數位行銷已經擺脫了專注於過去的經驗或增加品牌曝光的舊思維方式。現在的主要內容是收集數據並解釋其對分析和決策的意義。隨著數據的重要性不斷上升，這意味著行銷人員必須具備收集和呈現數據的知識。資料視覺化不再是只有研究人員或資料科學家才應該具備的技能。
What is Data Visualization?
Data visualization is the illustrated representation of data and information. By using visual elements like maps, graphs, charts, to help the audience understand the trends, patterns in the results at a glance.
Big Data has been around since 2005, DataScientists and Data Analysis have become one of the most in-demand jobs in tech and start-up industries. This has also changed the marketing ecosystem which gradually emphasizes data orientation. Hence, Data Visualization has eventually become a skill that marketers should have in order to help stakeholders make decisions more quickly and accurately.
Before we begin, you can click here to receive learning resources in the future to help you better understand the concept and the know-how of data visualization for marketing.
How can Marketers learn Data Visualization?
In terms of large data analysis and data visualization, R programming and Python skills are often required, but that is also some in-depth programming skills that most marketers do not have. Fret not, there are many resourceful and good data visualization tools that can be used without having any programming skills.
但是，請記住，如果您想學習如何視覺化數據，掌握這些工具並不是主要目標。請查看以下步驟以了解更多資訊。
1. 學習如何組織數據
Marketers are always looking at numbers and are not new to Facebook Advertising or Google Ads which have huge amounts of data that can be analyzed. What metrics are important are decided by the marketers. Do I want to track monthly CPA? Do I want to see weekly conversion rates of different products? Marketers will need different data for different goals respectively, then export and organize them through Excel or Google Sheet to have clean and usable data.
2. 決定圖表中所包含的內容
The purpose of data visualization is to convey complicated data in the simplest and clearest way. A clear chart usually is not allowed to have too much information, you will have to decide what information you need the most.
例如，您想要按地區顯示用戶百分比、貼文排名或每月的轉換率嗎？規劃您想要先呈現什麼類型的資訊以及每個資料如何相互關聯。該圖表將更加簡單且更容易理解。
3. 選擇正確的圖表類型
There are a few common types of data visualization which include charts, tables, graphs, maps, infographics, etc. The right visualization must be paired with the right set of information.
For example, pie charts are suitable for presenting different proportions of information such as the percentage of revenue generated by different products; bar graphs are good for changes in trends such as the revenue generated by 2 products for each month.
當你理解了這些圖表和資訊之間的關係時，你絕對可以更好地形象化它。
建議的數據視覺化工具
Once you have the basics of data organization, data analysis, and understanding the charts’ differences, it’s time to visualize the data. Check out the top 5 user-friendly data visualization tools for marketers.
Excel 與 Google 表格
你一定在想，我每天都用這個！是的，但是您真的熟悉可以用它執行的每個公式或函數嗎？大多數想要學習資料視覺化的行銷人員都有一個誤解，認為一定有一些工具可以透過輸入資料來產生漂亮的圖表。
The prerequisite for creating beautiful data charts is to get familiar with the characteristics of the data and the relationship between them. If you are relatively new to data, Excel and Google Sheet are the best tools to learn to organize, interpret and visualize data. When you are familiar with them, you can actually create professional charts from scratch in both Excel and Google Sheet.
Google Data Studio
Google Data Studio是Google推出的免費資料視覺化工具。它可以與其他工具集成，例如Google Analytics、Google Sheet、YouTube、Google Ads等。它有很多模板可以用來讓你免去思考簡報的麻煩。它還具有一些動畫功能，可讓您製作令人驚嘆的視覺化效果。
Tableau
Tableau is probably one of the most well-known data visualization tools in the world. It is very easy to use as it does not require programming skills and is able to visualize data by dragging and dropping. Tableau is also very fast and user-friendly even when the data is huge.
Power BI
Power BI is a data visualization tool by Microsoft . If you are a Microsoft Office user, it will be the most convenient option for you to use Power BI. In addition, Power BI emphasizes the combination of analysis and visualization. Import the raw data and let Power BI help you analyze and visualize your data.
Visme
One of the biggest advantages of Visme is there are tons of beautiful templates that can be used, not only for data visualization but also for branded content. There are many elements that can be made in infographics, many people use Visme for Instagram content creations as well.
結論
To give you a recap, effective data visualization is the significant step of data analysis. Although marketers usually don’t have to deal with complicated data like Data Engineers or Data Scientists, Data Visualization is still a big learning curve for most marketers. This article only includes the basic guides for beginners. If you wish to learn more about data visualization, click here to receive exclusive learning resources. Become a data-driven marketer who excels in Data Visualization!