Unlocking Retail’s Big Data Opportunity

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Walmart remains the world’s largest company by revenue and the retail sector employs more people in the U.S. than any other sector outside of healthcare. While the 2015 holiday season was considered a lackluster one, the industry still saw sales increase 3 percent to $626.1 billion.

As retail organizations continue to see huge growth in the volume and variety of data available to them, they are smart to realize the importance of data management to help them optimize customer personalization, manage inventory levels, and even support the data privacy needs required by customers and regulators alike. Discussions at the industry’s largest gathering, the BIG Show Expo hosted by the National Retail Federation (NRF), centered on what’s needed to acquire, retain and influence consumers. Newer challenges relating to personalization and building better buyer connections are issues all retailers are working to address.

At the heart of a retailer’s success is data – and a deep understanding of that data. I believe there are four key retail trends that have significant data management implications.

Omnichannel and the Unified Data Stream

The idea of seamlessly selling to and servicing customers across all channels – online and offline – is not a new concept. The challenge is in creating a unified data stream that enables retailers to improve the customer experience. This can take multiple forms. Ordering online and picking up in a brick-and-mortar is just one obvious example. Yet companies still struggle to get to this promised land. According to a Forrester report, nearly 40% of retailers haven’t integrated the different back office systems that house their various data streams that would enable them to support this omnichannel experience.

Mobility

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E-commerce, by far the fastest growing sector of retailing, is increasingly driven by mobile shopping. A recent survey of U.S. retailers shows that mobile

commerce is growing at 2.5 times the rate of e-commerce overall, securing nearly 30% of the overall e-commerce pie. In other parts of the world, the growth of mobile commerce is even more pronounced. Mobile commerce provides yet more data to help retailers understand buying patterns of their customers.

Rise of Connected Devices

The Internet of Things (IoT) – the move toward smarter, interconnected devices – represents a potential boon for retailers. Examples of these interconnected devices include inventory sensors, automated checkouts, and promotional software that can be tied to a customer’s phone, allowing for the ultimate personalization for anyone walking through a store. For a retailer like Lululemon for example, this means that a valued customer could receive an immediate 25% discount coupon on her smartphone for her favorite yoga pants upon entering the store. Those pants could be paired with other suggested items and available to try on in the changing room. Then, as she walks out of the store with her purchases, her preferred credit card is automatically debited. This seemingly futuristic experience is soon the new normal and one that many retailers aspire to. What’s more, the economics are meaningful given the profit margins retailers live with. McKinsey estimates a positive economic impact of between $410 billion to $1.2 trillion per year by 2025 as a result of retailers adopting these connected devices and processes.

Social Selling

Revenue from social network referrals remains an important of a retailer’s mix, growing by more than 60% in the last couple of years. Retailers are able to tap into trending conversations (more data!) and place “hot products” in people’s viewing streams. However, social interactions go far beyond selling – they enable customer service organizations to engage with customers outside of a typical e-commerce or in-store environment.

So what do all these trends mean for the teams responsible for managing the data?

First, they often require new types of data platforms to process the huge volumes of data being generated. This has led to adoption of platforms such as NoSQL data stores and Hadoop. Of course, the next step is actually analyzing the data that is collected – even today, over 80% of the data collected in retail environments isn’t considered for analysis.

Second, since data is the relevant business currency for the next wave of retailing success, they’ll need to figure out how best to protect customer privacy as these data sets cross different environments to support the personalized customer experience.  Given that 10% of customers stop shopping at a retailer after a breach and 36% shop less frequently, it’s incumbent on retailers to ensure that they integrate privacy concepts and processes directly into their data management infrastructure.

Third, data availability is critical to the financial success of these companies. If companies want to have 1,000 website versions for 1,000 customers then keeping those various data elements available to the algorithms that use them is critical. This is a non-trivial task when we’re talking about petabyte-scale data sets.

The Bottom Line 

It’s inevitable that retailers will spend more time and resources to aggregate, process, and analyze their numerous data streams to ensure better relationships with customers. Customers are beginning to expect enhanced, personalized experiences, and competition for that customer loyalty will demand this level of investment. Addressing fundamental issues around scale, security, and infrastructure readiness will remain critical before retailers can reap the full benefits of their data investments.

About the author: Nitin Donde is the founder and
CEO of Talena, a developer of solutions aimed at ensuring the availability and recoverability of data and applications built upon modern distributed architectures. Prior to founding Talena, Nitin was an engineer with Aster Data Systems, EMC, and several other technology companies.

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