*icons created with Venngage*

## Line Chart

Line charts are the best way to visualize trend over time. In digital marketing a line chart is most used to show a website traffic trend and how it has changed over a certain time period.

The direction of the lines speak for the data: an upward trend means an increase in the values and a downward trend means the values have decreases over the time period shown.

On a line chart the vertical, y-axis shows the metric values, while the horizontal, x-axis shows the time sequence – days, weeks, months and years.

Typically a line chart is sorted by date ascending to show the progression from start to finish of the selected time period.

Line charts can also be graphed in the following two ways:

### Stacked line chart

To visualize how parts of a whole have change over a certain period of time

### 100% stacked line chart

To visualize the percentage contribution to a whole or the change to the percentage each value contributes over a certain period of time.

### Line charts best practices

- Use solid lines only for best visualization
- Don’t include more than four series (lines) in one chart to avoid distraction and confusions.

### Tools to create line charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Column Chart

Column charts are mostly used to visually compare values across a few categories. Data is visualized with vertical columns (bars) were the height of the columns represent the category value.

The vertical, y-axis represents the numerical values and the horizontal, x-axis shows the category.

In digital marketing a column chart use case would be to visualize traffic by each channel for a selected time period. For example how many sessions each marketing channel has brought to the site last month? The highest column would show the biggest traffic driving channel.

With column charts more than one value can be plotted for a category.

For example a column chart can compare traffic by marketing channel for the last and previous month.

Column charts can also be used to visualize trends where the horizontal axis would plot the time sequence and each bar would represent a week, a month, a quarter.

Column charts can also be graphed in the following ways:

### Stacked column chart

To compare parts of a whole for a category or visualize how parts of a whole change over time

### 100% stacked column chart

To compare the percentage each value contributes to a total or visualize how the percentage each value contributes has changes over a certain time period.

### Best practices for columns charts

- Use consistent colors throughout the chart
- Select different colors to highlight meaningful data points, changes over time or when comparing two values for the same category
- Use horizontal labels for the x-axis to be easier to read
- Always start the y-axis at 0 to properly visualize the values and the difference between values in the chart.

### Tools to create column charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Bar Chart

Bar charts are similar to column charts but they use horizontal bars to visualize the date. Bar charts are best to visually compare values across a few categories, when the chart shows duration or the category name is too long.

With a bar chart the vertical, y-axis shows the category value while the horizontal, x-axis shows the numerical values.

Unlike column charts, bar charts are not suitable to visualize trend over time.

Bar charts can also be plotted as:

### Stacked bar chart

To compare parts of a whole across categories or visualize how parts of a whole have change over a certain period of time

### 100% stacked bar chart

To compare the percentage each value contributes to a total or visualize how the percentage each value contributes has changes over a certain time period.

### Best practices for bar charts

- Use consistent colors throughout the chart
- Select different colors to highlight meaningful data points, changes over time or when comparing two values for the same category
- Use horizontal labels for the x-axis to be easier to read
- Always start the y-axis at 0 to properly visualize the values and the difference between values in the chart.

### Tools to create bar charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Pie Chart

Pie charts are used to show proportions and percentages of a whole. Pie charts are circles divided into proportional parts, each part representing the value of the chart series.

Pie chart best visualize data when the total of the proportions is 100% and the data consists of two or three categories, i.e. the pie chart contains only two or three ** http://greatexumaclassic.com/author/bdggolf/?_escaped_fragment_=/schedule slices**. If a pie chart is plotted with too many slices it becomes hard to read. In these cases it is better to use a column chart instead.

In digital marketing for example a pie chart can be used to plot Social media traffic distribution between traffic from paid social media advertising and traffic from organic social media sharing or to visually compare new vs returning visitors.

There are a couple of variations for a pie chart where data can be visualized even when it contains more than three values

### Pie of pie chart

This chart will take some values from the first pie and combine them into a second pie to make small percentages more readable.

### Bar of pie chart

This chart will take some values from the first pie and combine them into a stacked bar chart to make small percentages more readable or highlight the values in the stacked bar

### Pie charts best practices

- Use contrasting colors
- Do not plot more than three categories with a pie chart

### Tools to create pie charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Doughnut Chart

Doughnut charts are essentially a variation of a pie chart with the center cut out. They are best used when there are multiple series related to a larger sum. Pie charts as discussed above are hard to use when visualizing values for more than three categories. Doughnut charts are somewhat better for comparing more values since the audience has to compare length of arcs rather than pieces of a pie. It is still better to use a column chart instead if comparing multiple values.

### Tools to create doughnut charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Scatter Plot

Scatter plot is used to visualize the relationship between sets of values. Scatter plot charts use tiny dots to compare two values and show their relationship. Scatter plot charts use numerical values for both the vertical and horizontal axis. The point where the two values relate is marked with a dot.

