Tag Archives: email marketing

Navigate Bulk Sender Requirements with Amazon SES

Post Syndicated from Vinay Ujjini original https://aws.amazon.com/blogs/messaging-and-targeting/navigate-bulk-sender-requirements-with-amazon-ses/

Introduction

Email communication remains a critical component of business operations and customer engagement. As the digital landscape evolves, major mailbox providers continually update their policies to enhance security and user experience. This blog will explore the changes implemented by Microsoft for bulk senders trying to reach Outlook.com (supporting Hotmail.com, live.com consumer domain addresses). This follows the Google & Yahoo! bulk sender requirements changes in February of 2024. Microsoft is implementing the enforcement of sender requirements for bulk email senders, particularly those sending over 5,000 messages daily, starting May 5, 2025. These requirements focus on improving email authentication and trust. This will ensure Outlook and Hotmail recipients are receiving messages that are authenticated and from who they claim to be from. These measures will help reduce spoofing, phishing, and spam, and safeguarding individuals and businesses relying on email.

This blog will discuss what these changes mean for you, and how Amazon Simple Email Service (Amazon SES) can help you maintain compliance and optimize your email sending practices.

Background

In February 2024, Google and Yahoo implemented new requirements for bulk email senders, building upon industry efforts to combat spam and improve email deliverability. These changes aligned with Google’s 2024 bulk sender requirements initiative, signaling a unified approach among major mailbox providers to enhance the privacy and compliance in email.

What does this mean for customers and email senders?

What’s Changing?

Microsoft’s New Requirements

  1. DMARC enforcement with at least a p=none policy
  2. Sender domain authentication (SPF, DKIM)
  3. Functional unsubscribe links required in the email
  4. Requirement for From and Reply-to addresses to be deliverable

Why These Changes Matter?

These new requirements serve several crucial purposes:

  1. Enhances trust in your sending domain: Validates that the sender is who they are claiming to be. Enhances trust by delivering messages that are authenticated and aligned with the bulk sender requirements.
  2. Improved Deliverability: Ensuring legitimate emails reach the recipients who have subscribed to sender’s messages.
  3. User-Centric: Providing recipients with control over their inboxes.
  4. Industry Standardization: Aligning sender requirements across major email providers

Best Practices for Compliance

To adhere to these new requirements and optimize your email sending practices, consider the following best practices:

1. Implement Strong Authentication

  • Configure SPF: SPF (Sender Policy Framework) is an email authentication standard that’s designed to prevent email spoofing. Domain owners use SPF to tell email providers which servers are allowed to send email from their domains. Follow setup instructions to authenticate your email with SPF. Must pass SPF for sending domain.
    • Configure “custom MAIL FROM“, which is how senders can ensure that the SPF-authenticated domain is aligned with the From header domain’s DMARC policy.
  • Enable DKIM signing: DomainKeys Identified Mail (DKIM) is an email security standard. It is designed to ensure that an email that claims to have come from a specific domain, was indeed authorized by the owner of that domain. It uses public-key cryptography to sign an email with a private key. Recipient servers use a public key, published to a domain’s DNS to verify that parts of the email have not been modified during the transit. Follow these set up instructions to authenticate email with DKIM in SES. Must pass to validate email integrity and authenticity.
    • Verify your domain with Easy DKIM. If currently using email identities, you have to move to domain
    • If you utilize email identities only, you will default all authentication to amazonses.com. That will not align with your friendly from address which will not satisfy the bulk sender requirements. This means that when you send email to mailbox providers, your messages will be rejected because you do not have proper authentication on your emails. To satisfy the bulk sender requirements, you must use domain verified identities which ensure that you have ownership of or permission to use the sending domain. That will allow SES to sign the outgoing emails with a DKIM signature that aligns with the friendly from domain.
  • Set up DMARC with an appropriate policy: Domain-based Message Authentication, Reporting and Conformance (DMARC) is an email authentication protocol that uses SPF and DKIM to detect email spoofing and phishing. To comply with DMARC, messages must be authenticated through either SPF or DKIM. Ideally, when both are used with DMARC, you’ll be ensuring the highest level of protection possible for your email sending.
Name Type Value
_dmarc.example.com TXT “v=DMARC1;p=none;rua=mailto:[email protected]“

In the preceding records:

    • example.com is your domain
    • Value of the TXT record contains the DMARC policy that applies to your domain.
    • In this example, the policy tells email providers to do the following:
      • At least p=none should be implemented.

2. Optimize Email Content

  • Clearly identify yourself as the sender: Use a recognizable “From” name and email address that accurately represents your brand or organization. For example, use “[email protected]” instead of a generic or misleading address.
  • Implement user friendly unsubscribe mechanisms: Include a visible, easy-to-use unsubscribe link in every email, typically in the header. Ensure the unsubscribe process is simple and honors requests promptly, ideally within 24-48 hours. Visit this guide on how Amazon SES helps you do that.
  • Subject line aligns with content: Avoid deceptive subject lines that don’t match the email content.
  • Clearly identify commercial content: If your email is promotional, make it obvious. Use clear language in the subject line and body that indicates the nature of the email, such as “Special Offer” or “Newsletter.”
  • Include a valid physical address: Add your company’s physical mailing address in the email footer. This is not only a legal requirement in many jurisdictions but builds trust with recipients.
  • Verify URLS in the emails: Verify that links in the emails you send work and are not misleading to the reader/subscriber. Be transparent with URLs/links in the email content.

3. Monitor and Maintain

  • Monitor bounces: A bounce typically indicates why a message was not delivered. The SMTP response in the bounce message will have details on why the message was bounced. For example: if it is missing authentication records (fix: include authentication records for the domain – quick fix) versus an IP or domain reputation bounce reason (this maybe a longer term fix).
    • Track both hard bounces (permanent delivery failures) and soft bounces (temporary issues). High bounce rates can indicate list quality problems or delivery issues. Visit this blog to set up notifications for bounces & complaints. Virtual Deliverability Manager (VDM) is an Amazon SES feature that helps you enhance email deliverability. It helps increasing inbox deliverability and email conversions, by providing insights into your sending and delivery data. VDM advices on how to fix the issues that are negatively affecting your delivery success rate and reputation.
  • Track complaint rates: Regularly monitor the number of spam complaints your emails receive with a goal of keeping the complaint rate under 0.2%. Not all mailbox providers have complaint feedback loop data, so use aggregate data from the mailbox providers that do, such as Hotmail and Yahoo. Email providers that don’t provide complaint feedback loops, such as Gmail may have alternative dashboards or tools available like Google Postmaster tools.
  • Perform regular authentication checks: Periodically verify that your SPF, DKIM, and DMARC records are correctly set up and functioning. Alternative to manual DNS checks, Amazon SES has a feature in Virtual Deliverability Manager that performs authentication checks for your sending identities.
  • Maintain list hygiene: Regularly clean your email list by removing inactive subscribers, correcting typos in email addresses, and honoring unsubscribe requests. This helps improve deliverability and engagement rates.

