Sir Francis Bacon made the infamous statement in 1597, “Knowledge is power.” Four decades later, as big data provides organizations with invaluable insights, this saying still stands tall. Business leaders must make important daily choices that will affect their company’s performance. The ramifications of some of these choices can significantly affect the company’s bottom line. Thankfully, in today’s digital age, big data has taken the reins and given executives the tools they need to make more informed choices.
Companies could use big data to profit from a wealth of previously untapped data. Every single day, we generated 2.5 quintillion bytes of data. Even while modern tools allow us to amass vast quantities of data, this knowledge is only meaningful if it can be transformed into useful insights.
Here comes marketing data visualization, or the visual depiction of data and information. Data visualization is a potent tool for helping people make better decisions because it can distill a dearth of raw data into digestible insights.
Even if your company doesn’t generate large volumes of data every day, you can still benefit from using types of data visualization to guide your team’s deliberations and boost your company’s financial health.
This guide will cover the fundamentals of marketing data visualization and its significance in leveraging marketing analytics dashboards to aid your decision-making process effectively.
Tools Used for Marketing Data Visualization
A wide range of programs, utilities, and scripts under the umbrella of marketing data visualization software. They provide marketers with the resources to visualize massive amounts of data. Here are the most common ones:
- Domo
- Dundas BI
- Infogram
- Klipfolio
- Looker
- Microsoft Power BI
- Qlik
- Sisense
- Tableau
Significance of Marketing Data Visualization
Marketers can better contemplate their business decisions if they have the right datasets. However, the raw data is often confusing and difficult to contemplate. This calls for the need to visualize data beyond displaying it.
First, data visualization facilitates rapid comprehension of complex data and unearths the hidden patterns, outliers, opportunities, and trends, thus providing actionable insights for strategic decisions. This graphic aid makes data comprehension easier and more broadly applicable.
Consequently, stakeholders can lay their foundation to sound strategic decisions grounded in evidence and promote a common understanding. Not only this, decision-makers can forecast any threats and avoid unfortunate pitfalls. This allows for preemptive choices and timely measures, ultimately leading to better business results.
According to research, businesses can get an 85% competitive advantage in revenue growth over their competitors if they use customer-behavior data to draw conclusions and make data-driven choices.
Selecting the Right Marketing Data Visualization Techniques
Visualization is not only about labeling facts and figures in a fancy format. The data visualization dashboard must interpret information that is easier to understand and facilitate data-driven decision-making.
There are several types of data visualization with a specific purpose. Let’s look at the most common ones:
1. Infographics
These visuals summarise raw data and key takeaways in a neat and digestible manner. Such illustrative visualization combines text, numbers, and graphics to present data in a visually engaging way.
2. Charts
Different types of graphs, such as line graphs, bar charts, and scatter plots, help to show the relationship, comparison, and trends between numeric data sets. These graphs are useful in identifying patterns and making strategic decisions.
3. Diagrams
This graphic visualization assists in decoding the data set’s flow and structure, further identifies bottlenecks, and analyzes variable dependencies. Here, network diagrams, flowcharts, and decision trees are usually used to visualize relationships, processes, and hierarchies.
4. Maps
Marketers use maps to visually represent spatial and geographical data, including demographic information, regional variations, and distribution patterns. These maps typically pinpoint specific geographic targets and draw location-based conclusions.
Remember that you don’t have to stick to just one marketing data visualization technique for your findings. The key is to consider your audience and the type of data you’re working with to determine the most effective way to present it.
5. Table
A pivot table entails rearranging your data to make drawing conclusions simpler. Spreadsheet programs like Google Sheets and Excel make frequent use of pivot tables. Additionally, more advanced BI applications like Tableau or Looker Studio (formerly Data Studio) allow you to ‘pivot’ data similarly.
Alternate Marketing Data Visualization Techniques
We’ve included some of the most regularly used charts in use today. However, there is a plethora of different marketing data visualization options to choose from:
- Scatter diagrams- also known as plotted graphs, illustrate the correlation between two independent variables.
- Bubble charts – a modified scatter plot in which the bubble size is the third dimension.
- Dispersed charts – show information groups as different colored circles, with the amount of information shown in each circle depending on its size.
- Treemaps – the visual representation of a hierarchy or comparison of categories and their subclasses.
- Polar charts – also known as polar area diagrams are used to illustrate the connections between numerous independent variables.
And the list goes on. However, the aforementioned charts should be sufficient for your marketing data visualization requirements in most circumstances.
Best Practices for Marketing Data Visualization
1. Design Neat and Effective Visuals
For the dataset to be useful for decision-making, it must be effective and clear. When it comes to marketing analytics, visualization, simplicity, and clarity are two crucial characteristics. These traits reduce clutter by eliminating unnecessary details and provide the viewer with a clear understanding of the essential metrics.
The combination of contrasting colors and legible typefaces provides a user-friendly visual aid. Choose complimentary themes to provide a consistent appearance throughout your design and use color theory to draw emphasis where it’s needed; this will assist consumers in staying focused on the content that matters most to them.
