Just like a good sales person, a good chatbot should be aware of the context to deliver valuable experiences.
Many chatbots today fail to deliver valuable conversations because they lack context. Context means being aware of what’s going on around the conversation, something that humans are very good at.
Like a good salesperson or customer service representative, a good chatbot should be aware of the context to deliver a valuable experience. A chatbot should offer its users, just like a good sales manager, the right information at the right time. Or even contacting them proactively by initiating a conversation at the right time!
In this guide, we will show you how you can use existing data to create context for your bot so that it will be able to deliver valuable and personal experiences.
You can use different types of existing data to create context:
- Page information
- User Input
- Profile information
- Channel information
Existing data
You can use existing data to create context from several sources. We've list 4 common sources:
1. Page information
2. User input
The input of the user can be extracted for several workflows. You might want to create a ticket in your CRM, send an e-mail with the extracted data, request the status of an order or simply use the extracted data in your chatbot to personalize the experience.
Read more about extracting data in our article about Capturing and Extracting Data
3. Profile Information
When using messaging channels like WhatsApp or Facebook Messenger you will receive information of the user, just like when a friend calls you on your phone. You'll probably pick up in a different way when you don't know the user that's calling you. Why not let your bot do the same thing?
{{user.name}} //- name of the user
{{user.profile.firstName}} //- first name of the user
{{user.profile.lastName}} //- Last name of the user
{{user.profile.fullName}} //- first and last name combined
{{user.profile.picture}} //- profile picture
{{user.profile.locale}} //- user language
{{user.profile.gender}} //- user gender
Things starting to get fun when you use the available profile picture in combination with Machine Learning to detect age, gender, hair color to follow up with different flows.
4. Channel related
This one is a bit different from the three above as it's not really a data point where we extract data from but still we can use different channels to create unique customer journeys. Some channels are considered "richer" than others, meaning that they allow more types of messages.
The Web Widget and Facebook Messenger are considered as very rich while WhatsApp is a bit more limited. You can check which channel is using to deliver the richest reply possible on that channel. Read more at our article Channel specific flows.
