Connecting AfterShip to Redshift Simplified 101

E-commerce companies and online merchants are always on the lookout for easy ways to collect customer data from several sources into a centralized location so they can make informed business choices. This is because a cloud-based solution helps businesses to guarantee that their data warehouses can scale up and down on-demand, automatically accommodating during peak activity periods.

One of the most popular cloud data warehousing services is Amazon Redshift. Retailers could extract and store data in Redshift from online tracking platforms like AfterShip. This data can then be utilized to monitor deliveries among many couriers. In addition, businesses can also use tracking data from AfterShip to perform data analysis using data analytics tools, mapping every aspect of the shopping experience, from email marketing to customer retention. 

In this blog, we shall learn more about AfterShip and Redshift and how we can connect AfterShip to Redshift. 

Prerequisites

• Basic knowledge of integration

What is AfterShip?

Founded in 2012, AfterShip is a web-based application that keeps your clients informed about the progress of their orders from an online store. Businesses can use the platform’s automation features to aid with sales, marketing, order management, and shipping tracking. The platform connects the world’s e-commerce infrastructure, making buying and selling possible for anyone, anywhere. AfterShip’s solutions are utilized by clients ranging from small to medium-sized businesses to major corporations. 

Once you’ve set up an AfterShip account and integrated it with your e-commerce or online business, it is quite intuitive to use. It imports all of your store’s tracking numbers automatically. The tracking numbers can also be manually entered into the app’s dashboard. When all of the tracking numbers from your e-commerce business are imported, it simultaneously imports customer information such as phone numbers and email addresses.

At the same time, frequent email alerts are sent to purchasers anytime their tracking number is updated. This enables users to keep track of all their items and communicates with their suppliers in real-time in case of any delays or misplacements.

For example, suppose you use Forward Air or Yifan Express as a courier service. The courier service company’s database is updated every time your item’s status changes while in transit. When the courier provider updates their website with new information about your product, AfterShip sends an email (or SMS alerts) to your customer informing them of the update.

Key Features of AfterShip

Here are some features of Aftership:

• Branded tracking: A branded tracking page eliminates the need to visit a courier’s website because customers can check the status of their packages right on the website where they placed their order. Setting up a branded tracking page on your e-commerce site can give your consumers a consistent, end-to-end tracking experience. Store owners can use AfterShip to build customized tracking pages and increase income through personalization and upselling. End-to-end tracking, reroute delivery options, multilingual tracking, and more are all available on AfterShip’s branded tracking website.
• Shipment Notifications and Visibility: Customers want companies to communicate the status of their product via shipping notifications once they make a purchase. From the time an item is shipped until the time it arrives at the customer’s doorstep, AfterShip allows you to provide email, SMS, and Facebook updates. You can opt to send notifications to customers, email subscribers, or yourself to remain updated on delivery events.
• Integrations: AfterShip can integrate with a variety of e-commerce systems, including Shopify, WooCommerce, BigCommerce, Magento, and others. Apps for tracking eBay shipments, offering last-mile courier delivery, and sending timely delivery emails to clients are also available on the platform. AfterShip works with over 850 courier services globally and is constantly expanding.
• Analytics: Analyzing your shipping performance helps in finding areas where you can improve and address the bottlenecks in logistics. With AfterShip, you can monitor your delivery rate, parcel acceptance rate, and courier performance to manage logistics with an interactive dashboard that gives you insights into shipping and post-purchase performance.

Furthermore, on the branded tracking page, AfterShip analytics allows you to check your CTR and customer interaction. These findings can be used to improve a unified marketing effort. With customer review data, the platform can also allow retailers to reduce client attrition. The analytics function provides a breakdown of ratings, positive and negative reviews, and consumer feedback to help you understand problem areas in your business strategy.

Additionally, AfterShip provides notification analytics, which offers information on SMS and email engagement. If necessary, these analytics allow you to update your notification content ahead of time.

What is Amazon Redshift?

Amazon Redshift is an Amazon cloud data warehouse designed to work with a wide range of SQL-based clients, business intelligence tools, and data visualization solutions to democratize data within organizations. Amazon Redshift is built on PostgreSQL 8, which provides increased performance and efficient queries when compared to other data warehouse platforms. This enables organizations to effectively evaluate data-driven business choices before making a final decision. 

Amazon Redshift can enable quick query processing and high-class performance because of its Massively Parallel Processing (MPP) and columnar data structure layouts. In addition, Amazon Redshift includes features for managing huge datasets, high-performance analysis, and subsequent report production.

You can query and integrate exabytes of structured and semi-structured data across multiple data warehouses, operational databases, and data lakes with Amazon Redshift. Thus, allowing you to do large-scale database migrations.

AWS Redshift is used by a number of high-profile enterprises today because it is quick, secure, and allows disaster recovery across many regions in seconds. Amazon Redshift also enables you to save the results of your query to your Amazon S3 Data Lake in open formats like Apache Parquet, where you can use EMR, Athena, and SageMaker to perform additional analysis.

