Post Syndicated from Murat Balkan original https://aws.amazon.com/blogs/messaging-and-targeting/create-a-serverless-feedback-collector-application-by-using-amazon-pinpoints-two-way-sms-functionality/

Introduction

Two-way SMS communication is used by many companies to create interactive engagements with their customers. Traditional SMS notifications are one-way. While this is valid for many different use cases like one-time passwords (OTP) notifications and security notifications or reminders, some other use-cases may benefit from collecting information from the same channel. Two-way SMS allows customers to create this feedback mechanism and enhance business interactions and overall customer experience.

SMS is chosen for its simplicity and availability across different sets of devices. By combining the two-way SMS mechanism with the vast breadth of services Amazon Web Services (AWS) offers, companies can create effective architectures to better interact and serve their customers.

This blog post shows you how a serverless online appointment application can use Amazon Pinpoint’s two-way SMS functionality to collect customer feedback for completed appointments. You will learn how Amazon Pinpoint interacts with other AWS serverless services with its out-of-the-box integrations to create a scalable messaging application.

Architecture

By completing the steps in this post, you can create a system that uses the architecture illustrated in the following image:

The flow of events starts when a Amazon DynamoDB table item, representing an online appointment, changes its status to COMPLETED. An AWS Lambda function which is subscribed to these changes over DynamoDB Streams detects this change and sends an SMS to the customer by using Amazon Pinpoint API’s sendMessages operation.

Amazon Pinpoint delivers the SMS to the recipient and generates a unique message ID to the AWS Lambda function. The Lambda function then adds this message ID to a DynamoDB table called “message-lookup”. This table is used for tracking different feedback requests sent during a multi-step conversation and associate them with the appointment ids. At this stage, the Lambda function also populates another table “feedbacks” which will hold the feedback responses that will be sent as SMS reply messages.

Each time a recipient replies to an SMS, Amazon Pinpoint publishes this reply event to an Amazon SNS topic which is subscribed by an Amazon SQS queue. Amazon Pinpoint will also add a messageId to this event which allows you to bind it to a sendMessages operation call.

A second AWS Lambda function polls these reply events from the Amazon SQS queue. It checks whether the reply is in the correct format (i.e. a number) and also associated with a previous request. If all conditions are met, the AWS Lambda function checks the ConversationStage attribute’s value from its message-lookup table. According to the current stage and the SMS answer received, AWS Lambda function will determine the next step.

For example, if the feedback score received is less than 5, a follow-up SMS is sent to the user asking if they’ll be happy to receive a call from the customer support team.

All SMS replies from the users are reflected to “feedbacks” table for further analysis.

Deploying the Sample Application

1. Clone this GitHub repository to your local machine and install and configure AWS SAM with a test AWS IAM user.

You will use AWS SAM to deploy the remaining parts of this serverless architecture.

The AWS SAM template creates the following resources:

• • An Amazon DynamoDB table (appointments) that contains information about appointments, customers and their appointment status.
  • An Amazon DynamoDB table (feedbacks) that holds the received feedbacks from customers.
  • An Amazon DynamoDB table (message-lookup) that holds the Amazon Pinpoint message ids and associate them to appointments to track a multi-step conversation.
  • Two AWS Lambda functions (FeedbackSender and FeedbackReceiver)
  • An Amazon SNS topic that collects state change events from Amazon Pinpoint.
  • An Amazon SQS queue that queues the incoming messages.
  • An Amazon Pinpoint Application with an associated SMS channel.

This architecture consists of two Lambda functions, which are represented as two different apps in the AWS SAM template. These functions are named FeedbackSender and FeedbackReceiver. The FeedbackSender function listens the Amazon DynamoDB Stream associated with the appointments table and sends the SMS message requesting a feedback. Second Lambda function, FeedbackReceiver, polls the Amazon SQS queue and updates the feedbacks table in Amazon DynamoDB. (pinpoint-two-way-sms)

          Note: You’ll incur some costs by deploying this stack into your account.

2. To start the SAM deployment, navigate to the root directory of the repository you downloaded and where the template.yaml AWS SAM template resides. AWS SAM also requires you to specify an Amazon Simple Storage Service (Amazon S3) bucket to hold the deployment artifacts. If you haven’t already created a bucket for this purpose, create one now. The bucket should have read and write access by an AWS Identity and Access Management (IAM) user.

