Predictive Analytics In Retail

Predictive Analytics In Retail

Authored by Ameex Technologies on 05 Sep 2019

Data is the key to make successful decisions for any business, but it all depends on how well we utilize the data, there are few industries that collect more data than the retail industry. The global big data analytics in retail market was estimated at $3.45billion in 2018 and this market is expected to reach $10.94 billion by the end of 2024. Still there are many challenges that the retails face.

What are the challenges stores face?

  • Promotions
  • Fixing the right price
  • Inventory management
  • Personalization

Predictive analytics will help us overcome these challenges.

What is predictive analytics?

Predictive analysis uses various statistical techniques (data mining, predictive modelling, machine learning) that analyse current and historical facts to make predictions about future or the unknown events.

How can predictive analytics be used in retail to overcome the challenges faced?

1.Promotional activities

Amazon uses offers and discounts to pull in more customers to its site, they use predictive analytics to forecast demand and provide discount for the products, unfortunately retail stores don’t use data as much as amazon or any other ecommerce business. The profit margin of stores takes a hit as they provide huge discounts on slow moving products

Solution

An application with mix of machine learning algorithm and coded rules can help in predicting the price point at which the product will yield profit using the marketing elements and also will help in analysing the impact of promotions.

2.Pricing

Pricing is an important factor that determines the sales and profit in any retail, a small change in price will impact sales. Price optimization is important because customers when in store check the price of the product online and purchase the product only if the price matches. The cheaper the price of the product the more it sells but this might not work for the premium products.

So how do we arrive at the optimum price?

Price optimization should be done using both predictive and prescriptive analytics to predict the future trends and optimize the prices. Predictive analytics predicts the future trends whereas prescriptive analysis gives the possible outcomes and the solutions to the future trends. Predictive model is the best solution because it considers various factors (Inventor level, Pricing models etc) before predicting a price.

3.Inventory management

Inventory management is the key to boost sales, the moment customer does not find the product he is looking for, he moves to the competitor, this is also known as inventory distortion. According to a study from IHL group retailers lose $814 due to distortion, in which 56% is due to out of stock and rest of the 46 % is due to over stock. The solution to avoid inventory issues is to predict the customer purchase behaviour effectively. This can be done with the help of advanced analytics and predictive analytics.

To solve the inventory issue predictive analytics can also be used in ABC approach.

Retailers use ABC approach for effective inventory maintenance.

4.Personalization

According to a research from epsilon 80 % of consumers are likely to make a purchase when brand offers personalized experience. Personalization in retail is not as simple due to the variety of products and number of stores available.

As they collect so much information, we can use advanced analytics to provide personalized experience.

For example

Providing coupon code to consumers as an incentive to download the app and send notifications regarding discounts, recommend the products that they may be interested while they are in the store.

Conclusion

At this point of time where the customer is very much interested in personalized experience, retail industries must focus on advanced analytics to increase their sales and to provide a fruitful customer experience.

To know about how we have helped clients with advanced analytics, write to us at info@ameexusa.com

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