Download scores in Customer AI

This document serves as a guide for downloading scores for Customer AI.

Getting started

Customer AI allows you to download scores in the Parquet file format. This tutorial requires that you have read and finished the downloading Customer AI scores section in the getting started guide.

Additionally, in order to access scores for Customer AI, you need to have a service instance with a successful run status available. To create a new service instance, visit Configuring a Customer AI instance. If you recently created a service instance and it is still training and scoring, please allow 24 hours for it to finish running.

Currently, there are two ways to download Customer AI scores:

Find your dataset ID dataset-id

Within your service instance for Customer AI insights, click the More actions dropdown in the top-right navigation then select Access scores.

A new dialog appears, containing a link to the downloading scores documentation and the dataset ID for your current instance. Copy the dataset ID to your clipboard and proceed to the next step.

Retrieve your batch ID retrieve-your-batch-id

Using your dataset ID from the previous step, you need to make a call to the Catalog API in order to retrieve a batch ID. Additional query parameters are used for this API call in order to return the latest successful batch instead of a list of batches belonging to your organization. To return additional batches, increase the number for the limit query parameter to the desired amount you wish to be returned. For more information on the types of query parameters available, visit the guide on filtering Catalog data using query parameters.

API format

GET /batches?&dataSet={DATASET_ID}&createdClient=acp_foundation_push&status=success&orderBy=desc:created&limit=1

Request

curl -X GET 'https://platform.adobe.io/data/foundation/catalog/batches?dataSet=5cd9146b31dae914b75f654f&createdClient=acp_foundation_push&status=success&orderBy=desc:created&limit=1' \
  -H 'Authorization: Bearer {ACCESS_TOKEN}' \
  -H 'x-api-key: {API_KEY}' \
  -H 'x-gw-ims-org-id: {ORG_ID}' \
  -H 'x-sandbox-name: {SANDBOX_NAME}'

Response

A successful response returns a payload containing a batch ID object. In this example, the key value to the object returned is the batch ID 01E5QSWCAASFQ054FNBKYV6TIQ. Copy your batch ID to use in the next API call.

{
    "01E5QSWCAASFQ054FNBKYV6TIQ": {
        "status": "success",
        "tags": {
            "Tags": [ ... ],
        },
        "relatedObjects": [
            {
                "type": "dataSet",
                "id": "5cd9146b31dae914b75f654f"
            }
        ],
        "id": "01E5QSWCAASFQ054FNBKYV6TIQ",
        "externalId": "01E5QSWCAASFQ054FNBKYV6TIQ",
        "replay": {
            "predecessors": [
                "01E5N7EDQQP4JHJ93M7C3WM5SP"
            ],
            "reason": "Replacing for 2020-04-09",
            "predecessorListingType": "IMMEDIATE"
        },
        "inputFormat": {
            "format": "parquet"
        },
        "imsOrg": "412657965Y566A4A0A495D4A@AdobeOrg",
        "started": 1586715571808,
        "metrics": {
            "partitionCount": 1,
            "outputByteSize": 2380339,
            "inputFileCount": -1,
            "inputByteSize": 2381007,
            "outputRecordCount": 24340,
            "outputFileCount": 1,
            "inputRecordCount": 24340
        },
        "completed": 1586715582735,
        "created": 1586715571217,
        "createdClient": "acp_foundation_push",
        "createdUser": "sensei_exp_attributionai@AdobeID",
        "updatedUser": "acp_foundation_dataTracker@AdobeID",
        "updated": 1586715583582,
        "version": "1.0.5"
    }
}

Retrieve the next API call with your batch ID retrieve-the-next-api-call-with-your-batch-id

Once you have your batch ID, you are able to make a new GET request to /batches. The request returns a link thats used as the next API request.

API format

GET batches/{BATCH_ID}/files

Request

Using your own batch ID, make the following request.

curl -X GET 'https://platform.adobe.io/data/foundation/export/batches/035e2520-5e69-11ea-b624-51evfeba55d1/files' \
  -H 'Authorization: Bearer {ACCESS_TOKEN}' \
  -H 'x-api-key: {API_KEY}' \
  -H 'x-gw-ims-org-id: {ORG_ID}' \
  -H 'x-sandbox-name: {SANDBOX_NAME}'

Response

A successful response returns a payload containing a _links object. Within the _links object is an href with a new API call as its value. Copy this value to proceed to the next step.

