Any organization primarily measures its growth in terms of Sales. An increment in Sales can be attributed to more customers, revenue, and profits. Earlier the Sales data was tracked and analyzed manually but now analyzing Sales has become more complex due to huge amounts of varying and dynamic data. Organizations are looking for real-time Sales information and mechanisms to decrease their Sales analysis time.
Sales can help an organization identify the best & worst-performing assets and help them make better business decisions that will drive future sales even higher. A Power BI Sales Dashboard can enable an organization to visualize its real-time Sales data and boost productivity. In this article, you will learn about the Power BI Sales Dashboards, steps to create a Power BI Sales Dashboard, important metrics to include, and some sample templates to guide you with your Sales Dashboard.
Introduction to Microsoft Power BI
Power BI is a Cloud-based Business Intelligence tool used to analyze and visualize data in real-time. It converts data from multiple sources into interactive dashboards and reports, managing your business needs. Power BI is available across numerous formats namely, Power BI Desktop, an online Software as a Service (SaaS) called Power BI Service, and a range of mobile apps for Windows, iOS, and Android devices. It also has Power BI Report Server which allows you to publish Power BI reports to an on-premises report server, after creating them in Power BI Desktop.
These tools enable you to analyze your data and in turn, helps businesses and organizations to ask the right questions and get appropriate insights. Power BI takes data from different sources and turns it into custom visuals designed to not only help you understand the information derived from it but also get a clear idea of actions to be taken. Also, check our in-depth article on Self Service BI.
Key Features of Microsoft Power BI
- Easy Set-up and Implementation: You can set it up for free and build your visualization within minutes.
- Real-Time Visualization: Data is available for visualization in real-time. You are capable of capturing opportunities and solving problems.
- Customized Visualization: Power BI offers customized visualization by custom visual SDK.
- Multiple Data Sources: Power BI supports a range of data sources such as Excel, Oracle, SQL Server, etc.
Understanding Sales Dashboards
Sales Dashboards break down complex information into handy chunks of information, which can be used to obtain actionable insights regarding your business. Simply put, the role of a Sales Dashboard is to extract the most actionable information from your CRM (Customer Relationship Management) system and present it in a more palatable format.
The most challenging task of building a Sales Dashboard is understanding the specific goals you are trying to reach. One can start by identifying the key metrics to keep track of to ensure peak efficiency.
Image Source: https://www.klipfolio.com/resources/dashboard-examples/sales
While building a Sales Dashboard, here are a few things you should keep in mind:
- The target audience.
- The frequency of viewing the Sales Dashboard.
- The volume of data included.
- The type of chart(s) needed.
- Purpose of the Dashboard.
Understanding the Importance of Sales Dashboards
Sales teams function in a highly target-oriented environment. Sales Dashboards give you a comprehensive glance at your Sales teams’ performance and give you an idea about where you stand vis-a-vis your company’s revenue targets. They also help come up with effective strategies to reach those revenue targets within the set deadline. As a Sales leader, this allows you to:
- Track progress towards goals.
- Make decisions and plans based on your team’s performance.
- Adjust compensation accordingly and award bonuses & incentives.
- Identify key issues before they snowball into major problems for the enterprise.
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Steps to Set up Microsoft Power BI Sales Dashboards
Step 1: Setting up an account
If you are a new user you may start by clicking on the “Try Free” or “Start Free” button here.
Image Source: https://docs.microsoft.com/en-us/power-bi/fundamentals/service-self-service-signup-for-power-bi
Or you may Open a Link you received in an email or Power BI report.
Image Source: https://docs.microsoft.com/en-us/power-bi/fundamentals/service-self-service-signup-for-power-bi
Enter your Email Address and other Microsoft 365 credentials to login into Power BI.
Image Source: https://docs.microsoft.com/en-us/power-bi/fundamentals/service-self-service-signup-for-power-bi
Image Source: https://docs.microsoft.com/en-us/power-bi/fundamentals/service-self-service-signup-for-power-bi
Step 2: Importing Data
Power BI offers multiple ways to import data for the creation of Dashboards. Beginners can simply import data in the form of Excel or CSV files. Other ways to import data include multiple variants of Databases, well-known APIs like SharePoint, Dynamics, Salesforce etc.
