Google Sheets Data Visualization – Essential Guide to Visualize Time Scale Data

Whether you are an entrepreneur, a CEO, or an employee, you need to utilize data to excel in your career.Every day, most times subconsciously, data is shaping your perception, influencing your behavior, and directing your actions. So why not take advantage of it?

Data, however, is of little to no use if it makes no sense to the audience. Numbers and percentages make sense when represented by data visualization. If you have seen data in a spreadsheet and wondered what all the numbers meant, then you know how effective visualization is. Why spend hours in a boardroom going through a thirty-page report when all that information can be translated into a thirty-minute visual presentation?

Time series data has been adopted by many industries globally. It has been of value to finance, research, web services, social media and pharmaceuticals, and more.

Time series data provides you with insights after analyzing important real-time and historical metrics. What is better than using some good visualization tools to make that analysis?

This article will give you a guide to time scale data visualization and show you easy-to-use tools you can adopt.

Try to Find What Data Wants to Say

With data becoming a key factor in organizational decision-making, visualization is playing a big role in making sense of the large volume of data that is produced every day. It takes a lot of time to find a trend in rows and columns of a grid other than using a chart.

Data visualization presents data in a form that is easier to understand while highlighting trends, anomalies and outliers. It is like you telling an interesting story in a noise-controlled room. You will capture your audience instantly.

Have you ever made a presentation and the audience was nodding, clapping, and engaging with you? What a great feeling?

When creating an effective data visualization, balance between form and function. You can create a plain chart that is boring and does not capture the attention of the audience. A stunning visualization might fail to deliver the right message. The point is that data and visuals must work together to convey a message effectively.

Visualizing time scale data translates to what we see and how our brain processes information.

Time scale data is especially important to industries where you need to track your progress. It could be something as simple as tracking the sales performance of a product over a certain time.

The ability to spot a certain trend and track change over time and generate forecasts is essential. It helps in knowing what is being done right, what to change and what to avoid in the future.

Why Time Scale Visualization is Important for Any Industry

Can you think of a professional field that does not gain by creating easy-to-understand time scale data visualizations? Every STEM field greatly benefits from gaining insights from scale data and so do other fields in government, finance, marketing, history, consumer goods, service industries, education, sports, and so on.

It is mainly up to the data analysts to draw actionable insights for better business outcomes. These kinds of people practically understand numbers and percentages as you do in your line of work.

An excellent time scale visualization portrays the message without the unnecessary tiring information and without obstructing the main point.

The greatest challenge you will face is separating tiring information from the important data. As much as the goal is to make data interesting and easy to understand, you still need to focus on the important aspects of the data to avoid miscommunication. They say prevention is better than cure. This is one such instance. The data and the art need to be accurate and in sync.

Principles of Successful Time Scale Visualization

When creating any graphic, the first thing you should do is check that the data is correct and consistent. Errors can greatly impact your company or client if an incorrect decision is made from your insights.

In life, we believe the right message should be delivered to the right person so, do not make that mistake with time scale data. Here are three popular principles that apply to data visualization.

Analyze your goal and choose the graphic that suits it – Different graph charts are made for different purposes. If you want to track the sales performance of a product throughout the year, you can use a line chart. However, if you want to analyze the performance of a PPC campaign in terms of impressions and clicks on a daily and weekly basis, use a day-parting chart.

Confirm that the message in your data visualization suits your audience – Use the appropriate design depending on your audience.

1. Choose the right graphic depending on your goal.​
2. Confirm that the message of your graphic suits the audience. If your message is timely but the graphic isn’t dynamic, or there’s an incorrect insight or a difficult design, then you won’t get the result you hoped for.
3. Use an appropriate design for the graphic. This is also linked to the type of audience you are making your graphics for. You cannot present the same data visualization you would for CEOs and business executives to students or interns.

Tools for Creating Interesting Time Scale Visualizations

Visualization tools have their unique time scale interface. Most of these tools have limited analytics options, the numbers are soloed and in the end, they do not bring the desired results. So how do you use these tools without making errors? With deadlines to meet, you do not have time to figure out how to make them work.

Tools like Google Sheets data visualization helps you load your set of data, choose a chart type and insert the data.  An amazing alternative tool is ChartExpo. After getting your data in Google Sheet, use ChartExpo for Google Sheet add-on to visualize the data. ChartExpo has extra features that are not available on other platforms.

