AppJolt lets you analyze, recapture, survey and monetize users who update & uninstall your app.

Integrating AppJolt with Cooladata allows you to append your existing analytics with uninstall data, link to any event you are currently tracking, and instantly find out who, why and when users are uninstalling your apps.

For example:

  • You invested in paid acquisition campaigns, but did you measure which campaign has the highest uninstall rate? Track each media source all the way to the uninstall event.
  • Tie in any behavior, retention and user engagement metric you are currently tracking all the way to the user uninstall.
  • Track specific cohorts and profiles to see who is uninstalling your app.
  • Integrate in less than five minutes to enhance your existing in-app reports with uninstall data.
  • Available for both iOS and Android
  • Free service to all developers regardless of uninstall volume

Upon the uninstallation event, Appjolt sends the event to CoolaData and it is added to that user’s events, and can be associated to any other action performed by that user.


Integration with CoolaData

Setup the integration in two quick steps:

  1. Connect to Cooladata in Appjolt admin console: In Appjolt’s developer zone, click on the CoolaData icon and enter your CoolaData app key, as found in the project>Tracking page.
  2. Identify your users in Appjolt: Identify the user by using the setIdentify(id) method. Pass Appjolt the same userId you pass to CoolaData in the initialization of the app or the event tracking. For example:
    String userId = "user_id"; // sample user ID, replace with actual
    // CoolaData Init - with user ID
    "app_key": "aknek0zuo8i4ztcmgopn5wotsceg80m9" // sample app key, replace with actual
    // Appjolt UserId identifying

    For more information on user identification see Appjolt Identifying Users for Analytic Partners documentation.

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Segment is the single platform that collects, translates, and routes your user data to hundreds of analytics & marketing tools with the flip of a switch. By integrating Segment with Cooladata you can track events using the Segment APIs from any source and save them to your Cooladata project, in addition to or instead of using Cooladata’s SDKs or APIs.

Segment integration with Cooladata works via Amazon Kinesis. Integrating Segment with Cooladata allows you to stream event data via Amazon Kinesis in addition to, or instead of using Cooladata’s SDKs or APIs.



Settings up a Segment integration

  1. Set up an Amazon Kinesis integration, as explained here.
  2. In your Segment account, set up a new Amazon Kinesis source. You will need the following details:
    1. AWS User access KEY ID
    2. AWS Kinesis Stream Regio: use “us-east-1”
    3. AWS user secret  access KEY
    4. AWS Stream kinesis name
  3. Click “Activate integration”

For more information on Segment’s integration with Amazon Kinesis see Segment’s documentation.



Cooladata supports the following Segment APIs:

  • Identify
  • Track
  • Page
  • Screen

For more information on the various Segment APIs see Segment’s documentation.


Event structure

Segment events are slightly different from Cooladata events. Segment events use nested JSON, and have different property names than Cooladata. When integration Segment and Cooladata, Cooladata flattens these event Segment property names are mapped to Cooladata properties.

JSON Flattening:

When a Segment event contains a nested JSON, it will be flattened using the standard JSON format. For example:


 will be converted to


Thus, the property name of this key will be “a.b”.


Property Mapping

Segment property names are mapped to Cooladata properties according to the following table. Where more than one Segment property can apply, the priority matches the order in the table.

Segment PropertyCooladata Property
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Firebase is Google’s mobile platform that helps you quickly develop high-quality apps and grow your business.

You can now integrate Firebase with Cooladata so that all the events generated by Analytics for Firebase will be sent as any other event to your Cooladata project.

To do so, you will need to link your Firebase app to BigQuery. Linking your Firebase app to BigQuery allows you to access your raw, unsampled event data along with all of your parameters and user properties.

Once you’ve linked your Firebase app to a BigQuery project, we will connect it to your Cooladata project. This will stream all your event data directly into your Cooladata project, where you can query, export or join your data with data from other platforms and data sources in your project, to perform custom analysis.

To set up a new Firebase integration, contact your Customer Success Manager or email us at

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Amazon Kinesis

Amazon Kinesis is a cloud-based service for real-time data streaming, able to process thousands of data streams per-second. It has some similarities in functionality to Apache Kafka.

Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Integrating Amazon Kinesis allows you to stream event data in real time via Amazon Kinesis, in addition to or instead of using Cooladata’s SDKs or APIs.

If you already use Amazon Kinesis, you can use your existing service to integrate with Cooladata. If not, we can create one for you.

Using your own Amazon Kinesis account

  1. Contact your CSM or email us at to set up a new integration.
  2. Provide your CSM with the following details:
    • IAM User Access Key ID
    • IAM User AWS Secret Access Key
    • AWS Kinesis Stream Name
  3. Your CSM will provide you with the Cooladata service account details. In your AWS account, allow Cooladata read permissions on your Kinesis server.

Once done, all events sent to the Kinesis server defined will also be tracked by Cooladata, the same way as any event sent from the SDKs.


Setting up a new Amazon Kinesis account

  1. Contact your CSM or email us at to set up a new integration.
  2. We will create a new Kinesis server account for you and provide you with all the access information to it.