For Real-time data transfers, you can use DirectQuery connections to Databases. DirectQuery enables your reports to be rendered in real-time from your database, as well as enabling row-level security filtering so that users only see the data they’re authorized for in your reports.
The figure below shows the relational data model displayed in the Power BI Desktop relationships view.
Image Source: https://docs.microsoft.com/en-us/power-bi/connect-data/service-get-data
Different types of data sources for importing data into Power BI are described below. You can check for the various sources of data by clicking on the “Get Data” button on the bottom left corner.
Image Source: https://docs.microsoft.com/en-us/power-bi/connect-data/service-get-data
After you select “Get Data” you may choose the data source you want to access.
Image Source: https://docs.microsoft.com/en-us/power-bi/connect-data/service-get-data
The “Discover Content” section hosts the data and reports already created for you.
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
The “Create New Content” section hosts the option to import new content for your project.
Types of Files:
There are multiple file formats supported by Power BI.
- Excel: .xlsx, .xlsm format is supported to import data into Power BI, that data loaded into worksheets using Power Query can also be used to load data from external sources.
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
- Power BI Desktop Files: .pbix file format can be used to extend the data model with measures and relationships or import your Power BI Desktop file into your Power BI site.
- Comma Separated Value: .csv files consist of simple text files with rows of data.
- Databases: There are databases where you can establish live connections, such as Azure SQL Database, Azure SQL Data Warehouse, Spark on Azure HDInsight.
Step 3: Importing a Dataset with a Report
Firstly, you are required to import Power BI datasets to create your new dashboard. When importing data into Power BI, it adds a dataset and a report to the workspace. The report automatically gets created from PowerView sheets.
You need to open the “Navigation Pane”, select “My Workspace” and then select “Get Data”.
Image Source: https://docs.microsoft.com/en-us/power-bi/connect-data/service-get-data
Under the File section select “Get”.
Image Source: https://docs.microsoft.com/en-us/power-bi/connect-data/service-get-data
Navigate to the location where the target file is saved, make the selection and choose “Connect” and subsequently select “Import”.
Image Source: https://docs.microsoft.com/en-us/power-bi/connect-data/service-get-data
Image Source: https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboard-create
Proceed to the selection of “Reports Tab”, then select the dataset to open the report.
Image Source: https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboard-create
You may select “More Options” and then “Edit Report” to open the report in the Editing view.
Image Source: https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboard-create
To add a visualization to your dashboard select the pin icon.
Image Source: https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboard-create
To create a new dashboard, select the option “New Dashboard” and give it a name.
Image Source: https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboard-create
Step 4: Selection of Tables for Reports
Image Source: https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboard-create
Transformations on the input tables can be performed in the Navigator View. Users can click “Edit” and will proceed to the query editor where transformations and filtering of data can take place.
Step 5: Defining Data Source Relationships
The user can select the Foreign Keys defined between the tables to establish the relationships in a data model.
Image Source: https://docs.microsoft.com/en-us/power-bi/create-reports/service-dashboard-create
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
After defining relationships users can switch back to the “Report View” using the top tab on the left.
Step 6: Adding Visual Elements
You can start dragging and dropping the visual elements that are relevant to your Sales Dashboard.
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
Step 7: Configuring Database Credentials
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
The user is required to enter the login credentials and click on the Sign In button. After the configuration of the database, the report should be ready for embedding.
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
Step 8: Creation of a Power BI Application [Optional]
Initially, the user is required to register an application with Power BI, then the user obtains the Application ID and application secret generated for the app.
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
Important Metrics to Include in a Power BI Sales Dashboard
Here are some important metrics that you would like to include in your Power BI Sales Dashboard:
1. Lead Conversion Ratio
This Key Performance Indicator (KPI) deals with asking the question: Is your Conversion Ratio stable? Lead Conversion Ratio is defined as the number of people that get converted into paying customers.
Image Source: https://www.pinterest.com/pin/576531189780765751/
Once a company has established a baseline, you will get an idea of how many leads to convert. Once you have gained a good enough understanding of conversion ratio and Average Sales Cycle length, you will know how many leads you will be needing to keep your team running at full throttle. Armed with this information, you also gain an idea of the number of reps you will be requiring at any given time. Accordingly, find benchmarks for your specific industry and use them as a target for your Sales pipeline.
