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How to Build your Customer Data Technology Stack

Building a best-of-breed customer data tech stack is crucial for understanding your customers and their journey. Are you getting the most of your tech stack today?

Download our ebook to learn:

  • The important considerations and approaches for building a best-of-breed data tech stack
  • How to make sense of the data technology landscape with overviews and analyses of notable tools grouped by each layer of the data stack
  • How everything comes together with real-life examples of data tech stacks

Break down data silos to emerge with a clear, unified view of your customers.

In this ebook, we offer the ultimate guide for how to go about building a modern, best-of-breed tech stack for your customer data with the express goal of unifying it and creating a complete and actionable view of your customers. We cover:
  1. Why Your Customer Data Technology Stack Matters
  2. Storing and Querying Data: Data Warehouses
  3. Data Pipelines to the Warehouse: ETL/ELT Tools
  4. Capturing Customer Interactions: Customer Behavioral Data Tools
  5. Connecting and Distributing Data: Customer Data Platforms
  6. Visualizing and Exploring Data: Business Intelligence Tools
  7. Other Tools and Sources of Data
  8. How it All Comes Together

Thousands of companies choose Heap for automatic, retroactive insights.

Companies like Payless, Microsoft, and Instapage use sources to optimize their customer’s experience.

Read customer stories from Sur La Table, The Atlantic, Instapage, and others

Heap allows us to stop relying on multiple vendors for marketing attribution. We finally have a complete, centralized view of which campaigns were associated with outcomes. We can get granular on who is doing what, when, and how.
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Arvind Ramesh, Data Scientist