According to a BMO Capital Markets report, marketers are spending $50 billion on Big Data and advanced analytics in hopes of improving the impact of their marketing efforts on their businesses. Social media has inundated brands with immense amounts of data, but that data in itself is not enough. Analytics from social media need to be overlaid with sales, retail, and other data sets within the organization for brands to be able to see the full picture.
In order to fully harvest the benefits of Big Data, the future CMO will have to invest in technology and tools that not only integrate various data sources but also squeeze efficiencies and maximize ROI throughout the brand building process. With the help of Big Data, brands can now pre-predict customer needs, target segments that provide the most value, scale pricing, create a one-on-one dialogue, identify bubbling trends, be thrifty yet targeted with media spend, and create intrinsic value that generates brand loyalty. Thus, Big Data has the power to create value throughout the brand building process and, in turn, create competitive advantage. Below are some examples of brands that have successfully leveraged Big Data throughout the brand planning process.
Big Data & Innovation
Ford Motor Co. has recognized the importance of Big Data and analytics and is opening a Research and Innovation Center in the Silicon Valley. Currently, Ford engineers collect a variety of data points on its products and customers. How drivers are using their vehicles, the driving environment, electromagnetic forces affecting the vehicle, and feedback on other road conditions all have the potential to help Ford improve the quality, safety, fuel economy and emissions of its vehicles. Big Data also has the potential to help Ford determine which features are most popular in vehicles to improve the customer experience. In the future, Ford plans to expand the use of its analytics tools into marketing and sales, finance, purchasing and manufacturing.
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Big Data & Segmentation
With the help of Big Data, brands can now create micro-segments of customers they want to prioritize by quantifying their worth. This enables marketers to prioritize marketing spend and resource allocation to maximize ROI. Neiman Marcus has developed both behavioral segmentation and a multi-tier membership reward program. This combination has led to substantially more purchases of high-end products from its most affluent, higher-margin customers.
Big Data & Pricing
Pricing models are important for all brands. Price too high, and you risk losing the customer. Price too low, and you leave money on the table. Big Data can play a critical role in helping brands determine the proper price point. The online travel industry, for example, has one of the most complex pricing models in the marketplace. Airlines and hotels have to price their time sensitive inventory quickly, and Big Data makes it possible with the help of automation software. Brands are able to overlay a variety of data sets including customer segmentation, historical demand data, competitor information, and inventory data to charge customers the right price. According to McKinsey, Big Data has helped travel companies improve revenue per unit by 3-8 percent and market share by 1-2 percentage points.
Big Data & Marketing Campaigns
Big Data can help predict trends before they happen, thus inspiring campaigns that are on point. Temptations cat treats noticed how cat owners seemed to enjoy posting photos and videos of destroyed packets of cat treats to social media. So, with help from its agency, Temptations created an unusual campaign that showed its product packaging after it had been completely torn up, clawed, and chewed to pieces.
Big Data & Media Planning
Marketers have long purchased TV ads based primarily on program and commercial ratings provided by Nielsen. However, with the help of Big Data, brands are now able to pinpoint viewers with much greater specificity than the traditional demographic categories of age and gender. Choice Hotels International Inc., which owns Comfort Inn and Sleep Inn, used to target ABC’s “Good Morning America” for would-be travelers. Each spot cost $43,000. However, with granular data now available through Simulmedia, it learned that “Big Cat Diary” on Animal Planet hit the precise target consumer for a lot less. Each spot cost only $650. Thus, Choice Hotels was not only able to maximize its ROI, but specifically target its niche customer base.
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Big Data & Brand Loyalty
It requires four to ten times more resources to acquire a new customer vs. retain an existing customer. Brands that can understand purchase drivers and other behavioral triggers at a granular level can create a lifetime of value for its customers and, in turn, generate brand loyalty. Hilton Worldwide, which has 4,200 hotels in 90 countries, used to look at customers for its Hampton Inn, Hilton, and Waldorf Astoria hotels differently and apply different marketing strategies to each audience. That is, until the hotel giant realized it should be segmenting its audience by travel needs instead of by property. With the help of Big Data, Hilton realized that the same customer might stay at a Waldorf Astoria for a wedding, at a Hilton for business, and a Hampton Inn for family travel. Thus, the hotel chain was able to shift its marketing focus to specific aspects of the customer experience to generate the most brand loyalty.
Whether you’re in the retail, banking, hospitality, automobile or software industry, application of Big Data for brands is endless and the opportunities are immense. Though companies will have to invest a significant amount of resources to fully harvest the benefits of Big Data, companies that do so will reap big rewards: satisfied customers, resource efficiencies, a competitive edge, and maximized ROI.
Image: Gwen Vanhee