Post-Cookie & IDFA Readiness Checklist
End to End Data Management on the Private Web
We know there are hundreds of opinions, strategies and tactics to approach the world of digital advertising and marketing in the privacy-forward future. While the following checklist may not cover every little detail suggested by tech vendors and influencers alike, we believe the following covers the most critical items for end to end data management going forward.
So don’t sweat privacy changes any more – whether these current ones or future changes that we have yet to realize, we have a solid checklist to future proof your digital advertising and marketing.
To start, you need to organize all the data inputs you currently have. Consider:
- A data standards plan so that all of your data can be effectively connected across all platforms in your technology stack
- A plan and taxonomy structure that takes the unique needs of different teams, systems and channels into account
- Know what you want. A well-defined and externally verifiable measurement methodology that can operate independent of persistent digital identifiers.
Here are some tools to consider when doing the above. These are the systems our Fortune 1000 customers are using:
- Claravine (of course)
- Google Sheets/Excel
Next, make sure you are addressing sensitive data handling in the middle of your data flow and management. Important steps:
- First-party data strategy is defined and rolled out to scale your 1P data (or starting to roll out)
- A high-quality deterministic identity graph has been developed of your own customers
- Identify and select a data sharing enabler that meets your firm’s PII handling security and privacy requirements
And again a set of technologies to evaluate/include in your “stack”:
- Data Republic
- Datafleets (part of Liveramp)
- Snowflake Data Exchange
Make sure you are also organizing your outputs so that everything remains connected and consistent. Steps include:
- Aggregate data pipelines from hundreds of marketing point solutions into a single repository.
- Ensure that the data inputs are organized in step #1 so the information is prepared to support finance, business intelligence and data science teams.
- Pull through measurement methodology from step #1 to set up the next phase of budget allocation automation.
Here are technologies that support this stage in the data management process:
- Salesforce Datorama
- Estuary Flow
The new world of marketing and advertising on the private web requires new technologies and new ways of doing data management. The above is just a glimpse into where to go and what approaches to take. Contact us at Claravine to learn more about how we can help you with a lot of the above.