Retail analytics offers analytical data on the state of the supply chain, consumer demand, sales, and other crucial business data points. Retail analytics provides both in-depth understanding of the fundamental business operations supporting retail and CPG as well as specific customer behavioral data.
An growth in the use of just-in-time (JIT) supply chains and inventories has had an impact on retailers of all sizes, both online and offline. Being able to acquire exactly what they are certain they can sell, especially for smaller merchants, helps keep operational expenses low and preserve tight profit margins. JIT is not risk-free, though, as the COVID issue showed when some JIT supply chains found it difficult to meet demand.
Retailers are relying more than ever on operations, sales, and marketing statistics (internal, offline, and third-party) to make better business decisions in response to these difficulties.
The importance of retail analytics
Retailers both online and offline faced challenges as a result of the pandemic disruption. Despite the decrease in foot traffic brought on by the restrictions, statistics shows that consumers prefer an in-store purchasing experience. According to a PwC poll, approximately 40% of consumers make purchases in person at least once every week. Over 60% of customers chose in-store shopping because they wanted the things right away, while 65% did so to avoid paying delivery fees. Customers prefer purchasing in-store 61% of the time because they like to touch or utilize the merchandise.
With the help of retail analytics, retailers can take full advantage of this demand and tip the balance in their favor. Retail analytics are responsible for the success of purely online competitors like Alibaba and Amazon. They developed hyper-personalization tactics as a result of better understanding their clients. By using data-driven tactics, physical stores can also advance. They do, after all, have one very clear edge over pure-play retailers: physical accessibility.
The leverage is the in-store experience. Analytics in-store can have an impact
Once clients enter the store, retailers in the modern day employ a variety of techniques to monitor their movements.
Brands can improve the in-store experience by utilising innovations like smart mannequins that analyse faces to determine age, gender, race, and how long customers spend in the store. Customers’ information on the store aisles visited, the amount of time spent, the products they selected but didn’t buy, and more are gathered via smart carts with location beacons and sensors.
Using in-store analytics is beneficial because:
- Identify the differences between customers and shoppers, as well as their behavior from the entrance to the exit.
- Determine which products sell quickly and which ones don’t.
- Avoid stealing and shoplifting.
- Analyze how well store displays and employee behavior influence customer purchases.
- Assign staff resources effectively.
Since data quality from many sources, including social network chats, online purchases, and local-specific smartphone contact, has developed into a brand-new type of digital-based transactions, retailing has become the setting for additional disruption driven by data.
The majority of retail establishments will employ techniques to build customer loyalty, enhance brand perception, and raise promoter scores as a result of the enormous surge in interest in data analytics for the retail sector. The use of digital transformation in the retail industry enables businesses and retailers to better understand their customers’ needs and how to meet those needs to boost sales. Data analytics will be around for a while as technology continues to govern the retail world!