What is sales intelligence?
In general, sales data analytics is the process of turning sales-related data into insights that can be used to improve sales success.
Defines 4 types of sales analytics:
The goal of descriptive sales analysis is to draw conclusions from past sales data that comes from a variety of sources. Its results help you answer questions like, “How much did the company make last quarter?” or “Which products or services sold the most last month?”
Diagnostic sales analysis goes one step further because its data can help you figure out why something happened the way it did. So, if you do a detailed diagnostic analysis, you may find that the drop in your quarterly sales was caused by recent changes to a Google algorithm that affected how your web pages ranked in search results and, as a result, how many people visited your site.
Predictive analytics uses past data to make predictions about the future. It can be done with high-tech tools like machine learning and artificial intelligence. For an example of this type of sales analytics, look at one of VaporVM’s projects, in which our experts used data science to help a dairy maker get a good sales forecast.
When you combine the results of all of the other types of sales analytics, you get prescriptive sales analytics. The goal of this type of analytics is to tell you what steps to take to get the results you want. For example, a sales rep can see the best way to close more deals with each customer group after analyzing how customers act in the past.
What are the pros of sales analytics?
More information about your sales process With sales analytics, you can find out things like, “What sales strategies are working best?” to make your sales department more efficient and productive. What parts of your sales process do people leave the most? Who on your sales team isn’t doing a good job, and why? Look at how a solution for advanced sales research helped one of VaporVM’s clients see how their sales process was going. This will show you how it works in real life.
Better service for customers You can do deep customer segmentation and give personalized customer service based on the results of sales data. By analyzing your sales, you can also find out which of your customers’ needs aren’t being met. You can then use this information to improve your customers’ experiences and use upselling and cross-selling to build customer trust. Opportunities for growth have been found.
Sales analytics helps you grow your market by looking at your possible customers and those who don’t buy from you. This helps you figure out why they don’t buy from you. With this kind of analytics data, you’ll be able to make changes to your goods or services and the way you sell them so that you can turn people who aren’t customers into paying customers.
Do the benefits of sales analytics seem out of reach?
The team at VaporVM is ready to help you set up effective sales data so you can get the gains you want and drive sales. PICK UP SALES ANALYTICS Sales analytics’ most important parts To get started with good sales analytics, you need a system that includes the following parts: Data integration layer – to collect data from internal (CRM, accounting software, website) and external (social media, public data like weather, disease data, and survey data) data sources for a complete study of sales data. Data management layer – to make sure that the data is of good quality and safe.
Data analysis layer is the combination of the different types of data analytics that are needed to meet the goals of a business. Analytics outcomes layer – to give analytics information to decision-makers in a suitable visual format (presentations, reports, and dashboards). Here are some examples of the sales data dashboards we make for our clients to help them answer any questions about sales. If you want to learn more about dashboards and see how they work, you can watch our BI video.
How to do well with sales analytics: Things to remember Follow a step-by-step plan. You don’t have to spend a lot of money right away to build your sales analytics system. You could start by putting simple analytics functions in the cloud to save money on hardware and speed up the deployment process. Once the business benefit of sales analytics is clear and you need to meet new analytics needs, you can improve your solution (by adding a strong DWH, predictive analytics, data science, etc.). Focus on getting the results of data to business users.
You need to make sure that your business users can get the results of sales data when they need them most. I think you should use self-service tools like Power BI or Tableau for this. Also, don’t forget to make the launch of your sales analytics solution clear through training and good end-user support. This will help make sure that the solution is widely used. Get the key to growing your sales! With a sales analytics system, your sales process and the results of it will change in a big way. But making such an answer takes a lot of hard work, including a well-thought-out plan for implementation, the right tools, and the right ways to analyze data. If you feel like you can’t handle all of these jobs, you can always hire a data analytics vendor to help you with your sales analytics project.