A positive customer retention rate is one of the most wanted outcomes of applying Big data analytics in retail. Data analytics is a powerful catalyst for many innovations and advancements that have enabled retailers to understand what their customers expect from their products and brands.  

Did you know that a 5% increase in customer retention can increase your profits by 95%? Also, it is seven times less expensive to retain customers than to acquire new ones. When you ask retailers like Walmart, Amazon and Costco how they built this huge customer base, the answer would be data. 

Data Analytics combined with the latest cutting-edge technologies such as data warehouses, data lakes and generative AI, retail businesses can expect an upward trajectory in their customer retention in retail. This blog discusses what retail data analytics is and how it helps improve customer retention in the retail industry.

What is Big retail data analytics?   

Big Data analytics in retail typically involves gathering, processing and interpreting data from various retail sources, such as sales transactions, customer interactions and inventory, to gain valuable insights. The primary goal of retail data analytics is to extract valuable insights from this data, which can help retailers make informed decisions and improve customer retention.

What does Big data analytics in retail mean to today’s retailers? 

There is no doubt that Big data analytics in retail is a game-changer for today’s retailers on so many levels. All retailers want the same thing. A few seconds of attention from their customers. It may seem like a simple objective for many, but the amount of money and effort retailers invest is significant. But the question is, “What does it take for retailers to grab the right kind of customer attention that can be translated into customer retention in the future?” The answer is here — retail data analytics. 

Benefits of Leveraging Big Data Analytics in Retail  

Today, customers want more than a good product and customer service from a retailer. Retailers need to understand this growing array of customer expectations from their customer data of preferred and favourite brands. Most retailers know this and do whatever it takes to make their customers happy and retain the brand.  

Data analytics in retail

Here is how Big data analytics in retail can help retailers:   

  • Understand customer better: Retailers can analyze customer data to get deep insights into preferences, behavior, and buying habits. Retailers with retail data analytics in place can provide a personalised user experience to their customers. This way, creating better customer retention in retail becomes easier for retailers across the globe.    
  • Streamline inventory management: Data analytics in retail help retailers forecast demand accurately, ensuring that they have the right products in stock at the right time. This minimizes overstocking and understocking, reducing costs.  
  • Build resilient and efficient marketing strategies: With real-time data analytics that help visualise data a retailer deals with in a more simplified way; retailers can measure the effectiveness of marketing campaigns. Simplified reports and dashboards integrated with CRMs and ERPs can drastically change how retailers allocate resources to their marketing campaigns.  
  • Improve Pricing Strategies and Sales: Leveraging data analytics in retail enables retailers to set prices more strategically. Data analytics combined with business intelligence in retail help customers enjoy a personalized shopping experience with more relevant product recommendations. Data-driven insights can lead to better product recommendations and cross-selling opportunities, increasing sales.  
  • Implement loyalty programs that work for customers and retailers alike: Now, retailers can measure customer loyalty, which allows them to identify and reward loyal customers and build stronger relationships with them in the long run. Big Data analytics in retail enables retailers to understand individual customer preferences and behaviors. This data, in turn, can be used to tailor loyalty program rewards and offers to match each customer’s interests and shopping habits. Moreover, personalized incentives are more likely to engage existing customers and play a key role in improving customer retention in retail.  

Transmuting customer attention into customer retention with data analytics…

Unlike any other industry, the retail industry deals with massive data. In fact, that is what makes this industry more competitive and proactive. More data means better analytics. And with better analytics, retailers can make the most favourable business decisions. Studies show that 80% of retailers say that they would highly benefit from a CRM system that provides an accurate single source of information. However, over 75% of retailers don’t have one as of 2023.   

In today’s highly competitive retail environment, data analytics is a critical tool that empowers retailers to make informed decisions, drive customer satisfaction and remain relevant in responding to market trends and consumer preferences for their preferred products. To learn more about how data analytics in retail helps your retail business increase its customer retention and ROI using real-time data analytics, talk to our data analytics experts today.   

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