Case Study

Global retailer fills gaps in first-party data

The Industry

ABOUT THE INDUSTRY

As the retail industry continues to shift to “digital first” experiences, consumer expectations for speed, convenience and personalisation are greater than ever. In order to deliver on these expectations, retailers are hard at work building a foundation of customer data that offers a more granular look at their customers’ behaviours and preferences.

In this initiative, the global retailer aimed to double down on its core value of customer-centricity by improving the quality of its personalised product recommendations, ensuring customers were only served the products that were most relevant to them.


The Challenge

GAPS IN FIRST PARTY DATA MEANS LESS OPPORTUNITIES TO PERSONALISE

The main challenge in this initiative was that the retailer’s data set lacked an additional layer of insights that would make it better equipped to deploy more personalised recommendations. The retailer needed to fill gaps in its data that would allow it to paint a better picture of its customers’ preferences.

After identifying gaps in its first-party data, the retailer searched for a strategic partner that offered this high-quality data to better profile its customers – and that’s where Zeotap stepped in to help.


The Solution

ENTERPRISE DATA ENRICHMENT BASED ON QUALITY DATA SETS

Zeotap was selected based on the quality and availability of its data across the many countries where the retailer is present.

To start, the retailer’s CRM was enriched with Zeotap’s Enterprise Data, composed of a unified and curated age and gender dataset. Zeotap’s quality ID-verified or self-declared data is sourced from over 130 premium data sources, including telecom operators, e-commerce marketplaces, apps and publishers. This allows for up to 35% higher performing personalisation.


THE RESULTS

RELEVANT PRODUCT RECOMMENDATIONS THAT ARE CONSUMER-CENTRIC

By the end of the initiative, the retailer was able to leverage Zeotap’s Enterprise Data to run its internal analytics, measurement and activation in its own properties – allowing it to deploy more relevant product recommendations and deliver on its ‘customer first’ promise.

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