Beyond big data: the evolution of predictive analytics

Predictive analytics have been around for a while: but do recent developments mean it is now time for businesses to make the most of their financial potential?

In the era of big data, companies across the board are recognising the need for better intelligence and insight about their business; wanting to work out how to make the best decisions, drawing on the right information, at that right time.

This provides a golden opportunity to sharpen business performance by differentiating offerings to uncover new opportunities whilst minimising risk exposure.

Predictive analytics isn’t something completely new, but the technologies that enable organisations to make sense out of their data, rather than just sitting on it, is a rather recent phenomenon.

As a result, businesses are able to uncover and exploit patterns in their historical data, identifying both risks and opportunities ahead. Technology tools, like those provided by Kairos, make it possible to leverage customer data and begin making smarter digital and overall decisions. You are better able to tie together all efforts, turn available data into actionable insights and move to a level of maturity where you are consistently, and efficiently, delivering the right message to the right people at the right time.

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From predicting market trends to gaining insight into customer needs, predictive analytics can help businesses tap into their data to explore new opportunities and gain the upper hand over competitors.

Unsurprisingly, the US is ploughing the way and over the last couple of months, alone, companies such as Custora and 6Sense have raised over $25m in funding, which only confirms that we’ve only seen the beginning of this and Europe is most likely to follow suit.

In the world of consumerisation, those businesses who are able to monitor and predict customer behaviour and preferences closely, without crossing the line on privacy, are most likely to gain a significant advantage.

Cutting edge customer analysis

Over the past two years, big data has become the latest buzzword. Businesses are collecting information on their customers’ mobile habits, buying habits, browsing habits… The list really does go on. It allows businesses to use historical data, combined with customer insight, to predict future events. This could be anything from anticipating customer needs, forecasting wider market trends or managing risk, which in turn offer a competitive advantage, the ability to drive new opportunities and ultimately increase revenue.

With most companies having huge amounts of data stored away, tracking behaviour across various platforms isn’t rocket science. However, to actually find actionable customer insights within this vast amount of data has proven challenging. By engaging predictive analytics, insightful customer stories buried within the data are all of a sudden revealed, providing actionable information including individual-level analysis of who is active, who is cooling down and who is gone for good.

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All of a sudden, stored information becomes a corporate asset. By gaining access to this information enables agile planning, more accurate forecasting, better budgeting and trusted decision-making support – all to improve the overall business performance.

New beginnings

I’ve got no doubts of the immense value in the ability to predict upcoming trends and events and for companies that fail to appreciate that are likely to fall off the bandwagon.

As data analytics continue to evolve, we’re going to experience, and in fact already are, a move towards personalisation. As a result, customers will expect a higher level of customisation that can only be achieved by having a clear understanding of what that individual actually wants.

Some may call it a guessing game but I’d beg to differ. Data has allowed companies to become the modern day ‘wizards’, nothing is by chance anymore; firms that quickly implement predictive analytics will have a first mover advantage while the adoption laggards will wonder why so few of their sales reps manage to meet quota. 

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Praseeda Nair

Praseeda Nair

Praseeda was Editor for from 2016 to 2018.

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