Five Big Data Trends Revolutionizing Retail

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More retailers are finding that Big Data can revitalize an industry challenged by a slow economy, increasingly empowered consumers, mobile proliferation and an ever-growing number of channels. By Andrew Brust for Big on Data | August 16, 2013 -- This guest post is from Kelly Kennedy, Senior Vice President of Enterprise Sales at Info group Targeting Solutions, where she supports large enterprise clients with a wealth of industry experience across both B2C and B2B solutions. By Kelly Kennedy Its Moore’s law of marketing: The aggregate amount of data available to retailers doubles every two years. Acquiring the insights that retailers need to find, target and retain their ideal customers used to be a problem.

Now, marketers are tasked with sifting through the enormous amount of data they have on hand. Big Data is just that, and the sheer amount makes it difficult not only to discern what’s valuable, but to discover what information might be missing or lost in the shuffle. The retail industry may have turned a corner. In a recent interview, Karem Tomak, vice president of analytics for Macys.com, admitted that just three years ago the department store relied on Excel spreadsheets to house and make sense of customer data. Now the retail giant is crediting Big Data and analytics with a double-digit percentage increase in revenue.

More retailers are finding that Big Data has the potential to revitalize an industry being challenged by a slow economy, increasingly empowered consumers, mobile proliferation and an ever-growing number of channels. Although Big Data is having profound impacts on retail and marketing strategy, it’s important for brands to use these trends as building blocks for a greater process flow overhaul. Without the proper technology, internal knowledge and best practices in place, it’s difficult to maximize Big Data’s potential benefits. Five ways Big Data is revolutionizing retail marketing

1. Growing, cross-channel data volumes

The rise of mobile, tablets and social media has accelerated the growth of available customer data.

A typical retailer knows not only the basic demographic information about a customer, but purchase history, call center interaction, mobile/social interaction, supply chain data and more. The sheer volume of information available to retailers is unprecedented, even for brands that have years of experience analyzing customer data.

2. Increasing investment in technology

You’d be hard-pressed to walk into a Best Buy right now and find a hard drive that stores less than a terabyte. Storage is so cheap that it’s leveling the playing field for many companies when it comes to Big Data.

Retail leaders have started investing in centralized databases and focusing on data hygiene and analytics, giving them insight into their customers that wasn't possible even a few years ago. In 2013, retailers will spend nearly $2 billion on business intelligence and $9.4 billion on infrastructure. For Macy’s, the investment has paid off: Tomak, the executive who modernized Macy’s data processes, attributes a 10 percent increase in store sales to improved analytics capabilities.

3. Solving the Omnichannel puzzle with data

Retailers with a data-centric mindset are crunching an incredible amount of customer behavior data to understand how customers are researching and buying products. Insights reached through analyzing transaction data, foot traffic and in-store checkout wait times have led to shifts in marketing strategies and in-store tactics.

In response, retailers have introduced in-store kiosks, free Wi-Fi, and armed their sales staff with mobile devices that allow them to better serve Web-savvy customers on the spot. Similarly, marketers shouldn’t ignore one channel at the expense of the other. Walgreens found that customers who shop both in-store and online spend 3.5 times as much as customers who favor only one channel.

4. Improving personalization

Big Data gives retailers the unique opportunity to mirror the shopkeeper of yore, adapting communication and sales techniques to life events and preferences.

Research cited on the Harvard Business Review blog found that personalization can deliver five to eight times the ROI on marketing investment and boost sales 10 percent. Consumers are fine with sharing personal details so long as it earns them something. Technology will further enhance the consumer experience as Next Best Offer (NBO) technology becomes reality. NBO represents the convergence of real-time data analysis and mobile offers. By reaching consumers at the right time, in the right place, through the right channel, NBO provides personalization on steroids and is the future of the industry.

5. Segmenting the most valuable customers

Harnessing Big Data is a massive undertaking, but the payoff lies in finding the most profitable customers. Prioritizing these high-value customers is essential to success, especially considering that it costs more to acquire new customers than to keep the best customers. Improvements in data-crunching abilities allow retailers to analyze the behavior and needs that drive individual customers, which results in more relevant and targeted offers.

A recent study by Aberdeen Group found that 59 percent of retailers identified a lack of consumer insights as their top data-related pain point. Yet retailers have more customer data than ever. For brands competing in an industry with slim margins, harnessing the right data and smart analysis will lead to better engagement, more loyal customers and a competitive advantage.