At the command line, enter the following command to package the application:

sam package --template template.yaml --output-template-file output_template.yaml --s3-bucket BUCKET_NAME_HERE

In the preceding command, replace BUCKET_NAME_HERE with the name of the Amazon S3 bucket that should hold the deployment artifacts.

AWS SAM packages the application and copies it into this Amazon S3 bucket.

When the AWS SAM package command finishes running, enter the following command to deploy the package:

sam deploy --template-file output_template.yaml --stack-name BlogStackPinpoint --capabilities CAPABILITY_IAM

When you run this command, AWS SAM shows the progress of the deployment. When the deployment finishes, navigate to the Amazon Pinpoint console and choose the project named “BlogApplication”. This example uses “BlogStackPinpoint” as the stack name, you can change this to any other name you want.

3. From the left navigation, choose Settings, SMS and voice. On the SMS and voice settings page, choose the Request phone number button under Number settings

4. Choose a target country. Set the Default message type as Transactional, and click on the Request long codes button to buy a long code.

Note: In United States, you can also request a Toll Free Number(TFN)

A long code will be added to the Number settings list.

5. Choose the newly added number to reach the SMS Settings page and enable the option Enable two-way-SMS. At the Incoming messages destination, select Choose an existing SNS topic, and from the drop down select the Amazon SNS topic that was created by the BlogStackPinpoint stack.

Choose Save to save your SMS settings.

 

Testing the Sample Application

Now that the application is deployed and configured, test it by creating sample records in the Amazon DynamoDB table. Navigate to Amazon DynamoDB console and reach the tables view. Inspect the tables that were created by the AWS SAM application.

Here, appointments table is the table where the appointments and their statuses are kept. It tracks the appointment lifecycle events with items identified by unique ids. In this sample scenario, we are assuming that an appointment application creates a record with ‘CREATED’ status when a new appointment is planned. After the appointment is finished, same application updates the status to ‘COMPLETED’ which will trigger the feedback collection process. Feedback results are collected in the feedbacks table. Amazon Pinpoint message id’s, conversation stage and appointment id’s are kept in the message-lookup table.

1. To start testing the end-to-end flow, choose the appointments table to open table overview page.
2. Next, select the Items tab and choose the Create item From the dropdown, select Text. Add the following and choose Save to create your first appointment object. While adding the following object, replace CustomerPhone attribute’s value with a phone number you own. The feedback request messages will be delivered to that number. Note: This number should match the country number for the long code you provisioned.

{

"CustomerName": "Customer A",

"CustomerPhone": "+12345678900",

"AppointmentStatus":"CREATED",

"id": "1"

}

3. To trigger sending the feedback SMS, you need to set an existing item’s status to “COMPLETED” To do this, select the item and click Edit from the Actions menu.

Replace the item’s current JSON with the following.

{

"AppointmentStatus": "COMPLETED",

"CustomerName": "Customer A",

"CustomerPhone": "+12345678900",

"id": "1"

}

4. Before choosing the Save button, double check that you have set CustomerPhone attribute’s value to a valid phone number.

After the change, you should receive an SMS message asking for a feedback. Provide a numeric reply of that is less than five to this message. This will trigger a follow up question asking for a consent to receive an in-person callback.

 

During your SMS conversation with the application, inspect the feedbacks table. The feedback you have given over this two-way SMS channel should have been reflected into the table.

If you want to repeat the process, make sure to increment the AppointmentId field for any additional appointment records.

Cleanup

To clean up the resources you used in your account, simply navigate to AWS Cloudformation console and delete the stack named “BlogStackPinpoint”.

After the stack is deleted, you also need to delete the Long code from the Pinpoint Console by choosing the number and pressing Remove phone number button. You can also delete the Amazon S3 bucket you used for packaging and deploying the AWS SAM application.

Conclusion

This architecture shows how Amazon Pinpoint can be used to make two-way SMS communication with your customers. You can implement Two-way SMS functionality in other use cases such as appointment reminders, polls, Q&A services, and more.

To learn more about Pinpoint and it’s two-way SMS mechanism, you can visit the Pinpoint documentation.