How Big Data Analytics can be Applied in Various Industries
While approximately 41% of companies worldwide use big data analytics to make smarter business decisions, 53% of these enterprises are in North America alone, according to research by BARC.
Like others, are you too interested in knowing more about the application and benefits of big data analytics, but are wondering how it can be used to grow your business?
Use of Big Data Analytics can help you gain:
- Better Data Visualization
- New Business Opportunity
- Marketing Optimization
- Deal Personalization
- Operational Intelligence
- Security & Risk Management
Application of Big Data Analytics in Industry
Conventional analytics tools enable companies to track conversions, demographic statistics, average time spent by users on each page, pages that have highest bounce rates, etc. Companies have also been using heat maps to make changes in page design as well as arrange call-to-actions. The user data captured can be used to recommend which travel solutions would be relevant for a particular passenger, or which hotel would be the most appropriate for a young couple who booked their flight for summer holidays. Sentiment analysis of reviews and recommendations on blogs and social networks can help gauge the polarity of those posts and contribute to understanding customer requirements. Big Data can also be used for real-time analysis of competitor’s prices to devise an effective pricing strategy.
The financial services industry has seen unprecedented changes in the last few years. It is more critical than ever to ensure the integrity of data provided to regulators and executive management. Improved data quality and analytics offer a chance to gain competitive benefit by changing the way decisions are made. With big data analytics, complex algorithms use a broad range of data collected from a variety of sources to support trading decisions. Live and historical data can be used to notify new opportunities as well as predict if a customer is likely to default. Thus, big data can play a significant role in the recovery of bad debt as well. Understanding customer circumstances better can improve recovery targeting and affect recovery rates while reducing cost.
Having data-driven insights can help energy companies make provisions more efficient. By analyzing historical data, power plants can forecast energy demands for any season or time of day. If data regarding electricity usage, outages, transformers, and generators are available, automated predictions, optimization of grid devices’ performance and visualizing energy usage trends can be done easily. Also, a software that uses big data analytics can predict when trees growing around a power grid may fall on power lines, thereby needing maintenance. Such predictions would mean power companies can save money by avoiding outages.
With the vast amount of customer data available to telecom companies, it has become easier to understand customer needs and behavior and offer services for which users are looking to obtain. With personalized deals, chances of conversions are higher. Big Data analytics can help segment the market more accurately, providing insight into services that customers might be looking for as well as providing a better understanding of frequency utilization, switching and capacity use.
In the agriculture sector, being able to forecast pesticide quantities, crop prices and the health of livestock can largely improve profitability. The sooner farmers get access to this information, the better it will be for them to develop a clearer picture of their expected costs and profits. To reduce waste, farmers can use predictive analytics to have an idea of exactly how much stock they will need to feed their livestock.