Discovering insights with Customer AI
Customer AI, as part of Intelligent Services provides marketers with the power to leverage Adobe Sensei to anticipate what your customers next action is going to be. Customer AI is used to generate custom propensity scores such as churn and conversion for individual profiles at-scale. This is accomplished without having to transform the business needs to a machine learning problem, picking an algorithm, training, or deployment.
This document serves as a guide for interacting with service instance insights in the Intelligent Services Customer AI user interface.
In order to utilize insights 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.
Service instance overview
In the Adobe Experience Platform UI, click Services in the left navigation. The Services browser appears and displays available Intelligent Services. In the container for Customer AI, click Open .
The Customer AI service page appears. This page lists service instances of Customer AI and displays information about them, including the name of the instance, propensity type, how often the instance is run, and the status of the last update.
Only service instances that have completed successful scoring runs have insights.
Click on a service instance name to begin.
Next, the insights page for that service instance appears, where you are provided with visualizations of your data. The visualizations and what you can do with the data are explained in more detail throughout this guide.
Service instance details
There are two ways to view service instance details, the first is from the dashboard and the second from within the service instance.
To view details from within the dashboard, click on a service instance container avoiding the hyperlink that is attached to the name. This opens a right rail that provides additional details such as the description, scoring frequency, the prediction goal, and eligible population. Additionally, you can choose to edit and delete the instance by clicking Edit or Delete .
In the event that a scoring run fails, an error message is provided. The error message is listed under Last run details in the right rail which is only visible to failed runs.
The second way to view additional details for a service instance is located within the insights page. You can click Show more in the top-right to populate a drop down. Details are listed such as the score definition, when it was created, and the propensity type. For more information on any of the properties listed, please visit Configuring a Customer AI instance .
Edit an instance
To edit an instance, click Edit in the top-right navigation.
The edit dialog box appears, allowing you to edit the Description and Scoring Frequency of the instance. To confirm your changes and close the dialog, click Edit in the bottom-right corner.
The More actions button is located in the top-right navigation next to Edit . Clicking More actions opens a dropdown that allows you to select one of the following operations:
- Delete : Deletes the instance.
- Access scores : Clicking Access scores opens a dialog providing a link to the downloading scores for Customer AI tutorial, the dialog also provides the dataset id required for making API calls.
- View run history : A dialog containing a list of all the scoring runs associated with the service instance appears.
Scoring Summary displays the total number of profiles scored and categorizes them into buckets containing high, medium, and low propensity. The propensity buckets are determined based on score range, low is less than 24, medium is 25 to 74, and high is above 74. Each bucket has a color corresponding to the legend.
If it is a conversion propensity score, the high scores show in green and the low scores in red. If you are predicting churn propensity this is flipped, the high scores are in red and the low scores are green. The medium bucket remains yellow regardless of what propensity type you choose.
Distribution of Scores
The Distribution of Scores card gives you a visual summary of the population based on the score. The colors that you see in the Distribution of Scores card represent the type of propensity score generated.
For each score bucket, a card is generated that shows the top 10 influential factors for that bucket. The influential factors give you additional details on why your customers belong to various score buckets.
Create a segment
Clicking the Create Segment button in any of the buckets for Low, Medium, and High propensity redirects you to the segment builder.
The Create Segment button is only available if Real-time Customer Profile is enabled for the dataset. For more information on how to enable Real-time Customer Profile, visit the Real-time Customer Profile overview .
The segment builder is used to define a segment. When selecting Create Segment from the Insights page, Customer AI automatically adds the selected buckets information to the segment. To finish creating your segment, simply fill in the Name and Description containers located in the right rail of the segment builder user interface. After you have given the segment a name and description, click Save in the top-right.
Since the propensity scores are written to the individual profile, they are available in the Segment builder like any other profile attributes. When you navigate to the segment builder to create new segments you can see all the various propensity scores under your namespace Customer AI.
To view your new segment in the Platform UI, click Segments in the left navigation. The Browse page appears and displays all available segments.
The following video outlines how to use Customer AI to see the output of the models and influential factors.