How Predictive Analytics Reinforces the Retail Sector

The retail sector has undergone a tonne of changes since the popularization of e-commerce. After a long battle between the offline and the online stores to win more consumers, the online commerce has finally taken a convincing position on the front seat. The fight right now is for visibility and customer retention. Predictive analytics is becoming the primary resource for retail units to survive and thrive in the unforgiving market.


What is predictive analytics?


Data or information is the only way to know your customers as well as the market. The sales records from the previous quarter, the feedback provided by consumers on the company website, the amount of time spent by a customer on a certain page of your website, all qualify as data.

When this data is run through analytical models to predict the future it is called predictive analysis. Predictive analysis can take a number of different factors into account to provide accurate results. Although absolute accuracy in predictive analysis is never guaranteed but the rate of accuracy improves with the quality of data and the skills of the analysts.


Analytics to set prices


Pricing is one of the key aspects that retailers focus upon in order to lure in and retain customers. Not only can a predictive model factor in customers’ buying habits, and general feeling about a certain products, but also the weather and the economic conditions of a state, to optimize pricing. It is very important to find an optimal price for a product which ensures profitability while creating a good deal for the customers.

Analytics for stock management


Just looking into the sales records from the previous year, you can pile the stocks. But this approach can easily take your business south if there is a sudden change in consumer behaviour. Allowing advanced predictive models to help you manage the warehouse can significantly reduce the risk of heavy losses.

Marketing and promotions


Analytics can help you pin point your marketing strategies on a certain group of consumers based on demographic and transactional data. You can also use data analytics to optimize the content of the ads to strike the right chord in the consumer’s mind.

Promotions can be quite irritating if they appear too often and it gets worse if they appear at a wrong time. Predictive analytics can help time the promotions better based on the customers’ online activities.


Optimizing logistics


The pandemic has forced a lot of retailers to reach the customers. Proper logistic support is an essential component of a successful business today. Data analytics can help you proactive in terms of maintaining the vehicles.


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