Once logged in to Stackchat, navigate to Bots in the left hand menu, select your Luma Bot and then hit the Integrations button on your bot menu. Now click the Manage button for the Stackchat Web Messenger.
You’ll then see this. Hit the + button next to the input on the Default Avatar URL field.
First download the below image to your computer:
Then upload it in the popup window in Stackchat Studio:
Finally, click Upload.
Now do the same for the Button Icon URL field (or just copy and paste the new URL from the previous field). Leave the other fields alone.
Select the Brand tab and upload the same image for the Business Icon URL field (or just copy and paste the URL from the previous field).
For the Brand Color and Conversation Color fields, use the value F3793B. For the Action Color field, use the value 26A9E0.
You should now have this:
Select the Initial Greetings tab and add this text to the first message field:
Ready to get started?
Then add this text to the first Quick Reply field:
Let’s go! 🚀
If you’re curious, open the bot builder, edit your CDML and perform a search for the term Let’s go! 🚀. You will see that it has been configured as a keyword on the Welcome flow. This is where Luma Bot will navigate users if they choose this quick reply.
Click Update Integration to save your changes.
After the save is complete, open the web messenger widget and preview the Luma branding that is now displayed!
However, you’ll see that the quick reply you configured in the Initial Greetings tab isn’t displayed. This is because it will only be seen by new users.
To test it out, click the Overview button from your bot menu then click the Share button in the top right.
Click the Copy Link button.
Then open a new incognito window and paste the URL you copied.
You should now see your quick reply initial greeting appear. Click it and see how your Luma Bot takes you to your Welcome flow.
Your web messenger is now ready to be embedded on your Luma demo site!
Go back to your Visual Studio Code editor.
Once open, navigate to the ./web-messenger folder.
Open a terminal (View -> Terminal).
Enter the command cd web-messenger and hit enter.
Run the command npm i to install the project dependencies.
Take a moment to explore the src folder of the project. Here is a breakdown of the two folders:
Before we build and test the project, the config needs to be updated with your bot’s App Id.
Go to Stackchat Studio, navigate to your Luma Bot and click Integrations on the bot menu. Click on the Manage button for Web Messenger.
In the Web Messenger screen, copy the App ID:
Now go back to Visual Studio Code, open the config file: src/messenger/config.ts and add your App ID value to the config object on line 4, making sure it’s a string, i.e in quotations:
appId: null, // Replace this null value with your Luma bot's App Id! e.g "k9s9xxxxxx"
In this example, the App ID is “ctduc8z4hn6x03”, so the updated line 4 should now look like this:
appId: "ctduc8z4hn6x03", // Replace this null value with your Luma bot's App Id! e.g "k9s9xxxxxx"
Save your changes in the config file. Now you’re ready to build and test your project. Bring up your terminal (View -> Terminal) and run the build command:
npm run build
The build should complete successfully:
Your project will now have a dist folder that has been generated by Webpack. It will contain a file called bundle.js. You’ll need to host this file in the next step so that it can be accessed by the demo website.
In order to get your Luma Bot on the demo site, you need to host your bundle.js file somewhere and make it publicly accessible. In Exercise 5.1 - Setup an AWS S3 bucket you’ve already set up an AWS bucket that we can leverage.
Log in to your to your AWS S3 account: https://console.aws.amazon.com/s3. Since you need this file to be publicly available, let’s create a new Bucket. Click Create Bucket.
Name the bucket aepmodule20LDAP, for example aepmodule20vangeluw and choose the region applicable to you.
Scroll down until you see Bucket settings for Block Public Access.
You should have a similar view now:
Scroll down and click Create Bucket.
Now your new Bucket is created, click it to open it.
You’ll then see this.
Click Upload. You’ll then see this:
Click Add Files, navigate to and then select your bundle.js file.
You now see this. Scroll down a but onto the Destination field and check the checkbox for I acknowledge that existing objects with the same name will be overwritten.
Scroll down and click Upload.
You’ll then see this. Click the filename bundle.js.
You should now be able to view the file’s overview details, including an Object URL. Copy this URL as you’ll need this in the next step. Click the Make Public button.
You’ve now successfully hosted your bundle.js file. In the next step, you’ll have to paste the Object URL in the Update Configuration ID screen.
To ensure the demo site loads your Luma chatbot, you’ll need to update your demo website configuration ID to include:
Go to https://public.aepdemo.net/admin_configuration_update.html page in a fresh, clean incognito window. You’ll then see this:
Enter your configuration ID and hit the Load Configuration button. You’ll then have this:
Scroll down until you see the fields EventID - Stackchat Journey and Stackchat Chatbot Tag.
Replace the EventID - Stackchat Journey value (which is empty) with your orchestration EventID that you created in Exercise 20.4.1 and replace the current Stackchat Chatbot Tag value with the Object URL of your hosted file bundle.js, which is the AWS S3 Object URL you created in the previous step.
Scroll down and click the Update Configuration ID button. You’re now ready to test!
Go to https://public.aepdemo.net/. Enter your Configuration ID and click Load Configuration. Then, select your LDAP and then select your brand. Select the brand Luma.
When you then reach the Luma homepage, you’ll see your chatbot being loaded and the icon will display in the bottom right part of the screen.
First, go to LOGIN/REGISTER, fill out your personal information and create a new account.
You’ll then see that the chatbot is using your first name in the call to action:
This can be achieved this by attaching user information to message metadata in the beforeSend delegate in the file helper.ts, so that the chatbot doesn’t have to ask for info we already know. You can learn more about message metadata here.
Open the chat widget and click Let’s go!.
You’ll then see this. Next, select the I need ideas menu item.
You’ll then see that Luma products are displayed inside the chatbot.
Next, hit the ❤️ button on a few products to generate product viewed events and to trigger your journey in Journey Orchestration.
A couple of seconds later, you should receive an email from Adobe Experience Platform and Journey Orchestration with a promotion for the item you just liked.
The next question in the chatbot is if you would mind giving feedback on your chat experience. Click Sure.
Make your choice, in this case the choice is Great.
Click Happy to!
Give your additional detailed feedback and click Send.
Finally, open your X-ray panel and click the refresh button. You’ll then see your product view appear in the X-ray panel.
Your web messenger chatbot is now working fine. Let’s now connect your chatbot to Facebook Messenger.