How Amazon SES Helps

Amazon SES provides a robust set of features to help you meet these new requirements and optimize your email sending practices:

Authentication Support

  • Easy DKIM configuration
  • SPF record management
  • DMARC implementation guidance

Comprehensive Monitoring

  • Virtual Deliverability Manager
  • Complaint tracking
  • Bounce rate monitoring
  • Event publishing to Amazon CloudWatch, SNS , Kinesis Firehose and Event Bridge
  • Detailed sending statistics

Compliance Tools

  • List management capabilities (included with SES)
  • Suppression list handling (included with SES)
  • Feedback loop processing (included with SES)
  • Authentication status tracking: This is done through Amazon SES feature Virtual Deliverability Manager (VDM).

Implementation Strategy

To successfully implement these changes, consider the following strategy:

  1. Assessment: Audit your current email practices, review authentication status, and evaluate compliance gaps.
  2. Technical Implementation: Configure authentication protocols, update DNS records, and implement required unsubscribe mechanisms.
  3. Monitoring and Optimization: Track deliverability metrics, monitor complaint rates, and adjust sending practices as needed.

Measuring Success

To ensure ongoing compliance and optimize your email practices, track these key metrics:

  1. Delivery rates
  2. Complaint rates
  3. Authentication pass rates
  4. Engagement metrics (open rates, click-through rates)

Conclusion

The new bulk sender requirements from Microsoft and Yahoo represent an important step towards a more secure and reliable email ecosystem. By leveraging Amazon SES’s powerful features and following industry best practices, you can maintain compliance, improve deliverability, and enhance the overall effectiveness of your email communications.

Amazon SES is committed to helping you navigate these changes and optimize your email sending practices. For the most up-to-date guidance and support, please consult SES’s documentation or contact Amazon SES support.

Additional Resources

The email landscape is constantly evolving. Stay informed and adaptable to ensure your email practices remain effective and compliant.

About the authors:

Streamline SMS and Emailing Marketing Compliance with Amazon Comprehend

Post Syndicated from Koushik Mani original https://aws.amazon.com/blogs/messaging-and-targeting/streamline-sms-and-emailing-marketing-compliance-with-amazon-comprehend/

In today’s digital landscape, businesses heavily rely on SMS and email campaigns to engage with customers and deliver timely, relevant messages. The shift towards digital marketing has increased customer engagement, accelerated delivery, and expanded personalization options. Email and SMS marketing is essential to digital strategies according to 44% of Chief Marketing Officers and they allocate approximately 8% of their marketing towards this. Industries face stringent restrictions on the content they can send due to legal regulations and carrier filtering policies.

Messages related to the subjects listed below are considered restricted and are subject to heavy filtering or even being blocked outright. Failing to comply with these restrictions can result in severe consequences, including legal action, fines, and irreparable damage to a brand’s reputation. Marketers need a solution that will proactively scan their content used in campaigns and flag restricted content before sending it out to their customers without facing penalties and losing trust.:

  • Gambling
  • High-risk financial services
  • Debt forgiveness
  • S.H.A.F.T (Sex, Hate, Alcohol, Firearms, and Tobacco)
  • Illegal substances

In this blog, we will explore how to leverage Amazon Comprehend, Amazon S3, and AWS Lambda to proactively scan text-based marketing campaigns before publishing content . This solution enables businesses to enhance their marketing efforts while maintaining compliance with industry regulations, avoiding costly fines, and preserving their hard-earned reputation, conforming to best practices.

Solution Overview

AWS provides a robust suite of services to meet the infrastructure needs of the booming digital marketing industry, including messaging capabilities through email, SMS, push, and other channels through Amazon Simple Email Service, Amazon Simple Notification Service, or Amazon Pinpoint.

The main goal for this approach is to flag any message that contains restricted content mentioned above before distribution.

Figure 1: Architecture for proactive scanning of marketing content

Figure 1: Architecture for proactive scanning of marketing content

Following are the high-level steps:

  1. Upload documents to be scanned to the S3 bucket.
  2. Utilize Amazon Comprehend custom classification for categorizing the documents uploaded.
  3. Create an Amazon Comprehend endpoint to perform analysis.
  4. Inference output is published to the destination S3 bucket.
  5. Utilize AWS Lambda function to consume the output from the destination S3 bucket.
  6. Send the compliant messages through various messaging channels.

Solution Walkthrough

Step 1: Upload Documents to Be Scanned to S3

  1. Sign in to the AWS Management Console and open the Amazon S3 console
  2. In the navigation bar on the top of the page, choose the name of the currently displayed AWS Region. Next, choose the Region in which you want to create a bucket.
  3. In the left navigation pane, choose Buckets.
  4. Choose Create bucket.
    • The Create bucket page opens.
  5. Under General configuration, view the AWS Region where your bucket will be created.
  6. Under Bucket type, choose General purpose.
  7. For Bucket name, enter a name for your bucket.
    • The bucket name must:
      • Be unique within a partition. A partition is a grouping of Regions. AWS currently has three partitions: aws (Standard Regions), aws-cn (China Regions), and aws-us-gov (AWS GovCloud (US) Regions).
      • Be between 3 and 63 characters long.
      • Consist only of lowercase letters, numbers, dots (.), and hyphens (-). For best compatibility, we recommend that you avoid using dots (.) in bucket names, except for buckets that are used only for static website hosting.
      • Begin and end with a letter or number.
  8. In the Buckets list, choose the name of the bucket that you want to upload your folders or files to.
  9. Choose Upload.
  10. In the Upload window, do one of the following:
    • Drag and drop files and folders to the Upload window.
    • Choose Add file or Add folder, choose the files or folders to upload, and choose Open.
    • To enable versioning, under Destination, choose Enable Bucket Versioning.
    • To upload the listed files and folders without configuring additional upload options, at the bottom of the page, choose Upload.
  11. Amazon S3 uploads your objects and folders. When the upload is finished, you see a success message on the Upload: status page.

Step 2: Creating a Custom Classifiction Model

Custom Classification Model

Out-of-the-box models may not capture nuances and terminology specific to an organization’s industry or use case. Therefore, we train a custom model to identify compliant messages.

A custom classification model is a feature that allows you to train a machine learning model to classify text data based on categories that are specific to your use case or industry. It trains the model to recognize and sort different types of content which is used to power the endpoint. A custom classification model is designed to save costs and promote compliant messages and further prevent marketing companies from potential fines.

Requirements for custom classification:

  • Dataset creation
    • A CSV dataset with 1000 examples of marketing messages, each labeled as compliant (1) or non-compliant (0).
    • Designed to train a model for accurate predictions on marketing message compliance.
Figure 2: Screenshot of dataset – 20 entries of censored marketing messages

Figure 2: Screenshot of dataset – 20 entries of censored marketing messages

  • Creating a Test Data Set
    In addition to providing a dataset to power your customer classification model, a test dataset is also required to test the data that the model will be running on. Without a test dataset, Amazon Comprehend trains the model with 90 percent of the training data. It reserves 10 percent of the training data to use for testing. When using a test dataset, the test data must include at least one example for each unique label (0 or 1) in the training dataset.
  1. Upload the data set and test data set to an S3 Bucket, by following the steps in this user guide.
  2. In the AWS Console, search for Amazon Comprehend.
  3. Once selected, select custom classification on the left panel.
  4. Once there, select Create new model.
  5. Next specify model settings:
    • Model name
    • Specify the version (optional)
    • Language: EnglishModel Setting
  6. Specify the data specifications:
    • Training model type: Plain Text Documents
    • Data format: CSV File
    • Classifier Mode: Using Single-Label Mode
    • Training Dataset: Give the name of the bucket you created in step 1
    • Test Data set: Autosplit, i.e. how much of your data will be used for training and testing.
    • Data Specifications
  1. Specify the location of the model output in S3
    • Output data
  1. Create an IAM Role
    • Permissions to access: Train, Test and output data (if specified in your S3 Buckets)
    • IAM Role
  2. Once all parameters have been identified, select Create.
    • Preferences
  3. Once the model has been created, you can view it under Custom Classification. To check and verify the accuracy and F1 score, select the version number of the model. Here, you can view the model details under the Performance tab.

