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Business is known for having no shortages of processes and tasks to complete. In fact, there are so many, it's not easy keeping track of everything. If there's one thing every owner must do, it's getting a clear vision of the future. The future can have a multitude of outcomes that you need to be aware of and there's no better way to get a grasp on the future than by using predictive analytics. Predictive analytics is when you use data to foresee potential outcomes and future trends. Sounds simple, right? Unfortunately, getting the hang of predictive analytics isn't easy, but that's why you're here. We've done the research for you and have broken the information down into its simplest form. In this post, we'll be covering how predictive analytics works and the ones you should be using for your business.
You now know that predictive analytics uses data to predict future outcomes. However, that's just the bare basics of it. The processes involved with it are far more complex. The first aspect involves analyzing the data of your consumer's behaviors, spending habits and what they're most likely to buy. The next step is to automate the analytics through artificial intelligence (AI) and machine learning. You can do it manually, but it's incredibly time consuming.
Now that you know what's typically involved, let's get into a few examples of predictive analytics you should use. We'll start off with customer segmentation as this is when you divide your consumers into individualized groups based on their habits. This is meant to give you a better understanding of who your target audience is, so you can cater to their wants and needs more effectively. Below is a list of other benefits to be had with customer segmentation:
Customer segmentation comes in four different types: age demographic, behavioral, geographic, and psychographic. Age demographics is self-explanatory, behavioral refers to how customers behave when doing business, geographic means where the consumers are located, and psychographic goes over what influences a consumer to make a purchase.
Measuring your marketing effectiveness is when you thoroughly analyze your current strategy and see how its currently performing. Especially now that AI is shaping business marketing, there are many ways you can see how your strategies are doing. Your company's website is the central hub people visit to get a better understanding of what your business is all about. This is a vital component to your company's success. Your website needs to be clear, concise, and provides what your audience is looking for in a short amount of time. If your bounce rate is too high, you need to figure out why, especially if your website is used to place orders.
Is it because of too many pop-ups? Are your clients scouring your website to read a single page? Is your site not mobile-friendly? Does the design conflict with the overall usability? These are all problems you need to consider as you go over your website analytics. Another potential problem you can face when dealing with marketing effectiveness is your fleet's performance. If your fleet isn't performing properly, this can cause a huge rift between you and your consumers, especially if you use it to deliver products and services. A great way to gain insight into your fleets operations is to implement telematics.
Telematics is when you use telecommunication and informatics to gain better visibility into your fleet. It can also help you be more alert to problems, like an illuminated check engine light. A check engine light that's illuminated can mean a lot of things, but not knowing what it means can be very problematic. This light can turn on due to having bad spark plugs or a broken oxygen sensor. Another thing that can help you identify problems with your fleet are DTC codes, or diagnostic trouble codes. These are used to signify specific problems with the vehicle. DTC codes are displayed when a scan tool is connected to the onboard diagnostics module. Being more aware of what the issue is can help you take the necessary action to fix it.
We briefly mentioned price optimization in the list above, so you're probably surprised to know it's a form of predictive analytics. Price optimization is when you tailor prices based on the information collected from your competitors, the current condition of the market, and the demand from customers. The goal of optimizing prices is to make them optimal; more specifically, it's used to find a balance between affordability and turning a profit.
