MCI Masterclass/ Datorama Webinar
Topic: Harmonization Center
Duration: ~20 minutes
Publish date: July 20, 2023
Marketing Cloud Intelligence (MCI) offers multiple tools for harmonizing your data. Because you can upload data from various sources, you need a way to merge the data and provide a complete view of your marketing activity. In most cases, no single data source holds all relevant data on a marketing event or campaign. The data is shared by multiple platforms that digital marketers use to do things like promoting the campaign on multiple channels. To analyse the full picture, harmonize data from all sources into one. If data isn’t harmonized, you must analyse each source individually, making it a challenge to gain insights quickly and efficiently.
The MCI data model is marketing oriented and facilitates natural harmonization of marketing data from multiple sources. Another option is to use data harmonization tools, like Data Fusions, Parent-Child connections, Calculated dimensions and measurements and the focus of this session – Harmonization Center.
Let’s get to know the Harmonization Center and look at a holistic use case of utilizing the Harmonization Center as a whole.
The Harmonization Center is meant to streamline the entire process of creating meaningful dimensions from naming conventions patterns across all your marketing channels. Also allowing you to classify and validate your harmonized data all in one place.
Let’s get into how we can best use the Harmonization Center via the following use case:
“RentACar” is a car rental agency, which sells dozens of car models from various manufacturers. They use multiple platforms to promote their content – Facebook, Twitter and more. Each platform has its own naming convention pattern – but when it comes to analysing their data, they need one coherent source of truth. Up until now their team invested hours in connecting the pieces with excels, calculated dimensions, extractions, classifications etc.
With the Harmonization Center the process of creating this source of truth becomes much easier and helps focus on data driven data sources. The older methods of extracting data and classifying it were mostly based on coding, have now turned into 3 easy steps:
- Extract data from naming conventions through Patterns and create Harmonized Dimensions
- Classify data via Data Classification
- Validate data via Data Validation
During this Datorama webinar session, we’ll showcase live use cases classifying data from 3 different sources.
Data streams used for demo:
- Facebook Ads
- Twitter Ads
- Google Ads
