Make your web analytics data easy to understand by visualization. Here are the ways to visualize your data with charts and graphs.

1. How to Visualize Web Analytics
Data and Choose a Graph

2. Web analytics data is worth nothing if it can't be used in
the correct way. In order for it to be used, it has to be
understood. So how do you make data easy to
understand? With visualization of course!
The best way to do it is to know what your audience
might like the most – infographics, tables, graphs, etc.
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.

3. 1) 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

4. 2) 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 &
Stacked Column

5. 3) Distribution of Data
The following charts help understand the range of information in
your values, normal tendency and outliers.
•Line
•Bar
•Column

6. 4) Analyzing Trends in Your Data Set
When analyzing how a particular data set performed over a given
period of time, the following charts perform very well.
•Line
•Column

7. 5) 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

8. Types of Charts for Visualizing Data

9. 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.

10. 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.

11. 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.

12. 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.

13. 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.

14. 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%.

15. 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.

16. 8) Bubble
A bubble chart is a combination of scatter plot and area chart 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.

17. 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 colors to
differentiate between the slices and to make them easy to understand.

18. 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.

19. 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 you want to showcase. Visualization charts are
a powerful source to deliver information and insights when used in the
right manner.
Thank You
Data Visualisation & Reporting is art and science combined.
Web analytics experts works together in pulling out data from your
campaigns to report how they have been performing.