We'd like to use cookies on your device. You can accept our recommended cookies or customize your settings for better functionality.
We'd like to use cookies on your device. You can accept our recommended cookies or customize your settings for better functionality.

Data Lake...Data Store...Marketing Database – How about “all of the above”? Collecting marketing and sales data from many sources means it’s crucial to have a centralized storage solution. The platform you choose needs the agility to quickly ingest data and make it available for analysis, but it also should allow for expansion to include data hygiene, identity resolution and standard data structures.


Rapid Audience Layer is a Game Changer

Rapid Audience Layer (RAL) is a cloud-based data management solution that is quickly onboarded to allow for analysis, insights, and visualization of your data.

The ability to get a database environment deployed and functioning within weeks so you can build insights, is a huge win. With RAL, your analytics team can spend less time on data management and more time on analysis. You can take the analytics one step further with the power of our RAL Data Management Extensions

15 +
years of combined cloud development experience
25 +
years of marketing data management experience


We work across multiple industries and have partnerships with leading cloud providers:  Google Cloud Platform, Amazon Web Services, and Microsoft Azure

Rapid Audience Layer solves for the following use cases:

  • Match individuals across disconnected data sources.
  • Comply with CCPA and GDPR regulations.
  • Build better customer experience and prospect audiences based on activities, events, and demographics.
  • Accelerate into cloud-based data management.
  • Generate analytics and reporting.
  • Customize to support your specific needs and grow over time.


Start small with your data management, then expand as needed

Offered on Google Cloud Platform (GCP), Amazon Web Services, or Microsoft Azure, RAL is a cloud-based repository used to collocate marketing data from many different sources. Your data is stored in its natural/native form and can be delimited, fixed width or Excel format. Using tools such as Big Query, Snowflake and Redshift, it enables you to explore, query, report, visualize, and analyze your own data quickly.

A modular approach to solve your marketing technical stack needs

Data Management Extensions (DMEs) are additional tools, services, and/or integrations that either enhance your existing data or assist with delivering audiences to external systems.

Key Benefits Include:

  • Affordable and quick deployment – using cloud technologies, latest ETL tools, and shared support teams
  • Only purchase the extensions you need to be successful — sparing you additional investment in marketing cloud technologies
  • See ROI on all your disparate marketing and CRM data
  • Prebuilt hooks into marketing industry tools and technologies

Explore Data Management Extensions


Choose from one of two ways RAL can meet your needs and budget:


RAL Standard
RAL Premium
Cloud-based, centralized storage for CRM, digital and third-party data  
Rapid deployment to suit common use cases  
Standard data hygiene and identity resolution so you can recognize the same individual 
CCPA and GDPR compliant
Complyi – Merkle’s compliance and consumer lookup tool 
Support B2C use cases
Support B2B use cases  
Custom built to suit your specific needs  
Dedicated support team  
Standard extensions  
Customizable extensions  


Dive deep on Rapid Audience Layer

Whether you're ready for a demo, prefer to view a webinar, or are just interested in receiving more information about data management in the cloud, we've got a number of ways for you to learn more about RAL. Complete the form on this page, and we'll make sure you have the information you need.

Webinar: The Deep Dive on Rapid Audience Layer

Key takeaways from the webinar include:

  • An overview of RAL— Merkle’s scalable data management solution.
  • Understanding how to onboard first-party, second-party, and third-party data into RAL quickly.
  • Exploring common RAL use cases, including how it solves for recognizing the same individual across data sources.
  • Two clients present their challenges and results after implementing RAL
  • A review of buying model options and how to get started with RAL

Meet Our Team

Michael Deeter

Vice President, Database and ETL Capability Lead

Jon Regan

Senior Director, Technology and Data Management

Looking for technical information about RAL?