Predictive Analytics Can Optimize Performance, Client Relationships

Businesses around the world are realizing the benefits associated with collecting large volumes of information and analyzing those resources to gain insight into how they can improve operations. In many cases, decision-makers are learning to identify trends, giving them the foresight needed to accurately anticipate how customers will act in the future.

Although a number of companies around the world are leveraging predictive analytics solutions, insurance agencies in particular are benefiting from doing so. This trend was highlighted in a recent Earnix and ISO survey of nearly 270 insurance professionals in North America, which found that more than 80 percent of respondents are currently using predictive modeling strategies in some way, shape, or form.

At the same time, the survey revealed that organizations are using predictive analytics for a variety of purposes, suggesting that the Big Data phenomenon is broad enough for virtually any company to embrace. This finding also means that using tools to forecast future behavior will become more common in the coming years, especially as decision-makers become more familiar with Big Data and all its working parts.

"The results show that the use of predictive analytics is, and will likely remain in the future, a clear priority for insurers seeking to better understand current and future risk and improve their decisions related to pricing/rating, underwriting, marketing, and claims," said Meryl Golden, general manager of North America Operations at Earnix.

As insurance agencies understand the benefits associated with adopting predictive technologies, they'll find it easier to participate in a wide variety of opportunities that promise to benefit current operations.

Why use predictive analytics?
In today's competitive business world, organizations need as many advantages as they can find to gain and keep an edge over rival firms. If decision-makers can't engage with customers, optimize business processes, and generate new forms of revenue, they will probably fall behind -- a circumstance that can be deadly in the current economy.

Earnix and ISO found that the main reason to use predictive analytics is to drive profitability, with 85 percent of respondents claiming this was the primary function behind the strategies. Another 55 percent of insurance agencies said they use predictive modeling to reduce risk, and 52 percent stated they leverage the strategies to generate new revenue streams. Finally, 39 percent of executives said they have also adopted the methodologies to optimize efficiency, giving them a better chance to reduce unnecessary costs and streamline operations.

In addition to driving new revenue and improving productivity, companies are also using predictive analytics to augment customer experiences. By assessing what prospective and existing clients want, companies can change processes and launch innovative products to keep consumers happy. A separate AgilOne study highlighted this trend, revealing that 75 percent of marketers are using predictive strategies to maximize the lifetime of relationships with customers.

"The age-old problems for marketers of revenue attribution and increasing lifetime value never go away. What is changing is the explosion of multi-channel data and an intense focus on customer relationships," said Omer Artun, CEO of AgilOne. "Finally, technology has caught up with the business issues. A new paradigm of using predictive analytics to increase customer intimacy is now possible."

In the coming years, remaining one step ahead of both rival firms and customers will be the best way for organizations to be successful. By gathering large volumes of information and converting insight into foresight, companies of all sizes will be able to optimize performance without compromising their ability to engage with and retain clients. Ultimately, doing so will give them an edge in today's highly competitive business environment.

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