Unknown to you, predictive analytics is a part of your daily life in many ways – in the search suggestions on your Google search, in the product suggestions you see on our page when you shop on Amazon, and even in your Gmail account that automatically detects and filters spam messages.
Healthcare, insurance, and banking are some of the more important areas where predictive analytics is being used in a big way. However, it is B2B marketers, 89% of them, who have embraced predictive analytics as an essential part of their business roadmap. By 2020, predictive analytics is expected to attract 40% of an organization’s net new investment in BI and analytics.
So why should entrepreneurs and businesses in India care?
Netflix analyzes millions of viewer data to predict which movies or shows would be most popular with their audience as well as to provide program recommendations to their customers.
Facebook uses customer data to predict product preferences, which it applies to its advertising activities. It uses Facebook interactions and ‘likes’ posted by its members to predict preference patterns among customers.
Predictive analytics has immense scope for utilization in a country like India, which has an economically disparate cross-section of consumers, as also in sectors riddled with high unpredictability like the oil and gas industry. 80% of CIOs belonging to the oil and natural gas industry feel that increasing their big data and analytical capability can optimize their businesses. Predictive analytics has helped such companies by predicting maintenance requirements of high-value machines and facilitating proactive maintenance.
More and more companies are trying to apply predictive analytics to their business to get a deeper understanding of customer relationships, build better products, and secure higher revenue. There is a great demand in the Indian market for analytics-driven tools and solutions that offer deeper data visualization and accelerate business decisions.
Predictive analytics help businesses improve their customer service and their branding, and market their products more effectively, besides improving employee relationships. Employee data can be analyzed to identify high-performing employees as well as employees who show signs of discontentment. While the organization can ensure that the former are suitably rewarded, managers can take timely steps to engage employees who are at risk of attrition, thereby increasing the average retention rate in the company.
The challenges of predictive analytics
Predictive analytics comes with its challenges – the first one is in identifying the areas within your business that can gain the most from predictive analytics. An organization needs to be clear on the problems that it seeks to solve using analytics, and the business goals it aims to achieve at the end of the process. Implementing any technology without a clear goal and direction can be risky.
Often, there is a clear disconnect between the CIO and the management within an organization in harnessing technology for business advancement; which can be a problem in applying predictive analytics. In a study, 60% of CIOs believed that analytics enable corporate strategists to make fact-based decisions. However, only 35% of the management agreed with this. To implement data analytics within an organization, you need specialized tools and solutions that can put a strain on your budget. The management needs to have a unified approach towards the rationale and objectives behind investing in this technology.
When done right, predictive analytics can give you deep customer and market insight, drive high operational efficiency, and enable fast and accurate decision-making. In short, it can be the game changer you seek to turn the market in your favor.