They look a lot like line charts especially when there are lines connecting the dots but the way they represent data is very different.

Here is a scenario in digital marketing where a scatter plot chart can be used.

To visualize traffic and revenue trend for a certain website a line chart is the best chart to do so.

To visualize the relationship between sessions and revenue however a scatter plot chart can be used. It will show website traffic on the vertical axis and revenue on the horizontal axis to detect the correlation between these two values. Then we can see how increase or decrease in website traffic affects revenue.

### Tools to create scatter plot charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Bubble Chart

Bubble charts are similar to scatter plot charts. They can be used to compare two values and show their relationship for different categories on two numerical axis. The difference is with Bubble chart a third value can be visualized using the bubble size. Different colors can be used for the different categories or to represent an additional value.

I have a video on Excel bubble charts visualizing conversions by category on the website, where the horizontal and vertical axis represent sessions to the website category and sales for each category and the bubble size represents the revenue for each category.

### Tools to create bubble charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Area Chart

Area charts are similar to line charts and they are mainly used to show how values progress over time and to visualize trends for a certain time period.

Area charts use lines to connect the values and fill the area below the line with a certain color.

There are two variations of an area chart:

### Stacked area chart

Stacked area charts are used when you have multiple data series to visualize, each data point is represented by a different color area and each color area starts at the point left by the previous color area.

This chart can also be used to show the relationship of parts to a whole and their change over time.

### 100% Stacked area chart

Like the stacked area chart, the 100% stacked area char is used when you have multiple data series and each series is represented with a colored area. It shows the percentage contribution to a whole over time.

### Best practices for area charts

- To avoid confusion and clutter do not visualize more than four data series.
- Use colors and color combinations carefully for easy understanding of the data

### Tools to create area charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Combo Chart

Combo charts typically use columns and lines to visualize multiple data series. Combo charts can also be a combination of a column chart and an area chart. These charts are best to use when you have mixed types of data or the values in your data vary significantly.

For example you might want to see how all sessions to a website compare to session with conversions over a certain period of time. And also to visualize the rate between the two and how this rate changes over time. You can use a combo chart and visualize the sessions values with bars and use the line for the rate.

### Best practices for combo charts

- Use the y-axis on the left side for the primary variable
- Choose contrasting colors for the two data sets.

### Tools to create combo charts

- Excel
- Google Data Studio
- Google Analytics Dashboards
- Google Sheets
- Tableau

## Geo Map

Maps are best when used to visualize how data is distributed across a certain geographical region.

In digital marketing geographical map charts are most often used with color intensity or different color shades to represent data values for a geographical area divided by locations. For example a map of the United States divided by states, or a map of Europe divided by country. These charts are often a heatmap of the region where the color intensity will mean a larger or a smaller data value

Geographical map charts can also use dots to visualize data distribution across a certain region. With this map chart type we only see how data is distributed looking for patterns rather than rely on color to evaluate data values.

### Tools to create geo map charts

- Google Data Studio
- Google Analytics Dashboards
- Tableau

## Heatmap

Heatmaps are a great visual to show relationship between two categores. Heatmaps use color intensity or different color shapes and most often consist of square shapes (cells) with all the rows representing one category and all the column representing another category. Each vertical category has a corresponding horizontal category and their relationship is represented by a value in the corresponding cell. Typically a more intense color in the cell means larger value and more opaque color means a smaller data value.

Heatmaps in digital marketing can reveal patterns for conversion by time of day or sessions by day of week.

### Heatmaps best practices

- Use a single color in varying shades to show changes in data.

### Tools to create heatmaps

- Excel
- Google Sheets
- Tableau

## Treemap

I rarely see people use treemaps but I think they serve their purpose in digital marketing data.

Treemaps visualize data using a rectangular or square divided into smaller rectangular or square shapes each of which representing a category. For data values treemaps use size and color intensity or shade to visualize data. The rectangular size would represent one data value and the color shade another data value revealing patterns where these two values share commonalities.

Google Analytics visualizes acquisition using a treemap chart where the size of each rectangular shape shows sessions ( the bigger the size the bigger number of sessions) while color represent pageviews (green represents high number of pageviews, red represents low number of pageviews). Using this treemap we can then analyze performance by acquisition channel to look for high number of sessions and low number of pagviews or vice versa)

### Tools to create treemaps

- Excel (2016)
- Tableau
- Venngage

## Scorecard

Scorecards in data visualizations are used to highlight a certain metric. They are a simple text with a number that represents an important value.

Scorecards can be used at the beginning of a report to highlight number of sessions and users to a website for a certain time period. Or to show engagement metrics like bounce rate and time on site.

### Tools to create scorecards

- Excel
- Venngage
- Google Data Studio
- Google Analytics Dashboards