Step 3: Creating an Endpoint in Amazon Comprehend

Next, an endpoint needs to be created to analyze documents. To create an endpoint:

  • Select endpoint on the left panel in Amazon Comprehend.
  • Select Create endpoint in the left panel.
  • Specify Endpoints Settings :
    • Provide a name
    • Custom model type: Custom Classification
    • Choose a custom model that you want to attach to the new endpoint. From the dropdown, you can search by model name.
    • create_endpointFigure 8: Amazon Comprehend – Endpoint settings
  • Provide the number of inference units (IUs): 1
  • Once all the parameters have been provided, ensure that the Acknowledge checkbox has been selected.
  • Finally, select Create endpoint.
  • inference_units

Step 4: Scanning Text with the Custom Classification Endpoint

Once the endpoint has been successfully created, it can be used for real-time analysis or batch-processing jobs. Below is a walkthrough of how both options can be achieved.

Real-time analysis:

  • On the left panel, select Realtime Analysis.
  • Pick Analysis type: custom, to view real-time insights based on the custom models from an endpoint you’ve created
  • Select custom model type
  • Select your Endpoint
  • Insert your input text.
    • For this example, we have used a non-compliant message: Huge sale at Pine County Shooting Range 25% off for 6mm and 9mm bullets! Lazer add-ons on clearance too
  • Once inserted, click Analyze.input_data
  • Once analyzed, you will see a confidence score under Classes. Because the dataset is labeled as 0 for non-compliant and 1 for compliant. The message that was inserted was non-compliant, the result of the real-time analysis is a high confidence score for non-compliant.insights

Real-time analysis in Amazon Comprehend:

  • On the left panel in Amazon Comprend, select Analysis Jobs.
  • Select the Create Job button.
  • Configure Job settings:
    • Enter the Name
    • Analysis Type: Custom Classification
    • Classifications Model: The model you have created for your Classifier, as well as the version number of that model you would like to use for this job.
    • create_analysis
  • Enter the location of the Input Data and Output Data in the form of an S3 bucket URL.
  • input_data
  • Before creating a job the last thing, we want to do is provide the right access permission, by creating an IAM role that give access permissions to the S3 input and output locations.
  • access_premissions
  • Once the batch processing job shows a status of completed, you can view the results in the output S3 bucket which was identified earlier. The results will be in a json file where each line represents the confidence score for each marketing message.
  • json

Step 5 (optional): Publish message to communication service

The result from the batch processing is automatically uploaded to the output S3 bucket. For each json file uploaded, S3 will initiate an S3 Event Notification which will inform a Lambda function that a new S3 object has been created.

The Lambda function will evaluate the results and automatically identify the messages labeled as compliant (label 0). These compliant messages will then be published to communication services using one of the following three APIs, depending on the desired service:

To automatically trigger the AWS Lambda function, which will read the files uploaded into the S3 bucket and display the data using the Python Pandas library, we will use the boto3 API to read the files from the S3 bucket.

  1. Create an IAM Role in AWS.
  2. Create an AWS S3 bucket.
  3. Create the AWS Lambda function with S3 triggers enabled.
  4. Update the Lambda code with a Python script to read the data and send the communication to customer.

Conclusion

Proactively scanning and classifying marketing content for compliance is a critical aspect of ensuring successful digital marketing campaigns while adhering to industry regulations. Leveraging the powerful combination of Amazon Comprehend, Amazon S3, and AWS Lambda enables the automatic analysis of text-based marketing messages and flagging of any non-compliant content before sending them to your customer. Following these steps provides you with the tools and knowledge to implement proactive scanning for your marketing content. This solution will help mitigate the risks of non-compliance, avoiding costly fines and reputational damage, while freeing up time for your content creation teams to focus on ideation and crafting compelling marketing messages. Regular monitoring and fine-tuning of the custom classification model should be conducted to ensure accurate identification of non-compliant language.

To get started with proactively scanning and classifying marketing content for compliance, see Amazon Comprehend Custom Classification.

About the Authors

Caroline Des Rochers

Caroline Des Rochers

Caroline is a Solutions Architect at Amazon Web Services, based in Montreal, Canada. She works closely with customers, in both English and French, to accelerate innovation and advise them through technical challenges. In her spare time, she is a passionate skier and cyclist, always ready for new outdoor adventures.

Erika_Houde_Pearce

Erika Houde Pearce

Erika Houde-Pearce is a bilingual Solutions Architect in Montreal, guiding small and medium businesses in eastern Canada through their cloud transformations. Her expertise empowers organizations to unlock the full potential of cloud technology, accelerating their growth and agility. Away from work, she spends her spare time with her golden retriever, Scotia.

Koushik_Mani

Koushik Mani

Koushik Mani is a Solutions Architect at AWS. He had worked as a Software Engineer for two years focusing on machine learning and cloud computing use cases at Telstra. He completed his masters in computer science from University of Southern California. He is passionate about machine learning and generative AI use cases and building solutions.

How quirion created nested email templates using Amazon Simple Email Service (SES)

Post Syndicated from Dominik Richter original https://aws.amazon.com/blogs/messaging-and-targeting/how-quirion-created-nested-email-templates-using-amazon-simple-email-service-ses/

This is part two of the two-part guest series on extending Simple Email Services with advanced functionality. Find part one here.

quirion, founded in 2013, is an award-winning German robo-advisor with more than 1 billion Euro under management. At quirion, we send out five thousand emails a day to more than 60,000 customers.

Managing many email templates can be challenging

We chose Amazon Simple Email Service (SES) because it is an easy-to-use and cost-effective email platform. In particular, we benefit from email templates in SES, which ensure a consistent look and feel of our communication. These templates come with a styled and personalized HTML email body, perfect for transactional emails. However, managing many email templates can be challenging. Several templates share common elements, such as the company’s logo, name or imprint. Over time, some of these elements may change. If they are not updated across all templates, the result is an inconsistent set of templates. To overcome this problem, we created an application to extend the SES template functionality with an interface for creating and managing nested templates.

This post shows how you can implement this solution using Amazon Simple Storage Service (Amazon S3), Amazon API Gateway, AWS Lambda and Amazon DynamoDB.

Solution: compose email from nested templates using AWS Lambda

The solution we built is fully serverless, which means we do not have to manage the underlying infrastructure. We use AWS Cloud Development Kit (AWS CDK) to deploy the architecture.

The figure below describes the architecture diagram for the proposed solution.

  1. The entry point to the application is an API Gateway that routes requests to a Lambda function. A request consists of an HTML file that represents a part of an email template and metadata that describes the structure of the template.
  2. The Lambda function is the key component of the application. It takes the HTML file and the metadata and stores them in a S3 Bucket and a DynamoDB table.
  3. Depending on the metadata, it takes an existing template from storage, inserts the HTML from the request into it and creates a SES email template.

