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Do retailers require analytics to compete in digitalised marketplace?

Do retailers require analytics to compete in digitalised marketplace?

Retailers will not be able to compete in the digitalised marketplace without advanced analytic capabilities.

Retailers will not be able to compete in the digitalised marketplace without advanced analytic capabilities.

That’s according to Gartner, which claims retail organisations should look to invest in advanced analytics providers that specialise in retail solutions.

“Consumers have taken control of the shopping process, and there is no sign that they plan to let go,” says Robert Hetu, research director, Gartner.

“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.”

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.

“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 adds.

“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.”

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.

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.

Retailers without advanced analytic capabilities may be toppled by their inability to capitalise on IoT-driven revenue opportunities.

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.

This is an evolutionary step not dissimilar to the disruption of digital media that impacted retailing of books, music and video, creating a myriad of opportunities for disintermediation from Amazon, Netflix and others, while eliminating traditional market leaders such as Borders and Blockbuster.

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 that 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.

“Big data discovery tools put information in the hands of business analysts and business users to enable better decision making,” Hetu adds.

“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.

“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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