“Information is the oil of the 21st century, and analytics is the combustion engine.” – Peter Sondergaard, Gartner
In today’s hyper-connected digital world, big data is everywhere. We all have a digital footprint and believe it or not, almost everything we do online can be analyzed, quantified and used to help track consumer trends, behaviours and insights that help brands reach out to us on an engaging, personal level.
That said, should you be a retailer and reading this: if you’re not at present, you need to start using big data to your advantage, by mastering and understand it namely thanks to a retail analytics software for instance. According to a recent study, 54% of consumers would consider terminating their relationship with a retailer if they don’t benefit from the bespoke content, offers and deals. And to connect with your target audience with valuable, personalized content or deals tailored to their personal needs, you need big data.
Big data offers in-depth information about the people your brand is targeting and it’s changing the face of the retail world in a colossal way.
To help you understand the impact of big data in retail, we’re going to look at the reasons why big data is important to the sector. We’re also going to delve into some valuable big data retail use cases to paint a vivid picture on the value of these metrics in the consumer world.
Let’s get going.
Why Is Big Data In Retail Important?
As mentioned, we live in a time where the average consumer is not only incredibly tech-savvy, but they crave intimacy with the brands in which they’re looking to invest, both on financial and emotional level.
Nowadays, a one size fits all mentality just won’t do.
Big data is helping retailers to understand their prospects on a deeper level and with a host of metrics including social media preferences, browsing behaviours, devices preferences, geographical demographics and much more readily available, brands are branching out in more meaningful ways than ever before.
And the value of big data isn’t just exclusive to digital-only retailers. Cisco discovered that in-store analytics alone offers a $61 billion value stake for retail. What this means is that older, more traditional brick-and-mortar stores have been given a new lease of life.
By leveraging highly-precise insights on how shoppers engage with their products or displays while in-store, high street businesses have been able to tailor their merchandising, deals and marketing campaigns to meet the needs of their shoppers. It’s also helped physical retailers measure their ROI far more accurately, helping with growth, development and commercial progression. The best tool that can help you with that is a retail dashboard, that lets you visualize all your analytics easily.
It’s clear that big data is an essential component of any modern retailer’s arsenal and without using such information, insights and metrics to your advantage, you could risk seriously falling behind the competition.
Using Big Data To Your Advantage
Besides the fact that big data analytics is helping those in the retail sector understand their customers far better, making the experience more personal, engaging and initiative at every stage of the buying journey, it also has notable benefits in other areas:
- Demand: By understanding data-based insights on customer habits, retailers can understand which of their products and services are most in-demand and which ones they should potentially stop offering. Not only can these insights serve to save money and where to place investment, but it will also help brands to give the consumer exactly what they want.
- Prediction: Trend forecasting algorithms in big data can help brands make key market predictions and forecast consumer trends. Thanks to professional data alerts, retailers monitor the demand fluctuation in real-time, and can develop products that will provide them with the best return on investment.
- Pricing: By gaining access to insights on real-time customer transactions, retailers can gain a better understanding which prices yield the best results on particular products. Big data technology can also be utilized for ‘markdown optimization’ – an understanding of when prices on particular items should be dropped. Retail giant Walmart has reaped the rewards of real-time merchandising, and as a result of its success, the brand is now in the process of building the world’s biggest private cloud in a big to dig even deeper into the behaviour of its customers.
- Cross-channel: In today’s world, the omni-channel experience is a big deal. Google research suggests that 98% of Americans switch between devices in the same day. As mobile technology and social media become all the more sophisticated, consumer craves a retail experience that offers value across a host of mediums and devices. Retail big data gives brands the power to harness insights extracted from these various devices and mediums to create campaigns, initiatives and offers that create a buying journey that works seamlessly both in a digital and physical sense. And as retailers that adopt omni-channel strategies earn 91% greater year-over-year customer retention rates compared to companies that don’t, this is an area that you can’t afford to ignore.
In summary, by using big data analytics to your advantage, you will be able to understand the wants, needs and desires of your customer base, understand demand, predict priceless market trends, make smarter pricing decisions and create valuable cross-channel shopping experiences. In turn, these efforts will boost your brand awareness, customer loyalty and conversion rates exponentially.
Now you understand how you can use big data to gain an all-important competitive edge, let’s look at some big data in retail examples.
Brands Benefiting From Big Data And Analytics
In the world of retail, many innovative brands and businesses have already seen great results from using big retail data to their advantage. These big data retail use cases will show you how.
This colossal coffee brand needs little introduction – and there’s a reason this Seattle-based brand has not only survived but thrived over its many decades of existence. In a nutshell, that reason is innovation.
Starbucks has the uncanny ability to open a number of branches on the same block and enjoy a healthy level of profit from each. By using big data analytics to its advantage, Starbucks can predict the growth potential of each new store by looking at metrics such as location, traffic, area demographics and customer behaviour.
Moreover, Starbucks gathered insights from their 90-plus million transactions per week and used this data to deliver a personalized experience to its customers, sparking innovations including its tailored digital rewards scheme that becomes more intuitive the more data it gathers on a customers buying habits and purchase history.
