CallRail provides businesses with tracking phone numbers that they can use to gather valuable customer interaction data from phone calls. This includes the source of the call - an advertisement on social media, for example - as well as information about the callers themselves. Additionally, once a call is completed, CallRail automatically generates a transcript of the call. By gathering this data, CallRail allows businesses to score their leads more easily and gauge the effectiveness of different marketing campaigns.
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 CallRail data to Amazon Redshift
Load your CallRail data to Google BigQuery
ETL all your CallRail data to Snowflake
Move your CallRail 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
Create separate companies with different configurations and tracking numbers. Then, you can retrieve information like the company’s name, creation date, lead scoring settings and company ID. This will allow you to track each different parameter in your analytics.
Track any users who have access to your call data at various permission levels. This field provides you with contact information about the user - including their name, email, user ID, role and company - so that you can integrate your user and company data for analysis.
Retrieve an account’s name and ID and choose whether or not to enable outbound call recording. Since this is the top level object for CallRail, you can also use that account ID to integrate data - such as “Company” or “Tracker” - that is generated by any lower level object within that account.
Retrieve data from other data sources by integrating CallRail data with third party tools. The data in this field includes the name of the third party tool being integrated, the type of integration, its status, the unique integration ID, and associated companies. CallRail can use all of this data to provide more robust marketing analytics.
Gather call data from tracking numbers that can either be linked to a specific source or associated with a particular visitor. This field can retrieve a variety of data from those calls, including the tracker ID, tracking numbers and associated companies. This information can help you qualify leads and gauge the effectiveness of marketing campaigns.
Retrieve data on an individual call, including the duration, source, phone number and status i.e., whether it was answered, missed, etc. Additionally, you can retrieve contact information for the caller, including their name, phone number, and whether or not CallRail rates the call as having provided a good lead.
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.