Why Data Analytics Are Like Interest

As the insurtech industry continues to boom, the importance of data cannot be overstated. Data analytics is essential for success as the traditional model of insurance evolves and modernizes. Data analytics allow you to test, measure and implement changes to your digital processes—on your website, email or mobile platform. These adjustments and modifications are also important in a way that people often don't recognize, because they are the insurance industry equivalent of “compounding interest.” Remember, compounding interest is essentially interest on top of interest. As the months and years go on, the total sum will increase as the interest continues to accumulate and compound. While the original amount may not be significant, the value grows impressively over time. See also: Why Exactly Does Big Data Matter?   All of the small changes you make to improve your digital processes and platforms operate in a similar manner. The modifications build on each other, leading to greater success and profits. Of course, all of these changes require careful analysis, hard work and innovative thinking but don’t underestimate their resulting value. Keep the big picture in mind and remember the worth that will accumulate. Compounding Interest in Motion If someone has an idea for new copy on an advertisement, and it tests well, you may decide to implement the change widely. Perhaps the stronger copy better resonates with consumers and results in a 1% higher arrival rate. If you currently have 10,000 arrivals each day, and each arrival is worth $100 to you, then over the course of a year you will see an additional $3.7 million. That could be invested in new employees who are able to identify further improvement opportunities. Imagine if you could then make more changes and achieve an additional 1% to 2% higher arrival rate. The possibilities and resulting returns are endless. These small changes can truly compound over time and make a real impact on your growth. Individuals Are Not Representative When determining changes to test and implement, remember that individuals are not representative. Despite an individual’s broad experience, expertise and skill set, he or she does not accurately represent a total set of people. Your mind will be blown by how an individual’s assumptions may be wrong when extended to an entire set of people. While an idea or process may seem undoubtedly logical or appear to be common sense, don’t assume a way of thinking is fact. For example, one person may truly believe that a color is ideal for a website when in fact, once it is tested, only 10% of the population agrees. Another color may be a better match, one that 80% of consumers agree to. To overcome this tendency to rely on your assumptions, implement a data-driven culture that eliminates arguments and assumptions. You can remain welcome to any and all ideas as inputs and then let the data decide. You may be surprised by the ideas that return successful results. An Infinite Amount of Possibilities As technology advances and devices evolve, there will be a near infinite amount of opportunities for optimization. Invest in data-backed initiatives, and don’t hinder your success because you think small changes are too insignificant to be valuable. A better site or form layout could improve your click-through rate, which could lead to a more positive consumer experience. This could then lead to more return visits from consumers, who also tell their friends about you, which could lead to a bigger pool of satisfied customers and an overall stronger digital experience. You never know where small changes will lead or what their return will be. See also: 4 Benefits From Data Centralization These small changes are the compounding interest equivalent in this digital age of insurance. Receive input from multiple sources, remain open to ideas and continuously test modifications to improve on current processes. Thanks to technology’s continuous advancement, there will always be more that you can do. If you’re looking for more advice on how to determine ideas and test changes, take a look at the previous articles: Give Consumers the Experience They Want and 3 Types of Data You Need for Personalization.