Architecture diagram of the solution: new templates in Amazon SES are created by a Lambda function accessed through API Gateway. THe Lambda function reads and writes HTML from S3 and reads and writes metadata from DynamoDB.

The solution is simplified for this blog post and is used to show the possibilities of SES. We will not discuss the code of the Lambda function as there are several ways to implement it depending on your preferred programming language.

Prerequisites

Walkthrough

Step 1: Use the AWS CDK to deploy the application
To download and deploy the application run the following commands:

$ git clone https://github.com/quirionit/aws-ses-examples.git
$ cd aws-ses-examples/projects/go-src
$ go mod tidy
$ cd ../../projects/template-api
$ npm install
$ cdk deploy

Step 2: Create nested email templates

To create a nested email template, complete the following steps:

  1. On the AWS Console, choose the API Gateway.
  2. You should see an API with a name that includes SesTemplateApi.
    Console screenshot displaying the SesTemplateApi
  3. Click on the name and note the Invoke URL from the details page.

    AWS console showing the invoke URL of the API

  4. In your terminal, navigate to aws-ses-examples/projects/template-api/files and run the following command. Note that you must use your gateway’s Invoke URL. 
    curl -F [email protected] -F "isWrapper=true" -F "templateName=m-full" -F "child=content" -F "variables=FIRSTNAME" -F "variables=LASTNAME" -F "plain=Hello {{.FIRSTNAME}} {{.LASTNAME}},{{template \"content\" .}}" YOUR INVOKE URL/emails

    The request triggers the Lambda function, which creates a template in DynamoDB and S3. In addition, the Lambda function uses the properties of the request to decide when and how to create a template in SES. With “isWrapper=true” the template is marked as a template that wraps another template and therefore no template is created in SES. “child=content” specifies the entry point for the child template that is used within m-full.html. It also uses FIRSTNAME and LASTNAME as replacement tags for personalization.

  5. In your terminal, run the following command to create a SES email template that uses the template created in step 4 as a wrapper.

Step 3: Analyze the result

  1. On the AWS Console, choose DynamoDB.
  2. From the sidebar, choose Tables.
  3. Select the table with the name that includes SesTemplateTable.
  4. Choose Explore table items. It should now return two new items.
    Screenshot of the DynamoDB console, displaying two items: m-full and order-confirmation.
    The table stores the metadata that describes how to create a SES email template. Creating an email template in SES is initiated when an element’s Child attribute is empty or null. This is the case for the item with the name order-confirmation. It uses the BucketKey attribute to identify the required HTML stored in S3 and the Parent attribute to determine the metadata from the parent template. The Variables attribute is used to describe the placeholders that are used in the template.
  5. On the AWS Console, choose S3.
  6. Select the bucket with the name that starts with ses-email-templates.
  7. Select the template/ folder. It should return two objects.
    Screenshot of the S3 console, displaying two items: m-full and order-confirmation.
    The m-full.html contains the structure and the design of an email template and is used with the order-confirmation.html which contains the content.
  8. On the AWS Console, choose the Amazon Simple Email Service.
  9. From the sidebar, choose Email templates. It should return the following template.
    Screenshot of the SES console, displaying the order confirmation template

Step 4: Send an email with the created template

  1. Open the send-order-confirmation.json file from aws-ses-examples/projects/template-api/files in a text editor.
  2. Set a verified email address as Source and ToAddresses and save the file.
  3. Navigate your terminal to aws-ses-examples/projects/template-api/files and run the following command:
    aws ses send-templated-email --cli-input-json file://send-order-confirmation.json
  4. As a result, you should get an email.

Step 5: Cleaning up

  1. Navigate your terminal to aws-ses-examples/projects/template-api.
  2. Delete all resources with cdk destroy.
  3. Delete the created SES email template with:
    aws ses delete-template --template-name order-confirmation

Next Steps

There are several ways to extend this solution’s functionality, including the ones below:

  • If you send an email that contains invalid personalization content, Amazon SES might accept the message, but won’t be able to deliver it. For this reason, if you plan to send personalized email, you should configure Amazon SES to send Rendering Failure event notifications.
  • The Amazon SES template feature does not support sending attachments, but you can add the functionality yourself. See part one of this blog series for instructions.
  • When you create a new Amazon SES account, by default your emails are sent from IP addresses that are shared with other SES users. You can also use dedicated IP addresses that are reserved for your exclusive use. This gives you complete control over your sender reputation and enables you to isolate your reputation for different segments within email programs.

Conclusion

In this blog post, we explored how to use Amazon SES with email templates to easily create complex transactional emails. The AWS CLI was used to trigger SES to send an email, but that could easily be replaced by other AWS services like Step Functions. This solution as a whole is a fully serverless architecture where we don’t have to manage the underlying infrastructure. We used the AWS CDK to deploy a predefined architecture and analyzed the deployed resources.

About the authors

Mark Kirchner is a backend engineer at quirion AG. He uses AWS CDK and several AWS services to provide a cloud backend for a web application used for financial services. He follows a full serverless approach and enjoys resolving problems with AWS.
Dominik Richter is a Solutions Architect at Amazon Web Services. He primarily works with financial services customers in Germany and particularly enjoys Serverless technology, which he also uses for his own mobile apps.

The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post.

How quirion sends attachments using email templates with Amazon Simple Email Service (SES)

Post Syndicated from Dominik Richter original https://aws.amazon.com/blogs/messaging-and-targeting/how-quirion-sends-attachments-using-email-templates-with-amazon-simple-email-service-ses/

This is part one of the two-part guest series on extending Simple Email Services with advanced functionality. Find part two here.

quirion is an award-winning German robo-advisor, founded in 2013, and with more than 1 billion euros under management. At quirion, we send out five thousand emails a day to more than 60,000 customers.

We chose Amazon Simple Email Service (SES) because it is an easy-to-use and cost-effective email platform. In particular, we benefit from email templates in SES, which ensure a consistent look and feel of our communication. These templates come with a styled and personalized HTML email body, perfect for transactional emails. Sometimes it is necessary to add attachments to an email, which is currently not supported by the SES template feature. To overcome this problem, we created a solution to use the SES template functionality and add file attachments.

This post shows how you can implement this solution using Amazon Simple Storage Service (Amazon S3), Amazon EventBridge, AWS Lambda and AWS Step Functions.

Solution: orchestrate different email sending options using AWS Step Functions

The solution we built is fully serverless, which means we do not have to manage the underlying infrastructure. We use AWS Cloud Development Kit (AWS CDK) to deploy the architecture and analyze the resources.

The solution extends SES to send attachments using email templates. SES offers three possibilities for sending emails:

  • Simple  — A standard email message. When you create this type of message, you specify the sender, the recipient, and the message body, and Amazon SES assembles the message for you.
  • Raw — A raw, MIME-formatted email message. When you send this type of email, you have to specify all of the message headers, as well as the message body. You can use this message type to send messages that contain attachments. The message that you specify has to be a valid MIME message.
  • Templated — A message that contains personalization tags. When you send this type of email, Amazon SES API v2 automatically replaces the tags with values that you specify.

In this post, we will combine the Raw and the Templated options.

The figure below describes the architecture diagram for the proposed solution.