Sort and arrange information to put it in a coherent visual order. Bars, symbols, labels, and lines are all powerful visual cues that help organize information for users.
In order to keep the attention of visitors, marketing data visualization dashboards often use visuals. While charts and graphs grab attention, tables with the right dataset and some sparklines or conditional formatting may be just as interesting.
2. Incorporate Storytelling in Your Data Visualization
Improving marketing data visualization is essential for better insight into communication strategy and sound decision-making. Data storytelling is more than just presenting facts and figures; it is a process of holding your customers’ attention. Therefore, it must be organized and presented coherently and interestingly.
Annotations and captions greatly enhance the understanding of visualizations for a general audience. Therefore, businesses must include them in their reports to provide more depth, emphasize crucial results, and explain complex issues. The annotations and captions should be thoughtfully designed to help with comprehension and highlight key insights from the data.
Data storytelling becomes more effective when it includes relevant contextual information. Businesses can assist customers in making informed decisions by providing background details such as historical data, market trends, and comparative metrics.
3. Optimizing Data Visualization for Strategic Decision
It is important to prioritize the user experience and include interactivity when visualizing data for decision-making, particularly in business intelligence (BI). Users can utilize tooltips, filters, and drill-downs to be actively involved and given more agency to explore data by making infographics interactive.
By applying filters to data, marketers narrow down their search to just the results that meet their requirements. When you hover over a data point, a helpful tooltip will appear, giving you further context and additional insights. The drill-down feature allows users to go from high-level to granular views of the data, where they can discover previously unseen patterns and better grasp the whole.
Moreover, integrating dynamic data in real-time updates guarantees that decision-makers are working with the most recent data possible. Businesses can quickly adapt to shifting market conditions with regularly updated, dynamic data.
4. Ensure Compatibility & Accessibility
Data visualization’s impact can increase multi-folds when accessible to a wide range of users. This enables decision-makers to evaluate a large array of data and make more informed decisions.
Since information is increasingly being accessed in various mediums, visualizations must be adaptable to these many devices and platforms. All visualizations must be responsive, automatically adapting to fit any screen size or orientation.
One of the best ways to guarantee this is to follow responsive design principles. As such, it is important to have adaptable layouts, images, and interaction techniques. Marketers ensure a seamless and pleasurable experience across all devices by building responsive marketing data visualization dashboards from the ground up.
When modifying visualizations for use on various platforms, keep bandwidth and network constraints in mind and minimize the size of the files and the loading time, so users can view and engage with visualizations quickly and easily.
5. Measure the Impact of Marketing Data Visualization
To assess the impact of data visualization on decision-making, we need to measure its effectiveness.
First and foremost, it is essential to develop KPIs for visualizations that help the company steer in the preferred direction, whether it is about gaining data insights quickly or more user engagement. By establishing quantifiable measurements, firms can gauge the impact of their visualizations.
Second, it’s crucial to get input from real people. If you actively ask for feedback from different audiences like stakeholders, users, and decision-makers, you can gain practice insight into applied visualization approaches and whether they require iteration. User feedback is a great way to find out where you can make changes and learn about any problems with usability or understanding.
Finally, establish a data-driven iterative improvement cycle. When e-commerce organizations analyze their customer feedback and internal data, they can see patterns, trends, and opportunities for business growth. By implementing a feedback loop, the visualizations can be consistently enhanced to meet the evolving needs of decision-makers.
6. Eliminate Visual Noise from Your Data
The metrics you display on your visualization should make sense in context to generate a practical dashboard image. For instance, information concerning retention rate or LTV can be redundant in a graphic focusing on various marketing channels’ efficacy.
Additionally, only save data useful to stakeholders, such as information that can be used to develop conclusions. To ensure that your dashboard and its representation are as effective as possible, you should remove all the unnecessary data and charts.
Scope of Data Visualization
Marketing data visualization has been shown to be a catalyst for change. For instance, the Cholera Outbreak 1854 Map of London pinpointed the sites of epidemics and showed that homes infected with the disease shared water sources. By inspecting these water sources, scientists showed that cholera was caused by drinking tainted water. Due to these findings, the city was able to rid itself of cholera, which also facilitated Louis Pasteur in his quest to develop contemporary germ theory.
Now, more than a century later, organizations are trying to figure out how to use data to their advantage so that they may expand and succeed. Therefore, having a holistic marketing strategy that allows for visualizations that improve decision-making processes has become crucial.
Conclusion
To sum it up, marketing data visualization is crucial to corporate decision-making because it allows stakeholders to extract actionable insights from otherwise incomprehensible data.
You’ll have to zero in on the data that matters, choose the right visualization methods, and create representations that make an impression. In order to successfully convey insights to decision-makers, visualization design must promote simplicity, consistency, and narrative. To improve the user experience and attract a larger audience, it is also important to include interactivity and guarantee accessibility.
Businesses may boost their bottom line, make more well-informed decisions, and propel greater results with the help of marketing data visualization. Organizations will benefit from adopting a data-driven strategy and constantly improving their visualization techniques based on user input and verifiable results. Remember that data visualization is powerful because it simplifies complex information into actionable insights to enhance a company’s profitability.