The chief concern you’ll face as an insurance broker from your clients is about money. “How much is this going to cost me?” is usually one of the first questions you’ll hear. They want to know if their policy rate will increase over time or what factors affect it.
But the fact is, this information is just as important for you as it is for your clients. Not only do you need to have all the data on hand to provide quality customer service, but it is also essential for forecasting your own revenue.
In fact, 44% of brokers cite a lack of real-time data insights for both the broker and the client as a chief pain point.
The benefits of revenue forecasting for insurance brokers
Revenue forecasting is an estimation of the amount of money you expect to generate over a specific time period. If you want to know how much money you’re going to bring in over the next month, you need to begin forecasting.
But that’s not to say it’s all guesswork. In fact, it’s quite the opposite.
Revenue forecasting draws on your historical performance, the existing state of your business, and other data to give you as accurate a prediction as possible.
The main benefits of revenue forecasting in general are strategic, as they make it possible to scale your operations and at what speed. Beyond that, it aids in important decision-making, particularly with regard to staffing, and improves your ability to make accurate, quantitative analyses.
Factors involved in revenue forecasting
While there are various models and techniques you can follow to carry out your revenue forecasting, the same basic elements are always involved. By even just shoring up these areas, you can make a huge difference in your ability to forecast revenue.
Real-time data
The quicker the insights, the better you can use them. You need to know how your customers are behaving across any given time period. Having the ability to input assumptions such as rate changes or new exclusions, while also adding in real-time customer data, will help you to produce highly accurate forecasts.
Historic analysis
Keeping track of trends is just as important as instant information for insurance providers. When looking at your historical data, you should be keeping an eye out for anything that gives information on commission breakdowns & profit shares, claims overview and claims loss triangles. A good reporting system will be able to give you this information quickly and in a way that is easy to comprehend.
Expenditures
The next area that is absolutely essential for revenue forecasting is expenses. This can have a major impact on your predictions so being able to take associated risks into account is key. Of course, you can’t just work with real expenditures, so it’s a good idea to run assumption scenarios to see how this may affect your growth.
Risk
Above all, insurance is about risk and this can drastically influence how accurate your revenue reporting is. The amount of risk you take as a company will determine how much variance there is.
Methods for revenue forecasting
Now, when it comes to actually calculating your revenue forecast, there are a number of methods or models you can follow.
Straight line forecasting
Straight line forecasting assumes a linear growth rate over a certain period of time. For example, if you have grown your revenue by 5% over two years, you can reasonably expect it to grow by the same percentage over the next two years. This type of forecasting, while having its uses, introduces so many variables that it should be treated as a guideline rather than a very accurate measure of revenue predictability.
Moving average forecasting
This method is more for identifying underlying patterns by focusing on a specific metric over a period of time. It’s used more on a monthly basis rather than an annual one, frequently to evaluate revenues, profits, sales growth, etc. It’s particularly useful in industries like insurance where revenue can fluctuate over time, helping you identify recurring peaks and troughs.
Time series forecasting
The idea behind time series forecasting is to identify historical patterns that you think will repeat in the future. In this way, you’re able to forecast more accurately across a range of financial metrics. This approach is best suited for cases where you expect fairly steady performance, such a s using sales and revenue growth from previous months to estimate future growth.
Linear Regression
Finally we have linear regression, which shows the relationship between two or more data points on a graph. Using the relationship between X and Y variables, a trend line is charted that illustrates the relationship between the two.
Take sales and profits for an example, if sales increase, profits should increase, creating a linear regression that demonstrates how they are related. Now, if sales increases but profit decreases, you likely have an issue with expenses and have to identify areas to cut costs.
Choosing the right platform
Revenue forecasting for insurance brokers is a powerful tool, but it’s just one of the many applications of data. Having a CRM platform that allows you to keep everything stored in a centralized location and with strong reporting capabilities is essential for any insurance company.
At Pipeline.so, our best-in-class CRM platform allows you to easily store and analyze your data. Beyond that, it has extensive automation and workflow features that will help streamline internal processes and connect with clients.
If you’d like to learn more, please reach out to us today!
