Jan 29, 2023
The rate at which data is produced on a daily basis is alarming 😨. Data has become a gold mine for every business across all industries. However, just because you have a means of tracking data doesn't mean that the data can help you. There is more than just data tracking that needs to be done in order to convert the raw information into actionable insights to optimize your marketing campaigns (unless you are using Gretel!).
A research report published within the past few months revealed that 95% of companies struggle to manage unstructured data, and marketing departments suffer from it too. This is mainly because companies do not have the means of processing data and converting it into the useful information they need to make the right decisions. The good news is that you can visualize your data and break down the technical elements into a simple message with tools like Gretel or by analyzing the data yourself 📈. This needs to be the first step to be able to analyze marketing data.
Data visualization refers to the process involved in breaking down complex sets of data into simple messages that business stakeholders can utilize when making development decisions. Creating visual presentations of your marketing data makes it easier for you to communicate with a non-technical audience without wasting time making interpretations and will help you to better understand the insights received by Gretel. It's also key for futher marketing data analysis.
Besides, when data is presented visually, readers (or your team) can easily point out patterns, trends, outliers, and other critical points that they need to understand. Instead of employing complex analytics, you can save the cost and do the work with the aid of data visualization tools designed to help you maneuver the process.
This blog post outlines different methods that you as marketing professional, can use to visualize your data, and use it to underestand your marketing campaigns and focus your marketing efforts ✏️. Let's get started!
Line graphs are one of the most popular ways to analyze and visualize your marketing data. They are some of the simplest and most beneficial charts to serve a broad range of your data needs. A line graph is used when you want to showcase change over a particular period of time. When the lines go up, the numbers will automatically increase. On the flip side, when the lines go down, you will be experiencing a decline.
The simplicity that comes with the line chart makes it the best option for tracking your marketing data. On a line graph, the x-axis shows the data range, while the y-axis shows the kind of measurement that you are tracking. Ensure that every data point is represented using a solid line instead of a dashed or dotted line. The graph should make proper use of legends or labels.
Apart from making the lines appear solid, you can also use different colors to clearly outline your message. Note that all the clarifiers are outlined within the legend of the chart. Also, be careful when choosing the measurement range to ensure that you have values that can be easily measured and draw vital conclusions from the data presented in the line chart.
A line chart is a good example of a chart used to showcase progress over time. This can be arranged from the hours worked and the cost of revenue, wich can be used to measure the ROI (return on investment) and it's evolution. The data on the chart will help you compare the current status of your company with that of previous years.
A scatter plot, also known as a scattergram, is used when you want to find relationships in your data variables. The data values are displayed on both the X and Y axes to showcase similarities between different data points and point out any existing outliers within the data. When analyzing how your data is related to each other, you can easily find out other elements such as trends and patterns.
In order to use a scatter plot, marketers need to have several data points for every variable. After plotting your data on the chart, you can then analyze any points of data correlation that you can easily depict. When the data points move upward, ranging from the left to the right, there is a positive relationship in the data. If you do not locate any consistent patterns across the data, the chances of having correlations are minimal.
When using a scatter plot, you need to ensure that you choose metrics that have a robust impact on other values if you want to get the best results. Whenever you see a pattern in your marketing data, you need to continue doing analysis to find out if there is any other kind of relationship. Keep in mind that trends in your data do not result in causalities.
Given that scatter plots are used to identify data correlations, you can use them to investigate any problem in your marketing data. For instance, when you are running a delivery agency, you can use a scatter plot to find out the time of day that affects delivery services. A scatter plot can enable you to compare the average amount of time it takes to deliver every hour within a day.
A column chat is one of the most popular ways to visualize technical data. Also known as a column graph, the column chart is the simplest option that you can use to deliver your message in the form of data, and your audience will get it clearly. The chart is used when you want to compare the number of subjects present within a specific category.
The chart comprises vertical and horizontal lines that are used in data presentation. The data is outlined on both the X and Y axes, depending on the nature of the metrics you intend to compare. The vertical bars are outlined on the X-axis, while the horizontal bars are always present on the Y-axis. You can also switch the bars depending on the nature of the data you intend to visualize.
When you want to compare multiple data sets using a column chart, you can stack the columns on top of one another to accommodate as much data as possible. When using a column chart, ensure that it is well-labeled or colored so that readers can easily get your point without getting confused. Choose a numbered scale that your readers can read and understand when interpreting the message on the chart.
A column chart is the best data visualization model that you can use when you want to visualize the difference between various types of data and the kinds of changes that occur within a particular timeframe. For example, if you want to compare the conversion rates of different audiences.
If you want some of the most unique visualization charts, the matrix diagrams are the best! They play a significant role when we want to understand the relationship between one set of data and another. It has the capability to compare various groups of data within a comprehensive data category. With matrix diagrams, you can easily find out how different groups of data influence one another and interact.
Given that the matrix diagrams are much clearer than other visualization tools, they allow you to make more accurate decisions that can propel your business to greater heights. However, before using this chat tool, you need to have a clear understanding of what you intend to achieve. Avoid getting confused, and ensure that you are assigned a symbol on every data group to help you track the right numbers.
The matrix diagram is the best option when you want to detect causation for example, in some digital marketing campaign. Also, it can identify the root problem and display multiple solutions that you can put into practice for better results.
Even though a pie chart seems to be a simple option, there is a lot of untold information about how it works. This is the best data visualization option that you can use when you want to share information with a huge group of people, for example in a global presentation showing your marketing analytics. A pie chart resembles a circle that has multiple slices that represent different data components, and it is used to display the components that make up the whole thing under discussion.
The chart works well when your data is broken down into slices and displayed in percentages. The advantage of pie charts is that you don't need to dig deep inside the data to uncover insights since all the information is displayed at first glance. When using the chart, ensure that all your data components add up to 100%. Ensure that every data segment is well labeled to avoid confusion during interpretation.
Apart from labeling the chart, ensure that every data slice is highlighted with a different color to make it unique. Limit the number of pieces you outline on a pie chart since it can get congested, making it difficult to interpret.
The chart works well when allocating resources within your marketing campaigns or when you want to identify the conversions from your marketing channels.
Data visualization is an easy process that you can invest in when you want to extract insights from data and use it to make key development decisions or a support to explain your analytics. However, it can only work for you if you understand some of the best visualization tools to use, depending on the nature of the data you intend to visualize.
The visualization tool you choose depends on the nature of your data and the goal you intend to achieve.
Once you understand the best visualization tool that reflects the nature of your data, you will be better positioned to analyze marketing data and break down the complexity of these metrics. The visualization tools outlined in this article are designed to analyze your data points, uncover significant insights required during decision-making and help you to complement your marketing data analysis techniques.
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