The year 2021 for the Retail Industry has been an incredibly challenging time. New technologies have emerged in response to rapidly changing consumer demands. The plethora of choices available for customers today have multiplied their expectations many times over. To cater to these multi-faceted demands whilst ensuring profitability, retailers are increasingly relying on AI and data-driven solutions. Retail analytics solutions make strategic use of data to map every aspect of customer behaviour. From their product preferences and shopping patterns, to purchase behaviour and cost constraints, it uncovers all important areas of customer-centric data.
How Do Retail Analytics Solutions work?
Some retail companies have sufficient resources to hire and train an in-house retail analytics team. Others find it more cost-effective to outsource their requirements to an experienced retail analytics solutions provider. Whatever be your choice, the core operating principles of retail analytics remain the same. Here’s a snapshot of the same:-
- Synergizing various retail departments (sales, marketing, merchandising, operations) to work in tandem with data-driven insights
- Tactical use of big data and AI to improve the customer experience at all moments of truth (MOT)
- Weeding out duplicities, errors, and other loopholes in the store KOPs
- Using real-time data for Sales Forecasting, formulating Merchandising Plans, and Inventory Management
- Assisting Retail Marketers with a reliable, updated, and error-free database for effectively nurturing leads
- Leveraging data science to identify the primary growth drivers and focus on improving them
- Intelligent Data Assessment to monitor Employee Productivity
5 Incredible Customer-Centric Advantages of Retail Analytics Solutions
The customer’s in-store experience includes several important stages like:-
- Checking out the store window display
- Stepping inside the store
- Reaching the product aisles and finding what one is looking for
- Browsing offers and other products
- Asking for shopping assistance
- Sampling/Trying products if applicable
- Heading to the checkout aisle
- Billing and feedback
Each of these in-store experiences constitutes moments of truth (MOT). These are the key customer experience stages or moments that determine how they perceive your brand. These also determine the probability of a repeat visit or a repeat purchase. Let us understand the benefits of retail analytics solutions for shaping the best in-store customer experience:-
- Improved Personalization– Retail analytics provides precision-based and valuable insights to enhance the customization or personalization parameter. This is the key to a superlative in-store experience for the customer. Furthermore, the concrete data provided by retail analytics align in-store services with the exact requirements of customers.
- Precise targeting– With proper data-backed insights, a retail marketer can formulate marketing strategies that focus on the ideal customer persona. This is a sea change from legacy-based retail when marketing strategies were outlined as per the mostly tunnel-vision strategies of the top management.
- Virtual Brand Consultation– Owing to the Covid-19 pandemic, the customers who preferred physical shopping are largely confined to their homes. Online shopping appears to be the only feasible way for making safe, contact-free purchases. But the average Indian customer is largely dissatisfied with not being able to physically check out and buy the products. Here comes the role of virtual brand consultation, essentially driven by retail analytics services.
- Better Retail Merchandising– Merchandising covers all the aspects of in-store products promotion. This includes creating attractive displays, bundling products to sell better, up-selling, cross-selling, product demos, highlighting discounts, offers, and so on. Retail analytics data helps merchandisers to align their efforts towards creating an exceptional customer experience.
- Better Checkout Efficiency- Retail analytics can play a big role in easing out the checkout process. The speed and efficiency of checkout is the single-largest factor that determines whether the customer will visit you again or not. Retail Data Science can guide you on which POS systems are the best. Furthermore, it can help you in training staff to prioritize checkouts, and putting a structured feedback mechanism in place.
Conclusion
Of all the advantages of relying on retail analytics solutions, the customer experience improvement parameter is the most important. With the escalating competition, the only way to differentiate your offerings is by providing a remarkable in-store experience. This will create a positive brand image, ensure repeat visits, higher sales, and expand your customer base. The streamlining of inventory management, employee management, and operational efficiency are add-on benefits that make this process furthermore lucrative.
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