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Taking the Complexity Out of Analytics


There is more data filtering through retail enterprises than ever before. But while most retailers have data collection down to a science, they still need to learn how to extract value from this information.

Social media, mobile devices and emerging digital channels are creating a new level of data volume; and the pace of this incoming data shows no sign of slowing. Unstructured data, such as metadata, audio and video files, is different from structured data, which includes currency, numbers, names, dates and addresses filtered through point-of-sale solutions, customer relationship management systems and other mission-critical applications. Unstructured data evolves faster and is much less predictable.

“Big data began swelling during the late 1990s and early 2000s, and retailers quickly began storing it in robust data warehouses,” said Marc Janssens, EVP of retail business unit, Fujitsu America.

“However, information was still batched, making analyzed predictions inaccurate,” he added. “For retailers to survive in an increasingly fast-paced, digitally influenced world, they need innovate within their analytics efforts, and add tools that will enable them to quickly access data and make decisions in real-time.”

Retailers saddled with legacy systems lack the agility needed to achieve these goals. Besides being antiquated technology, legacy systems are often disparate systems that manage silos of data — making it a struggle to integrate today’s more agile analytics architectures.

This is further exacerbated as more competitors hit the scene, especially more nimble online players such as Amazon, which continues to edge out retailers on price, value and shipping. Many of these online marketers already use flexible analytics-based optimization solutions — for operations from marketing promotions to pricing — to stay abreast of customer behavior and traffic patterns at a moment’s notice. And this information keeps them one step ahead of more traditional competitors.

But more traditional competitors are fighting back. They are embarking on “digital transformations” across their enterprises, a move that often involves adopting flexible, cloud-based architectures. Besides reducing their reliance on legacy architecture, cloud-based platforms also give retailers streamlined, cost-effective access to next-generation analytics tools — an opportunity that enables them to leverage data quicker and make decisions faster.

These new data analytics investments will contribute to an expected 114% growth in the analytics market. In fact, the segment is expected to more than double between 2016 and 2020, surpassing $7 billion, according to global analytics and advisory firm Quantzig.

As more retailers reach for the cloud for their data analytics needs, here are some of the functionality priorities on their radar:

Graphical solutions. Retailers want more accessibility to data, and to get it into decision makers’ hands in a more digestible way. New content management tools display details in a more graphical, interactive format — a move that evolves data beyond static Excel spreadsheets, making it easier for users to slice and dice information.

Flexible rules and key performance indicators (KPIs). As data continues to enter organizations in real-time, retailers need flexible solutions designed to handle this fluid flow of information, and assist in making decisions that meet shopper demand and expectations. However, the rigid, sales-based KPIs many chains currently rely on won’t give users the answers they need.

New solutions have smarter engines and the ability to customize rules. As thresholds are met, such as specific product, department or channel performance, analytics tools push notifications to managers, giving them real-time insight into information, and the ability to make adjustments where needed.

“Moving away from generic metrics and rewiring KPIs will help retailers more accurately understand their goals and respond to demand,” said Maya Mikhailov, co-founder and chief marketing officer of GPShopper.

“The new state of analytics requires users to see the right KPIs — clearly defined metrics that pertain to modern customers,” she said. “And even if they fit now, they may not in 60 days. Continue to revisit KPIs and refine rules as needed. This is the only way to get a clear picture of the market and customer.”

Advanced employee training. As solutions evolve, so must associates’ analytics skills. Dashboards may be increasingly user friendly, graphical and rules-based, “but the staff must be trained to understand what metrics mean, and their overall impact on the business,” Mikhailov added. “Solutions may be getting more automated, but retailers will always need talented associates to understand the information and respond.”

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