Receive product information automatically via Facebook Messenger

This tutorial shows you how to provide a user with relevant product information automatically via Facebook Messenger.

In this use case the user greets the company via the company's Facebook Page. A message is automatically sent back to the user. Using keyword matching the user can receive tailored product and service information.

NOTE: This tutorial assumes you have already created a Facebook Profile and a Facebook Page.

Source code

The source code for this project is available in the Nexmo Community GitHub repository.


  1. Create a Nexmo Account
  2. Install Node JS - required for using the Nexmo Command Line Interface (CLI).
  3. Install the Beta version of the Nexmo CLI
  4. Know how to test your webhook server locally
  5. Python 3 installed
  6. Flask installed

The steps

After the prerequisites have been met, the steps are as follows:

  1. Create a Nexmo Application
  2. Generate a JWT
  3. Link your Facebook Page to Nexmo
  4. Link your Nexmo application to your Facebook page
  5. Get Ngrok up and running
  6. Write your basic application
  7. Interact with your Facebook Page
  8. Minimal client for sending Facebook Messenger messages using Python
  9. The use case revisited
  10. A simple implementation

There are various ways you can achieve the same result with Nexmo. This tutorial shows only one specific way to do things, for example you will see how to use the command line to create the application, rather than the Dashboard. Other tutorials demonstrate other ways of doing things.

Create your Nexmo Application

If you have not yet done so, create a new directory for your project, such as fbm-app. Change into this directory.

Use the CLI to create your Nexmo application:

nexmo app:create "FBM App" --keyfile=private.key --type=messages

Make a note of the generated Application ID. You can also check this in the Nexmo Dashboard.

This command will also create a private key, private.key in your current directory.

This command also sets the two webhooks that need to be set. All interaction between your App and Nexmo takes place through these webhooks. You must at least acknowledge each of these webhooks in your app.

Generate a JWT

You will need to generate a JWT to validate the linking of your Facebook Page to your Nexmo account. You can skip this step if you have already linked your Facebook Page to your Nexmo account.

In the following command make sure you paste in the Application ID of the Nexmo application you just created:

JWT="$(nexmo jwt:generate ./private.key application_id=YOUR_APP_ID)"

Note the default expiry time for the JWT is 15 minutes.

Type the following command to echo your JWT:

echo $JWT

Copy the JWT to the clipboard. You will use it in linking your Facebook Page to your Nexmo account.

To link your Facebook Page to your Nexmo account navigate to the following page:

Select the Facebook Page you want to link to your account from the dropdown list.

Paste the JWT you copied to your clipboard earlier into the JWT Token field and click Subscribe. You receive a message confirming the page is now linked to your account.

Go into the Nexmo Dashboard and check your Nexmo application is listed.

Click on your app and then click the External Accounts tab. Facebook Pages that you've linked to your Nexmo account are listed. Click the Link button to link your application to the desired Facebook Page.

At this point you have the preparatory work completed. You now have a Nexmo app and your Facebook Page connected to your Nexmo account, and your app linked to your Facebook Page. In subsequent sections you will write the code for your application.

Get Ngrok up and running

Make sure you have Ngrok running for testing locally. To start Ngrok type:

ngrok http 9000

To generate a temporary Ngrok URL. If you are a paid subscriber you could type:

ngrok http 9000 -subdomain=your_domain

Note in this case Ngrok will divert the Nexmo webhooks you specified when you created your Nexmo application to localhost:9000.

Write your basic application

So in the simplest case your application would look like the following:

from flask import Flask, request, jsonify
from pprint import pprint

app = Flask(__name__)

@app.route('/inbound', methods=['POST'])
def inbound_message():
    data = request.get_json()
    return ("200")

@app.route('/status', methods=['POST'])
def message_status():
    data = request.get_json()
    return ("200")

if __name__ == '__main__':"localhost", port=9000)

Add this code to a file called and save it.

Run it locally with:


Your base application is now up and running and ready to log events.

