Connect to the Adobe Analytics API v2.0, which powers Analysis Workspace. The package was developed with the analyst in mind and will continue to be developed with the guiding principles of iterative, repeatable, timely analysis. New features are actively being developed, and we value your feedback and contribution to the process. Please submit bugs, questions, and enhancement requests as issues in this Github repository.
A special thanks to our company, Further (formally Search Discovery), for giving us the time, encouragement, and support to build out this package. There is no way this would have been possible without the opportunity to learn from and work with some of the most amazing people in the analytics industry.
The Adobe Analytics v1.4 API, while on its way out, still has some functionality that is not (yet?) available in the v2.0 API. As such, the RSiteCatalyst package created by Randy Zwitch remains a useful package. While this is not a comprehensive list, some of the features that are available through RSiteCatalyst that are not available through the v2.0 API (and, by extension, are not available through this package) are:
The v1.4 API also allows the user to pull data once they have web services access set up for their account and the client ID and client secret that comes along with that. In other words, it does not require that an Adobe Console API project be created, which is something that is required to use the v2.0 API. The benefit of getting an Adobe Console API project set up, though, is that the user then does not need web services access set up on an account-by-account basis to pull data using the package if using the OAUTH authentication. If using the JWT authentication method with v2.0 API, then a project does need to be created for each company account.
As a purely editorial side note, the creators and maintainers of this package would like to express their eternal gratitude to Randy for the work he put in to creating and maintaining
RSiteCatalyst. His work brought the power of R combined with data pulled directly via the Adobe Analytics API to a global audience, and we can only hope (for ourselves and the analyst community writ large) that
adobeanalyticsr can live up to the high standard he set with his work.
# Install from CRAN install.packages('adobeanalyticsr') # Load the package library(adobeanalyticsr)
# Install devtools from CRAN install.packages("devtools") # Install adobeanayticsr from github devtools::install_github('benrwoodard/adobeanalyticsr') # Load the package library(adobeanalyticsr)
There are four setup steps required to start accessing your Adobe Analytics data. The following steps are each outlined in greater detail in the following sections:
aw_auth_with(type = ""). The
typevalue should be jwt or oauth
aw_auth(). Once the authorization type has been set (the previous step), this will look for
.Renvironvariables and complete the authorization.
company_idby using the function
If you are using the OAuth authorization, regardless of how many different Adobe Analytics accounts you will be accessing, you only need a single Adobe Console API project (you will still need to have working user credentials for each account you want to access, but the Adobe Console API project is just the way you then get access to authenticate using those user credentials; yes…confusing!) If you are using the JWT authorization then you will need an Adobe Console API project created for each company you will be accessing. The following steps will get you setup on either of the different authorizations:
* This is simply a helper site we’ve set up in order to make it easier to generate a token. The site does not store any information.
Creating an Adobe Console API Project in under 60 seconds
This file is essential to keeping your information secure. It also speeds up analysis by limiting the number of arguments you need to add to every function call.
If you do not have an
.Renviron file (if you have never heard of this file you almost certainly don’t have one!), then create a new file and save it with the name
.Renviron. You can do this from within the RStudio environment and save the file either in your
Home directory (which is recommended; click on the Home button in the file navigator in RStudio and save it to that location) or within your project’s working directory.
Get the following variables from the OAuth project and add them to the file* (see Creating an Adobe Console API Project above):
AW_CLIENT_ID– the client id found in the Adobe Developer Console
AW_CLIENT_SECRET– the client secret key found in the Adobe Developer Console
AW_PRIVATE_KEY– unzip the downloaded config.zip file and move the .key file to a convenient location. An example file name is
~/aa_20_api/private.key. This variable,
AW_PRIVATE_KEY, should reference the accurate path for the file.
AW_AUTH_FILE– The path of a JSON file containing fields with JWT authentication data. This file may be found packaged in the
config.zipfile, or you may create it yourself. See below.
AW_REPORTSUITE_ID variables once you know them (how to find available values for these two variables is described in step 4 below).
After adding these variables to the
.Renviron file and saving it, restart your R session (Session > Restart R in RStudio) and reload
* The format of variables in the
.Renviron file is straightforward. If you add all four of the variables above, they would simply each be their own line in the file:
## If using OAuth AW_CLIENT_ID = "[OAuth client ID]" AW_CLIENT_SECRET = "[OAuth client secret]" AW_COMPANY_ID = "[Company ID]" AW_REPORTSUITE_ID = "[RSID]" ## If using JWT AW_AUTH_FILE = "[auth_file.json]" AW_PRIVATE_KEY = "[private.key]" AW_COMPANY_ID = "[Company ID]" AW_REPORTSUITE_ID = "[RSID]"
An example authentication JSON file contains the following at a minimum:
Other fields are simply ignored. Note:
API_KEY means the same thing as
The token is actually a lonnnnng alphanumeric string that is the what ultimately enables you to access your data:
OAuth process OAuth requires an interactive environment (see step 3 below), and the authentication token expires after 24 hours, which then requires repeating steps 2-9 below:
aw_auth_with('oauth')and press Enter.
aw_auth()and press Enter.
adobeanalyticsr.com* and a screen that displays your token.*
As noted above, this token will expire every 24 hours, so you will have to periodically repeat this step.
* Again, this is simply a helper site I’ve set up in order to make it easier to generate a token. The site does not store any information.
JWT process JWT does not require an interactive environment and does not require a token refresh every 24 hours, but it does require a bit more work to set up initially (as described above). To authenticate using JWT:
aw_auth_with('jwt')and press Enter.
aw_auth()and press Enter.
The last step is to get your
company_id (or, if you have access to multiple accounts, get the
company_id you want to work with). This is also an excellent way to confirm that everything is set up correctly:
get_me()and press Enter.
.Renvironfile as described in step 2 above. Otherwise, you can specify it within each function call that requires it.
AW_REPORTSUITE_IDin your file as described in step 2 above. You can retrieve all of the report suite IDs for a given
company_idusing the function
aw_get_reportsuites(company_id = '[the company ID for account of interest]').
If you added any values to your
.Renviron file (and then saved it!), then restart your R session (Session > Restart R in RStudio) and reload