2. Customer Acquisition Cost (CAC)
Customer Acquisition Cost (CAC) refers to all the costs incurred in signing up a customer. Depending on your line of business, different costs would be associated with CAC. For instance, if you are an Online Marketer, you will be including the costs of all your campaigns. In a traditional SaaS (Software as a Service) business this would include all your staff’s salaries, Marketing, and Sales costs.
The general recommendation is to recover your Customer Acquisition Cost (CAC) within a year of the customer’s subscription. Otherwise, you end up burning through all your capital, before you can bank on your Monthly Recurring Revenue (MRR).
Image Source: https://www.quora.com/How-to-calculate-CAC-for-outbound-sales
Therefore, the goal should be to increase Customer Lifetime Value (LTV) and Average Revenue per Unit (ARPU) while cutting Customer Acquisition Cost (CAC) to maintain profitability in your enterprise.
3. Customer Churn Rate
The Customer Churn Rate is defined as the number of customers who stopped using your company’s products or services in a given timeframe. Customer Churn Rate, therefore, gives you a realistic overview of your customer retention strategies and the kind of trends you should cope with.
Image Source: https://lumoa.me/blog/customer-churn-and-how-to-calculate-it
To calculate Customer Churn Rate, divide the total number of customers at the beginning of the month by the number of customers you ended up losing. The goal should be to keep this metric as low as possible. These calculations can be automated by using professional software that can trigger alarms as and when any Sales anomalies occur.
Image Source: https://www.datapine.com/kpi-examples-and-templates/sales
4. Customer Lifetime Value (LTV)
This metric asks the question: How much do you expect to earn from each customer? Customer Lifetime Value (LTV) allows you to track how long you have had paying customers. This is essential since the longer you have had paying customers the more revenue your enterprise will generate. Customer Lifetime Value (LTV) in mathematical terms is the total revenue you expect to get from a new customer throughout your relationship minus the Customer Acquisition Cost (CAC).
Image Source: https://chartio.com/blog/calculate-your-customer-lifetime-value-but-understand-its-limitations/
If you see your Customer Lifetime Value (LTV) increasing, it means you are getting more revenue from each customer for a longer duration which is a very good thing. This metric gives you an idea of how much Customer Acquisition Cost (CAC) can be allowed for the relationship to still be profitable.
Image Source: https://www.slidegeeks.com/business/product/customer-lifetime-value-process-curve-powerpoint-shapes
5. Number of Sales Opportunities
The number of Sales opportunities talks about your potential purchase volume. Sales management largely depends on current and new sales opportunities. The number of Sales opportunities should be pretty high to optimize and increase the value of your sales metrics. Valid qualified leads are critical for Sales, as is the potential purchase volume of these open opportunities. These require regular monitoring to have a real impact.
Image Source: https://www.datapine.com/blog/sales-graphs-and-charts-for-managers/
Templates for Power BI Sales Dashboards
Here you can check out some sample templates for your Sales Dashboards in Power BI.
1. Sales Scorecard Dashboard
Image Source: https://community.powerbi.com/t5/Data-Stories-Gallery/Sales-Scorecard-Where-are-we-losing-money-by-Decisive-Data/td-p/104653
This template helps businesses track their Sales and find insights in critical areas about Sales performance. The elements used in this Dashboard include treemaps, cards, shapes, and DAX [Data Analysis Expressions]. The granularity of the data depicted is by state, product, and region. There is also a provision to view comparisons of Sales and other metrics in comparison to previous years.
2. Invoice Trends Dashboard
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
This Power BI Sales Dashboard provides the user with the option to monitor the average amount per invoice count, average items per invoice, etc. This can help the user identify the patterns in the sales for that time period.
3. Pharma Sales Analysis Dashboard
Image Source: https://community.powerbi.com/t5/Data-Stories-Gallery/Pharma-Sales-Analysis/td-p/631028
This Power BI Sales Dashboard provides an overview of Sales of veterinary products. This dashboard can help analyze the Sales of the top 5 cities and bottom 5 cities. Users can also track therapeutic Sales trends across any given period.
