The popularity of online shopping has led to the rise of an omnichannel retail experience, but omnichannel means more than consumers simply browsing and buying on their computers and phones in addition to coming into brick-and-mortar stores. The reality of customers using more than one channel for shopping is simply a "multichannel" customer experience. Omnichannel, on the other hand, is only achieved when all channels are fully integrated — and that's only a reality when advanced, agile analytics are employed.
A basic example of a successful omnichannel experience is when an in-store customer service rep can immediately reference a shopper's past purchases and preferences just as easily as a rep on the phone or online (i.e., live chat). Conversely, omnichannel could also enable customers to use a desktop computer to check inventory in-store, or perhaps purchase an item on a smartphone then pick it up later.
In retail, timing is everything, so these experiences rely on getting the right data sets to the right people quickly. This is no small challenge since data now lives in many different places, including legacy systems and different database platforms that include both on-premise and cloud data. That challenge is only going to grow as the number of data sources continues to explode. Everything from products to foot traffic to merchandising displays now have sophisticated sensors that collect and relay information for analysis.
However, with connectivity everywhere and data from in-store mobile devices growing in volume, so too will the potential for actionable insights. The Internet of Things (IoT) is poised to grow in prevalence for retailers in 2016, but that data won't have nearly the same impact if it's not integrated across all channels and proactively applied to improving the omnichannel customer experience. Successful retailers must be able to see and understand, in one holistic view, commerce-channel data, supply chain data, customer data and more.
Major brick-and-mortar stores are already using IoT data to understand shopper behavior. Mobile data helps retailers see which in-store marketing techniques work best, and which walking pathways shoppers use the most. Marketing teams then use this information to determine which visual breadcrumbs and shopping routes result in increased sales.
Smart retailers are also using this type of data to engage in proximity marketing — i.e., a new way to trigger instant communications with shoppers via an app, SMS text message or email, which may include a coupon to incentivize a purchase during that visit.
Still, working across different channels and data sources can seem tedious, impossible, or both. The good news? That's bound to change as well. This year, we're likely to see many new players in the data integration space. With the rise of sophisticated tools and the addition of new data sources, companies will stop trying to gather every byte of data in the same place. Instead, retailers will connect to data sets where they live and combine, blend or join other data sets with more agile tools and methods.
This will have a direct impact on the omnichannel experience and on improving the timing and application of retail analytics. Consider Metro, for example, a progressive retail business valued at more than $194 million as of fiscal year 2014. Metro operates a chain of department stores in Singapore, and the Metro team constantly collects a variety of data at its stores to gain valuable insights into peak and lull shopping periods, inventory flow, and customer purchase behaviors.
The Metro team has sales data from data source A, transactions data from source B, and customer data from source C, but it's able to combine all that data from those various sources. By putting it all together, applying that data to a seamless omnichannel experience takes seconds instead of weeks. Furthermore, by analyzing the trends with data from multiple sources, Metro's team can set operational and promotional strategies and continue to improve efficiency and performance.
As the number of channels and data sources continue to grow, it's more important than ever that a variety of sources can be combined, analyzed and accessed by a variety of team members. Only then can retailers offer consumers the seamless experiences that are increasingly expected in a digital, data-rich world.
Jeff Huckaby is market segment director, retail and consumer goods, at Tableau Software, a business intelligence software provider.
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