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Why you need DATA ANALYTICS for your E-COMMERCE Business?
Why you need DATA ANALYTICS for your E-COMMERCE Business?

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In the words of Claire Hennah, Global VP of eCommerce at Unilever,

“E-commerce is no longer a channel simply for the future. The future is here.”

Data analytics is the process of collecting valuable information from large amounts of data. It is the method of doing predictive analysis on a large volume of data to derive actionable insights. Data analytics is one of the most rapidly expanding disciplines today. Nowadays the fastest adopters of Data Analytics are e-commerce companies.

Let’s dive into the different avenues where analytics has a high potential of helping consumer goods companies scale up e-commerce sales.

Product Recommendations

A product recommendation engine is a solution. What is a recommendation engine?

It is simply an automated form of the ‘friendly storekeeper’. It is a tool that uses machine learning algorithms to suggest products to customers that they might be interested in. The recommendations can happen through the following channels:

  • Within websites
  • Email campaigns
  • Online ads

The recommendation engines are of two types:

a) Impersonalized Recommendation Engine:

This is useful for sending out recommendations via welcome emails or bulk newsletters, without using customer data. Here are some useful categories:

  • new products like a new chocolate ice-cream that has been recently launched
  • trending products like a fast-selling coffee brand to help recruit new customers
  • slow-moving products like a luxurious bar soap at a discounted price
b) Personalized Recommendation Engine:

This is gold! It uses customer data to recommend the best offers and promotions. It uses deep learning algorithms and Natural Language Processing (NLP) to make the customer experience as personalized as possible. The algorithms use data from the following spheres:

  • Purchase history
  • Recent activity
  • Online behavior
  • Social media browsing

These algorithms are really powerful and can greatly boost e-commerce sales by:

  • improving conversions rates
  • increasing the average purchase value of customer
  • reducing bounce rates & cart abandonments

 

APPROPRIATE PRICING ANALYSIS

Right Discount provided at the right time increases conversions. Pricing is one of the most important things on a customer’s shopping list in the field of e-commerce. Companies must constantly battle with one another to offer the best relative costs with their pricing strategies. Data Analytics enables e-business owners to update the pricing of millions of products regularly, resulting in customer loss to competitors. eCommerce data analytics will also assist marketers in determining the best selling approach to use, whether promotional incentives are appropriate and whether the product is priced higher or lower than anticipated.

 

Demand Forecasting

Demand forecasting refers to the use of analytics techniques to predict the demand for a product and forecast sales. When you know the sales trends in advance, it gives you an advantage over your competitors in the following ways:

a) Better Inventory management

An underestimation of inventory levels can lead to inventory getting out of stock and hence cause customer dissatisfaction. An overestimation of inventory stock levels can lead to overstocking of inventory and hence cause unnecessary storage costs.

Demand forecasting helps in informed inventory planning and saves you from both selling out of popular products and warehouse space wastage due to slow-moving stock.

b) Better cashflow management

Since the money is not tied up in slow-moving inventory, It helps you plan the budget properly and use the cash optimally. Thus, it helps you to reduce financial risk.

c) Better pricing strategy

.You can charge more for the products having a high demand forecast, and vice versa. You can better plan the marketing budget, advertising investment, and discount plans.

d) Better customer service

Knowledge works wonders.The prior knowledge of the product demands and their fluctuations helps in planning better customer service.

FEASIBILITY OF DATA ANALYTICS

It is not mandatory to spend a lot of money to start a Big Data project. The required analytical resources and data could be obtained for affordable prices. Cloud platforms are now gaining unrivaled popularity over all other platforms. Cloud data management, on the other hand, can be used for eCommerce data analytics. With data expected to expand at an exponential rate, cloud computing could have a significant benefit in terms of versatility and growth.

 

 

Sources: TowardsDataScience, Unilever, Amazon


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Nishant Kumar
Technology Enthusiast

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