Once done, all events sent to the Kinesis server defined will also be tracked by Cooladata, the same way as any event sent from the SDKs.

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Google Cloud Storage


CoolaData provides an integration option that enables you to upload the content of any CSV or JSON file from a Google Cloud Storage bucket into your CoolaData project. This type of integration is typically used to enrich your CoolaData events with your own data.

CoolaData creates a dedicated bucket for you in Google Cloud Storage and then automatically uploads the file name and file type that you specify every hour.

To upload content into CoolaData from a Google Cloud Storage Bucket:

  1. Contact your CoolaData customer success representative or write to Ask them to create a Google Cloud Storage bucket for you into which you can dump your CSV and JSON files to be integrated into CoolaData.
  2. Upload your files into this Google Cloud Storage bucket. For example, by using the UPLOAD FILES button in the Google Cloud Platform user interface. You could also use the gsutil tool in order to automate this process. See the following link for some useful commands:
  3. Follow the instructions in Integrating with Predefined Data Sources and then select Google Cloud Storage:
  4. Fill in the following:
    • Integration Name – The name of this integration.
    • Load data only once – Check this option to specify that CoolaData only loads the data from your CoolaData bucket once. Otherwise, data is loaded every hour, if available.
    • Upload Data Format – Select CSV or JSON to specify the format of the files to be uploaded from your CoolaData bucket. JSON files must be flat (not nested) newline – delimited.
    • File Name – The file name to be uploaded. Make sure to add the file type ending, such as csv/json.
    • Use File Name as Table Name – Check this box to specify that the name of the table that is created in CoolaData is the same as the File Name (described above). This is the table name to be used in the queries that you will perform on the uploaded data. If you choose this option, then make sure that the file name is a valid table name.
    • Table Name – If you did not select the option above, then enter the name of the table to be created in CoolaData to contain the data that is uploaded. Like all table names, it is case sensitive and cannot include spaces or special characters.
    • Append Date to the Table Name – Appends the date when the table is created to the table name. A new table partition is created for each date. Its format is TableName_YYYYMMDD. Selecting this feature enables you to use Google’s BigQuery Data Partitioning feature. You may contact your CoolaData’s customer success representative to hear more about this feature.
    • File Scheme – Define the scheme of the columns of the table to be uploaded by defining the name and data type of each column. Click the Add + button to add each new column. The following data types are supported – string, integer, float, Boolean and timestamp. For example, name:STRING, id:INTEGER, birthdate:TIMESTAMP.
    • In the Insert Strategy field, select either –
      • Append New data is added to the table each time data is uploaded.
        – OR –
      • Replace The table is overwritten each time the data is uploaded.
    • In the Emails to Notify If the Failure field, type in the emails to whom to send integration upload and failure notifications.
    • [Optional] You can use the Google Project ID and Google Dataset fields to define that CoolaData uploads data from your CoolaData bucket into your own Google project instead of into your CoolaData project. Contact your CoolaData customer success representative for more information.
  5. Click the Save button.

Each hour CoolaData will then integrate the files that are dropped into this bucket into your project. The first integration process should take place within a few minutes.
After CoolaData has integrated the files into your CoolaData project, the CoolaData Google bucket is emptied. The files are moved to a subfolder named Uploaded in the bucket and a timestamp is appended to the beginning of the file name. The syntax is – YYYYMMDD_filname.filetype. For example, 20160823_stats.csv.

The Status column of the Integrations list changes to show Data Received.
If the integration process fails for any reason, then the file is moved to a subfolder in the bucket named Failed. An email is sent to the specified recipient(s) (described above) alerting them regarding the integration failure. The same filename convention would be applied in the Failed folder as well.

Data can now be queried using the following syntax:

FROM tableName


Date Format

Define the Date Format to recognize and convert timestamps columns so they can be used as such in Cooladata. All JAVA standard time formats are supported. The following characters can be used – 1-3 chars represents the abbreviated form, if one exists; 4+ chars represents the full form. The date syntax is case sensitive, so (for example) MM represents month and mm represents seconds.

Letter Date or Time Component Presentation Examples
G Era designator Text AD
y Year Year 1996; 96
M Month in year Month July; Jul; 07
w Week in year Number 27
W Week in month Number 2
D Day in year Number 189
d Day in month Number 10
F Day of week in month Number 2
E Day in week Text Tuesday; Tue
a Am/pm marker Text PM
H Hour in day (0-23) Number 0
k Hour in day (1-24) Number 24
K Hour in am/pm (0-11) Number 0
h Hour in am/pm (1-12) Number 12
m Minute in hour Number 30
s Second in minute Number 55
S Millisecond Number 978
z Time zone General time zone Pacific Standard Time; PST; GMT-08:00
Z Time zone RFC 822 time zone -800


Date Format
04-18-17 MM-dd-yy
18-04-2017 dd-MM-yyyy
18/04/2017 19:36:55 dd/MM/yyyy HH:mm:ss
18/04/2017 07:36:55 dd/MM/yyyy hh:mm aa
Tue 04/18/2017 EEE MM/dd/yyyy
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