Feb 07, 2022

The Disappearing User Part 4: Five Helpful Tools

Ward Rushton
Hanna Chun
Alaina Huslig

Ward Rushton, Hanna Chun, and Alaina Huslig

The Disappearing User Part 4: Five Helpful Tools

As the advertising technologies (AdTech) market continues to be swayed by public opinion, governmental regulation, and tech giant forces, there is no one-size-fits-all response to the deprecation of Apple’s Identifier for Advertisers (IDFA). To avoid the everything-looks-like-a-nail approach where more and more ad spending goes toward existing technologies, it is important to understand the various tools offered in the MarTech marketplace and the gaps filled by each. 

In our last three blog posts, we walked through the different marketing solutions to these privacy restrictions, how companies can optimize future mobile campaigns, and dissected how different users are impacted by this change.

In this post, we discuss five important tools to be aware of and understand to retain a marketing edge against any potential threat.

1. Customer Data Platform

As mentioned in the third part of this blog series, a customer data platform (CDP), such as Tealium and mParticle, serves as the single source of truth for customer data. A CDP is a software or collection of tools that allows you to collect consented first-party data, manage this data, and act on data in a meaningful way. It is a helpful solution in the days of tightening data privacy in that it assists in ensuring compliance across multiple data sources. With CDPs, you can holistically understand your customers' needs for more informed decision making.

2. Decisioning Engine 

A decisioning engine takes CDPs one step further by automating the decision process in cases of conflicting customer personas. Decisioning engines rely on AI and machine learning to predict future user behavior. This provides improved customer experience through consistency for your customers. 

One example of a well-developed decisioning engine is PEGA. At Credera, we chose to implement PEGA as the new decisioning engine and email service provider for one of our government industry clients. By switching to the use of PEGA, the client hopes to capture more meaningful analytics and make better educated decisions on who to send specific email campaigns to. 

3. Analytics Workbench

An analytics workbench such as Credera’s own Marketing Analytics Platform combines data from multiple sources to cover the end-to-end data science lifecycle, allowing companies to own data from start to finish. From data extraction and storage to transformation, warehousing, and visualization, an analytics workbench provides the ability to cater your data analysis to your customers without external restrictions and unlock value from your existing data. 

Additional mobile advertising restrictions will disproportionately harm companies that do not have the ability to own and analyze their own customer data whereas an analytics workbench hedges against future changes.

4. Identity Resolution & Enrichment Services

Identity resolution and enrichment services can be very useful for filling the user information gaps in a data pipeline left by the changes in iOS 14.5 and the upcoming changes in third-party cookies. 

For example, if you acquire a new user and collect some basic information during signup, you would be able to match and enrich that data externally with an identity enrichment service. Additionally, if a user were to sign up with a work email address, it is possible the identity resolution partner could cross-correlate with other known emails to create a fuller picture of a single user. 

One example of this service is the MarTech provider LiveRamp. LiveRamp utilizes a compiled user id graph to deterministically match users across different experiences. By matching data across its different sources, LiveRamp can provide a fuller picture of the user’s behavior than any single data source alone. 

Our same government client also chose to implement LiveRamp to capture data across multiple different marketing channels. With this LiveRamp data, the client has created a single view of each user, which they use to determine what marketing campaign may by the most appealing to each individual. This tactic in turn allows the client to create a more personalized user experience while also complying with the new iOS regulations.  

The limitations of LiveRamp greatly depend on a particular instantiation of the tool—for example, a company that does not collect and store any first-party data will be unable to effectively leverage the ID matching tool. LiveRamp could be less effective when users are more likely to use a fake or machine-generated email address

5. Data Clean Rooms

Another option for staying grounded to your customer base is to use a data clean room—an aggregated set of user segmented data to ensure you’re correctly allocating resources across the audiences relevant to your market. 

One example of this AdTech is provided by Omnicom Media Group and InfoSum to provide industry-specific reference media mixes. By pulling together large amounts of aggregated data to compare against, a smaller company can utilize the insights of an industry leader. 

Below is a sample illustration of a company’s self-determined media mix over time compared to an industry reference. 

Sample Company Media Mix
Sample Company Media Mix

Figure 1: A sample company media mix over time compared to a current data clean room reference. Note the disparities between various categories in the sample media mix and the reference that could be realigned to optimize return on ad spend.

Once the sample company compares their media mix to the reference, they will be able to adjust their ad spending appropriately to stay in line with the industry-wide audience and recapture potentially underserved audiences without blindly increasing ad spending.

Even as the volume and demographics of opt-in mobile ad data changes, the overall market customer segments may not. A data clean room is a tool that allows for a clear line of sight into overall market audiences without the fog of unclear mobile data. 

What to Do Next for AdTech and MarTech Enablement 

Now that we have identified ways to reduce IDFA’s data deprecation through CDPs, decisioning engines, analytic workbenches, and identity resolution and enrichment services, the next step is to understand the best tool additions for your particular tech stack. 

Analyze your company’s tech stack and project the impacts the iOS updates will have on your specific data ecosystem to determine which tool, if any, will bridge a meaningful data gap. If you have any questions about your specific situation or are ready to connect with a new tool, our MarTech and mobile solutions experts are available to answer questions at

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