Massive digitization in recent years has taken hold of the grocery industry. Grocery retailers constantly face the battle to meet customer demands. Furthermore, thousands of product lines require sound management and shelf space. Because numerous competitors compete for customer attention, remaining profitable has its challenges. In this article at McKinsey & Company, Gemma D’Auria, Andreas Ess, Holger Hürtgen, Gereon Sommer, and Alex Sukharevsky explain how the retail industry is making use of their data to run their business the right way.
Can Data Analytics Help Grocery Retailers Boost Their Operations?
“Many grocers have made great progress on analytical maturity. Leaders in analytics have tackled the majority of fundamental use cases, such as pricing, mass promotion, and assortment optimization,” explains the authors. Today, industry leaders are increasingly turning to pursuing new use cases while refining existing use cases, such as utilizing real-time data.
Significant Impact of Advanced Analytics on Grocery Retailers
Marketing Campaigns and Promotions
Data analytics enables grocery chains to take advantage of valuable data generated by consumers whenever they make a purchase—online or offline. An in-depth understanding of what products customers buy, their purchase habits, and their spending behavior allows grocery retailers to create well-targeted marketing promotions. Furthermore, advanced analytics will enable supermarkets to gauge their marketing campaigns’ overall profitability and effectiveness.
Planning and Forecasting
Consolidation of strategic, financial, and operational data into a single point of truth creates a strong foundation for forecasting activities. This increases the planning accuracy of grocery retailers. Furthermore, data analytics helps HR, sales, marketing, finance, and management teams to see the bigger picture and build strategies accordingly.
Studies reveal that in 2021, nearly two-thirds of in-store shoppers and 51% of online customers experienced out-of-stock products. This resulted in more than $3 billion loss for supermarkets across the US. What makes inventory management so daunting? Experts point to fluctuating demand, seasonality, and delays in re-ordering as some of the reasons. Data analytics can help grocery chains to explore:
- The average spoilage time for each item
- Seasonality impacting customer needs
- Special event demands
- Excessive inventory
To read the original article, click on https://www.mckinsey.com/industries/retail/our-insights/grocers-can-fuel-growth-with-advanced-analytics.