How to Create Cross-Channel Normalization: Google Ads, Bing, DV360, Facebook [2020 Guide]

Ecommerce & Retail
Analytics
All data sources

In this recipe, you’ll learn how to create cross-channel normalization across the most popular digital advertising providers: Google Ads, Bing, DV360, and Facebook.

Create Cross-Channel Normalization across Google Ads, Bing, DV360, Facebook with Improvado

Collect data in one place with Improvado and send it any tool you use. No more engineering resources wasted. No more manual anything.

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What do you need?

Problem

The problems of big data disparities affect more than statistical aggregates. From data aggregation and data transformation to data warehousing, visualization, and even data pipelines, it's safe to say that big data transcends all levels of most businesses.

Normalizing data ahead of time in a pre-processing step is a great idea. The objective here is to transform all data and put them on the same scale. Otherwise, there is uneven data distribution which may cause imbalanced gradients in the network.

That said, data normalization is necessary for data to be properly utilized. It also serves to reduce redundancies and group data logically.

Data Normalization on Social Media Platforms and Advertising Providers

Typically, cross-channel normalization operations utilize local responses in different channels to normalize their data. In practice, this could be useful in tuning out noisy data sets and eventually placing all analyzable contents from each platform on the same scale.

With Improvado’s solid algorithm, a business can easily carry out the cross-channel normalization on Google Ads, Bing, DV360, and Facebook. This algorithm and the intuitive, user-friendly interface eliminate the need for an expert developer.

It is pertinent to note that this data normalization process is not meant for any specific business. We recommend that all businesses working with large quantities of data should consider this route.

Step 1.

Authorize on the improvado.io platform. Connect Google Ads, Bing, LinkedIn or Facebook data to Improvado and Extract.

Step 2.

Request specific transformation template through customer support/sales or engineers/sales. After that data for “ads dimensions” for Facebook, Bing, Google Ads, Google DV360 (or any of them) will be connected.

Improvado cinnectors API


Step 3

Return to the data warehouse with this template in 24 hours. There should be a new table with combined data.

Data warehouse templete
Improvado template

At this step data extraction from ImDataPrep to customer DW: PostgreSQL, GBQ can be set up. Customer can not visualize data in Improvado Reporting Platform, but all the operations needed to prepare data for 3rd party visualization tools can be done by Improvado.

Conclusion

With this, a business can get a summary of all activities across its channels at a glance. Performance analytics metrics are better and easier to use here, as well.

Regardless of which platforms are used, data visualizations become so much simpler. It’s also easier to compare data points across each channel without ever needing to separate any of them.

What's more? These are pretty standard benefits of cross-channel normalization. In addition to them, the business has maximum control over their data concerns as well as other control resources.

Create Cross-Channel Normalization across Google Ads, Bing, DV360, Facebook with Improvado

Collect data in one place with Improvado and send it any tool you use. No more engineering resources wasted. No more manual anything.

Schedule a demo
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