How Marketing Is Leading the Charge to Extract Value From Big Data

It seems the hope and hype of big data has an array of perpetual headline across an spectrum of publications with stories that discuss the what-ifs and some day-whens of how businesses will be able to extract unprecedented value from their massive data streams once they are able to manage their data tsunamis.

The majority of these articles tend to focus on the potential contributions “big data” may one day deliver on a widespread, mainstream basis to an organization and often feature hypothetical milestones reviewing how “big data” intelligence will serve teams across the organization once it’s extracted. Often, these articles tend to focus on Finance, Operations and Technology teams as the anticipated and logical benefactors of “big data.”

However, one largely unexpected area of an increasing number of leading brands is overcoming the hype of “big data” to make its utility and value a reality. The Marketing (a.k.a. Insights, Experience or Brand) team is leading the charge across many companies to deliver valuable, actionable insight from massive, fragmented, complex data sources. This intelligence is being used to understand customers on unprecedented levels, manage operations more effectively and even track and measure brand equity.

As other groups across the company hold out and hope for the promise of “big data,” the ability to conduct digital consumer ethnography through real-time customer data streams is transforming how Marketing is able to understanding, engage and motivate consumers.

Centralized Success

As the “Age of the Consumer” advances and more individuals evolve into “always on” consumers with shopping engines, price comparisons and product reviews it’s increasingly viral for Marketing teams to access the intelligence from their customers’ “digital footprints” from across the expansive array of data sources, from point-of-sale systems and ecommerce platforms to mobile applications and social networks. Marketers have to gain access to multidimensional, streamlined views of their customers in order to gain a robust understanding of their shopping habits, purchasing tendencies and engagement preferences.

The key to achieving this is to centralize and synthesize the organization’s cross-channel customer data. This is an initiative that scares more organizations given the diverse, fragmented nature of the data sources, many of which are antiquarian. The way many brands are achieving this is with Consumer Management platform technology, which integrates to their wide variety of systems, collecting the ongoing data feeds in order to collate the information from each and every system into a central profile for each customer.

This allows the brand to gain the advantage of a holistic view of their customers, replacing the obsolete approach where each individual customer interaction, say an online purchase, in-store purchase and mobile app purchase, are treated individually. In this case each purchase is viewed as a separate individual since the platforms traditionally don’t have a method to share and centralize their information to discover that the three transactions are actually made by one shopper.

Intelligent Impacts

Here is a review of five ways Marketing is enhancing its impact on the organization with ‘big data’ customer intelligence:

Customer Understanding. By synthesizing customer data sources across POS, ecommerce, social and mobile channels, Marketers are able to construct multidimensional personas, segments and purchase paths, understanding their specific purchase tendencies related to where they purchase, when they purchase and even what they purchase. This helps the brand to deliver more effective and relevant communications that motivate behavior based on customer preferences.

MVC Identification. Centralized cross-channel data also helps the brand to unveil their Most Valuable Customers (MVCs) based on a multitude of dimensions beyond simple dollar value, like frequency, engagement, evangelism or volume. This allows the brand to not only focus on and foster their best customers to increase their lifetime value and cultivate their evangelism, but also helps identify potential MVCs the brand can strategically shepherd up the customer value chain.

Operational Efficiencies. By understanding how consumers shop, brands can manage their in-store operations better. On the front end, having ongoing visibility into shopper behaviors based on when they shop during the week or day helps brands to manage their staffing levels more effectively. On the back end it allows the company to deploy strategic campaigns to attract traffic and demand during slow periods.

Inventory Management. With intelligence on purchase trends and tendencies the organization has the ability to enhance its inventory management by bundling high demand products with lower demand items or even offering specials to move overstocked products. This delivers cross-channel demand visibility, allowing the brand to manage and move inventory more strategically and effectively to specific, relevant customer segments.

Strategic Merchandising. Customer purchase tendency data can also extend to support merchandising efficacy across promotion optimization, or getting the right products in front of the right customers. It also helps with pricing optimization by understanding pricing points products move at, new product development and new product or market introductions. It also provides insight into declining and obsolete products to discontinue and delist, which drive margin and expense efficiency.

The Bottom Line

To gain full advantage of the wealth of intelligence within your organization’s customer data sources, the first step is to centralize each data source across your point-of-sale system(s), ecommerce platform, mobile application and social network accounts. A growing number of brands are realizing that only once their customer data is synthesized can it deliver a true, ongoing understanding of their customers’ tendencies and trends.

Given the sheer volume and fragmented nature of a company’s cross-channel data, extracting customer intelligence now requires advanced Consumer Management technology which integrates directly to the brand’s standing data platforms, avoiding massive internal development and/or system upgrades. Once achieved, the synthesized data delivers an unprecedented understanding of the customer, a vital component to succeeding into today’s “Age of the Consumer.”