Examples of ChartExpo Time Scale Data Visualization Options

A multi-axis line chart is a line chart that helps represent data in multiple axes. You can have multiple y-axes in the same chart. The advantage of this chart is that it brings together different sets of data with different metrics. Below is the features ChartExpo Multi-Axis Line Chart offers:

1. Multiple axes on the same chart.
2. Interactive axis. This allows you to show or hide data sets (lines) plotted against that axis.
3. An option that makes the axis visible or imaginary.
4. You can draw the axis on the left or right side of the chart.
5. Interactive options. These include dynamic sliding of the axis that you can click to move from one end to the other.
6. You can plot different multiple data sets on the same axis.
7. The option to manipulate axis-specific properties like:

1. 1. −Cosmetic properties
   2. −Divisional Lines
   3. −Cosmetic properties of data-sets plotting against the particular axis
   4. −Number formatting
   5. −Upper and lower limits

• Multi-Axis Line Chart in Action

  Suppose you are a PPC marketer and have been running a digital marketing campaign for a while. You decide to compare clicks, conversions, and impressions with the passage of date. You want to understand the insights without having to get headaches doing the hard work.

  You want to make it easier for your clients to understand the performance of the campaign within a glance. You decide to use data visualization using ChartExpo. The data is in Google Analytics. This is how you can create such a chart;

  
  1. First, click on Add-ons > ChartExpo > Open.
  2. Click PPC Charts and then click on Multi-Axis Line Chart.
  3. Select Sheet Name.
  4. Click on Add new metric and then select Column that has a numerical value (Avg. CPC, Clicks, Cost).
  5. Click on Add new dimension and then select Column which has Date.
  6. Finally, click on Create Chart.
  

  Insights

  By putting 3 different metrics across the same range of data, you can unpack a lot of insight from the chart. You can see that at the beginning of the period, costs, clicks were the lowest but average. The most important metric, CPC, was high.

  Also, with time all the metrics took off. This is a clear indication that the campaign had a turnaround for the better during that period. You can then investigate further and find what changes you might have made that you improved the campaign.

  The advantage of this visualization is that it helps analyze multiple metrics and trends simultaneously on a single chart. You do not have to go through the inconvenience of flipping back and forth between charts trying to create connections and conclusions.

  Area Line Chart

  If you have different ranges of values you would like to display, a area line chart is your answer. This chart used 2 axes to show the relationship between 2 variables that have different scales of measurement. It represents data in an arrangement of information using data points called markers. These markers are connected by straight line segments.

  This chart shows how data changes over time. Area line charts are versatile. You can compare different and multiple metrics of data sets.

  Example

  If you want to see how many women’s clothing items and men’s clothing items your apparel company sold online in the last quarter, you would plot data points for each category. You can see at a glance which apparel line performed better in quarterly sales.

  It may be easier for your audience to see and understand the data with a colorful line chart instead of multiple line charts each showing different results. You might need to use an area line chart if you want to:

  • Display large differences between your data points
  • Show multiple values over time
  • Plot data over a longer period of time
  • Explain how multiple data points relate to the total value

  Area Line Chart Example

  Mark has an agency he is running by himself. He gets a new client who left the old agency because he was dissatisfied with the services he was getting. After 15 days of working, the clients ask Mark to show him the performance of the campaign. The client wants to evaluate whether he should stay with Mark’s agency or move on.

  Mark knows his client does not like seeing numbers on a boring spreadsheet. He decides to use time scale visualization, so his client may understand the performance easily. For this, he collects all the data from Google Analytics. Here is a step-by-step guide on how to do this.

  
  1. First, click on Add-ons > ChartExpo > Open.
  2. Click General Analysis Charts and then click on the Area Line Chart.
  3. Select Sheet Name. Click on Add new metric and then select the Column that has a numerical value (Clicks, Conversions).
  4. Click on Add new dimension and then selected Column which had Date
  5. Finally, click on Create Chart.
  

  Insights

  From the chart, you can see where the conversion budget was working in the favor of the campaign. You can also see where the budget was being wasted because there were no conversions. When the non-conversion line goes up abruptly above the positive conversion line, it is time to take some immediate action to salvage the situation. This issue might be influenced by an error on the landing page or the relevance of the ad.

  This is the kind of issue that needs to be fixed as soon as possible to resume positive conversion spending. To achieve the best campaign results, the non-conversion trend line needs to be on the lower end of the chart.

  

  Wrap Up

  Data visualization is part of our daily lives. You might have come across some of them while reading a newspaper or watching TV. For instance, corporate annual reports, graphs showing the country’s GDP growth, or a top sales company growth audit in the last 4 quarters. These are examples of time scale data visualizations that track changes of different variables over time.

  Many tools that offer time-scale data visualization options are limited in the options they have. However, ChartExpo is a perfect Google Sheets data visualization tool that gives you versatility while creating time-series data. Use charts like multi-axis line charts and area line charts to understand how different metrics of data relate over a certain time.