analytics-mayhem-adobe 0.0.3

Manage Adobe Analytics Reports API v2 requests to build reports programmatically.

Adobe Analytics Python package

Download Reports data utilising the Adobe.io version 2.0 API.

For more Digital Analytics related reading, check https://analyticsmayhem.com

Requirements

Adobe.io access

In order to run the package, first you need to gain access to a service account from Adobe.io. The method used is JWT authentication. More instructions on how to create the integration at: https://www.adobe.io/authentication/auth-methods.html#!AdobeDocs/adobeio-auth/master/JWT/JWT.md. After you have completed the integration, you will need to have available the following information:

• Organization ID (issuer): It is in the format of < organisation id >@AdobeOrg
• Technical Account ID: < tech account id >@techacct.adobe.com
• Client ID: Information is available on the completion of the Service Account integration
• Client Secret: Information is available on the completion of the Service Account integration
• Account ID: Instructions on how to obtain it at https://youtu.be/lrg1MuVi0Fo?t=96
• Report suite: Report suite ID from which you want to download the data.

Make sure that the integration is associated with an Adobe Analytics product profile that is granted access to the necessary metrics and dimensions.

Package installation

pip install analytics-mayhem-adobe

Samples

Initial setup

After you have configured the integration and downloaded the package, the following setup is needed:

from analytics.mayhem.adobe import analytics_client

adobe_org_id = '<adobe org id>@AdobeOrg'
subject_account = '<technical account id>@techacct.adobe.com'
client_id = '<client id>'
client_secret = '<client secret>'
private_key_location = '.ssh/adobe-auth/private.key'
account_id = '<account id>'
report_suite_id = '<report suite>'

Next initialise the Adobe client:

aa = analytics_client( \
    adobe_org_id = adobe_org_id, \
    subject_account = subject_account, \
    client_id = client_id, client_secret = client_secret, \
    account_id = account_id, \
    private_key_location = private_key_location)

Request with 3 metrics and 1 dimension

aa.set_report_suite(report_suite_id = report_suite_id)
aa.add_metric(metric_name= 'metrics/visits')
aa.add_metric(metric_name= 'metrics/orders')
aa.add_metric(metric_name= 'metrics/event1')
aa.add_dimension(dimension_name = 'variables/mobiledevicetype')
aa.set_date_range(date_start = '2019-12-01', date_end= '2019-12-31')
data = aa.get_report()

Output:

itemId_lvl_1	value_lvl_1	metrics/visits	metrics/orders	metrics/event1
0	Other	5000	3	100
1728229488	Tablet	200	45	30
2163986270	Mobile Phone	49	23	31
...	...	...	...	...

Request with 3 metrics and 2 dimensions

aa.set_report_suite(report_suite_id = report_suite_id)
aa.add_metric(metric_name= 'metrics/visits')
aa.add_metric(metric_name= 'metrics/orders')
aa.add_metric(metric_name= 'metrics/event1')
aa.add_dimension(dimension_name = 'variables/mobiledevicetype')
aa.add_dimension(dimension_name = 'variables/lasttouchchannel')
aa.set_date_range(date_start = '2019-12-01', date_end= '2019-12-31')
data = aa.get_report_multiple_breakdowns()

Output: Each item in level 1 (i.e. Tablet) is broken down by the dimension in level 2 (i.e. Last Touch Channel). The package downloads all possible combinations. In a similar fashion more dimensions can be added.

itemId_lvl_1	value_lvl_1	itemId_lvl_2	value_lvl_2	metrics/visits	metrics/orders	metrics/event1
0	Other	1	Paid Search	233	39	10
0	Other	2	Natural Search	424	12	412
0	Other	3	Display	840	41	31
...	...	...	...	...	...	...
1728229488	Tablet	1	Paid Search	80	12	41
1728229488	Tablet	2	Natural Search	50	41	21
...	...	...	...	...	...	...

Issues, Bugs and Suggestions:

https://github.com/konosp/adobe-analytics-reports-api-v2.0/issues

Known missing features:

• No support for filtering
• No support for segments
• No support for custom sorting
• Not much customisation on the private key location