"As the Internet of Things (IoT) continues to expand over the next five years, the effects on multichannel retailers will be more disruptive than anything seen to date and will require advanced analytics capabilities to cope with this disruption,” says Robert Hetu, research director at Gartner, and author of the report Retailers Find Success Using Self-Service and Advanced Analytics.
The report says retailers should look to invest in advanced analytics providers that specialise in retail solutions.
In a world where customers are no longer humans, but "things" that band together with other things to negotiate prices, the retailer must reconsider its role, the report states.
This is an evolutionary step similar to the disruption of digital media that impacted retailing of books, music and video, creating a myriad of opportunities for disintermediation from the likes of Amazon and Netflix, while eliminating traditional market leaders such as Borders and Blockbuster.
Retailers without advanced analytic capabilities may be toppled by their inability to capitalise on IoT-driven revenue opportunities, notes Hetu.
For example, a customer's refrigerator that can sense the need to replace its water filter is an example of the retailer's need to compete and the associated need for advanced analytics.Read more: When the IoT meets your IT department…
"While today the retailer may feel confident in that customer's repeat purchase — perhaps because the customer acquired the appliance from the store or is comfortable locating the filter in the physical store — the refrigerator, seeking the replacement on its own, has neither loyalty to the retailer nor concern about finding the item," Hetu explains.
In a world where customers are no longer humans, but 'things' that band together with other things to negotiate prices, the retailer must reconsider its role.
"As a result, the "thing" (in this case the refrigerator) will seek the best combination of price and availability. This change will require the retailer to evaluate the potential transaction in an instant and determine a course of action to save the sale or allow it to pass to others."
New tools of the trade
Gartner defines advanced analytics as the analysis of all kinds of data using sophisticated quantitative methods to produce insights that traditional approaches to business intelligence (BI) — such as query and reporting — are unlikely to discover.Read more: Vocus acquires Amcom for $780 million
These advanced analytics tools enable deeper insights and discovery that will challenge business assumptions. They also put information in the hands of business analysts and business users and offer significant potential to create business value and competitive advantage.
The impact of digital business and the IoT will require advanced analytics to support real-time decision making to take advantage of momentary business opportunities. These opportunities will demand a different approach to marketing, merchandising, pricing, distribution, store operations and every other internal process.
Ultimately, the retailer will need to be able to decide in a split second if an opportunity is potentially desirable or should be passed up in favour of the next momentary opportunity. Success will require retailers to use a combination of knowledge, innovation, speed and strategy to maintain and grow market share in the digital economy.
Gartner believes the need to improve real-time business decision-making will force retailers to acquire self-service and big data discovery capabilities. With big data discovery, the entry bar to explore big data sources will be lower. Analysis will be delivered at a lower cost and faster, by a broader and less-skilled set of users, ready for consumption by a broader audience.Read more: Tour de France provides platform for big data analytics
"Big data discovery tools put information in the hands of business analysts and business users to enable better decision making. Since these analysts and users are less skilled than their counterparts in traditional BI roles, they will only handle less complicated problems, which will take them less time to fail or succeed," says Hetu.
"They are also closer to the business complexities, making it easier to establish interactive analytic processes that will speed up results. This will allow big data sources to be explored more often, feeding valuable information into the business and yielding faster results."
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