In 2019, companies worldwide had invested a whopping $180 billion in Big Data analytics and there’s no sign of stopping. Big data, which is a large amount of structured and unstructured data beyond the processing capability of conventional methods, continues to fuel the growth of leading companies.

 

Here are 5 examples of how big data is applied in the real world.

1. Personalising the Customer Experience

Today’s business is all about creating a personalized customer experience. Companies should anticipate the customer’s behavior and tailor the buying journey accordingly. The ability to process immense data such as purchase history, interests, and shopping behaviors has enabled companies like Amazon to apply big data to revolutionize and set the standard for real-time personalised customer experience thanks to machine learning algorithms that respond to the specific needs of customers in real-time. 

Amazon shoppers are subtly targeted with product recommendations, which they are more likely to buy, thus increasing the revenue per session. 

2. Predictive Content Delivery

The digital media industry is expected to be worth $255 billion in 2025. Content providers are trying their best to acquire and retain subscribers on their respective platforms. One of the key strategies is to stay one step ahead of the users when recommending content. 

Netflix is an excellent example of big data analytics done right. It analyzes the users viewing history to recommend related TV shows that keep them glued onto the screen. The data is also used to determine which new titles are to be introduced into its content library. 

The result? Netflix now has 192.95 million paying subscribers around the world.

3. Targeted Advertisements

Ever wonder why you see the same ads on financial education on several websites after visiting a blog on the same subject? 

That’s a classic example of big data in action. Advertisers like Google and Facebook are harvesting user information to deliver targeted ads. Data like browsing histories, locations, and hobbies are used to send ads that are likely to get your attention. 

Targeted advertising creates a win-win scenario for each party. You don’t feel annoyed by ads that align with your interests, and the vendors will have a better click-through-rate.

4. Dynamic Pricing

While the law of supply and demand holds true in any industry, setting the right price is a delicate process. Businesses strive to achieve a good balance between profitability and customer acquisition and retention. Big data analytics have proved to be helpful in this.

Marriot, which manages more than 7,000 properties worldwide, uses big data to determine its room rates. Factors like availability, seasonal holidays, and events held in the city are used in its algorithm to maximize profitability.

5. Supply Chain Management

Rotten goods, late delivery, and missing parcels are just some of the problems that plagued the supply chain industry, which connects manufacturers with end-users. Risk management and anticipative measures are crucial in minimizing supply chain issues.

FedEx has turned to big data analytics in its bids to help the pharmaceutical industry, which suffers an annual loss of $9 billion, where the drugs went bad while in transit. It installed sensors to gather logistic and storage data, which are then used for mitigative measures such as preventive maintenance and route planning.

Final thoughts

While industry giants make perfect examples for big data analytics, the application isn’t strictly limited to a few. Businesses of all sizes stand to benefit from harvesting and analyzing big data.

But first, you’ll need to store and secure the immense stream of real-time information, and that’s what Axual does best. 

 

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