Four ways big data is set to change retail

DATAx takes a deep dive into how big data will transform four areas of retail over the coming years

16Apr

Data is aiding, abetting and propelling every industry into the future in a myriad of ways, ranging from the creation of advanced AI to simply providing businesses with a greater understanding of their clientele. As such, it is projected to become a market valuing an eyewatering $103bn in 2027, according to Statista – and its potential to transform retail is particularly exciting.

Very few industries experience such a consistent flow of high-quality, constructive data as the retail industry. Vend's 2018 Retail Benchmarks Report found that the average number of transactions a small-to-medium sized retailer processes a month is 482 – that is 482 unique opportunities to generate insightful data. And this is just the smaller operations, with the bigger players like Amazon and Walmart dealing with mindboggling quantities of data every minute of every day. This data has huge potential to shape the industry into a sector that is ready for anything the next technological revolution throws its way.

So, to help prepare retailers from all walks of life for this exciting future, DATAx takes a look at four of the most significant ways big data is set revolutionize retail.

The GDPR effect sparks a new emphasis on data security

With a number of high-profile incidents over the last year, data security has never experienced so much time in the limelight, yet this concern is nothing new to retailers. In fact, half of all US retailers reported a cyberattack in 2017, according to Thales' 2018 Data Threat Report.

Responding to the increasingly dangerous digital landscape, last year saw the introduction of the EU's General Data Protection Regulation (GDPR), forcing many retailers to double down on the way they were securing data from European consumers. However, GDPR was just the start. Following in the EU's wake, more and more data regulations are set to spring up across the globe over the coming years as a domino effect takes hold.

In the last few months several US states have pushed through legislation calling for more data security. In June 2018, California's state legislator passed a digital privacy law that will come into effect in January 2020 and will enforce more regulation over the data-collection practices of businesses throughout the state.

Moving forward, retailers in regions where regulation comes into force will need to employ multiple procedures to keep their data secure. Among these methods are the use of strong passwords and two-factor identification; controlled access to data; installing firewalls and security software; and ensuring programs and systems are regularly updated.

What's more, retailers will have to pay closer attention to their employees' role in data security, as 47% of business leaders told information security company Shred-it that human error had caused a data breach. To avoid becoming part of this alarming statistic, workers must be fully versed in any legislation impacting their particular region, in addition to being regularly trained to avoid any inadvertent slipups. Coaching to identify breaches as soon as they happen will also become more crucial, with regular drills an important way to ensure staff know exactly how to respond.

Data and transparency

Concern over data security comes hand in hand with a desire for transparency over the way customer data is used, as the security of their personal information has become something many customers are anxious about every time they fill out a form. According to a CustomerThink survey, just 21% of consumers trust companies with their personal information and more than half do not want them storing it. So, in order to receive and store the data, retail companies will need to let customers know exactly how they are using, storing and sharing their sensitive information.

But transparency does not stop at use of customer data. A Label Insight survey found that 56% of consumers would be loyal to a company for life if it provided complete transparency, meaning honesty about every step of the supply chain. And this is where data steps in to the rescue, in particular the Internet of Things (IoT) and blockchain.

The IoT in the supply chain is set to value $15 trillion by 2023, according to Transparency Market Research, as connected mobile devices make communication and accountability radically easier, meaning that retailers are able to pinpoint exactly where products are in the supply chain. This is information forward-thinking companies will increasingly share with their visibility-hungry customers. Meanwhile, blockchain's immutable ledger system can help enhance transparency while ensuring that the supply chain remains untampered with, which is something legacy tech colossus IBM realized early, most notably with its investment in TradeLens, a blockchain solution for shipping supply chains. Yet, with just 1% of companies worldwide currently experimenting with the technology, Gartner predicts that larger, focused investments in blockchain will not begin until 2022 and large-scale, global value-adds will have to wait until 2027.

AI-enabled dynamic pricing

Since its inception in the 1980s, dynamic pricing has been an increasingly common exercise for retailers to use data to enhance profitability in relation to changes in supply and demand. But it can now be enhanced enormously with the introduction of 2019's sweetheart technology: AI.

A Capgemini report revealed that retailers are expected to spend $7.3bn a year on the technology by 2022. Yet, while many leaders only consider its applications in sales and marketing, it is AI's ability to streamline factors such as procurement, supply chain and logistics which is set to generate $339bn in cost savings. This is where AI-enabled dynamic pricing steps in.

Machine learning (ML) and AI are able to take dynamic pricing beyond its traditional inventory management function, ensuring that pricing is continuously adjusting to changing consumer behaviour and preferences while taking into account inventory and profit requirements.

A company already embracing AI-enabled pricing with enthusiasm is Danish data analytics company a2i, which has used its learning algorithms to create the AI PriceCast Fuel to price the infamously fluctuating cost of fuel. The firm claims that, when using its system, fuel retailers can enjoy margins of around 5% on average.

"With the use of AI, PriceCast Fuel detects behavioral patterns in big data and relates to customer and competitor reactions with a frequency and level of accuracy that users of traditional pricing systems only can dream about," a2i outlines. "Dynamically mapping customer and competitor behavior in order to identify the optimal route (price setting) throughout the day, makes it possible to relate to any given change in the local situation for a given station and re-route accordingly when necessary and within seconds."

Data and the return (and revolution) of in-store experiences

When Amazon enters a space, you can put money on that sector experiencing a revolution. Lately, the retail giant has turned its colossal eye in an unexpected direction: Physical stores. The very same we have been hearing about declining for years in the face of such a competitive digital market.

But the stores themselves are not shaping up to be the standard experience one would have anticipated. Instead, Amazon is infusing the data and technology it used to develop its hyper-successful online marketplace to redefine the retail experience.

For example, Amazon Go, which first went public in Seattle on January 22, 2018, uses 'walk around' technology meaning that individuals, equipped with the Amazon Go app on their phone, can simply scan a QR code at the entry turnstiles then pick up what they want and walk out, with the app processing payments automatically. Early reports have suggested Amazon is considering opening 3,000 of these stores by 2021 across the world, and even a fraction of this number will have a significant impact on the market and how its competitors use data and technology. The company also opened a new concept store, Amazon 4-Star, which uses Amazon's pre-existing online algorithms to only stock products that have been rated four stars and above by customers, or "the best of the best" – although Bezos has yet to reveal if there are more to come.

This U-turn in Amazon's strategy is not as surprising as it initially seems. Despite physical retail seemingly on the decline, property consultancy Colliers predicts that the current online shopping bubble is set to burst, declining from the current level of 11% of the market to 7% by 2022, pushing retailers to invest back in the physical realm – but taking with them the lessons they have learnt in the digital world.

Others latching onto this trend include retail behemoth Walmart which recently announced it would add 4,000 robots to its stores over the coming years – a move that will likely get people off their couches out of sheer curiosity at the very least. Chinese e-commerce giant JD.com also opened a new store, 7fresh, last year. Featuring a number of digital technologies, 7fresh stores most notably boast smart shopping carts which follow the customer around the store.

Over the next few years, we will see retailers, especially the larger players, using the data they have compiled and their greater understanding of consumers to build brick-and-mortar stores that focus on establishing the most exciting, most attractive and most convenient customer experience. Brick-and-mortar stores are not dead, but they will look very different to how we remember them.

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