Analysing ratings and recommendations by using big data helps determine the possibility of a customer repaying debt, buying a good or service, or the fate of a movie at the box office.
Ratings and recommendations exist across all industries to assess the quality of products and services. It could either assess how many people are visiting a blog or website, to how much potential does a customer have to repay a debt. As we are living in the digital era, customers understand the importance of ratings and recommendation as these metrics ensure that organizations are providing quality services and that their after-sales services are also up to the mark. As 84% of people rely on online reviews today, rather than traditional recommendations, businesses are vying to increase their online ratings and improve their image on digital platforms. Big data analytics is a technology that holds the ability to provide actionable insights from the information stored in a company’s database for a plethora of causes. Combining the power of ratings and big data helps enterprises and consumers get consistent high quality services thanks to instant analytics.
Ratings and recommendations are one of the few things that people refer to in the process of an online purchase. One of the reasons people rely on ratings and recommendation systems is because by reviewing the ratings, people get an insight of how well a product is performing and how it can prove to be a bad buy. Apart from proving to be beneficial for customers, ratings and recommendations also prove to be of aid for financial organizations offering loans. When organisations possess the availability of customer credit ratings and recommendations at their disposal, determining the possibility of a customer repaying a loan becomes an easy task.
The reason rating and recommendations industry required transformation is the failure of traditional rating systems to provide accurate and reliable information. Ease of access and use by unqualified individuals also lead to ratings that differ and consumers buying products that are faulty.
One of the primary reasons that explain the failure of traditional review and rating systems is the unavailability of reliable information and actionable insights. With the advent of sources from which data generates, organizations have disparate sources to collect information. All of this data gathered from various sources culminates into big data for organizations.
With information arriving from almost every source, obtaining actionable insights is becoming easy for both, the companies as well as the consumers. With the application of big data analytics, businesses can better know how well a customer can repay a loan based on information from the past.
Companies providing other services, apart from finance, can also leverage big data analytics to have better recommendations at their disposal about a customer. Big data analytics empower businesses with the availability of information, such as a customer’s buying habits and how well a service would suit their need. With such actionable insights available on customer behaviour, companies can create tailored products for individual customers to retain their loyalty. Chief Technology Officers (CTOs) and Chief Information Officers (CIOs) should focus on finding the right vendors that can provide them the right big data analytics software. In addition, they should also focus on training their employees to leverage the power of big data to increase sales for their organisation.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.