Key Features of Amazon Redshift

Here are some features of Amazon Redshift:

• Architecture for Massive Parallel Processing: The shared-nothing Massively Parallel Processing (MPP) architecture underpins Amazon Redshift. It consists of data warehouse clusters, each separated into a Leader Node and a group of Compute Nodes. The code is compiled and distributed by the leader node to the cluster’s various computing nodes. Each computing node is equipped with its own CPU, RAM, and disk storage. And all compute nodes are separated into slices, each of which is responsible for a proportion of the workload.
• End-to-end data encryption: Amazon Redshift’s encryption is optional, but it’s a remarkable feature that safeguards your sensitive data. Redshift’s end-to-end data encryption function is exceptionally customizable, ensuring the complete privacy of your data. Users also have complete control over configuring and utilizing a customer or AWS-managed key to change an unencrypted cluster.
• Scalability: Customers can choose the level of capability that best suits their peak workload hours, and Redshift can scale accordingly. There are two types of scaling procedures supported: classic and elastic. You can also use Redshift to quickly set up a cluster by recovering data from a snapshot. This is a great solution when consumers demand more processing resources to support high concurrency.
• Outstanding Performance: R3 instances can handle performance-intensive tasks with ease, delivering three times the performance of available alternatives. R3 instances come with an Advanced Query Accelerator (AQUA) cache that allows you to receive quicker query responses for large datasets at no extra cost. For repeated queries, Amazon returns the result instantly from the cache.
• Security: Whether the data is in transit or at rest, Redshift provides complete data security. It also assures absolute security for all Redshift-related activities, including cluster administration, cluster connection, database management, and credential management, by having third-party auditors assess the security regularly. AWS Redshift supports well-known data protection and security compliance protocols, including SOC1, SOC2, SOC3, PCI DSS Level 1, HIPAA BAA, and others. Users can also specify access rights for columns and rows. You get additional control since Redshift uses the Amazon Virtual Private Cloud to specify firewall settings and isolate your data warehouse cluster.

Connecting AfterShip to Redshift

Many organizations want to take advantage of Amazon Redshift’s ability to swiftly run complex analytical queries across petabytes of data, so they’ll need to move their data from AfterShip to Redshift service for centralized storage and further analysis. 

1) Manually Exporting and Importing Data from AfterShip to Redshift

To get started with connecting AfterShip to Redshift,

• Go to Shipments page > Set up filters
• Export shipments. 

The CSV file will be sent to the registered email address.

• To import a Google Sheets file into Amazon Redshift, first, open it in Google Sheets.
• In the top left corner, select File.

• Click Download As and then choose Comma-Separated Values (.csv). 

After that, the data will be exported to CSV and downloaded to your local machine. If you want to import data from numerous Google Sheets to Redshift, follow the same steps.

• The following steps can be used to load data from CSV files to Redshift:

• Log in to the Amazon Web Services Management Console.
• Create a bucket in the Amazon S3 Console by clicking the Create Bucket button.

• Enter a distinctive name for your AWS S3 Bucket, then choose a region that meets your needs and click Create.

• Click on the AWS S3 Bucket you just created, select Create Folder, give it an appropriate unique name, and then save it.
• By clicking Upload and choosing the relevant files in the Upload Wizard, you can upload the CSV data that was previously exported to the newly formed folder.

Now, the COPY command could be used to import data from Amazon S3 into Amazon Redshift Cluster.

• Connect to the Cluster with your preferred SQL Workbench tool and perform the following query:

#AfterShip to Redshift--

COPY table_name 
FROM 's3://<your-bucket-name>/load/file_name.csv' 
credentials 'aws_access_key_id=<Your-Access-Key-ID>' 
CSV;

#AfterShip to Redshift--

Your AfterShip data is now available on Amazon Redshift, ready to be queried.

2) Connecting AfterShip to Redshift Using APIs

You’ll need to leverage the AWS REST API to transfer your data from AfterShip to Redshift, both for data extraction and loading into the Redshift warehouse. The first step is to create a bucket, which you can accomplish by using the Amazon AWS REST API endpoints for Redshift to conduct an HTTP PUT.

You can accomplish this AfterShip to Redshift connection with a service like Postman’s shipping API, which is currently available for free and has no volume restrictions.

Once you’ve set up your bucket, use the same AWS REST API to transmit data to the input platform supported by Redshift (Amazon S3, Amazon DynamoDB, or Amazon Kinesis Firehose), but this time using the Object operations endpoints. You may either access the HTTP endpoints directly or utilize the library of your choice, just as with bucket.

The most effective approach to import data from AfterShip to Redshift is to use the COPY command to perform bulk uploads. When you use COPY commands for AfterShip to Redshift, Redshift can read multiple files at once and distributes the workload across the cluster nodes, allowing the load to be processed in parallel.

Conclusion

The article explores the importance of two distinct online solutions – online tracking service AfterShip and Cloud data warehouse Amazon Redshift. It also explains how AfterShip to Redshift connection can help enhance the offerings of AfterShip and how these platforms can be connected using APIs and manually via Google sheets.

However, there are certain limitations in carrying out the above processes. For instance, the use of APIs can be challenging if you lack an adequate understanding of the technical know-how of APIs. And, the manual exporting of data from Aftership to Redshift can be a time-consuming affair.

There are various Data Sources that organizations leverage to capture a variety of valuable data points. But, transferring data like AfterShip to Redshift, from these sources into a Data Warehouse for a holistic analysis is a hectic task.

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