Successful marketing, in which outreach leads to conversions, all starts with data. The more you know about your potential customers, the better you can tailor marketing efforts that will resonate with them and lead to conversions, instead of prompting them to scroll by or click that “unsubscribe” button.
The more data you can collect, the better, but there’s a problem: A surplus of data can become overwhelming. That 50-page spreadsheet with information collected from thousands of potential conversions may contain a wealth of data, but it may also be nearly incomprehensible for a person to process.
The solution to excess data is data visualization.
In simple terms, data visualization is transforming raw data — such as numbers, percentages, or averages — into visual representations like charts, graphs, and maps. Organizing data this way allows marketers to identify the patterns and trends hiding within dense datasets. Data visualization can enable businesses to make informed decisions based on easily understood visual representations of stats rather than by going through the numbers alone.
“I see data visualization as the bridge between raw data and actionable insights,” says Pieter Wellens, co-founder and CTO of Apicbase. “For marketers, it’s all about making sense of the endless metrics and turning them into something that drives decisions. Whether it’s using heatmaps to analyze customer interactions or dashboards that track KPIs like campaign ROI, visualization tools are game-changers.”
Why Data Visualization Matters for Marketers
“Data visualization is about transforming spreadsheets full of complex data into something visually clear, like a chart or dashboard, that helps marketers make smarter decisions,” says Binod Singh, founder of Cross Identity. “It isn’t just creating pretty graphs, it’s about uncovering connections and patterns that might otherwise go unnoticed. For example, when you map customer demographics against purchase trends in a visual way, you can identify key audience segments and tailor campaigns specifically for them. That kind of insight can mean the difference between a campaign that connects and one that falls flat.”
Done well, data visualization not only makes the information you’ve collected more easy to process, it can help confirm or dispel assumptions you and your team made. They may even reveal hidden trends, patterns, and behaviors you didn’t anticipate. The metaphor of a 1,000-piece jigsaw puzzle is accurate when it comes to data visualization: Only the assembled puzzle reveals the full picture.
Key Principles of Effective Data Visualization
If you know what you’re looking for — and you don’t anchor yourself to preconceived notions — data visualization can help reveal significant and actionable information about your potential customer base. But you have to know when it’s time to stop collecting data and to start putting it to work.
“Finding the right balance between being complicated and being clear is important,” says Michelle Nguyen, product owner and marketing manager at UpPromote. “Even though it might be tempting to put all of your possible data points on a dashboard, I’ve found that focused, purpose-driven visualizations work best.”
What Are the Advantages and Disadvantages of Data Visualization?
The greatest advantage of data visualization is that it makes information easily digestible. Through the use of charts and graphics, data visualization allows people without data analysis training to make sense of the numbers. When used properly, data visualization helps reveal patterns and trends in human behavior, and allows for more accurate predictions and better marketing initiatives.
There are a few potential disadvantages to data visualization if it’s improperly implemented, however. One major issue is that improperly created visualizations can lead to misinterpretation of data. It’s also sometimes possible to oversimplify a data set, which can lead to missed information that would have been otherwise informative and actionable. Also, it can sometimes be challenging to determine the best graph or chart to best represent the data.
Data Visualization and Big Data
“Marketers deal with tons of data daily,” says Jase Rodley, SEO consultant and founder of JaseRodley.com. “Website traffic, social media engagement, sales figures — the list goes on. But raw numbers can be overwhelming and that’s why we need visualization. So, if you’re tracking the performance of an ad campaign, a simple line chart can show you how clicks have changed over time. You can quickly see what’s working and what’s not.”
Data visualization turns that overwhelming wall of “big data” into manageable nuggets of information, so if you have a mountain of data through which you need to parse to find actionable insights about your customers (or potential clientele), you need to turn to the visuals.
Common Types of Data Visualizations for Marketers
- Bar charts: Charts with bars of differing height or length indicating an amount of data.
- Pie charts: A circular chart with data divided into segments that’s especially useful for showing percentages.
- Flow charts: A diagram connecting data points together with graphics and lines in a chronological or otherwise logical manner.
- Line charts: A chart using linear depictions of data, usually rising and falling over time, that helps demonstrate change.
- Scatter plots: A visual display, usually on an X-Y axis, with individual data points displayed.
- Heatmaps: A representation of data as a map or diagram, with data values shown as colors that can be used for functions such as showing frequency of website visits.
- Histograms: Similar to a bar chart, a histogram almost always involves numerical frequency of events over time.
- Treemaps: A graph with nested rectangles, each of varied size and representing different data, and with all data related as part of a larger whole.
