Editor's Note: This post originally appeared on SMA's in-house blog and appears here with their permission. Click here for the original post.

There seems to be a lot of misperception about what price optimization really is, largely driven by publicized assumptions that it will only serve the best interests of the company and hurt the consumer. Basically, price optimization boils down to applying analytics to available information in order to develop more quantitative and targeted pricing policies and processes. Price optimization is currently used extensively in many industries. The benefits and rewards to both the companies and the customers are plenty, with the customer rewards being highly visible. Through the use of price optimization, retailers are able to present highly personalized and appealing offers to their customers based on past shopping and buying patterns coupled with predictions of customer wants and needs. They are able to keep their best customers informed of sales and special offers that are of real value to them. The travel industry uses price optimization to manage profitability and, equipped with insights that give them the ability to fine-tune the metrics, they are able to offer very attractive options to travelers. Capacity that would otherwise have gone unused attracts happy customers and often brings them back.

For the insurance industry, it is important to understand that price optimization does not replace risk-based pricing; rather it is the next level of sophistication for risk-based pricing. With price optimization, insurers are able to explore and investigate product options, and then find an optimal balance point among all options and constraints within complicated rating orders and large sets of data. This makes it possible to construct and present more appealing, more targeted product and service offerings. It means that personalized offerings can be shaped to meet personalized needs. The laws of large numbers can be optimized for the individual situation.