SaaS Geographical Sales Analysis
Spatial data has given a huge opportunity to organizations in critically analysing software usage and expanding their customer base. This huge potential of geography based data can be harnessed to derive insights that could give the SaaS businesses an edge over its competitors.
How does Geographic Analysis help businesses?
Understanding where the customers reside, which regions are the most profitable, and how the product preference varies with the region can help in future planning. For instance, the marketing costs vary from state to state. As a result, the region that generates maximum revenue may not be the one that is the most profitable. This calls for a reassessment of the marketing budget to ensure it is utilized effectively.
Product preferences of customers may also vary with region.This information can also help while launching new products.
The average product price in some states may be higher than in others. This could be linked to the household income and the population of the region. The insights drawn from price comparisons can help the business in developing its pricing strategies.
This dashboard tries to analyze the performance of the business region-wise. It tries to understand how the sales, returns, customers, pricing and product preferences vary across regions. The dashboard has three tabs:
Summary Overview - This dashboard gives an overview of how the basic sales KPIs vary across regions.
Detailed Analysis – A detailed region-wise analysis is made in this dashboard, including the product purchase trend across these regions.
Refunds and Returns – This dashboard talks about how the return and refund trend varies across regions.
The dashboard helps the business in achieving the below goals:
Assess the efficiency of the current system
Understand Sales trend across regions
Plan region-based marketing and pricing strategies
Capture the product purchase trend across regions
Assess the customer satisfaction
Key Terms :
Average Price Paid or APP is the amount of money paid by each customer for a particular service/product
|Goals||Questions to ask||Dashboard views|
|Understand Sales trend across regions||How do sales vary across different states/regions?
Which city contributes to maximum revenue?
|Sales distributed geographically, Sales summary, Regional split, Top 10 cities by sale|
|Plan marketing and pricing strategies||How is the Average Order value changing across states?||Order summary|
|Capture the product purchase trend||Which are the top revenue-generating products in the east?||Top 10 products by sale|
|Assess the customer satisfaction
Assess the efficiency of the entire process
|Which states have returned maximum orders?
How is the refund percentage varying across states?
|Refund sales state-wise
Capturing the sales and product purchase trend across regions gives insights for designing the product and pricing strategies.
Average Price Paid drives key business decisions like product pricing, marketing expenses, etc. The increase or decrease in APP can be explained by the features/plans purchased, giving a complete picture for the decision-makers.
APP could also explain the effect of promotional strategies on sales. For instance, if APP increases during a particular time period, that can be attributed to discounts offered during a particular season or promotional campaigns conducted by the service provider.
Identifying the top 10 revenue-generating cities is important for further planning. The strategies that worked in these regions can be reused in other parts which have a similar sociocultural background.
When the refund/ return rate from a particular region is very high, it may indicate an issue in handling orders. The high refund rate can be due to poor customer support, deployment issues or any other operational failures.
The insights from the dashboard would help in planning region-wise product, pricing and marketing strategies. It could also help in assessing the customer satisfaction and efficiency of the existing process.
Senior Associate - Data & Technology @Palak Maheshwary
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We specialize in Power BI, Tableau, AWS Quicksight, Looker and Google Data Studio Implementation
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