  1. The entry point to the application is an EventBridge event bus that routes incoming events to a Step Function workflow.
  2. An event consists of the personalization parameters, the sender and recipient addresses, the template name and optionally the document-related properties such as a reference to the S3 bucket in which the document is stored. Depending on whether the event contains document-related properties, the Step Function workflow decides how the email is prepared and sent.
  3. In case the event does not contain document-related properties, it uses the SendEmail action to send a templated email. The action requires the template name and the data to replace the personalization tags.
  4. If the event contains document-related properties, the raw sending option of the SendEmail action must be used. If we also want to use an email template, we need to use that as a raw MIME message. So, we use the TestRenderEmailTemplate action to get the raw MIME message from the template and use a Lambda function to get and add the document. The Lambda function then triggers SES to send the email.

The solution is simplified for this blog post and is used to show the possibilities of SES. We will not discuss the code of the lambda function as there are several ways to implement it depending on your preferred programming language.

Architecture diagram of the solution: an AWS Step Functions workflow is triggered by EventBridge. If the event contains no document, the workflow triggers Amazon SES SendEmail. Otherwise, it uses SES TestRenderEmailTemplate as input for a Lambda function, which gets the document from S3 and then sends the email.

Prerequisites

Walkthrough

Step 1: Use the AWS CDK to deploy the application

To download and deploy the application run the following commands:

$ git clone [email protected]:quirionit/aws-ses-examples.git
$ cd aws-ses-examples/projects/go-src
$ go mod tidy
$ cd ../../projects/email-sender
$ npm install
$ cdk deploy

Step 2: Create a SES email template

In your terminal, navigate to aws-ses-examples/projects/email-sender and run:

aws ses create-template --cli-input-json file://files/hello_doc.json

Step 3: Upload a sample document to S3

To upload a document to S3, complete the following steps:

  1. On the AWS Console, choose the S3.
  2. Select the bucket with the name that starts with ses-documents.
  3. Copy and save the bucket name for later.
  4. Create a new folder called test.
  5. Upload the hello.txt from aws-ses-examples/projects/email-sender/files into the folder.

Screenshot of Amazon S3 console, showing the ses-documents bucket containing the file tes/hello.txt

Step 4: Trigger sending an email using Amazon EventBridge

To trigger sending an email, complete the following steps:

  1. On the AWS Console, choose the Amazon EventBridge.
  2. Select Event busses from the sidebar.
  3. Select Send events.
  4. Create an event as the following image shows. You can copy the Event detail from aws-ses-examples/projects/email-sender/files/event.json. Don’t forget to replace the sender, recipient and bucket with your values.
    Screenshot of EventBridge console, showing how the sample event with attachment is sent.
  5. As a result of sending the event, you should receive an email with the document attached.
  6. To send an email without attachment, edit the event as follows:
    Screenshot of EventBridge console, showing how the sample event without attachment is sent.

Step 5: Analyze the result

  1. On the AWS Console, choose Step Functions.
  2. Select the state machine with the name that includes EmailSender.
  3. You should see two Succeeded executions. If you select them the dataflows should look like this:
    Screenshot of Step Functions console, showing the two successful invocations.
  4. You can select each step of the dataflows and analyze the inputs and outputs.

Step 6: Cleaning up

  1. Navigate your terminal to aws-ses-examples/projects/email-sender.
  2. Delete all resources with cdk destroy.
  3. Delete the created SES email template with:

aws ses delete-template --template-name HelloDocument

Next Steps

There are several ways to extend this solution’s functionality, see some of them below:

  • If you send an email that contains invalid personalization content, Amazon SES might accept the message, but won’t be able to deliver it. For this reason, if you plan to send personalized email, you should configure Amazon SES to send Rendering Failure event notifications.
  • You can create nested templates to share common elements, such as the company’s logo, name or imprint. See part two of this blog series for instructions.
  • When you create a new Amazon SES account, by default your emails are sent from IP addresses that are shared with other SES users. You can also use dedicated IP addresses that are reserved for your exclusive use. This gives you complete control over your sender reputation and enables you to isolate your reputation for different segments within email programs.

Conclusion

In this blog post, we explored how to use Amazon SES to send attachments using email templates. We used an Amazon EventBridge to trigger a Step Function that chooses between sending a raw or templated SES email. This solution uses a full serverless architecture without having to manage the underlying infrastructure. We used the AWS CDK to deploy a predefined architecture and analyzed the deployed resources.

About the authors

Mark Kirchner is a backend engineer at quirion AG. He uses AWS CDK and several AWS services to provide a cloud backend for a web application used for financial services. He follows a full serverless approach and enjoys resolving problems with AWS.
Dominik Richter is a Solutions Architect at Amazon Web Services. He primarily works with financial services customers in Germany and particularly enjoys Serverless technology, which he also uses for his own mobile apps.

The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post.

Customize marketing messages and promotions for personalized outreach

Post Syndicated from binpazho original https://aws.amazon.com/blogs/messaging-and-targeting/customize-marketing-messages-and-promotions-for-personalized-outreach/

Introduction

Amazon Pinpoint is widely used by many customers for their various user engagement use cases like marketing campaigns, scheduled communications (newsletters, reminders, etc.), and transactional messaging. By using the message template feature in Amazon Pinpoint, customers can design messages personalized to the specific end users, by using variable attributes. While Amazon Pinpoint enables customers to include up to 250 attributes for each user, often times there might be need to pick and choose from a wide range of attributes about a user, that can lead to needing more than the allowed number of attributes.

The CampaignHook feature of Amazon Pinpoint can come to rescue for a situation like this. Using the CampainHook feature, we can filter out attributes that are not applicable to a specific user, while allowing to add new attributes, right before of sending the message. In this blog, I will walk you through how I have implemented the CampaignHook feature for a similar use case.

Sample Use-Cases

When setting up your Pinpoint campaign, following are the use cases where a CampaignHook can be enabled:

  • Retrieving data and perform custom compute logic in real time from third party data stores.
  • Filter endpoints out of the send: This is useful if you need to do some type of custom logic that you can’t do in Segmentation (custom opt-out, quiet time, campaign prioritization, etc.)
  • Avoid costly and time consuming Extract, Transform & Load (ETL) processes by accessing the data sources directly and applying custom compute logic in real-time.

Solution overview

CampaignHook Demo Architecture

The diagram above shows the solution that we will setup in this blog. As you can see, the Campaign event will trigger the Amazon Pinpoint Campaign. The event can be triggered from your web or mobile app that are accessed by your end-users, and can be setup to be triggered when the user performs a certain action. You can read more about setting up Amazon Pinpoint campaign in the user guide. By having the CampaignHook enabled on your Amazon Pinpoint campaign, the Lambda function that is configured with the CampaignHook will be triggered. This function will have access to the endpoint attributes passed by the Campaign event, and perform additional logic to derive new attributes for the user. Once all the new fields are derived, the function will update the user endpoint. Amazon pinpoint will then perform the next steps in the Campaign, and substitute the variables in the message template, before the personalized message is sent to the end user.

Prerequisites

  • AWS Account with Console and Programmatic access
  • Access to AWS CloudShell
  • Email channel enabled in Amazon Pinpoint

Building the demo

Build the Amazon Pinpoint Project

From the AWS Management console, go to Amazon Pinpoint and create a new project called “PinpointCampaignHookDemo”, and choose the option to enable the email channel. For more information about creating a project see the user guide, and follow the instructions here to setup your email channel.