Interact with your Facebook Page

Now that your base app is up and running, you can send a message to your Facebook Page and then check that the message is logged. So, if you send a basic message to your Facebook Page using Messenger you will see logging such as the following:

{'direction': 'inbound',
 'from': {'id': '1234567890123456', 'type': 'messenger'},
 'message': {'content': {'text': 'Hello Mr. Cat', 'type': 'text'}},
 'message_uuid': 'da13a7b0-307c-4029-bbcd-ec2a391873de',
 'timestamp': '2019-04-09T12:26:47.242Z',
 'to': {'id': '543210987654321', 'type': 'messenger'}} - - [09/Apr/2019 13:26:58] "POST /inbound HTTP/1.1" 200 -

There is some important information here which you can use to build out your application to make it more useful.

Field Description
from The Facebook ID of the person sending a message to your page.
to The Facebook ID of your page (the page the person is sending a message to).
message The message being sent.

You can see that the message is a JSON object. You can extract the message text from this object.

Note that it is useful to record both the Facebook ID of your page (which you might not have known), and the Facebook ID of the user sending you a message. Note the Facebook ID is especially useful if your application is handling multiple Facebook Pages.

Minimal client for sending Facebook Messenger messages using Python

Currently Nexmo does not officially support Messages and Dispatch API in the Python client library, but our REST API is fully supported and the Python code is provided in the project for you in a reusable class. As the code is provided we will not cover it further in this tutorial.

The use case revisited

It's time to look into this use case in more detail so you can more effectively build out your application.

Imagine a user messages your Facebook Page via Messenger with a message such as "Hi". However, due to time zones you are not available to respond to the message - this may leave the user feeling dejected. On the other hand it would be great if you could automatically respond with useful information. For example, to a message such as "Hi" you might respond with "Welcome to T's Cat Supplies. Here are our main product categories: toys, food, medicine, bling."

Using a Python construct such as if keyword in msg you can detect keywords and send material based on that. For example, if a user sends in a message like "Hi my tanks need sorting" you might detect the word tank and send information on your tank cleaning services. Or if you receive a message such as "Hi, I think I need a crane to lift our pipeline sections." You could send information on your crane hire services. Where keywords are not detected it is a simple matter to send a generic message back to the user to help orientate them.

This auto-response feature is useful as some companies have hundreds of products and services.

Another feature that is useful is the ability to switch auto-response off, perhaps to deal directly with a human. You could build in commands such as auto: off and auto: on to control how your customer interacts with your Facebook Page.

In the following sections you will see how to implement this use case.

A simple implementation

One of the useful data structures in implementing this use case is the Python dictionary. You can see an example here:

cats_dict = {
    'other': 'Our products: toys, food, meds, and bling',
    'toys': 'More info on cat toys here',
    'food': 'More info on cat food here',
    'meds': 'More info on cat meds here',
    'bling': 'More info on cat bling here'

To put this into perspective review the following code:

class ProductMatcher:

    auto_mode = True

    cats_dict = {
        'other': 'Our products: toys, food, meds, and bling',
        'toys': 'More info on cat toys here',
        'food': 'More info on cat food here',
        'meds': 'More info on cat meds here',
        'bling': 'More info on cat bling here'


    def product_matcher(self, fb_sender, user, msg):
        product = 'other'
        msg = msg.lower().strip()
        if self.auto_mode:
            if "auto: off" in msg:
                self.auto_mode = False
                self.fbm.send_message(fb_sender, user, "Auto mode is off")
            for k in self.cats_dict.keys():
                if k in msg:
                    product = k
            self.fbm.send_message(fb_sender, user, self.cats_dict[product])
        if "auto: on" in msg:
                self.auto_mode = True
                self.fbm.send_message(fb_sender, user, "Auto mode is on")
        return product

If the user sends a message via Messenger, and there's no human to respond, a simple menu is sent back to the user. In the user's message the product is extracted and the appropriate message sent. Of course this code takes a naive approach, but hopefully it indicates the potential.

You might be wondering would this get annoying for the user if they want to talk to a real person? However, the auto-respond could be disabled once you are online and able to take messages. The code allows the user to use the commands auto: off and auto: on to control interaction. This could also be controlled by the channel manager.

In the above code the product the user is interested in is also returned. This could be used if, for example, you wanted to log the user and their product choice to a database. You could also look up a user in the database to find out if they are a new customer or they have had dealings with the company before.


In this tutorial you have seen a use case where the user can receive product information automatically via Facebook Messenger. This was based around simple keyword matching. The user also had the ability to toggle auto-response mode as required.

Further resources