Predictive Analytics Solutions

What is Predictive Analytics?

A branch of advanced analytics, it is used to make predictions about unknown events in the future. It extracts information from existing sources of data to determine patterns and predict future trends and results. It uses different techniques to make such predictions, like artificial intelligence, statistical modelling, machine learning, etc. A reliable method of forecasting, it also focuses on risk management and takes what-if scenarios into account. Moreover, it helps organisations adapt to the needs of the industry and innovate on the go.

When applied to business, predictive models can analyze historical and current data to understand products, customers and partners, and identify potential opportunities and risks. Thus, it can be used to analyse buying patterns and provide meaningful insights to organisations to help them add more value to their offerings and ensure that customers enjoy a better buying experience.

predictive analytics tools

Why Predictive Analytics?

Predictive analytics offers decisions makers the insights required to foresee developments, respond to challenges proactively, and capitalize on future trends. It aids industry experts uncover relationships between unstructured and structured data, draw relevant inferences and plan accordingly. It also helps businesses harness big data to their advantage, which in turn helps them in pricing products, indentifying trends, maintaining inventory, etc.

Predictive analytics solutions can help organisations reduce risk, improve efficiency and increase profits through data analysis and systematic reasoning. Businesses can use data to understand customer preferences and respond accordingly. Leveraging big data to collect information from social streams could help companies get a holistic report based on behavioural data, which in turn can help them initiate marketing campaigns targeting certain segments of the market, depending on their interests.

What is scope of Predictive Analytics?

Predictive analytics can help companies analyze the entire customer lifecycle and increase sales by devising better marketing strategies and ensuring better customer service. Organisations can use in-house data on customer preferences to improve their offerings and study the data collected by partners to know what more the customers shop for outside their stores. Not only is it the key to understanding behaviours and attitudes, but it can also be used to identify critical factors like the type of customer base the company is catering to, i.e. price-drive or brand-driven, and stock products accordingly. Also, in the service industry, predictive analytics can help organisations pre-empt if customers (categorised on the basis of certain attributes) would prefer a specific kind of service or deal in certain situations.

Functional Analytics: Predictive analytics can be applied to various functions too. Since employees generate a lot of information, HR can tap that data to glean useful information. Marketers can use analytics to uncover deficiencies/deviations/issues in specific channels in the marketing mix, while companies offering risk management services can use it for probabilistic risk assessment in order to make accurate forecasts. Moreover, executives can study various factors affecting business operations and analyse them for patterns/trends, impact on business performance or costs. This can help them restructure the business model, if need be, in order to be better equipped to fight operational challenges.

Industry Analytics: Predictive analytics also has varied applications in other sectors like banking, retail, healthcare, insurance, telecommunications, pharmaceuticals, etc. Through proper charting of reports, it can be used to identify patients who are at a risk of developing certain health conditions like diabetes, etc. For companies providing financial services, it can help find inaccurate credit applications and fraudulent transactions done offline or online and identify thefts and false claims. Apart from this, it can optimize resource allocation by effective identification of contact strategies, collection agencies and legal actions to increase recovery and reduce costs. Manufacturing firms can use it to keep a tab on changing consumer sentiments, which can help them improve the quality of their offerings. In the retail sector too, organisations can analyse the information collected from various online and offline data streams for understanding trends and customer behaviour and preferences.

Predictive Analytics Portfolio





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