If your account is in the Sandbox account, you will need to verify the email address, before you can send the email. You can follow the steps here to upgrade your account to a Production status if you are ready to deploy this solution to production.

Create the segment.

A segment is a group of your users that share certain attributes. For example, a segment might contain all of your users who use version 2.0 of your app on an Android device, or all users who live in the city of Los Angeles. You can send multiple campaigns to a single segment, and you can send a single campaign to multiple segments.

For this demo, let’s create a Dynamic Segment. Let’s call it ‘CampaignHookDemoSegment’.  Follow the steps here to create your Dynamic Segment.

Create a Segment

Setup message template

Let’s create our first template and call it “CampaignHookDemoTemplate”. You can read more about Amazon Pinpoint templates in the user guide.

For this demo, I have used the HTML template shown below, and I have 3 endpoint attribute variables: 2 that are passed from the campaign event trigger, and the third one (Company) that will be generated by the CampaignHook lambda function. For the subject of the email, I used “Campaign Hook Demo Campaign“.

Create eMail Template

The email template can be found in this GitHub repository.

Create Campaign

Next, create your campaign and use the Segment and email Template that you created in the previous steps by following the instructions here.

Select the ‘when an event occurs’ option to trigger the campaign when an event occurs. (This option will trigger the campaign when a specific event occurs). Yoy may also schedule your campaign to run on a scheduled bases as available in the setup screen. I used ‘CampaignHookTrigger’ as my event name.

Create a campaign

Set your Campaign Start date, time and end date. I have left all the other settings to default and saved the campaign. Now that you have successfully created your first Campaign, you are ready for the next steps.

Set Campaign Start and End Times

Create the Lambda function

This is the function that we will configure to trigger the Amazon pinpoint campaign event . From the Lambda console page, create a new function by clicking on the ‘Create function’ button. You can then pick the following options and create the function.

Name: Campaign_event_trigger_function

Runtime: Python 3.9 or higher.

Replace the default script with the code from the GitHub repository, and then deploy your code by clicking on the “Deploy” button.

Assign permissions

In-order for the Lambda function trigger to trigger the Pinpoint Campaign, you will need to add an inline policy to the IAM role that is attached to your Lambda function, by selecting Pinpoint as the service and PutEvents from the Write options. You can select the Lambda function as the resource to which the access will be granted.

{

    "Version" :"2012-10-17",

    "Statement":[

        {

            "Sid": "VisualEditor0",

            "Effect": "Allow",

            "Action": [

                "mobiletargeting:PutEvents"

            ],

            "Resource":"ARN of your Lambda function goes here."

        }

    ]

}

Create the CampaignHook Lambda function

This is the function that we will triggered from the CampaignHook. From your Lambda console, click on “Create function” and enter the basic information as shown below to create your function.

Name: CampaignHookFunction

Runtime: Python 3.9 or higher.

Next replace your default code with the sample GitHub code, and then deploy your code by clicking on the “Deploy” button.

Assign permissions

Next add permissions for Amazon Pinpoint to invoke the Lambda function by running the command below from your Command Shell. Replace the Lambda function name and Account number with yours.

aws lambda add-permission \

--function-name [YourCampaignHookLambdaFunctionName] \

--statement-id my-hook-id1 \

--action lambda:InvokeFunction \

--principal pinpoint.us-east-1.amazonaws.com \

--source-arn 'arn:aws:mobiletargeting:us-east-1:[YourAccountNumber]:apps/*'

You can also do this from the Lambda console, by clicking on “Configuration” and then scrolling down to “Resource based Policy” and by clicking on “Add permissions“.

Update Campaign settings to add the Campaign Hook

Now that you have the Lambda function that needs to act as the hook is created, and granted Amazon Pinpoint service to invoke that function, run the command below to update the Campaign settings to add the Campaign Hook. You can also set a default CampaignHook for ALL campaigns in the project by setting the CampaignHook property on the Project Settings via this API.

Replace the application-id (project id), campaign-id, and the arn of the Campaign Hook lambda function and run the command below. (You can find the Project ID by clicking on All Projects at the top-left of the Pinpoint Console. The Campaign ID can be found by opening your Pinpoint Project and then clicking Campaigns in the Pinpoint Console.)

aws pinpoint   update-campaign --application-id /

[your-application-id-goes-here] –campaign-id /

[your-campaign-id-goes-here] --cli-input-json '{"ApplicationId": /

"","CampaignId": "","WriteCampaignRequest": {"Hook": {"LambdaFunctionName": /

"your-CampaignHook-Function-goes-here","Mode": "FILTER","WebUrl": ""}}}'

You can optionally run the command below to make sure that the campaign settings have been updated:

aws pinpoint get-campaign –application-id [your-application-id-goes-here]  –campaign-id [your-campaign-id-goes-here]

Test your Campaign.

Go back to your Lambda function that you have created to trigger the Campaign in the “Create the Lambda function” step above. I have used the test event as shown below. Update the Application id to reflect your Project id and change the email address to the email you verified earlier and click on “Test” button.

{

    "application_id": "your application id",

    "endpoint_id": "223",

    "event_type": "CampaignHookEvent",

    "nextTestDate": "12/15/2025",

    "FirstName": "Jack",

    "email": "[email protected]",

    "userid": "Jack123"

}

You should now receive an email with the variables replaced with the values that was passed from your json payload. Further you can see the Company name was added to the endpoint from the CampaignHook Lambda, which is passed to the email template. If you have not received the email, please check the following:

  • The Lambda function ran without any errors
  • The LambdaHook function has the proper rights assigned to be invoked from Pinpoint
  • The From and To email id that you have used are verified in SES.

Verify email identity

Clean up resources

Once you are satisfied with your setup and testing, you can now clean up the resources by following the steps below:

  • Delete your Amazon Pinpoint Project, Campaign and Segment.
    • aws pinpoint delete-campaign –application-id [your appl id] –campaign-id [your campaign id]
    • aws pinpoint delete-segment –application-id [your app id]  –segment-id [your segment id]
    • aws pinpoint delete-app –application-id [your app id]
  • Delete you Lambda functions
    • aws lambda delete-function –function-name CampaignHookFunction
    • aws lambda delete-function –function-name Campaign_event_Trigger_Function

Conclusion

By dynamically generating the attributes in real-time, customers can now add greater levels of personalization within a single user message template. By invoking a Lambda function, you can perform custom compute logic, calculate new attribute values, and access external data stores, to modify the campaign’s segment, right before Amazon Pinpoint sends the message. Campaign Hook feature makes this possible as explained in this blog by running few basic CLI commands to enable the feature on your Amazon Pinpoint Campaign. You can read more about Amazon Pinpoint Campaign from the user guide documentation”.

Advanced Amazon Pinpoint Templates using Message Template Helpers

Post Syndicated from davelem original https://aws.amazon.com/blogs/messaging-and-targeting/advanced-amazon-pinpoint-templates-using-message-template-helpers/

Personalization of customer messages is a proven way to increase engagement of promotional and transactional communications. In order to make these communications repeatable and scalable, building personalization through templates is often required.

Using the Advanced Template Capabilities feature of Amazon Pinpoint, it’s now possible to create highly customized templates used for email, SMS, and Push Notifications.

