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How to Upgrade Analytics by Building a Single Source of Truth

In order to understand your customers and reach analytics maturity, you need to build and own a single source of truth.

Download our new whitepaper to learn:

  1. The analytics maturity journey and why you need to build a single source of truth
  2. The challenges around creating a single source of truth
  3. What your single source of truth should look like and how to enable it

Web analytics has evolved over the past few decades, and it’s possible to understand your customers at a deeper level than ever before. To reach true analytics maturity, you must build a single source of truth. With the advent of cloud data warehouses, it’s now possible to do so with a customer data technology stack that is intentionally designed to achieve this goal. When you build it well, you can break down data silos, bring all of your customer data into your data warehouse, and emerge with a clear and unified view of your customers.

In this whitepaper, we lay out the analytics maturity curve, analyze why single source of truth initiatives efforts fail, and detail how to approach building your own successfully. The paper also introduces Heap's new solution for bringing customer behavioral data into your data warehouse. The paper covers:

1. Evolving Your Understanding of Customers Means Breaking Down Data Silos
2. Why Creating a Single Source of Truth Is So Challenging
3. What Should Your Source of Truth Look Like?
4. Customer Data as a Service Enables Your Source of Truth
5. Heap-Supported Warehouses
6. Conclusion

Download the whitepaper now!

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

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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