Top 3 Big Data Use Cases in Retail Industry

Something a lot of people don’t know, and the ones who do know still have difficulty believing, is the fact Data has become the most valuable resource on earth, overtaking oil.

The dawn of the digital age has given rise to Big Data. Every day, billions of people on the internet create 2500 trillion bytes of data, with over 682 million tweets and social media posts.

People love to share their likes, dislikes, experiences, preferences and moreover the internet so there is a good chance that a company can figure out everything they want to know about an individual and whether he or she is a prospective customer or not just by looking at their social media profiles. Read more about the interesting projects in big data

While analyzing the data of one person might seem easy, there are so many factors that making wrong predictions about a person’s purchasing behavior is also quite possible. This probability of making the wrong predictions grows exponentially large. This is where big data analytics comes into the picture.

To oversimplify, big data analytics is basically making understandable music out of the loud screaming sound that is made by people of the internet.

Big data analytics helps companies find patterns and trends in the behaviors of a particular section of people and thus make better predictions and projections based on this data.

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Big Data Analytics has a bright future in India & has a lot of amazing use cases, so let’s have a look at some of these use cases in retail. 


big data courses use cases

Directly targeting prospective customers is what made selling things on the internet all the rage. Using big data analytics, targeting can be taken to the next level. By analyzing the data of users like their purchase history, frequency of ordering and consumer satisfaction, recommendation engines have been developed.

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People who like to buy science fiction books are far more also likely to buy science fiction movies so these recommendation engines will automatically start to make the appropriate suggestions whenever the user visits the site.

However, as the user does more shopping and shares about it on the internet, the recommendation engines get even more data and grow increasingly smarter and start to make even more complex associations between items on sale to make even better recommendations and thus pushing the conversion rate even higher.

Finding the best price

Find the best amount of money to sell an item for a painstakingly difficult task. The amount of the item should be low enough that the targeted customer segment of the company can buy it but also high enough that the company can generate maximum profit from it.

Big Data Analytics go a long way in making this decision easier by informing the company about the behavior of their customer segment when it pricing of an item that they want to buy and at which amounts, maximum conversions have witnessed.

The companies then set the prices taking this information into account to set the best possible price and again uses big data analytics to monitor the behavior of customers whenever the prices are changed.

Customer Sentiment or Emotion Analysis

One of the biggest advantages of people sharing their raw thoughts and emotions of the internet for companies is that they can find out exactly how their customers feel or what has been the emotional or sentimental response to any of their products, services have been.

This gives valuable insights about any changes that they need to make ensure maximum customer satisfaction.

These are just a few use cases that big data analytics has for the world of retail. Statistically speaking, using big data analytics, a company can cut its marketing cost by almost 49.2 %. 

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Consequently, the number of companies adopting big data as a tool to improve business is also increasing. With a thing as capricious as data, and with quite a number of bright brains working to improve all the data-related technologies even more, one can’t predict what the future has in store. But we’re sure it’ll be good.

If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore.

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What is Big Data?

Big Data is a term that refers to massive and complex data collections that are too large to manage with traditional computing solutions. Unstructured and structured data collections, such as movies, photographs, music, websites, and multimedia material, make up Big Data. Businesses can gather data in a variety of ways. Integration, management, and analysis are three activities that Big Data entails. Integration entails combining data from various sources and molding it into a form that can be analyzed to provide insights. Management entails storing Big data in a repository where it can be collected and accessed easily. Analysis entails reviewing massive data sets with AI and machine learning-driven techniques.

What is Big Data Analytics?

Evaluating enormous amounts of data is referred to as Big Data Analytics. Big Data refers to a significant volume of data obtained from a range of sources, such as social networks, movies, digital photographs, sensors, and sales transaction records. The goal of analyzing all of this data is to find patterns and relationships that would otherwise go unnoticed and might provide useful information about the people who produced it. Businesses might well be able to acquire an advantage over their competitors and make better business decisions as a result of this knowledge.

Why are businesses opting for Big Data technology?

With so much data available, Big Data technology can help businesses ramp up their decision-making process while still being confident in their judgment. It denotes the ability of corporations to manage assets on a personal level. This means they can properly optimize assets based on the data source, increase productivity, prolong the lifespan of help, and minimize downtime for specific assets. This provides a competitive edge by ensuring that the firm gets the most out of its assets while also lowering expenses. This technology may also assist firms in reducing their costs. Companies can utilize consumer preferences to create and modify consumer interaction, resulting in greater sales. Analytics may also aid businesses in finding new income streams and expanding their operations.

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