Marketing-Cloud-Intelligence Exam Dumps - Marketing Cloud Intelligence Accredited Professional Exam

To create a linkage between Google Analytics and Salesforce Marketing Cloud data based on the "Message Send Key" and a portion of the "web_site_source_key," both values need to be harmonized into a common key. This is done by mapping the full Message Send Key from Salesforce Marketing Cloud and the extracted part of the web_site_source_key from Google Analytics to the same Custom Classification Key. This mapping will create a common identifier that can be used to combine the data from both sources for analysis and visualization.

To extract specific elements from a string in Marketing Cloud Intelligence, such as the second position of a Campaign Name with multiple delimiters, several harmonization methods can be employed:

• Calculated Dimensions:These allow for the creation of custom dimensions using expressions or formulas that manipulate existing data. A calculated dimension can be designed to parse and extract segments of a string based on delimiters.
• Patterns:This method involves defining a pattern or regex (regular expression) that matches and isolates the desired portion of the string. Patterns are highly effective for strings with complex structures and varying delimiter types.
• Mapping Formula:Similar to calculated dimensions, mapping formulas provide a way to apply a transformation or extraction rule to data fields directly withindata streams, enabling targeted data extraction like the desired 'Delux' from the Campaign Name.

These methods enable the implementation engineer to accurately segment and extract the needed data from complex string fields efficiently.

In Marketing Cloud Intelligence, the "Media Buy Key" is typically associated with the purchase details of a media campaign, such as the platform, audience, and budget. The "Creative Key" relates to the specific creative asset used within a campaign, like an image, video, or text. A single media buy can have multiple creative variations to test performance or to target different audiences, leading to a one-to-many relationship.

The goal is to obtain a "Campaign Planned Clicks" value per Campaign, not accumulated by Media Buy keys. Option 1 (SUM aggregation function) would sum all the "Campaign Planned Clicks" across Media Buy keys which would not yield the unique value per Campaign. Similarly, Option 5 (AVG aggregation function at Campaign Key level) would incorrectly average the values. Both options do not provide a way to return a singular "Campaign Planned Clicks" value for each Campaign.

To achieve a final view of Product Group alongside Clicks and Sign Ups, we should use:

Option A:

• Custom Classification: By using a Custom Classification key populated with the extraction of the Media Buy Name in Source 1, we can then map 'Product' in Source 2 to this key and 'Product Group' to a Custom Classification level. This will allow for grouping and analysis by Product Group, as well as enable the desired view to be created.

Option D:

• Harmonization Center: With patterns from Sources 1 and 3, we can create a harmonized dimension 'Product'. Then, by applying a Data Classification rule using Source 2, we can enhance the harmonized dimension. This allows us to align 'Product Group' with the 'Product' from Sources 1 and 3, facilitating an integrated view of Clicks and Sign Ups by Product Group.