Bar Charts Remake Bar charts are used extensively in marketing dashboards. They are my favourite way to visualize data since they are simple yet comprehensive and can be used for lots of types of data including trend over time and comparing categories.

watch Bar charts have to be used for their simplicity, yet most of the bar charts I see in reports and dashboards are cluttered with unnecessary colour and background distractions. Below are some examples: bar chart

go to link bar chart

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follow url I am not remaking these particular charts. I found some interesting travel data from the National Travel and Tourism Office and using this data I am creating a few bar charts the way I like to use them – with fewer colours and no background clutter.

Cheap Provigil Uk The example below is data from 1997. It shows the number of Americans that travelled to Europe, Mexico and Canada each month. Back then Europe was the most popular destination among Americans. I have highlighted the bars with red as a contrast colour and used grey for the other Mexico and Canada.

enter bar chart The next example is the same data for 2017, 20 years later. In 2017 the number of Americans travelling to Mexico has significantly increased from 20 years ago. Using the same color scheme, I highlighted Mexico numbers in red and used grey for Europe and Canada.

go bar chart 2017 The outcome from comparing the two bar charts above is the significant increase in Americans holidaying in Mexico over 20 years period. So below is an example of combining the data from the charts above into a horizontal bar chart. Since the outcome is related to Mexico I highlighted the data with red in both parts of the charts and used grey for Europe and Canada.

Buy Amoxicillin Online Europe bar charts 1997 vs 2017 Conclusion:

Buy Cytotec Online With Mastercard When using bar charts be careful how you use colour. Use colour wisely to draw the audience attention where needed, remove all background elements and use an outcome title.

The Waterfall Chart

source site I recently took part in a challenge organized by Storytelling with Data to create a waterfall chart.

Amoxicillin Uk Online I rarely see this type of chart in digital marketing dashboards, if ever! The challenge wasn’t limited to data related to digital marketing but I wanted to find a use case for a waterfall chart in a digital marketing environment.

enter The Waterfall Chart

What is a waterfall chart

source Waterfall charts are used to show how an initial value has increased or decreased by a number of values in between that lead to a final value. These intermediate values can either be time based or category based.

Can You Buy Amoxicillin Over The Counter In Usa My challenge was not only to create such a chart for a digital marketing report but to also find real data.

enter A couple of years ago I started working with a client on their blog and content strategy. Since we started publishing content that is relevant but also targeting high volume search terms, their visibility improved significantly.

A Waterfall Chart To Visualize Online Visibility Improvements This type of data is a great candidate for a waterfall chart that will show how the number of keywords ranking on the first page of Google has increased over a certain period of time. Such data can also be visualized with a bar chart or even a line chart. The use of a waterfall chart however will emphasize on the intermediate values or in this case the number of new keywords in high positions for the intermediate time period (each month in 2017). With the inclusion of a takeaway title this visual turned into a great data storytelling example.

follow link Here are a few other use cases for a waterfall chart to be used in digital marketing dashboards

  • Newsletter subscribers at the start and end of year with their intermediate positive or negative numbers
  • Number of external links at the start of a link building campaign and at its end
  • Number of acquired leads for the duration of a paid media campaign You can create a waterfall chart in Excel 2016 and other data visualization tools like Tableau. I used Excel 2013 and this tutorial.

Data Storytelling With Excel – Episode I


go to site This is the first of series I plan to do on how you can use Excel for pretty data visuals and data storytelling. In this video I build a very basic Excel dashboard using data storytelling principles including:

  • Focusing audience attention
  • Removing clutter
  • Include insights and takeaways right into the charts

watch In this dashboard I use a 100% stacked area chart to visualize all users to a website and users who made a purchase on the website. The line where these metrics intersect on the area chart is the trend and the rate Made a Purchase/All Users. This visualization aims to show what percentage of the users who visit the website make a purchase.
There are a number of ways to visualize this, but I chose a 100% stacked area chart so I can focus on the rate. In this video the blue color on the area chart is for visitors who made a purchase on the website and the orange color is for all users.
Using a text widget I will include a clarification of what the white line between these two chart components is. This insight will also focus the audience attention on the rate which is what I aim with this visual. The second chart in this dashboard is a simple line chart with annotations. It visualizes the trend for revenue made from website purchases. To be easier to understand the real numbers behind the trend I am including data labels and removing the vertical axis to reduce clutter.
Using a text widget I will insert a takeaway insight onto the chart as well as further takeaways on the right hand of the chart. This is a very basic Excel dashboard, there are a number of other ways to make data look pretty in Excel which I will be exploring in future series.

Line Chart Examples For Data Storytelling These line chart examples show how to use annotations to not only show a trend whether in traffic, conversions or user behavior on your website, but to tell the full story about performance with your data.

Provigil Ordering I use line charts a lot in my reports since they are one of the best way to report and visualize trends, whether it is a trend in traffic, conversions or user behavior on your website. When the trend is consistently showing an increase or decrease or staying stale it might be a little easier to tell a story with your data with a simple line chart and couple of comments. But when a trend is fluctuating as a result of marketing activity a chart line might look confusing and the data story difficult to understand.

go here Below is a line chart showing the trend for social media traffic for 2017 for a certain website:

enter Line Chart Data Storytelling

here Traffic from social media is heavily dependent on social media campaigns activity and trend has been fluctuating throughout the year.
In the line chart example I have simply visualized the numbers for traffic from Social media each month in 2017.

go to site Upon exploring I understand that these fluctuation are resulting from advertising activity as well as success of the specific campaign. In order to fully tell a story with the data and explain traffic increases and sharp drops an analyst might want to include annotation to explain each significant fluctuation in the trend.

Line Chart Examples With Annotations

source Here is a line chart example of how I improved the visualization and insert explanation of why we are seeing big increases and decreases.

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watch It might make more sense than the first example however after looking at it I thought that the background color was not a good idea. I also thought there are options to improve the annotations and make the main takeaways more visible at first glance.

How To Buy Priligy Online So I made a few changes:

Annotated Line Chart Examples Data Storytelling FINAL

I changed the background to white and did some styling to the annotations text. I also decided to remove the data points and the data labels. All this is to try and draw the attention to the traffic fluctuations and the main reasons for these fluctuations which is what I am trying tell with this data.