- Data collected from surveys, feedback forms, reports and social media can be analysed using big data analytics to understand the specific needs of the consumers
Red Roof Inn, a budget hotel chain in the U.S., could have never imagined that it would be able to clock in a 10 per cent increase in its business when it used big data analytics to attract its potential customers in the winters of 2014. The hotel chain realised that most of its customers in bad-weather-affected locations would be using mobile devices to search for hotels. Hence the brand created targeted campaigns for such customers, which resulted in a surge in its footfall.
“The key for any company that wants to successfully use big data is gaining the right information that delivers knowledge and gives businesses the power to gain a competitive edge. And this can only be done by identifying and selecting from different types of big data analytics,” says Naveen Joshi, director at Allerin Tech, in his LinkedIn post.
Big data analytics offers much more than just target marketing. If implemented wisely, it can help a business grow by leaps and bounds.
Revenues maximised using existing resources
Imagine knowing where the demand for your product or service is coming from and then using existing resources with optimal efficiency to ensure that you cater to that demand right on time. In fact, a few companies have started using big data analytics to do exactly that.
For instance, hospitality giant Starwood Hotels and Resorts managed to increase its revenues-per-room by nearly 5 per cent by using big data in 2015. They used this technology to predict the demand as well as recalibrate room fares in order to get a higher footfall. The company claims that its demand forecasting has improved by 20 per cent since 2015.
Starwood used predictive analytics to understand its customers from their transactional data (number of bookings made, cancellations and others) and combined it with external semi-structured data such as weather reports for each of its locations. Since then, the company has been using analytical software to optimise its efficiency.
Similarly, another hotel major Marriott uses big data to enhance yield management of its rooms, thus maximising revenues. The company uses predictive analytics to predict the demand and accordingly make pricing decisions.
Experts project that predictive analytics could really be a game changer if used wisely. Implementing big data analytics while using existing resources is a smart way to up your revenues without much hassle.
Reduced operational costs
Every business strives to be efficient when it comes to operational costs. And companies in the West have been adopting big data analytics for this purpose. They implement big data analytics in their internal processes to gather data about their operational costs and use this data to downsize unnecessary expenses.
For instance, since 2012, Intel has been using big data to launch its chips in the market faster. According to reports, the company uses predictive analytics to understand and analyse historical data gathered from pre-release chips in order to cut down the time spent on quality checks of its chips. Instead of running every chip through 19,000 tests, the company selects certain chips for those tests to ensure the quality of its chips. If reports are to be believed, the company saved $3 million in 2012.
Similarly, retail giant Tesco used big data analytics to find out the exact temperature required for storage in its refrigerators. The company found out that most of its stores in Ireland were running refrigerators at a much lower temperature than needed. Thus, by understanding the fault and taking corrective step, the company was able to successfully reduce its refrigeration cooling costs by 20 per cent. It is only a matter of time before big data analytics becomes imperative to run a business.
Enhanced customer engagement
Companies have to constantly innovate in order to expand their consumer base. And this can only happen when they have a clear understanding of their consumers’ needs.
Industries such as banking and tourism can also turn to big data analytics to deliver customised products to their customers.
The biggest challenge that continues to haunt companies when it comes to big data analytics is the quantum of investment required to implement the technology. And while it is true that this technology is pricier than traditional ways of data analysis, the benefits of implementing it far outweigh the cost. To summarise, big data analytics—be it descriptive, predictive or prescriptive—is inevitable for a business. The sooner India Inc understands it, the better!