Image Source: https://community.powerbi.com/t5/Data-Stories-Gallery/Pharma-Sales-Analysis/td-p/631028
4. Customer Sales Overview Dashboard
Image Source: https://www.dataself.com/dashboard-samples-for-sales-pbi/
This Power BI Sales Dashboard contains multiple ways to analyze customer trends. It lists all the customers and their Total Sales in the last two periods. Upon selection, the user can drill down to view detailed invoice information for that customer.
5. Inventory Stock Analysis Dashboard
Image Source
Inventory and stock management can be quite challenging for eCommerce organizations. The Inventory Stock Analysis Dashboard is useful for people of all levels of expertise. It can be broken down by category and year.
The above dashboard by InfoCepts depicts a stock inventory analysis for the year 2018. The 3 main categories are Customer Views and Inventory, Category Selection – Men’s and Women’s Clothing, and Quarters 1, 2, and 3. Customer Views are further classified into Most Viewed, Least Viewed, and Unviewed Products. Percentage-based categorization and Total Sales in USD are also available. Finally, each category’s top 5 items are highlighted. The dashboard also gives you more information about your stock inventory.
6. Global Superstore Dashboard
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The Global Superstore Dashboard gives you a birds-eye perspective of your store’s total sales performance. It can be used by strategic users to swiftly examine KPIs for various properties. The Dashboard displays sales data by nation, category, and sub-category, allowing you to take action. Its users can see both high-level and comprehensive information analysis on a single screen. InfoCepts’ Data Visualization talents and technical knowledge are on display in the Global Superstore Dashboard. Its primary characteristics include very effective use of visualization, the use of InfoCepts’ Data Visualization best practices, and the emphasis on critical information to allow users to make rapid judgments.
7. Social Media Monitoring Dashboard
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The Social Media Monitoring and Analytics dashboard is simple to use. It is divided into many tabs, which means that each tab only contains a little quantity of information that you must comprehend. The dashboard above demonstrates how effective Power BI can be when firms like Cheetos utilize it as their primary Social Media Monitoring & Analytic tool to increase sales, product quality, crisis management, and understanding the customer’s perception of the product.
Users can also see User’s Mentions in Sentiment Analysis by Day, Hour, and Total Mentions, as well as the percentages of good, negative, and neutral mentions. This Power BI dashboard example can be used by businesses to see positive and negative remarks depending on geolocation, such as regions and cities.
Conclusion
Keeping track of all your Sales metrics is essential for boosting Sales and identifying underlying problems. Every metric in your Power BI Sales Dashboard will help you understand more about your company’s progress and it also allows you to make quick and accurate business decisions. In this article, you learned about Power BI Sales Dashboards, their importance, the steps to create a Power BI Sales Dashboard, important metrics to include in a Sales Dashboard, and some sample templates to guide you with your own Power BI Sales Dashboards.
You can also set up your Sales Dashboards with Tableau and Excel.
Automated integration with your Data Warehouses/multiple Data sources and the Analytics Database can make your choice much simpler as a lot of necessary features can be integrated readily. Integrating and analyzing data from a huge set of diverse sources can be challenging, this is where Hevo comes into the picture.
Hevo Data, a No-code Data Pipeline helps you transfer data from a source of your choice in a fully automated and secure manner without having to write the code repeatedly. Hevo with its strong integration with 150+ sources & BI Tools, allows you to not only export & load Data but also transform & enrich your Data & make it analysis-ready in a jiffy.
FAQs
1. Can I automate data updates in Power BI dashboards?
Yes, you can set automatic refreshes on your data so that you will always have the latest sales insights.
2. What are slicers in a Power BI dashboard?
Slicers are interactive filters whereby users can segment and view some subsets of data on the dashboard.
3. What are the prerequisites for creating a sales dashboard in Power BI?
Sales data accessibility, a Power BI account, and an understanding of at least the metrics that you might need to track.
Abhishek is a data analysis enthusiast with a strong passion for data, software architecture, and crafting technical content. He has strong data analytical skills and practical experience in leveraging tools like WordPress, RankMath, and SEMRush to optimize content strategies while contributing significantly to Hevo Data.
