Realising the value of data analytics: bringing big data and IoT together

Intel explains why retailers need to use analytics tools to gain actionable insights from their data

Rebecca Gibson
Rebecca Gibson
By Rebecca Gibson on 01 May 2015
Realising the value of data analytics: bringing big data and IoT together

This article was first published in the Spring 2015 issue of OnWindows

In the past, the most successful retailers were the companies that offered high quality products at the best prices, or the best promotional offers, or were simply situated in the prime position on the high street. However, the explosion of digital technology, e-commerce websites and changing customer demands have made it more difficult for brands to attract and retain customers in the same way.

“Today, the elements that previously differentiated brands have become commoditised and most retailers face minute-by-minute competition from many brands of greater sizes, so they must find new ways to foster brand loyalty,” says Jon Stine, global director of retail sales at Intel.

Although many retailers have deployed connected devices to boost customer experience and brand affinity, Stine explains that most have not yet implemented the accompanying analytics tools they need to make use of the valuable actionable data captured by these devices. “Every consumer, product and business process leaves a distinct data trail in both physical and online stores, which is known as the internet of things (IoT),” he says. “However, retailers often have no idea what information they are collecting via these infrastructures, let alone how to leverage it to improve business processes and customer engagement. In future, the most successful retailers will be those who deploy analytics tools and use data insights to better understand customers’ needs and align their products offerings with market demands.”

Not only does Intel provide mobile devices, RFID technology, in-store sensors and more to help retailers capture this data, it also offers analytics tools that help make it more accessible. The company’s suite of application programming interfaces management tools enables retailers to acquire actionable data by securely connecting previously siloed data sources.

“The Intel IoT platform provides retailers with new and secure data streams that can be incorporated into a wide variety of business decisions, opening the door to a whole range of new innovations and revenue opportunities,” explains Chris Hunt, IoT solutions architect at Intel.

Plus, retailers can use Intel’s range of IoT gateways to create efficient local architectures and leverage hyper-local data filtering and analysis tools to aggregate the data captured by their IoT networks. “Our ecosystem of on-premises and cloud-based third-party retail analytics firms can also provide retailers with the ability to rapidly prototype and develop the algorithms that drive insight,” adds Stine. Intel’s IoT platform also allows retailers to gather and analyse data from disparate sources more easily.

“Retailers are unable to use the data they have gathered because they are operating on legacy enterprise infrastructures that are comprised of different data silos and solutions from various technology providers,” explains Shailesh Chaudhry, director of business strategy in Intel’s Retail Solutions Division. “Intel’s IoT platform enables retailers to collect data from various devices and securely deliver it across their entire networks, including edge devices and the cloud. This allows them to analyse data to optimise profit, deliver personalised experiences and meet customer expectations.”

Retailers are also starting to recognise that consumer-owned devices can provide valuable insights into customer behaviour. “Data from these devices can help retailers to track the flow of customers in their physical stores, monitor stock levels, and even record the frequency of visits from their most loyal customers,” Stine explains. “This can be combined with external data about market trends and individual customers – such as purchase history or online habits – to help retailers understand how to optimise inventories, enhance the in-store experience and improve cross-channel processes.”

When retailers realise the potential of the valuable data stored in their connected devices and IoT infrastructures, the possibilities for improving the customer experience, boosting loyalty and driving revenue growth are endless, Stine says. “Yesterday’s retailing world was dominated by the merchant princes, but tomorrow’s world will be dominated by the insight kings and Intel is excited to see the value that retailers will create with simple but effective technology implementations.”

Predicting customer behaviour
US company Big Cloud Analytics (BCA), which provides real-time marketing prediction solutions, uses multiple algorithms running on the Intel IoT Gateway platform to aggregate multiple sources of historical and real-time data to provide retailers with predictive analytics capabilities.

“Intel’s IoT Gateway platform provides a secure environment to bring all raw sensor data together and transform it into easily digestible, actionable insights that can be used to personalise customer interactions, drive sales, optimise pricing structures, develop targeted marketing campaigns and more,” explains J. Patrick Bewley, BCA’s chairman and CEO.

For example, retailers can use BCA’s analytics tools to provide sales associates with access to a complete profile of a customer the second they walk in the store, allowing them to predict their behaviour based on past purchasing history, identify potential cross-sell and up-sell opportunities, or even forecast whether they are likely to become a long-term customer.

“Most brands already collect data, but are not sure how to leverage it, or combine it with other internal and external data, to gain new insights about their brand, customers and market trends,” says Lisa Cangro-Essary-Coons, global solutions executive at Intel. “Together, BCA and Intel enable retailers to insert real science into every customer interaction by providing them with the real-time analytics they need to understand the ‘shopping genome’ of each customer and develop ways to assist and excite them, while boosting revenue.

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