Maximizing Big Data’s potential

Retailers that are taking advantage of Big Data’s potential are reaping the rewards. They’re able to use data to effectively reach consumers through the correct channels and with messages that resonate to a highly targeted audience. Although there are obvious benefits, many retailers are surprisingly still failing to act on these trends. This delay is largely due to a dependence on siloed information, lack of executive involvement and a general trend among marketers to fail to understand analytics. Without advancing internal structures, gaining executive support or educating internally, jumping on these Big Data trends is nearly impossible. Big Data can be overwhelming, and it’s important that retailers understand what their current systems can handle. For data to produce results, retailers need to integrate technology to ensure that they are gaining insights they can quickly act upon. Once internal resources are up to date – including both human knowledge and technology assets – Big Data possibilities are limitless.

Paper For Above instruction

The rapid evolution of the retail industry in the digital age has underscored the transformative power of Big Data. As retailers encounter a challenging landscape characterized by economic slowdowns, empowered consumers, and proliferating channels such as mobile and social media, leveraging Big Data becomes essential to gaining a competitive advantage. This essay explores how Big Data is revolutionizing retail, focusing on its capacity to handle growing data volumes, enhance technology investments, improve multichannel integration, advance personalized marketing, and identify high-value customers. Moreover, it discusses the critical factors influencing the industry’s strategic decision-making and offers insights into effectively applying data analytics for sustained competitive success.

Introduction

Big Data refers to the massive volume of structured and unstructured data generated by organizational operations, customer interactions, and external sources. In retail, the adoption of Big Data analytics has proven to be a game-changer, enabling companies to understand consumer behavior more profoundly and tailor their strategies accordingly. The increase in digital touchpoints has exponentially increased the data available, compelling retailers to adapt their infrastructure, analytics capabilities, and organizational processes to capitalize on this trend. By examining the key ways Big Data is transforming retail, this paper underscores its strategic importance and offers a roadmap for harnessing its potential for above-average returns.

The Impact of Big Data on Retail

One of the most significant impacts of Big Data in retail is the exponential growth of cross-channel data. The omnichannel environment fosters data collection from mobile devices, social media, online browsing, in-store transactions, and supply chain management. This consolidated customer data provides richer insights into consumer preferences and behaviors, facilitating more targeted marketing and personalized service. For example, Macy’s has utilized analytics to boost sales by analyzing customer transaction and interaction data, paving the way for targeted promotions and inventory management enhancements.

Investment in technology is another crucial factor. As data storage becomes more affordable, retail leaders are investing heavily in centralized databases, data hygiene, and advanced analytics, thereby enabling real-time insights and more precise decision-making. Macy’s, for example, allocated nearly $2 billion in 2013 toward business intelligence and infrastructure, which translated into tangible revenue growth.

Improving Customer Engagement Through Data

Understanding how consumers research and purchase products across channels helps retailers optimize in-store and online experiences. Initiatives like in-store kiosks, free Wi-Fi, and mobile devices for sales staff exemplify efforts to integrate online and offline channels seamlessly. Walgreens, a prominent retailer, found that customers active in both shopping modes tend to spend significantly more, demonstrating the importance of a cohesive omnichannel strategy rooted in data analysis.

Personalization and Customer Value Segmentation

Big Data enables retailers to personalize offers and communications dynamically, mirroring traditional shopkeeper relationships but on a larger scale. Personalized marketing strategies deliver higher ROI and increased sales, with Next Best Offer (NBO) technology exemplifying how real-time data analysis can be used to reach consumers in the right context. Additionally, segmenting high-value customers allows retailers to focus resources on loyalty drivers, reducing acquisition costs and increasing profitability.

Challenges and Future Directions

Despite the evident benefits, many retailers lag in harnessing Big Data fully due to siloed information, insufficient technological integration, and inadequate organizational expertise. For the industry to realize the full potential, internal restructuring, technological upgrades, and employee education are essential. As retail firms progress towards data-driven decision-making, those who effectively integrate Big Data into their operations will attain sustainable competitive advantages, leading to above-average returns.

Conclusion

Big Data has become instrumental in transforming retail strategies, from managing vast data volumes to delivering personalized customer experiences and identifying high-value segments. The successful integration of Big Data analytics into core organizational processes offers a promising pathway to differentiate in a competitive landscape. Retailers who proactively adapt to these technological trends, invest in infrastructure, and foster data-driven cultures are positioned to achieve strategic competitiveness and above-average financial returns in the evolving retail environment.

References

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• Macy’s Inc. (2014). Annual Report. Macy’s Inc.
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