With reported revenue of $22.39 billion last year alone, it’s fair to say that Starbucks is a real retail winner.
The Weather Channel
Despite being a weather channel, The Weather Channel is one of the most forward-thinking broadcasters in the world of modern entertainment.
Through its data platforms, Location FX and Weather FX, the broadcaster studies the weather’s impact on the emotions of its viewers. By doing so, The Weather Channel harnesses the power of predictive analytics to steer its advertising partners’ campaigns in the right direction by spotting valuable locational trends.
Take the channel’s partnership with Pantene and Walgreens. By using the metrics collected by The Weather Channel, Pantene and Walgreens gained the power to anticipate when air humidity would be at its highest, launching a targeted campaign to prompt women to grab their products in a bid to prevent “embarrassing” (or so they say) seasonal frizz.
The result? A 10% increase in sales of Pantene at Walgreens for two months around the campaign’s launch.
Among the many consumer innovations Costco has launched as a result of harnessing digital metrics and insights, an incident involving a batch of contaminated fruit is perhaps the brand’s the most striking big data in retail examples.
Like many modern-day wholesalers, Costco tracks what you buy and when. A California-based fruit packing business warned Costco about the potential of listeria contamination in its stone fruits. Instead of sending out a blanket warning to all who shopped at Costco in recent weeks, the company was able to notify the specific customers that bought those particular fruits, first notifying them by phone, followed by a letter.
This particular example is a testament to the unrivalled power of big data analytics in the retail sector.
Ignore This At Your Own Peril
Contrary to the big data retail use cases detailed above, there have also been some infamous cases of commercial failures as a result of ignoring digital data and emerging technologies.
One of the most recent is the liquidation of the longstanding toy brand, Toys’R’Us. Not long ago, the children’s retailer announced that it would close around 180 stores in the USA alone as it begins bankruptcy proceedings.
Among a range of issues that led to its commercial doom, an obvious failure to undergo a comprehensive data-led digital transformation contributed to the brand’s downfall. By failing to use the wealth of available digital data to its advantage, Toys’R’Us failed to offer the kind of innovative omni-channel experience that helped set it apart from online retail giants like Amazon.
Had the company delved deeper into big data, it would have stood a tangible chance of retaining its established customer base and created a tailored shopping experience that would have helped it thrive in the digital age.
How Do Modern Dashboards Help You Make Sense of Your Big Data?
As we have seen all along this article, leveraging your big data analytics will lead to an increased business success. Hereafter we present you an actual way to use these analytics by visualizing important retail KPIs it in an understandable manner: professional real-time dashboards.
Sales & Order Dashboard
**click to enlarge**
With the advent and generalization of internet, consumption ways have changed, and today 96% of Americans now shop online against 22% back in 2000. This drastic increase also brings its load of analytics for you to track and understand consumer behavior better. As an online retailer, data collection is easier and abundant – so you better track the right metrics in an organized way to avoid drowning in information, and to make the most out of it.
With such a retail dashboard as the one above, you can evaluate how you perform in terms of orders and sales. Tracking the total orders you have and the average order per customer lets you manage the inventory to avoid product shortage or on the contrary, overflow.
Likewise, this dashboard shows you the perfect order rate, that gives insights on how efficient your business is when it comes to delivering without incident – from the fulfilment of the order to the shipping and delivering. This is precisely the type of metric you want to track as it directly impacts the customer retention rate and ultimately, the likelihood that they recommend your services to friends and relatives.
Finally, you can also see the returns, that need to be tracked and understood: why do customer send back their item? That will greatly help you improve your products and services in the future.
Retail Store Dashboard
**click to enlarge**
Now, not every retailer is online, even though it is less and less the case. But in many cases, the offline, in-reality presence is stronger than the online one. It is as important and needs even more tracking, as the data isn’t as easy to collect and compile as it can be online. Many different entities are involved, from the warehouse management to the sales store itself and its inventories.
By tracking what is happening in your retail store, you can identify some customers’ patterns and adapt your strategies accordingly to the results. Knowing what your best-seller articles are will give you insights on what is trendy at the moment and what customers like. You can order similar articles but also prevent stockout by identifying the top-10 items, and monitoring the OOS (Out of Stock) rate. Stockouts is a situation you clearly want to avoid because it will turn your unsatisfied customers to the competition, and harm your image.
Likewise, evaluating your total sales and breaking it down per category and per location will let you know who and where is your main point of revenue. That way, you can create customized campaigns that will have a higher impact on the audience, and better ROI.
The point is, big data is the future of retail and if you want to succeed in today’s and indeed tomorrow’s world, leveraging the wealth of consumer insights available to you is essential. If you don’t, you stand to fall behind the rest of the pack, rendering your brand as well as your products obsolete sooner than you might think. On the flipside, use big data to your advantage and the rewards could be endless – and that’s a beautiful thing. To enhance your big data knowledge further, you can check out our article on how big data in logistics is transforming the supply chain.