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Retail’s Digital Playbook—Today’s Tech Terms Decoded

Retail’s Digital Playbook—Secrets to Using Today’s Trendy Tech Terms

By Retail News Insider

We’ve all heard them before—a new word or phrase that suddenly starts making the rounds in meetings and online articles. Before you know it, everyone seems to be using it—from the CEO to the sales floor. At first it’s impactful. You think, “That’s a smart way of thinking.” But soon it becomes confusing. It seems everyone is using the same phrase to mean slightly different things. Of course, you think you’re using it right. But are you really?

If this scenario sounds familiar, you’re not alone. Just like the legions of us who belt out misheard lyrics to a song on the radio, many of us are adapting terms like Big Data, omnichannel and the Cloud in ways that those who originally coined the “tunes” didn’t quite intend. But because technology is playing an increasingly important role throughout the retail environment, it’s critical to know what key tech terms actually mean.

We’ve created this “digital playbook” to provide you with a handy reference of the real meanings and retail relevance of today’s—and tomorrow’s—key tech terms. Think of it as your teacher-approved cheat sheet. Go ahead and share it with the class.

Big Data (noun): Large sets of structured and unstructured data collected from online and offline sources.

As Rekha Ramesh, Senior Vice President of IT and Digital for Interactions and Daymon Worldwide explains, what sets Big Data apart from the typical large amounts of data of retailers are used to dealing with is the frequency and format in which it is generated. Big Data is generated in high frequency and includes unstructured data—information that is not organized in a pre-defined format. It includes not only the structured data retailers are used to handling—such as purchase and loyalty card information—but also social media sentiments, photos, location-based tracking and more.

The Play: By itself, Big Data isn’t particularly useful. There’s no way to discern simply by looking which data is helpful and which is “junk.” What makes Big Data valuable is its potential for revealing important patterns and business insights. Unlocking that potential is where analytics comes in—see below.

Analytics (noun): The systematic mathematical and statistical analysis of data used to derive meaningful patterns and insights.

Analytics is what makes Big Data powerful. It allows you to cut through the “noise” of immense amounts of data and to decipher meaningful connections even between seemingly unrelated pieces of information.

“Retailers have always had a ton of data. But if you can aggregate consumer sentiment and other non-transactional signals in some kind of meaningful way [using analytics], you can definitely improve merchandise sell-through and productivity,” says Paula Rosenblum, Managing Partner for intelligence firm RSR Research.

The Play: Today, retailers and brands are using powerful analytics software programs, combined with Big Data, to make more informed business decisions about everything from which new products to develop, to how to market them, to the best places to put them on the shelf. Just as online retailers have been doing for years, brick-and-mortar retailers are also now beginning to use Big Data to personalize the shopping experience for consumers. Examples include customizing interactive in-store displays as shoppers walk by or sending targeted location-based mobile offers as they browse the aisles.

Omnichannel (adjective): The merging of all channels to provide a seamless, consistent experience.

As Ramesh explains, omnichannel goes beyond simply having multiple platforms for customers to engage with you (that’s just multi-channel retailing). “If a retailer has a true omnichannel presence, I  can search for a product on social media, buy the product online, return it to a store and share my experience through a mobile app—and all the while the retailer recognizes me as the same customer and provides the ability to continue the transaction without interruption,” she says.

The Play: A successful omnichannel strategy keeps consumers engaged no matter where their shopping journey takes them. It ensures the same products are available via all channels at the same price; provides real-time, cross-referenced inventory information; and delivers a consistent experience, so shoppers get the same brand impression no matter where they interact with a retailer.

The Cloud (noun): A metaphor for the internet.
Related: Cloud Computing (noun): On-demand computing resources facilitated via the internet; storing and accessing data and programs over the internet.

Like many one-named stars, the Cloud may sound mysterious, but it’s actually quite simple—as is cloud computing (think Google Docs and Microsoft OneDrive). But for businesses, it can also be very powerful.

The Play: According to Ramesh, cloud computing enables retailers to be more nimble in their response to changing technologies and consumer expectations. Consider the omnichannel example on this page. “In the traditional IT world, integrating information such as inventory, shipping, consumer profiles, etc. was not easy and the previous operating models were vastly different than the current trends,” Ramesh explains. “Cloud computing provides flexibility to integrate different solutions and improve information flow across systems. You can choose the things you need for your operations and pay for what you plan to use. This helps achieve optimal cost and resource structure.”

Artificial Intelligence (noun): Computer systems developed to perform tasks that normally require human intelligence, such as speech recognition and decision-making.

No longer a figment of science fiction’s imagination, artificial intelligence (AI) is now widely available to businesses and consumers alike. In fact, you might even have it in your pocket right now, thanks to the growing number of AI-enabled smartphone apps.

The Play: Artificial intelligence can be used in a number of ways to improve the consumer experience. For example, voice-enabled digital assistants like Amazon’s Alexa, built into its wireless Echo, Tap and Dot speakers, can create shopping lists and even place orders all without the touch of a button. AI programs can also be used to help curate products for consumers, offering up recommendations based on shoppers’ natural language answers to questions like “What occasion are you shopping for?” or “When will you be wearing this?” According to research firm McKinsey, personalized recommendations are proven successes—driving 35 percent of what consumers purchase on Amazon and 75 percent of what they watch on Netflix.

Augmented Reality (noun): Technology that integrates digital information with a user’s environment in real time.

Augmented reality (AR) typically works by overlaying digital images, text and sounds on a real-time image of a user’s surroundings as viewed through a smartphone or tablet. Pokémon GO is one of the hottest examples today.

The Play: AR can be an ideal way to extend the store beyond its four walls. For example, furniture retailer IKEA uses AR to bring its showrooms inside consumers’ homes. Using the retailer’s digital catalog on a smartphone or tablet, users can hold up their device to any room in the home to see a true-to-live visual of what a particular product would look like in that space.

AR can also be used to enhance the in-store experience—for example, by allowing shoppers to access extended product information, videos and recipes or even by making shopping more fun. “Taking a cue from Pokémon GO, a retailer or brand could develop an augmented reality game in which shoppers are led to ‘capture’ secret deals on the products they love,” suggests Ryan James Dee, Interactions’ Creative Director.

Exponential Technology (noun): Technology that’s doubling in speed or power each year, and/or dropping in half by price.

Mobile apps are one of the best examples of exponential technology that’s had a major impact on retail in the last decade. Up-and-coming examples include 3D printing, virtual reality and drones.

The Play: Think of this as one element in your guide to technology investments. If a particular technology is growing at an exponential rate, chances are good you should be getting to know what it is and figuring out if and how it can work for your business. If it’s dropping in price by half, that likely means it’s becoming more commonplace and expected—often moving from a “nice to have” to a must-have.

Disruptive Innovation (noun): An innovation that creates a new market by successfully targeting new or overlooked categories of customers.

“The greatest disrupter of all was Google,” says Rosenblum. “It was (and is) free, and put information at peoples’ fingertips that they would have had to pay for in the past. Most recently, I see Uber as the tremendous disruption of the taxi business. Suddenly cabs are better kept up, easier to find, and slightly less pricey.”

The Play: For retailers and brands aiming to create the next disruptive innovation, the key is to focus on unmet customer needs. It’s not about improving an existing product or even marketing it to a wider audience. It’s about going back to basics to figure out who you and your competitors have overlooked and how you can create a new product or service to target them—with the ultimate goal of eventually winning over mainstream consumers as well.