How To Use Big Data Analytics | Increase Sales

The business environment has changed a great deal in the recent past to a highly competitive one due to many players’ and customers’ high expectations. As a result, companies have had to change tactics, especially in marketing, to remain profitable. Big data analytics services has become one of the most significant assets for businesses, especially in marketing.

It has drastically changed the way companies market their goods and services to the customers, which has improved their profits.

It is estimated that big data has seen some companies cut costs by 10% and increase profits by 8%. Data analysis enables businesses to uncover hidden trends and correlations and provide insights that facilitate proper decision-making.

Here are some ways that businesses can use big data to boost sales and improve their profitability:

Customer Demand Prediction

Using big data for sales to predict what the customer may want to buy

You may have looked at the purchase recommendations by some giant online vendors like Amazon and told yourself that whatever they are suggesting is something that you would buy and find useful.

This happens to many people frequently, and some purchase the items recommended. So, how do the vendors guess what you would need and be interested in buying? These vendors use big data to try to predict the items you would like in the future.

Online sellers use data from various sources to figure these things out. For example, they use data from the point of sale to find out what the customers buy, the feedback channel to know how the buyers rate their products, and other platforms like the loyalty programs to find the things that customers with similar buying habits are purchasing. Using the data on buyers with similar buying habits as you, the vendors can correctly predict what you may want to buy in the future.

That way, companies use big data for sales to upsell some items, like an electronic shop that realizes those who buy TVs will want to purchase TV mounts, thus endeavor to sell them together.

Influence New Product Development 

Using big data to influence innovations and new product development

Gone are the days when manufacturers would do mass production and put the items on the market, and customers would buy them. Nowadays, manufacturing businesses are using big data for innovation and redeveloping their existing products. Companies gather as much data as they can before designing new product lines and improving the existing ones.

Using various channels, the businesses study customer behavior and collects information on what the customer needs. And from that point, the businesses capitalize on the customers’ needs information derived from big data analytics to develop products or modify the existing ones.

More Targeted Advertising 

Using big data for sales to improve advertising and generate marketing insights

Businesses have to align their adverts with the audience, whether it is choosing the right media to reach them or the ads’ best timing. Using big data for sales also facilitates personalized selling where the companies know the best approach to use to reach each of the high-value clients.

For example, using a customer’s purchase data, companies can tell what they buy and contact them with attractive offers for such merchandise and even other related products.

Additionally, big data analysis has been used for online advertising to influence buyers’ behavior. For example, through analytics, it is possible to tell what action visitors to websites will take and thus intercept them before they exist a site by having pop-ups and impressive images. These make them stay longer on the websites and possibly submit their email addresses or phone number to get some freebies.


Besides the above-discussed ways of using big data for sales, businesses can utilize it to improve their operations. For instance, supermarkets and other stores can look at when they have high customer traffic to open more tills or have more service staff.

Big data can help companies in many ways, but only if they can collect the data, store it, analyze it, and implement the findings or use the insights gained.

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