{
    "data": [
        {
            "dataSetFileId": "035e2520-5e69-11ea-b624-51ecfeba55d0-1",
            "dataSetViewId": "5e3b2fe3fe4b9f18a8b7a3db",
            "version": "1.0.0",
            "created": "1583361894479",
            "updated": "1583361894479",
            "isValid": false,
            "_links": {
                "self": {
                    "href": "https://platform.adobe.io:443/data/foundation/export/files/035e2520-5e69-11ea-b624-51ecfeba55d0-1"
                }
            }
        }
    ],
    "_page": {
        "limit": 100,
        "count": 1
    }
}

Retrieve your files retrieving-your-files

Using the href value you got in the previous step as an API call, make a new GET request to retrieve your file directory.

API format

GET files/{DATASETFILE_ID}

Request

curl -X GET 'https://platform.adobe.io:443/data/foundation/export/files/035e2520-5e69-11ea-b624-51ecfeba55d0-1' \
  -H 'Authorization: Bearer {ACCESS_TOKEN}' \
  -H 'x-api-key: {API_KEY}' \
  -H 'x-gw-ims-org-id: {ORG_ID}' \
  -H 'x-sandbox-name: {SANDBOX_NAME}'

Response

The response contains a data array that may have a single entry, or a list of files belonging to that directory. The example below contains a list of files and has been condensed for readability. In this scenario, you need to follow the URL of each file in order to access the file.

{
    "data": [
        {
            "name": "part-00000-tid-7597930103898538622-a25f1890-efa9-40eb-a2cb-1b378e93d582-528-1-c000.snappy.parquet",
            "length": "16214531",
            "_links": {
                "self": {
                    "href": "https://platform.adobe.io:443/data/foundation/export/files/035e2520-5e69-11ea-b624-51ecfeba55d0-1?path=part-00000-tid-7597930103898538622-a25f1890-efa9-40eb-a2cb-1b378e93d582-528-1-c000.snappy.parquet"
                }
            }
        },
        {
            "name": "...",
            "length": "16235375",
            "_links": {
                "self": {
                    "href": "..."
                }
            }
        }
    ],
    "_page": {
        "limit": 100,
        "count": 100
    },
    "_links": {
        "next": {
            "href": "..."
        },
        "page": {
            "href": "...",
            "templated": true
        }
    }
}

Copy the href value for any file object in the data array, then proceed to the next step.

Download your file data

To download your file data, make a GET request to the "href" value you copied in the previous step retrieving your files.

API format

GET files/{DATASETFILE_ID}?path={FILE_NAME}

Request

curl -X GET 'https://platform.adobe.io:443/data/foundation/export/files/035e2520-5e69-11ea-b624-51ecfeba55d0-1?path=part-00000-tid-7597930103898538622-a25f1890-efa9-40eb-a2cb-1b378e93d582-528-1-c000.snappy.parquet' \
  -H 'Authorization: Bearer {ACCESS_TOKEN}' \
  -H 'x-api-key: {API_KEY}' \
  -H 'x-gw-ims-org-id: {ORG_ID}' \
  -H 'x-sandbox-name: {SANDBOX_NAME}' \
  -O 'filename.parquet'

Response

The response downloads the file you requested in in your current directory. In this example the filename is “filename.parquet”.

Download a segment configured with Customer AI segment

An alternative way to download your score data is by exporting your audience to a dataset. After a segmentation job has successfully completed (the value of the status attribute is “SUCCEEDED”), you can export your audience to a dataset where it can be accessed and acted upon. To learn more about segmentation, visit the segmentation overview.

The export a segment section in the segment evaluation guide covers the required steps to export an audience dataset. The guide outlines and provides examples of the following:

Next steps

This document outlined the steps required for downloading Customer AI scores. You can now continue to browse the other Intelligent Services and guides that are offered.