Data Science for Retail domain

The 4 basic fundamentals of any retail business are sales forecasting, inventory management, assortment planning and pricing of the products. All of these are interrelated and if these are not in sync or accurate means loss. Also, the evolution of omnichannel retail the importance of the above four have also increased.

Big retail groups like Amazon, Big Bazaar are already having a system created to compute all these factors and run their business. However, the traditional techniques they are using is not much effective in terms of predicting as well as resources. And the expanding social media has also great impact on the sale of any product which is adding the complications in the forecasting. Now people first check social media for the reviews of the products first before buying it, so despite of investing a lot of money in marketing if the social media is ignored then sales forecasting would go horribly wrong.
Thus, the question arises what is the solution for this, the answer is obvious “Data Science“. Yes Data science was very expensive, reason was technology was not enough to read and analyze huge amount of data.
But now as technology has evolved a lot, data science has become affordable and days ahead it will be cheap enough that even a convenience store can also afford it.

Now the point is how data science can help the retail industry? The different machine learning regression techniques not only the sales forecast or inventory can be managed, but with the association models like Apriori, Eclat.. baskets can also be predicted.
The best live examples are the recommendation method of the Amazon. Small stores can also use it for there store layout like which products should be kept together and which should be apart to increase the sales.
As I mentioned, consumer emotion also drive the sale of the products, with increase in processing capacity and evolving technology with the help of NLP analyzing public emotion about the product has also become very achievable.
There is also one major issue which retail companies faces, the change in forecast with introduction of new competitor of new competitor product. And computing all the metrics with the traditional methods is not only expensive but also time consuming.
By the time you complete your analysis may be the comptitor has already captured significant market share. With the help of data science this time could be reduced significantly.

Since major part of Indian retail sector is run by small retail shops if they are not benefited by data science even the big CPG, fashion industries cannot reach the optimum revenue and profit.
With implementation of GST it has become mandatory for them to keep the records/invoices. If any CPG company could take initiative to educate them how to maintain the data and if it is expensive for them to analyze sales of an small store.
They can educate them how to get it done with minimal investment. There are many communities these days which will do this job for you at a very cheap rate as they are more interested in building their skill or researching in Data science field.
We cannot expect the change right away but education and evolving technology this is not impossible either.

Disclaimer: Views expressed here are personal.

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