Overview
Unified Profiles for Travelers and Guests on AWS helps you automatically source, merge, remove redundant data, and centralize traveler and guest information from across your enterprise. It offers a single data source for marketing, sales, operations, and customer experience leaders, providing the data they need to create a central view of the customer. A seamless and personalized customer experience helps deepen the connection between the customer and your brand, and with a few clicks, customer information is aggregated from multiple internal systems of record, producing a unified customer profile in both batch and near real-time. Now, you can achieve a faster and a deeper understanding of your travelers and guests to deliver a tailored, more personalized customer experience.
Benefits
Integrates with your property management systems and customer data platforms. Also, a detailed process plan is provided for all common travel and hospitality data sources, such as bookings, loyalty profiles, hotel stays, and customer service interactions, minimizing the data transformation work to integrate this solution.
Use a constellation of rule-based and artificial intelligence (AI)-based Identity Resolution capabilities. This solution's modular architecture also allows for custom-matching logic and can be integrated with AWS Partners.
Sensitive traveler data is stored in an AWS specialized customer data store and located in your AWS account. This helps you deploy a permissions system with strict access controls to traveler data.
Provides near real-time updates so that your customers can react to all changes within their traveler profiles, such as booking cancellations or hotel checkouts. Leverage a complete view of your travelers and guests for timely and personalized communications.
Technical details
You can automatically deploy this architecture using the implementation guide and the associated AWS CloudFormation template.
The high-level process flow for this AWS solution components deployed with the AWS CloudFormation template is as follows:
Step 1
Data – The solution allows customers to ingest data using a batch feed or a real-time feed. The batch feed has the option to ingest data directly into the solution’s Amazon Simple Storage Service (Amazon S3) bucket or use Travel and Hospitality Application Connectors Catalog on AWS.
The real-time feed ingests data by sending objects directly to Amazon Kinesis. Data must follow the Travel and Hospitality Application Connecters Catalog on AWS schema. All objects sent to the feed are backed up in Amazon S3 using Amazon Data Firehose.
Step 2
Ingest - Batch feed data is processed using AWS Glue. Real-time data is processed using AWS Lambda. The data is transformed into Amazon Connect Customer Profiles records, a flat format suitable for ingestion into Amazon Connect Customer Profiles.
Step 3
Data is ingested in Amazon Connect Customer Profiles. Real-time matching rules are applied along with weekly machine learning-based Identity resolution jobs.
Step 4
Amazon Connect Customer Profiles exports profile changes in real time to Amazon Kinesis Data Streams. A Lambda function retrieves the full profile and ingests through Firehose into Amazon S3. Profiles are also published to Amazon EventBridge.
Step 5
Additionally, or instead of AWS Entity Resolution, customers can use partners like Amperity or their own Identity resolution logic to feed profile matches to Amazon DynamoDB.
Step 6
The frontend allows a data administrator to monitor ingestions and data quality. It also contains out-of-the-box profile search and display functions which are usable by customer-facing staff. Profiles can be manually merged in by users. Data access is managed by permissions using Amazon Cognito groups.
Step 7
A Lambda function, initiated by Amazon CloudWatch, runs hourly to optimize data partitioning.
Step 8
All ingestions and processing errors are recorded in a DynamoDB table through multiple Amazon Simple Queue Service (Amazon SQS) queues.
The high-level process flow for this AWS solution components deployed with the AWS CloudFormation template is as follows:
Step 1
Data – The solution allows customers to ingest data using a batch feed or a real-time feed. The batch feed has the option to ingest data directly into the solution’s Amazon Simple Storage Service (Amazon S3) bucket or use Travel and Hospitality Application Connectors Catalog on AWS.
The real-time feed ingests data by sending objects directly to Amazon Kinesis. Data must follow the Travel and Hospitality Application Connecters Catalog on AWS schema. All objects sent to the feed are backed up in Amazon S3 using Amazon Data Firehose.
Step 2
Ingest - Batch feed data is processed using AWS Glue. Real-time data is processed using AWS Lambda. The data is transformed into Amazon Connect Customer Profiles records, a flat format suitable for ingestion into Amazon Connect Customer Profiles.
Step 3
Data is ingested in Amazon Connect Customer Profiles. Real-time matching rules are applied along with weekly machine learning-based Identity resolution jobs.
Step 4
Amazon Connect Customer Profiles exports profile changes in real time to Amazon Kinesis Data Streams. A Lambda function retrieves the full profile and ingests through Firehose into Amazon S3. Profiles are also published to Amazon EventBridge.
Step 5
Additionally, or instead of AWS Entity Resolution, customers can use partners like Amperity or their own Identity resolution logic to feed profile matches to Amazon DynamoDB.
Step 6
The frontend allows a data administrator to monitor ingestions and data quality. It also contains out-of-the-box profile search and display functions which are usable by customer-facing staff. Profiles can be manually merged in by users. Data access is managed by permissions using Amazon Cognito groups.
Step 7
A Lambda function, initiated by Amazon CloudWatch, runs hourly to optimize data partitioning.
Step 8
All ingestions and processing errors are recorded in a DynamoDB table through multiple Amazon Simple Queue Service (Amazon SQS) queues.
- Publish Date
Related content
Traveler profile search screen
Example of customer service interaction
Traveler profile display screen
Traveler profile search screen
Example of customer service interaction
Traveler profile display screen