Pinpoint templates are personalized using Handlebars.js. The new message template helpers are an expansion on the default Handlebars.js features. Please refer to handlebarsjs.com for more information on the default functionality of Handlebars.js

In this blog we will build an Order Confirmation template that will demonstrate a few helpers from each of the following categories:

Prerequisites

Before creating a template, you need to have an existing Amazon Pinpoint Project with the email channel enabled. The following will walk you through creating a project if you don’t already have one: Create and configure a Pinpoint Project

Architecture Overview

Step 1: Create a CSV file with sample Endpoint and Imported Segment

In Amazon Pinpoint, an endpoint represents a specific method of contacting a customer. This could be their email address (for email messages) or their phone number (for SMS messages) or a custom endpoint type. Endpoints can also contain custom attributes, and you can associate multiple endpoints with a single user. In this step, we create a simple CSV file which we will use to create a Segment in Pinpoint.

The data below contains the sample Order and Product data we will use in our Order Confirmation Email.

  1. Create a .CSV file named AdvancedTemplatesSegment.csv with the following data: 
    ChannelType,Address,Id,Attributes.FirstName,Attributes.LastName,Attributes.OrderDate,Attributes.OrderNumber,Attributes.ProductNumber,Attributes.ProductNumber,Attributes.ProductNumber,Attributes.ProductNumber,Attributes.ProductNumber,Attributes.ProductName,Attributes.ProductName,Attributes.ProductName,Attributes.ProductName,Attributes.ProductName,Attributes.Amount,Attributes.Amount,Attributes.Amount,Attributes.Amount,Attributes.Amount,Attributes.ItemCount,Attributes.ItemCount,Attributes.ItemCount,Attributes.ItemCount,Attributes.ItemCount,Attributes.CLVTier,User.UserId,Metrics.Age
EMAIL,[email protected],287b3858-3097-40e3-9af4-19bd4509a8f2,Mary,Smith,2021-01-15T18:07:13Z,460-ITS-2320,DWG8799598,XTC5517773,XRO7471152,EAT5122843,LNP9056489,non lectus aliquam,sapien placerat ante,semper sapien a libero nam dui,vitae consectetuer eget rutrum,nisl ut volutpat sapien arcu,68.88,32.89,53.19,45.38,47.31,20,76,33,15,53,High,66af7a81-77f2-485f-b115-d8c3a00f7077,84
EMAIL,[email protected],b42e6c5f-3e15-4fdd-b61c-499508271082,,,2021-01-30T22:33:22Z,296-OZA-6579,VMC0637283,RGM6575767,BTM9430068,XCV9343127,GVU2858284,a libero nam dui,sit amet consectetuer adipiscing,at ipsum,ut dolor morbi,nullam molestie,74.86,83.18,15.42,97.03,37.42,13,94,50,54,84,Low,dadc1be9-daf4-46ce-9069-13565e03eaa0,61

    NOTE: The file above has a few attributes that are the key to personalizing our email and including multiple items in our Order Confirmation table:

    • Attributes.FirstName – This will allow us to personalize with a salutation if available.
    • Attributes.CLVTier – This is an attribute that could be specified from a Machine Learning model to determine the customers CLV Tier. We will be using it to provide coupons specific to a given CLV Tier. See Predictive Segmentation Using Amazon Pinpoint and Amazon SageMaker for an example solution that demonstrates using Machine Learning to analyze information in Pinpoint.
    • Attributes.ProductNumber – Note that we have multiple columns that repeat for the product information in the order.  Pinpoint attributes are actually stored as a list, so if you pass multiple columns with the same name it will add items to the attribute list.This is the key to how we are able to display a table of information, but note that it does require making sure the attributes are aligned in the proper columns. For example, Attributes.ProductNumber[0] needs to align with Attributes.ProductName[0]See Using variables with message template helpers for more details.
  2. Search for [email protected] above and replace with two valid email addresses. Note that if your account is still in the sandbox these will need to be verified email addresses. If you only have access to a single email address you can use labels by adding a plus sign (+) followed by a string of text after the local part of the address and before the at (@) sign. For example: [email protected] and [email protected]
  3. Create a Pinpoint Segment
    1. Open the Amazon Pinpoint console at http://console.aws.amazon.com/pinpoint, and then choose the project that you created as part of the Prerequisites.
    2. In the navigation pane, choose Segments, and then choose Create a segment.
    3. Select Import a Segment.
    4. Browse to or Drag and Drop the .CSV file you created in the previous step.
    5. Use the default Segment Name and select Create Segment.

Step 2: Build The Message Template

  1. Open the Amazon Pinpoint console at http://console.aws.amazon.com/pinpoint.
  2. In the navigation pane, choose Message templates, and then choose Create template.
  3. Select Email as the Channel.
  4. For Template name use: AdvancedTemplateExample.
  5. For Subject use: AdvancedTemplateExample.
  6. Paste the following code into the HTML Editor. We will take some time later on to dig into the specific Handlebars helpers: 
    {{#* inline "salutation"}}
    {{#if Attributes.FirstName.[0]}}
        Dear {{Attributes.FirstName.[0]}},<br />
    {{else}}
        Dear Valued Customer,<br />
    {{/if}}
{{/inline}}

{{#* inline "clvcoupon"}}
    {{#if Attributes.CLVTier.[0]}}
        {{#eq Attributes.CLVTier.[0] "High"}}
            As a thank-you for your continued support, please use this coupon code for <strong>30%</strong> off your next order: <strong>WELOVEYOU30</strong>
        {{/eq}}
    {{/if}}
{{/inline}}

{{#* inline "footer"}}
    <hr />	
    Accent Athletics - 1234 Anywhere Ave, Anywhere USA, 12345 - <a href="https://www.example.com/preferences/index.html?pid={{ApplicationId}}&uid={{User.UserId}}&h={{sha256 (join User.UserId "d67c37ed538b751d850de18" "+" prefix="" suffix="")}}">Manage Preferences</a>
    <hr />
{{/inline}}


<!DOCTYPE html>
    <html lang="en">
    <head>
    <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
</head>
<body>
  {{> salutation}}
  Thank-you for your order! {{> clvcoupon}}<br /><br />
  Order Date: {{now format="d MMM yyyy HH:mm:ss" tz=America/Los_Angeles}}<br /><br />
  <table>
  <thead>
    <tr style="background-color: #f2f2f2;">
      <th style="text-align:left; width:75px">
        Product #
      </th>
      <th style="text-align:left; width:200px;">
        Name
      </th>
      <th style="text-align:center; width:75px;">
        Count
      </th>
      <th style="text-align:center; width:75px;">
        Amount
      </th>
    </tr>
  </thead>
  <tbody>
  {{#each Attributes.ProductNumber}}
    {{#eq (modulo @index 2) "1.0"}}
        <tr style="background-color: #f2f2f2;">
    {{else}}
        <tr>
    {{/eq}}
      <td style="text-align:left;">{{this}}</td>
      <td style="text-align:left;">{{#with (lookup ../Attributes.ProductName @index)}}{{this}}{{/with}}</td>
      <td style="text-align:center;">{{#with (lookup ../Attributes.ItemCount @index)}}{{this}}{{/with}}</td>
      <td style="text-align:center;">${{#with (lookup ../Attributes.Amount @index)}}{{this}}{{/with}}</td>
    </tr>
  {{else}}
    <tr>
      <td style="text-align:left;">{{Attributes.ProductNumber}}</td>
      <td style="text-align:center;">{{Attributes.ProductName}}</td>
      <td style="text-align:center;">{{Attributes.ItemCount}}</td>
      <td style="text-align:center;">{{Attributes.Amount}}</td>
    </tr>
  {{/each}}
  </tbody>
  </table>
  {{> footer}}
</body>
</html>

  7. Click Create to finish creating your template

Step 3: Create an Amazon Pinpoint Campaign

By sending a campaign, we can verify that our Amazon Pinpoint project is configured correctly, and that we created the segment and template correctly.

