Analytics in Retail: 5 Imperatives to Succeed in the Canadian Grocery Retail Sector in 2022

Jan 30, 2020

advantages of market basket analysis

In the realm of grocery retail globalization, Canadian grocery stores are challenged by the growing data volumes and are forced to make tough choices that can make or break their success. Data-driven disruptions and the evolution of new & advanced business models have not only complicated the current Canadian grocery retail landscape but have made it difficult for businesses to sustain a leading edge without the use of analytics in the retail industry.

In the face of these disruptions and the growing popularity of analytics in the retail industry, legacy Canadian grocery stores are forced to ramp up their analytics investments and focus on driving growth in several key areas including- procurement, inventory management, consumer demand management, supply chain optimization, and sales. However, to excel in each of these areas it’s crucial to note that analytics in the retail industry has a major role to play in offering rich data-driven insights and ensuring the availability of these insights across all business units.

Based upon the current Canadian grocery retail scenario and the combined views of our retail data analytics experts, we believe that success in the Canadian grocery retail sector in 2022 will be defined by the retailer’s ability to analyze data and master the highly dynamic marketplace in which they operate. In 2022 the Canadian grocery retail sector is expected to manifest itself in a variety of ways based on the following trends that shed light on the role of analytics in the retail industry.

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Analytics in Retail: 5 Imperatives

Focus on Assortment Optimization and Shelf Space Allocation

The growing use cases of analytics in the retail industry have shed light on assortment and shelf space optimization which impacts several business processes among the categories in the Canadian grocery retail sector. Owing to such factors and its widespread impact on other business processes inventory and shelf space allocation play a huge role in helping businesses succeed in the long run. Today analytics in the retail industry plays a critical role in driving business efforts forward by determining the products with the highest level of profits.

Improve your Ability to Detect and Prevent Fraud

As fraud prevention and detection gain prominence in the Canadian grocery retail sector, it becomes imperative for Canadian grocery stores to explore the true potential of analytics in the retail industry to preserve customer trust and prevent losses. With orchestrators of fraud using new tools, retailers must leverage analytics in the retail industry to identify and prevent fraudulent activities.

Localization and Clustering Gains Prominence

Leading Canadian grocery stores acknowledge that the demand for their goods varies by geography, demographics, and the behavioral attributes of customers. As such, it is crucial to customize the offerings and store formats for a wide variety of value proposition elements including assortments, store layout, and pricing.

Offer Personalized Product Recommendations

With the proliferation of the Canadian grocery retail sector and its wide array of offerings, there is a growing need for leveraging retail analytics to drive product recommendations and personalized experiences. While collaborative filtering is the most common approach that focuses on leveraging analytics in retail to improve product recommendations and offer personalized product experiences, one must not forget that the role of analytics in retail spreads across business functions impacting every aspect of decision-making in retail.

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Analyze the Importance of Supply Chain Analytics in Driving Outcomes

Retailers irrespective of the segment that they operate are aware of the importance of supply chain analytics in driving retail outcomes. Since the business benefits of supply chain analytics are widespread, its essential for retailers to analyze their use cases and adopt a comprehensive approach to drive maximum value from their investments in analytics.

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