Step 16 - Add Predictive Lead and Account Scoring (PLAS)
Automate rule-based B2B person and account scores with Intelligent Service.
Predictive lead and account scoring is one of the Intelligent Services offered in Adobe Experience Platform to automate the scoring process by learning from and predicting for the opportunity stage conversion events, and aggregating person activities onto the account level to produce the account scores. The scores are readily available as custom fields on person profiles and account profiles and can be easily included as segment criteria to refine your audience.
Scoring Results
Configure and Activities event data
Predictive lead and account scoring service require the following conditions to be satisfied for evaluation:
- "Person" should be created (_repo.createDate) 60 days before the scheduled execution date.
- "Activities" (events) should be at least 5K, spanned across the 2 years (as we have observed).
Before we begin the process, we should create new datasets for Accounts, Persons, and Activities and enable those for profiles. It's a good practice; in case, you need to undo the data ingestion. Refer to the following schemas for creating datasets:
- Demo System - B2B Account
- Demo System - B2B Person
- Demo System - B2B Activity
Data files
Once we are ready to ingest data, visit Demo System - Data for PLAS tool to generate data w.r.t. Marketo instance.
Limitations/information
- The tool generates a fixed number of Accounts, Persons, and Activities # of Accounts: 40 # of Persons: 100 # of Activities: 5,000
- Data generated considered Marketo as the B2B data source.
- Tool refers to sample Person data, which is defaulted with the Market demo instances. So, you can leverage the ingested Activities to show in the timeline.
- Activities generated store basic data to initiate a PLAS instance i.e. values for Event type eventType.
- Output data format: XDM-compliant JSON file.
Ingestion and setting up PLAS instance
Download the B2B data generated by the above-mentioned tool, by clicking on respective buttons.
Upload data to respective datasets (as mentioned above).
After uploading data files to corresponding datasets, wait for data ingestion and identity stitching to complete.
After data ingestion is completed, proceed to set up Predictive lead account scoring Predictive lead and account scoring, following the instructions.
With the data generated, please keep the setup simple as shown in the example below
Do not specify any "Goal specifics" and click "Finish" to complete setup.
Monitor model training/processing
After you've successfully created an instance, the setup of the Intelligent Service instance can be monitored as shown below:
