Marketing

Big Data Analytics

Use Cases
Retail Big Data
Analytics

 Use Cases

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Evolving digital advertising dictates increasing levels of personalization designed to scale to millions of users. To remain competitive, it needed to deploy advanced contextual and behavioral targeting and micro-segmentation to help its clients boost the return on investment of their online efforts.

Architectural Overview: The advertiser was relying on a traditional data warehouse to deliver insights based on historical consumer data such as purchase history, campaign responses and customer profiles. However, the growth in the importance of online behavioral data such as user clicks, page visits, contextual activity and social and mobile data led to Big Data requirements that were well beyond the capabilities of its data warehouse.

Customer micro-segmentation

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Customer micro-segmentation provides more tailored and targeted messaging for smaller groups. This personalized approach requires analysis of large sets of data collected through customers’ online interactions, social media, and other sources. Learn more about how companies are using big data to better segment and target customers.

Multi-channel marketing

 

Multi-channel marketing creates a seamless experiences across different types of media like company websites, social media, and physical stores. Successful multi-channel marketing requires an integrated big data approach during all stages of the buying process. Learn more about how a big data platform can streamline your multi-channel marketing

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Click stream analytics

Clickstream analysis helps to improve the user experience by analyzing customer behavior, optimizing company websites, and offering better insight into customer segments. With big data, click stream analysis helps to personalize the buying experience, getting an improved return on customer visits. Learn more about the impact of big data on clickstream analysis.

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