Using Big Data to Create Big Spenders
Retail on demand is here. The MIT Sloan Management Review describes it as “blurring the boundaries between traditional and Internet retailing, enabling merchants to interact with consumers through multiple touch points, and expose them to a rich blend of offline sensory information and online content.”
That is a lofty way of saying customers want what they want, when they want, how they want it — and at a competitive price.
Retailers and their supply-chain partners are making great strides in meeting the evolving customer demands associated with retail on demand, and at the same time rethinking their competitive strategies. The next competitive step is leveraging big data to monetize customer trends, turning them into actionable insights and, ultimately, revenue.
“Information leaders increasingly grasp the idea that information adds value to their organization beyond mere operational excellence and decision-making. They can realize that value by taking a disciplined approach to monetizing available information assets,” according to Gartner’s report, “Seven Steps to Monetizing Your Information Assets,” published October 15, 2015.
Big data, little insight
Information assets and key data points for retailers can include consumers’ brand preferences and shopping habits, as well as information on devices, networks and operating system usage, search keywords and more. The coming challenge is to take those data points, aggregate them into useful insights, and monetize them across relevant and appropriate channels.
"The trend to see and use information as an asset is still in the 'early adoption' phase, making doing so a competitive differentiator for leading organizations. But even where information leaders have embraced this idea, there's an array of challenges to transform the idea of value into a reality that benefits the organization,” according to Gartner’s report, “Seven Steps to Monetizing Your Information Assets,” published October 15, 2015.
Data aggregation challenges include not knowing “how to align big data with use cases, how to identify new types of (generally unstructured) data and how to harvest big data for improved decision making. This is according to the blog post by Chuck Schaeffer, “5 Retail Big Data Examples With Big Paychecks.” In the article, he also explains that “without understanding and hypothesizing how previously hidden data can be harvested and applied to business processes, challenges or opportunities, big data becomes another shelfware solution with a disappointing payback and short lifespan.”
In store for data-driven retailers
The future of retail relies on the combination of great design for a seamless shopping experience; and simple, easy-to-use ways to capture and analyze the buyer-journey data —from digital to brick and mortar. Merchants that embrace it, will stay competitive and keep up with what’s to come.
“By 2020, we can expect to see futuristic technology making inroads in the forms of augmented reality, beacons and anonymous analytical face detectors — each such technology doing its part in immersing customers in the shopping experience,” said Carol Spieckerman, a thought leader in the retail industry and president of Spieckerman Retail, in this IBM podcast, “What does the future have in store for the data-driven retailer?”
According to Juniper Research, retailers are expected to spend $2.5 billion in Internet-of-Things related investments over the next five years in the deployment of devices and sensors that collect and exchange information around consumer, inventory and maintenance. Meanwhile, the number of Internet of Things connected units is forecast to reach 38.5 billion by 2020.
Get started on your data monetization strategy today. Gartner provides a model for transforming data monetization into a significant business activity for most companies, suggesting a seven-step plan to drive value from enterprise data, and we’ve made it available for free download: “Seven Steps to Monetizing Your Information Assets.”