- Infographics: Various types of visual imagery used in place of words in the sharing of data.
- There are other types of graphics that can be used in data visualization, but these are the most common and, in most cases, the most useful.
Best Practices for Visualization Data
“The key is to make data visualization accessible, not overwhelming,” says Singh. “It’s not just for analysts, it’s for everyone on the team. When done right, it empowers marketers to be more creative and confident in their strategies.” To that end, use the simplest graphics that will display the data accurately.
Pie charts are easier for most people to process than scatter plots, for example, so use the former when applicable. Bar charts are clearer than bubble charts, so again, opt for ease of comprehension. Flow charts can help break down big ideas. Line graphs are great for picturing data over time.
Make sure to return to your data visualizations time and time again after you have collected new information. “The best visualizations are those that represent data as a story with a progression,” says Samantha Taylor, marketing manager and business consultant at LLC.org. “In a timeline chart, for example, you can visualize how a marketing campaign progressed through six months, and adding event cues like product releases or campaign pivots can help marketers visualize the effects of certain actions. Also, contrast is a necessary addition. Distinguishing anomalies, such as an uptick in traffic or a segment that’s performing poorly, instantly becomes useful.”
Tools for Creating Data Visualizations
There are myriad data visualization tools available today, with some of the most popular being Tableau, Google Charts, Datawrapper, and Domo. Google Charts has the advantage of being free, while other options often have free trial periods.
Tableau is a great tool for more novice users, as it offers a user-friendly interface, a wide range of chart types, the ability to handle large datasets efficiently, and an interactive dashboard, making it accessible for inexperienced and experienced analysts alike, including people without extensive coding knowledge.
Datawrapper is noted for prioritizing data transparency, so it’s a good platform for sharing information with an audience.
Domo offers a vast catalog of chart types and graphics, including many interactive features and real-time updates, so for creating visually engaging and dynamic presentations, it may be the best choice.
These are but a few of the many options out there, so be sure to search around for a data visualization option that’s easy to use and will serve you over time.
Case Studies and Real-World Examples of Data Visualization
Perhaps the best recent and widespread use of data visualization was during the height of the COVID-19 pandemic. Hearing about high levels of infection and transmission could be unnerving but ultimately abstract, but visual representations of the infection rates, death tolls, re-infections, and more made it easier for non-healthcare professionals to grasp the gravity of the spread of the disease.
Data visualization using charts and graphics is also an important way to make sense of the voluminous data that comes with trading stocks. With billions of transactions occurring every day, the proper tracking of stock performance would be impossible for the human brain without data visualization.
On a smaller scale, keeping a mood journal, tracking your fitness, or watching your diet can all be made simpler through data visualization.
The Future of Data Visualization in Marketing
The future of data visualization for marketers will surely be heavily influenced by ever more advanced artificial intelligence (AI). AI allows for real-time data analysis, the crunching of immense volumes of data, and the creation of customized graphics and analysis. This functionality will allow marketers to create interactive, personalized, compelling, and actionable visualizations that present better insights than ever. This will also enable better audience segmentation and will lead to more effective marketing efforts.
Key Takeaways
Data visualization demystifies data sets, revealing the trends, patterns, ups and downs, successes and misses from the abundance of information collected about people, marketing campaigns, timelines, and more. Common uses of data visualization include the use of charts and graphs, such as pie charts, heatmaps, and line graphs.
Data visualization is a necessary tool for marketers who want to maximize the efficacy of their efforts and create marketing campaigns and outreach that will match the behaviors and preferences of potential conversions.
Frequently Asked Questions (FAQs)
Which types of data are most important to visualize for marketing campaigns?
In the digital era, the most important types of data to focus on include customer demographics, website traffic, conversion rates, sales information, campaign performance information (click-through rates, open rates, and bounce rates), customer acquisition cost, customer lifetime value, social media engagement, and competitive analysis data.
How can data visualization improve decision-making in marketing?
Data visualization enhances marketing decision-making by presenting otherwise complex data in a visually intuitive way, enabling marketers to identify trends, patterns, and metrics that can help them make more informed decisions about campaign optimization, audience segmentation, resource allocation, and overall strategy.
What are the emerging trends in data visualization for marketers?
As noted, AI is the true game-changer when it comes to data visualization in marketing. No longer do marketers have to seek out the best available tool for converting the data they’ve collected into a pre-ordained type of visualization: Now, they can create customized tools from scratch that are perfectly tailored to suit their needs. Platforms like Qlik, GatherAI, and the aforementioned Tableau all offer such capabilities, and most offer free trials. Prices vary, but most such companies offer monthly plans that cost less than $100 for limited use.
