/ The sales forecasting app: How BI apps are changing the game
The sales forecasting app: How BI apps are changing the game
Forecasting sales is one of the most important aspects of any business. It can mean the difference between success and failure, and from your sales team to your CEO this data is crucial in making decisions.
One way that businesses are starting to improve their forecasting is through the use of business intelligence (BI) tools. BI tools offer a wealth of data that can be used to enhance your forecasting abilities.
Business intelligence allows companies to utilize data mining, data analysis, and visualizations to help them understand their business in greater detail. This understanding can then be used to improve performance in areas such as sales forecasting.
So how can BI tools help you build and deploy a powerful sales forecasting app? Let’s look closer at how you can use BI tools to create and customize the perfect sales forecasting app for your business.
The essential elements of sales forecasting
So what is sales forecasting? In a world where data is driving business decisions, forecasting sales has become more important than ever. Sales forecasting is the process of estimating future sales based on past performance and current trends.
This data can be used to make informed decisions about things like inventory, budgeting, and staffing. It’s also a crucial element in developing your marketing strategy.
There are a few different elements that you need to consider when forecasting sales:
1. Historical sales data
This is the data that reflects your company’s sales performance in the past. This data can help you understand patterns and trends in your sales data.
2. Current market conditions
Keeping tabs on current market conditions is essential for forecasting future sales. Factors like economic indicators, competitor activity, and customer demand all need to be taken into account.
3. Sales pipeline
The sales pipeline is a visual representation of your potential sales. This data can help you predict future sales based on current deals in the works.
4. Forecast model
A forecast model is a mathematical formula that uses historical data and current market conditions to predict future sales. This is often used as a tool to validate or adjust your sales forecast.
5. Customer behavior
Understanding how your customers behave is essential for accurate forecasting. Things like customer lifetime value, purchasing trends, and loyalty rates can all help to improve your forecast accuracy.
6. Competitor activity
Keeping an eye on your competitor’s activity can help you adjust your sales forecast. If a competitor launches a new product, for example, it could impact your sales.
There are just a few of the many factors that you need to consider when forecasting sales. But with the right BI tools, you can easily track all of this data and more.
How to use BI tools to build a customized sales forecasting app
Business intelligence tools offer a wealth of features that can be used to build a customized sales forecasting app. With the right app, anyone on your team can have access to the data they need to make informed decisions about your business.
Before we get into how to build a sales forecasting app, let’s take a look at some of the features that BI tools offer:
Data science is the process of extracting valuable information from large data sets. BI tools can help you understand your data to find trends and patterns that can be used to improve your forecast accuracy.
With data science, you can uncover insights that you would never have seen before. This data can be used to improve your forecasting accuracy and make better business decisions.
Once you have mined your data, it’s time to analyze it. Data analysis is the process of examining data in order to draw conclusions about it. BI tools offer a variety of analytical tools that can be used to examine your data.
With data analysis, you can answer important questions about your business, such as:
What are my most profitable products?
What are the current trends in my industry?
What is the average customer lifetime value?
What is the trend in customer demand?
Once you have answers to these questions, you can use them to improve your business.
One of the best ways to understand your data is to see it in a visual format. BI tools offer a variety of different visualization options that can be used to examine your data.
With visualizations, you can see your data in a way that is easy to understand. This can help you draw conclusions about your data and make better business decisions.
Once you have analyzed your data, you need to be able to share your findings with others. BI tools offer a variety of reporting options that can be used to share your data with others.
With reporting, you can share your data with anyone in your organization. This can help to improve communication and make sure everyone is on the same page.
Now that we’ve taken a look at some of the features that BI tools offer, let’s take a look at how you can use them to build a customized sales forecasting app.
Building a BI-driven sales forecasting app
Your BI app is only as effective as the data that is flowing through it. So before you start building your app, make sure you have a solid data set to work with.
One of the best ways to start is with a data audit. Consider what data you need for your sales forecasting and collect it from all of your various sources. Ask different stakeholders what data they need and make sure you have a complete picture.
Once you have your data, it’s time to start building your app. Here are a few tips to help you get started:
The best way to choose a BI platform is to consider your specific needs. What features and functionality does your app need? How much data do you need to process? How many users will be using your app?
Answering these questions will help you narrow down your options and choose the right BI platform for your needs.
2. Define the purpose and goals of your sales forecasting app
In designing your app, it’s important to start with the end in mind. What is the purpose of your app? What goals do you want to achieve with it?
Defining the purpose and goals of your sales forecasting app will help you determine what features and functionality it needs. It will also help you prioritize your development efforts.
3. Build a prototype
Once you have chosen a BI platform, it’s time to start building your app. The best way to do this is to build a prototype.
A prototype is a small, working version of your app. It can be used to test different features and functionality. It’s also a great way to get feedback from users and make sure your app is on the right track.
4. Test and iterate
After you have built a prototype of your app, it’s time to start testing it. Testing your app will help you identify any problems or issues. It will also help you determine if your app meets the needs of your users.
If there are problems or issues, don’t worry. This is normal. Just take note of them and fix them in the next iteration of your app.
5. Make it yours
The best thing about BI apps is that they are highly customizable. You can tailor them to fit the specific needs of your business.
So don’t be afraid to make your app your own. Add your own branding, style, and personality. Make it an extension of your brand.
What visualizations should I include?
When it comes to visualizations, there are a variety of different options to choose from. So which ones should you include in your sales forecasting app?
Here are a few of the most common visualizations that you could use for a sales forecasting app:
1. Line chart to track sales over time
A line chart is a great way to track sales over time. It can help you see how your sales have changed over time and identify any trends. Analyzing historical trends can help you uncover drivers of atypical performance that can be resolved or leveraged in the future.
2. Bar chart to track sales by product
If you sell multiple products, a bar chart can be a helpful way to track your revenue mix across products. This can help you see which products are your top performers and focus on implementing best practices for those that are lagging behind.
3. Pie chart to track sales by region
If you have sales data for different regions, a pie chart can be a helpful way to track sales for each region. This can help you see which regions are performing well and which ones need coaching or training to get up to speed.
4. Scatter plot to track sales by customer
A scatter plot is a great way to track sales by customer. It can help you see which customers are buying the most products and identify any patterns. Additionally, this type of visual can help you better understand the demographics of your customer base so you can identify strategies to expand your reach.
5. Bubble chart to track sales by product and customer
A bubble chart is a great way to track sales across multiple dimensions. This chart type helps you quickly see how each product is selling, as well as which customers are buying the most products.
Make use of BI tools and applications to boost your forecasting
If you are ready to take your forecasting to the next level, consider using a BI tool or application. Soon, you’ll be able to make more accurate forecasts and improve your business’s bottom line using the best data-driven forecasting tools.
Check out some related resources:
Data Never Sleeps 10.0
There’s an App for that—Tips for Crafting Apps, Dashboards, and other Engaging Data Experiences
POV: Next-Generation Banking
Try Domo for yourself. Completely free.
Domo transforms the way these companies manage business.