To create the segment and campaign:

  1. Open the Amazon Pinpoint console at http://console.aws.amazon.com/pinpoint, and then choose the project that you created in step 1.
  2. In the navigation pane, choose Campaigns, and then choose Create a campaign.
  3. Name the campaign “AdvancedTemplateTest.” Under Choose a channel for this campaign, choose Email, and then choose Next.
  4. On the Choose a segment page, choose the “AdvancedTemplateExample” segment that you just created, and then choose Next.
  5. In Create your message, choose the template we just created, ‘AdvancedTemplateExample. Note: You will see an Alert with: “This template contains a reference to an attribute from another project…” This is expected as Pinpoint is scanning the template for attributes allowing you to specify default values in case the endpoint doesn’t contain a value for the attribute. In this blog post we are using the {{#if}} conditional helper to handle any missing data, i.e. {{#if Attributes.FirstName.[0]}}
  6. On the Choose when to send the campaign page, keep all of the default values, and then choose Next.
  7. On the Review and launch page, choose Launch campaign.

Within a few seconds, you should receive an email:

So what just happened?

Let’s take a deeper dive at each of helpers we included in the template:

{{#* inline "salutation"}}
    {{#if Attributes.FirstName.[0]}}
        Dear {{Attributes.FirstName.[0]}},<br /><br />
    {{else}}
        Dear Valued Customer,<br /><br />
    {{/if}}
{{/inline}}

First you will notice that we are making use of Inline Partials. Using Inline Partials allows you to build a library of frequently used snippets of content. In this case we frequently use a salutation in our communications. You can build and maintain your own frequently used snippets and include them at the beginning of the template.

Later in the message we can simply include: {{> salutation}} to include a salutation in our email.

In this example we also see the {{#if}} helper which is used to evaluate if a first name is available on the endpoint. If the name is found, a greeting is returned that passes the user’s first name in the response. Otherwise, the else statement returns an alternative greeting.

{{#* inline "clvcoupon"}}
    {{#if Attributes.CLVTier.[0]}}
        {{#eq Attributes.CLVTier.[0] "High"}}
            As a thank-you for your continued support, please use this coupon code for <strong>30%</strong> off your next order: <strong>WELOVEYOU30</strong>
        {{/eq}}
    {{/if}}
{{/inline}}

Again, we are using Inline Partials to organize our code. Additionally we are using {{#if}} to see if the user has a CLVTier attribute and if so, we use the {{#eq}} conditional helper to see if their CLVTier is “High” as we only want this coupon to display for customers that fall into that tier.

Note that CLVTier is an attribute that is populated along with the Endpoint when we created the Segment above. You could also use a solution such as Predictive Segmentation using Amazon Pinpoint and Amazon SageMaker to incorporate Machine Learning to classify your existing users.

{{#* inline "footer"}}
    <hr />
    Accent Athletics - 1234 Anywhere Ave, Anywhere USA, 12345 - <a href="https://www.example.com/preferences/index.html?pid={{ApplicationId}}&uid={{User.UserId}}&h={{sha256 (join User.UserId "d67c37ed538b751d850de18" "+" prefix="" suffix="")}}">Manage Preferences</a>
    <hr />
{{/inline}}

In the example above we are using the {{sha256}} and {{join}} helpers to create a secure link to the Preference Center deployed as part of the Amazon Pinpoint Preference Center solution.

{{> salutation}}
Thank-you for your order! {{> clvcoupon}}<br /><br /><hr />
Order Date: {{now format="d MMM yyyy HH:mm:ss" tz=America/Los_Angeles}}<br /><br />

This is where all of our hard work implementing Inline Partials really starts to pay off. To include our salutation and coupon we simply need to specify: {{> salutation}} and {{> clvcoupon}}

The {{now}} string helper allows us to display the current date and time in the format of our choosing. Please reference the following for more details on the date pattern and available timezones:

<tbody>
{{#each Attributes.ProductNumber}}
{{#eq (modulo @index 2) "1.0"}}
    		<tr style="background-color: #f2f2f2;">
{{else}}
    		<tr>
{{/eq}}
    	<td style="text-align:left;">{{this}}</td>
    	<td style="text-align:left;">{{#with (lookup ../Attributes.ProductName @index)}}{{this}}{{/with}}</td>
    	<td style="text-align:center;">{{#with (lookup ../Attributes.ItemCount @index)}}{{this}}{{/with}}</td>
    	<td style="text-align:center;">${{#with (lookup ../Attributes.Amount @index)}}{{this}}{{/with}}</td>
</tr>
{{else}}
<tr>
    		<td style="text-align:left;">{{Attributes.ProductNumber}}</td>
    		<td style="text-align:center;">{{Attributes.ProductName}}</td>
    		<td style="text-align:center;">{{Attributes.ItemCount}}</td>
    		<td style="text-align:center;">{{Attributes.Amount}}</td>
</tr>
{{/each}}
</tbody>

This particular section has a lot going on. We will break each part down for further explanation:

  • {{#each}} – Allows us to loop through each of the values in our attribute. In this case our ProductNumber attribute will contain: [“order#1”, “order#2”,”order#3, etc.]
    Note that if you only have one item in the attribute array. Pinpoint will simplify that into a single string attribute. That is why we have the {{each}} part of the {{#else}} statement. This allows us to reference the attribute as a single string in case we don’t have a collection of values in the attribute.
  • {{#eq (modulo @index 2) “1.0”}} – In order to alternate our background color for even/odd rows, we are making use of the {{modulo}} operator from the Math and encoding helpers which will return the remainder of two given numbers allowing us to determine if this is an odd or even row.
    @index is a native Handlebars.js property that contains the current index we are on in the loop.
  • {{this}} – When iterating through a collection using {{#each}}, {{this}} allows you to reference the current item in the collection
  • {{#with (lookup ../Attributes.ProductName @index)}}{{this}}{{/with}} – Lookup is a built-in handlebars helper that allows us to find values in another collection. We are using the index combined with lookup to find the Product Name that goes along with the Product Number we are currently on. The same pattern is used for the remaining columns of the table.The ability to lookup values in another attribute collection is the key to how we are able to display a table of information, but note that it does require making sure the attributes are aligned in the proper columns. For example, Attributes.ProductNumber[0] needs to align with Attributes.ProductName[0]See Using variables with message template helpers for more details.
{{> footer}}

And just to wrap things up, let’s pull in the footer we defined with Inline Partials.

Next Steps

Using the techniques above, you can create sophisticated and personalized communications using Amazon Pinpoint.

Think about your existing communications to see if you can use personalization to increase customer engagement for your promotional and transactional messages.

Amazon Pinpoint is a flexible and scalable outbound and inbound marketing communications service. Learn more here: https://aws.amazon.com/pinpoint/