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Faster Data Operationalization

We worked with the marketing team at the world’s largest sporting goods brand in their sport. Their team initially came to us looking for a Customer Data Platform (CDP). Following our analysis of their business needs and technology solutions, we discovered a deeper problem: They were accessing their data through a third party service provider.

As a result, they didn’t own their own data or have the ability to quickly answer their business questions. Because their data was in a black box and not in one place, they lacked a holistic view of the relationship between online and in-store sales.

Personalizing Marketing Efforts

The marketing team’s initial goal was to personalize marketing efforts to specific customer segments and to get a holistic picture of each customer in order to market with greater precision. We realized that we could solve this problem and provide them with faster insights.

Cloud Data Warehousing

Consolidating the Data

We started by setting them up with Google’s BigQuery cloud data warehouse service. This was a good fit for them as they were already using Google products and it's a technology we have a great deal of experience using. 

The next step was to centralize their data. Their methods for gathering data had grown organically. Their business launched well before the internet and had transitioned into the digital realm piece by piece. That process resulted in some data being stored in the cloud and some in spreadsheets. We consolidated it all into BigQuery, placing everything they needed in one centralized repository.

Self-Serve Business Intelligence

Big Data. No Waiting.

We placed Looker’s business intelligence tools on top of BigQuery in order to put all of the company’s data at their fingertips. By building dashboards created to access the data in ways that made sense to the marketing team, we allowed them to slice and dice the data in any way that fit their needs. 

This was a game changer in ways they hadn’t anticipated. With direct access to their data they can now ask questions and produce reports in minutes instead of in weeks. They can quickly iterate on their inquiries and reach insights significantly faster. In addition, they have a better profile of individual customers, both online and in stores. They are able to highlight related products and promote in-stock items that are the right size.

Data Governance

Standardized Data

Although their data was now immediately available, it wasn’t yet defined. We educated them on the importance of data governance and helped them spin up a data governance program. Through this work we were able to help them standardize their data, define their metrics, and QA their data. Standardized KPI definitions allowed their marketing platform to customize messages to individuals and customer segments.

This process gave them confidence in the integrity and consistency of the data even though it was coming from several different sources. It also provided them with a level of internal transparency that they hadn’t had with the managed service provider.

Data Platform Modernization & Data Migration

From Chaos to Consolidation

They had done a good job of collecting data. The challenge we faced was that some of the data was in spreadsheets as well as being scattered across disparate data tools and technologies—some of which were outdated. We helped them develop a cloud strategy and consolidated the disparate pieces of data onto a modern cloud-based platform. We then worked with them to integrate what they were doing with the other cloud technologies that they wanted to continue to use.

Services We Provided

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Cloud Data Warehousing

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Platform Modernization & Data Migration

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Data Governance

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Self Service Business Intelligence

In Conclusion

From Darkness Into Light

Building out a FullStack solution gave this client more than they had wished for. While we delivered the CDP that they were looking for, they gained much more. Time to insight was reduced from over a week to a few minutes, making it easier for the marketing team to standardize customer segments and effectively operationalize their data.

Once their data was out of the black box and immediately at hand, they had more flexibility in their inquiries and were empowered to run more iterative and fine-tuned analytics operations. They gained a holistic view of their business and their customers, both online and in stores, allowing them to target them more efficiently and effectively.

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