DATA ENGINEERING:
Customer Data Platforms

Within an organization, customer data frequently resides in silos, either in a CRM, sales records, web analytics, and/or ad tech platforms. Mergers and acquisitions can lead to more disparate data sources. Because of the siloed data, it is difficult for companies to gain holistic insights and measure interactions across the entire customer journey. Our customer data platform architecture solves these problems and more.

WE DELIVER:

A central customer data store with cleansed and unified, structured data that drive cross-channel insights

1:1 addressability across segments or individuals in order to scale personalized experiences

Automated cross-channel activations and behavior-based learnings, leveraging data science

SUCCESS STORIES

Multinational Pharmaceutical Co. | Comprehensive Strategy Engagement
Top British multinational pharmaceutical company builds a center of excellence through comprehensive strategy engagement.

  • Released first production dashboards within 90 days
  • Built a center of data excellence.
  • Instilled an experimentation culture and optimization capability
Read More
High Tech | Optimization Program Across Channels
Insights from personalization program drive business growth, novel opportunities, and incredible media spend savings.

  • Drove 11% growth of registrations
  • 388 net new contacts, opportunity valued at nearly $7.7MM
  • Potential of $1MM cost savings in media spend
Read More
American Cancer Society | Optimization Current State Assessment & Vendor Evaluation
The new technology and processes created by Search Discovery helped American Cancer Society increase test volume and impact.

  • 5.4% growth in YoY donations
Read More
Previous
Next

OUR APPROACH

If you find yourself still not truly knowing who your customers are or what they want, sifting through data in siloed systems from siloed channels, making marketing decisions based on a single channel vs. your customer’s cross-channel behavior, and not taking advantage of ML/AI to create experiences that progress your customer along the customer journey, then you most likely could benefit from implementing a CDP. Here’s the process we follow to help our clients evaluate and select a CDP:

ASSESS

  • Data Strategy – We determine the business objectives and strategic goals for using data.
  • Technology Assessment – Assess the current state of technology platforms that are in use (e.g. MarTech, AdTech, Data Technologies).
  • Activation & Optimization Strategy – We determine the activation use cases, how will we measure impact, and how will we optimize activation scenarios.

ARCHITECT

  • Integration Strategy – We evaluate the most performant architecture for the data sources and determine how we’ll connect to inbound data sources and export to activation layers.
  • Data Preparation & Schema – We design how to harmonize all the data sources into a common model.
  • Segmentation and Profile Build – We construct the segmentation rules and attributes needed in a customer profile.

ACTIVATE

  • MarTech & AdTech Activation – We identify platforms that we need to activate and what data needs to be sent to power that activation.
  • Analytics and Data Science – We activate advanced analytics and data science capabilities in the most effective environments.
  • Governance – We determine the data validation process and how users will access the data.

LATEST INSIGHTS:

What is Datorama

Marketing Reporting and Automation with Datorama

Market Basket Analysis (MBA) is a popular rule-based machine learning technique that can provide product recommendations to customers. This post shows you how to pull and wrangle the transactional data from the Google Analytics API.

Data Mamagement Best Practice Hero

Four Data Management Best Practices

We review four data management best practices to help you make better data-driven decisions. See how our team of experts can help your business.

Reach out TODAY to CHAT MORE ABOUT CUSTOMER DATA PLATFORMS. WE'D LOVE TO HEAR FROM YOU!

Scroll to Top