In e-commerce, the analysis of customer data is an important part of optimizing sales figures. In addition to age, gender and interests, the geographical location of the target groups can also be an important criterion, for example. To track which country has the most sales or which region has frequent non-payments, a visually appealing map display in Tableau is the best tool.
Why use a map to visualize data?
Advantages of a graphical representation
We know many good reasons to display data on a map. At first glance, you can identify hotspots or see that there are hardly any data points in a region. All these are good reasons for creating a map visualization. However, remember that maps, like any other type of visualization, serve a purpose: They answer spatial questions.
But what is a spatial question anyway? Here are some examples:
- From which state do you receive the most orders?
- In which regions is the non-payment rate particularly high?
- Where are cancellations particularly frequent?
- In which city do you make the highest turnover?
- From which warehouse are your products delivered to which region?
Now we know what we want to say with the help of the tableau map. But what are the types of implementation? We briefly explain our two favorites here:
Choropleth cards, also known as filled cards in Tableau, are an excellent way to display ratio data. For example, if you want to display the cancellation rate in Germany per federal state, you can create a choropleth map for this purpose to identify spatial trends.
The card is not always the tool of choice
When is a table or list more useful?
Tableau maps can be used to analyze regional data in a visually appealing way. However, the Map visualization type in Tableau is not always the best way to get meaningful information.
When asked from which federal state most orders come, the map provides a visually appealing evaluation and also gives an initial impression of the regions in which orders are placed often and frequently. But you can’t tell here which state is the one with the most orders. The visual difference between the individual countries is too small for that.
Instead, these values could alternatively or additionally be displayed in a bar chart. Now you can see exactly which state most of the orders come from.
This example shows that maps can be used to collect data quickly. However, there are some cases where a different type of visualization provides a better answer to a spatial question.
Our customers benefit from our experience in evaluating data of any complexity. So we can always get the best answers in our reporting.
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