A global retailer is blending multiple streams of customer transaction and behavior data from several channels to better target customers and improve its bottom line.
A global retailer was eager to better understand the behavior of its customers across all of its channels-- online, mobile, and in-store. The company had multiple touchpoints and interactions with customers before, during, and after their purchases, but it lacked a unified way to tap into that data in order to glean useful marketing insights for each customer, regardless of channel. Achieving the goal of a single view of customer behavior across multiple channels and touchpoints would require changes to how data is collected, analyzed and used across the organization to connect with customers throughout their purchase experience.
PwC worked with the company to develop an initial vision of how customer data from various channels could be used to predict buying behavior and for 1-1 personalized marketing which would result in higher sales and customer satisfaction. Collaborating with the company’s project team, a business needs and technical assessment was conducted which identified opportunities to capture, analyze and leverage data to create a single view of the customer experience. The assessment also delivered a mapping of various alternative “Big Data” technologies (including a pilot proposal) to support the reconciliation of inconsistent customer data formats, as well as a proposed architecture for people, process and technology.
The company believes it’s positioned to capture ten percent more margin from five percent of its customers across each value tier now that it can identify and target them more accurately. It also believes it can reduce its marketing spend by 1.5 percent while producing the same or better results. By eliminating duplicate direct mailings and by reducing or eliminating ambiguity regarding customer identity, the company’s marketing efforts are becoming more efficient and targeted than ever, and the results so far prove it.