Happy new year everyone!
Hope you’re well-rested after the holidays.
Today, we’re talking to Xavier Herce about a multilingual lead qualification system he built using WhatsApp Business and Make.
Come give it a read!
If there’s one app that’s truly revolutionized the way we communicate with each other, it has to be WhatsApp.
Who could have predicted back in 2009 that this little app designed to keep us in touch with loved ones would mean big things for small businesses, too?
WhatsApp Business helps companies streamline and enhance the way they provide customer support and interaction, but despite its utility, this platform can present a few bottlenecks.
Xavier Herce of Nemeda Limited developed a solution for a client that was struggling with a language barrier in the lead qualification process.
With hundreds of WhatsApp conversations every month from across the globe, they needed a way to communicate with customers in their own languages, and in real-time.
Turns out, like many great Make solutions, it all starts with a webhook.
Read on to learn how this clever solution increases engagement rates by as much as 80%.
What problem were you trying to solve with your automation?
Streamline the process of lead qualifications through WhatsApp Business in different languages and with voice message transcription.
Why did the problem exist?
In an omnichannel world, we need to serve a way to respond to our leads and prospects through all available channels
How did you solve the problem? What does your solution look like?
This is what the process looks like:
- A webhook fires to WhatsApp Business when there’s a contact.
- Verification of whether it is an image, text, or voice (we invite the customer to use text).
- Google API is used to detect language.
- The customer is informed in their own language of the solution or project they want to explore.
- This information is recorded in Airtable and classified by type of message based on a database of possible responses in Airtable.
- The location, device, and type of service get stored.
- The whole process is finished with a call to action.
What did your solution achieve?
- generating a pipeline of classified leads
- management of voice and text responses
- frictionless prioritization
- communication in any language supported by google translate