Retail Analytics is the future of the Brick-and-Mortar world. The Retail world is steadily adopting the Retail Technology with Big Data solution to increase sales, which is by 73% as for now according to a recent analysis.
Common Challenges faced by Big Data:
- Predicting consumer behaviour has now become a difficult task after the advancement of science and technology. Technology now has become a double-edged sword which is after retail business. When one edge is providing constant newbies to consumers and making the consumer change their behaviour every now and then, the other end is providing information on consumer behaviour which is in a constant change.
- As the trend in retail is changing at a rapid pace, it is becoming very difficult for the retailers to reach into any conducive conclusion. The only option is thus Retail Analytics, without which trend determination is not at all possible.
- If you are happy with a product you will share your feelings to 1, but if you are not satisfied with the same, you will inform it to at least 10. It goes viral overnight with the blessing of social media platform and is enough to ruin the business from the bud.But with Hadoop and the Retail Analytics you can predict the feelings of your customer and think otherwise to save your business from sure closure.
Some customers reaction varies from cry to laugh and from sigh to praise with the launch of any advertisement while others are simply indifferent. But the retailers are investing millions in advertising and wasting the money without any assurance of being paid. And it is very likely that the product is not in demand or maybe the competitor is making a sound business. So, whatever the situation is, the result is a loss of capital. With the use of Big Data and Retail Analytics, the retailer can understand the choice and the top demanded products of the consumer and promote it accordingly.
Big Data Platform in Retail Stores:
Fraud determination has rocketed so high that every year one giant retailer is sure to get into the trap. Fraud detection is designed mainly to keep up consumer trust and reputation of the company. The most common frauds include stolen credit and/or debit card and the deceitful return of once purchased products. Hadoop used by online giants and some retail store proved to give fraud a good shot.
Localization and personalization of Customer Driven promotions: Role of Retail Analytics
Constant change in the buying behaviour of the customer forcing the retailers to change and personalize their promotion-pack, business strategies, pricing very frequently. Some of the localization factors are now on the list that is in extensively used by the retailers like – Geographic location, Nearby location, Seasonal variation, Festival criteria etc.
Suppose you are in Australia and it is the Christmas time, then you will get offers on summer products. While if you are in the US during Christmas, you will get offers on woollens. Various online eCommerce stores have mastered the art of consumer customization. Seasonal freebies, shopping offers floods our smartphone and emails. Hadoop technology is bringing a new wave in the retail online world. But we are explicitly looking for a prompt and perfect result from the brick-and-mortar to be actually happy after a tiresome shopping!
Hadoop is receiving consumer personal information, product information and purchase history through the retail apps. Hadoop Distributed File System analyze all the variables and personalized recommendation is generated which increase the sales and generate ROI.
Supply Chain Management: Role of Retail Analytics
Big Data is on the track to transform the meaning of the retail shopping, which was monotonous, tiresome and boring for many. With the new tech trend retailers can boost the efficiency of the supply chain management by enhancing the business status with supply chain stakeholders. Managing the supply chain can be more efficient with the use of Hadoop and Big Data. It can help in tracking the product package in real time and give the quick response in shipment process. Inventory optimization, Replenishment and Shipment costs can also be controlled by the Hadoop Distributed File System
Real Analytics: An approach for Dynamic Pricing
A customer always compares the price of online products with the retail store. So there must be 100% price transparency. Hence a dynamic price platform is a must that can help the customer to take a decision to buy any product.
It can be implemented either by Internal Profitability Intelligence (price determination based on own manufacturing and distribution cost ) or by Internal Profitability Intelligence (price determination based on competitive products).
Retail Analytics towards Integrated Forecasting
Prediction in the retail world in next to impossible. This is mailnly because the availability of an unlimited choice of any product in the present market situation. This is truly a perfect Big Data which needs to be analysed without any flaws. And flawless calculation of such Big Data is only possible with Hadoop technology and Retail Analytics.
Big Data in Retail can so be used to generate millions of predictions on a regular basis at a product or at store level.