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.
As an advanced, high-speed data analytics platform, Mode helps you understand the information in your data warehouses. As a hybrid solution Mode lets (1) data teams customize queries and visualizations in Python, SQL, or R; and (2) empowers non-tech-savvy users to dive into visualizations and explore live-updating reports to get the data they need.
Popular Use Cases
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 Mode data to Amazon Redshift
Load your Mode data to Google BigQuery
ETL all your Mode data to Snowflake
Move your Mode data to MySQL
CallRail's End Points
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.
Mode's End Points
Mode White-Label Embeds and Visualizations
Mode SQL Editor
Mode's SQL editor features a schema browser to explore the tables and columns of your connected data sources. It also has an autocomplete function to assist with query writing, a query history to browse and reuse old queries, and advanced logic tools for creating loops, IF statements, and more.
Mode Helix Data Engine
The technology behind Mode's analytics solution is Helix, a high-performance in-memory data engine that combines modern drag-and-drop business intelligence tools with a code-first (SQL, Python, R) data science platform to offer an instantly responsive user experience. Mode streams query results into the Helix data engine to reduce database load, provide quick responsiveness, and give users the ability to visually navigate as much as 10 gigabytes of data.
Mode Dashboard Features
Powered by SQL, Python, and R, Mode dashboards display automatically-refreshing metrics without the need for proprietary tools. Customize your dashboards the way you want, with on-brand reporting and interactive features to facilitate collaboration with others across your organization.
Mode Native Python and R Notebooks
Mode features native Python and R Notebooks. This allows you to query in SQL, send the results to a dataframe in R or pandas, and conveniently access them in the platform's native Notebook. At the same time, a sidebar provides tips, shortcuts, and documentation to help you get the most of these features.