusion

Using Make, Calen.ai is able to onboard clients fast and deliver a sophisticated solution for appointments, scheduling, and support.  

We hope this case study gave you a spark of inspiration as to what is possible. If you are up for more inspiring stories that display the power of Make, we invite you to read our featured use cases. Once you get started, it’ll be a one-way road towards better processes and products. 

Happy automating!

senior-content-writer-saas

Martin Etchegaray

Senior Content Writer and Editor at Make. I enjoy writing and reading about history, science, and tech.

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