Does your team find it difficult to understand data? Have you had a hard time cracking the numbers? Despite doing all things right with web analytics, you might find yourself in a muddle when it comes to visualising data. Your efforts are redundant if you or your team do not find it easy to understand data. Make it your goal to organize data in a way that even a layman can comprehend what you are trying to explain here. The best way to do it is to know what your audience might like the most – infographs, tables, graphs, etc.
Your data should tell a story. We all have heard this at some point. Let’s get real. A story of numbers is already boring; now making it complex will kill your audience. The struggle that slows down reporting is deciding which chart to use. Because choosing the wrong one can leave your audience in confusion or might result into wrong data interpretation. So before we dive into charts for friendliest data illustration, we will see which charts should be used when.
1) For comparing values
When comparing single or multiple value sets the use of following graphs is perfect. They easily show the high and low values.
- Columns
- Bar Graph
- Line
- Scatter Plot
- Bullets
2) For showing composition
Following charts should be used to show individual chunks standing for the whole of something. For example total sales sliced by sales rep.
- Pie Chart
- Area
- Waterfall
- Stacked Bar and Stacked Column
3) For understanding the distribution of data
The following charts help understand the range of information in your values, normal tendency and outliers.
- Line
- Bar
- Column
4) For analyzing trends in your data set
When analysing how a particular data set performed over a given period of time, the following charts perform very well.
- Line
- Column
5) For understanding the relationship between value sets
To understand how one variable is related to multiple other variables, you could use these charts to show how a variable affects the others positively or negatively.
- Bubble
- Line
- Scatter Plot
You can also read: How to Create a Web Analytics Measurement Plan?
Types of Charts for Visualizing Data
1) Column
This chart is used to draw a comparison between things. It can also be used to show a comparison of things over a period of time. For example, you can see the revenue of each landing page or customers acquired per day. To make it easier to understand and look at, use soothing colors that is constant throughout. Make the text readable by placing them horizontally rather than diagonal or vertical.
2) Bar
When you have more than 10 things to compare, bar graph should be used. It will help avoid clutter when the labels are longer than usual. This visualization chart makes your data look clean while maintaining its readability. The bar and the column graphs are not preferred by most as it does not show where the data came from and where it is going. The information provided in these visualization charts is limited in nature.
3) Line
This chart fills the gap that a bar or column graph can’t. It shows trends over time in different sets. Use it when you want to show where the data was and where it is going. It is usually used when the data is in continuation. To get the best out of this chart plot not more than 4-5 lines. Keep it less cluttered and easy to understand.
4) Dual Axis
This visualization chart is used to show correlation between data sets or the lack of it. The graph has two y axis and a shared x axis. It is used with three data sets when one is continuous and the others grouped category wise. Use different graphs to show the distinction. For example, use a line graph to show continuation and a column graph to show the rest.
5) Area
An area chart is used to show how individual parts make a whole. For example, showing how sales rep contributes to total sales. It is basically a line graph which has spaces filled with some pattern. It is useful in analysing whole and individual information from the data set. Break down segments and see how they relate to one another individually and as a whole over a period of time.
6) Pie
This visualization chart is used to show how parts represent the whole. It shows static numbers in percentage. Each part is formed based on the percentage it represents and the sum of all is 100%. You show percentage representation of new v/s returning visitors, mobile v/s non-mobile, visits from each device, etc. When using this chart make sure there are not too many sections. Make those sections according to the size they represent and be sure all of them add up to 100%.
7) Scatter Plot
A scatter plot is most useful when looking for outliers or for understanding the distribution of data. If you want to draw attention to the similarities in the data sets that have multiple data points, this visualization chart must be used. It shows how different variable are related to each other.
8) Bubble
A bubble chart is a combination of scatter plots and area charts where the dots are replaced with bubbles and an additional dimension of data. The plotted bubbles represent the third variable by the area of the bubble. Use different colors to differentiate between the bubbles. Too many bubbles can make the chart hard to read. Keep your visualization chart clean and clutter-free by having just the amount required to pass the information.
9) Funnel
This chart is used to show steps and the orderly completion of each step. This can be used to highlight the sales process with the number of conversions that took place across a number of pages. Show each slice of the funnel chart as per the size assigned to it. Use contrasting colours to differentiate between the slices and to make them easy to understand.
10) Bullet
This visualization chart is used to show progress towards a goal. It compares this to another measure and provides rating. They are handy for measuring growth in the direction of a goal. You can use it to show a key performance indicator and its context. It can help you measure a current metric alongside contextual markers including historical results.
Conclusion
There are many other methods for visualizing data. As we all work with unique information and different data sets, choosing the right one depends entirely on what web analytics consultants want to showcase. Visualization charts are a powerful source to deliver information and insights when used in the right manner.
