MailChimp is a marketing service designed to improve your email campaigns through easy-to-design, automated, and personalized emails. Some of the features that MailChimp uses to increase campaign performance include drag-and-drop email templates, automated product suggestions, follow-up emails based on customer actions and revenue reports. These can help refocus marketing campaigns to provide the customer experience that is most likely to translate into sales.
Amazon Kinesis is a powerful analytics solution that overcomes the batch-processing challenges of Hadoop — and similar solutions — which don't allow real-time precision in decision-making because they can't rapidly process high volumes of streaming data. With its ability to process hundreds of terabytes of streaming data per hour, Kinesis allows you to develop apps that rely on real-time data to fuel AI analytics, machine learning insights, and other applications. Kineses enables instant responses by eliminating the delay associated with batch processing.
Bring all your MailChimp data to Amazon Redshift
Load your MailChimp data to Google BigQuery
ETL all your MailChimp data to Snowflake
Move your MailChimp data to MySQL
Bring all your Amazon Kinesis data to Amazon Redshift
Load your Amazon Kinesis data to Google BigQuery
ETL all your Amazon Kinesis data to Snowflake
Move your Amazon Kinesis data to MySQL
Monitor replies to your email campaigns based on a number of filters, including which campaigns have unread messages, which replies are part of a specific campaign and the dates that the replies were sent on. This allows you to more carefully track customer responses to your marketing efforts so that you can integrate that data into your marketing analytics efforts.
Track an array of analytical data about your MailChimp campaigns, including how many emails have been sent, whether they were delivered or bounced and how the recipients interacted with them (whether they opened them, forwarded them, subscribed, unsubscribed, etc). These reports can inform future campaign design by providing you with deeper analytics about which campaigns were most successful and why.
Retrieve data about your email campaigns, including the recipients, the type of campaign and how many emails have been delivered since the campaign began. You can then use this information to closely monitor the success of each campaign, which can be especially useful for those that are designed to test for marketing effectiveness, such as A/B campaigns.
Create a list of contacts that are subscribed to your email campaigns and define details about the campaigns themselves (like the email address that the emails will send from). Then, you can request metrics related to that list, such as how many emails have been delivered, how many subscribers the list has and how many people have unsubscribed since a campaign began.
Create targeted, automatic campaigns that will send emails in response to time-based and activity-based triggers. You can also use this endpoint to retrieve information about a specific automation, including how many emails have been delivered, what the defined triggers are and who the recipients are.
Amazon Kineses Video Streams allow you to safely ingest streaming video data from millions of linked devices into AWS for machine learning, analytical, and other processing purposes. The platform then encrypts, stores, and indexes the video data so you can access video with simple APIs, play live video streams, and offer on-demand playback. When incorporating this technology with Amazon Rekognition Video, TensorFlow, ApacheMxNet, and OpenCV, Amazon Kineses Video Streams makes it possible to build video analytics and computer vision processes into your applications.
By capturing, processing, and storing data streams, Amazon Kinesis offers a real-time data streaming solution to ingest large amounts of information from hundreds of thousands — even millions — of sources at the gigabytes-per-second scale. The massive scalability of this solution lets you capture and produce immediate analytics on data pertaining to financial transactions, database event streams, location tracking data, clickstreams, social media activity, and more. Since the availability of streaming data happens in milliseconds, the platform enables real-time analytics of this information for instant detection of anomalies, dynamic price adjustments, precise dashboard metrics, and more.
Amazon Kinesis Data Firehose provides a simple and durable way to pull your streaming data into data warehouses, data lakes, and analytics solutions. Due to its compatibility with Splunk, Amazon Redshift, Amazon S3, and Amazon Elasticsearch Service, Kinesis Data Firehose empowers real-time data analytics for the dashboarding and BI tools you've come to trust. Fully managed and automatically scaling, you can use Firehose to encrypt, batch, transform, and compress your information before ingestion to boost security and save on disk space.
Amazon Kinesis Data Analytics helps users without programming knowledge to analyze data streams with SQL or Java. For team members who know SQL, an SQL editor and templates are available for creating streaming applications or querying streaming data. Meanwhile, those with Java knowledge can develop more nuanced streaming applications that perform real-time data transformations and analytical processes.