You are configuring data unification for a new Microsoft Dynamics 365 Customer Insights implementation. Individual consumers are the primary target audience.
You define several match rules that include address data and other personal identifiers. These match rules did not perform as well as expected in your first unification run.
You need to improve the match results before your marketing team starts using the system.
Which two data enrichments should you consider implementing to improve the match results? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
You are a Customer Data Platform Specialist. You are creating a new measure for business accounts (B2B) in audience insights.
One of the requirements for the new business-level measure is to add a dimension of the city for each business account.
What is needed to ensure that this measure is created as a business-level measure instead of a customer-level measure?
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
You are a Customer Data Platform Specialist. Your company’s information technology department already ingested a CSV file with column names in the first row into audience insights. You are asked to clean and transform the data to get it ready for unification.
What can you do to satisfy the requirements?
Solution: Clean the data by removing any rows with nulls and deleting any leading zeros on the primary key. Click “Next” and your data is now ready for unification.
Does this meet the goal?
You are implementing Microsoft Dynamics 365 Customer Insights at a bank. After going through the unification process, you notice that customer profile cards appear nameless.
You need to reserve this problem and add the full name to the customer profile cards.
What should you do?