There are a variety of tools that a researcher can use to present their ideas and to deliver their visualizations. Whatever tools you decide to use, you need to make sure you're choosing the best format for your audience, and follow rules that will help your ideas come across. By the end of this lesson, you should be able to: select the optimal visualization for multiple sets of data, list guidelines for effectively presenting information, and discuss some of the tools available for creating visualization. The researcher can use a variety of means to represent their data such as pie charts, histograms, scatterplots, and various other types of charts. Other design aspects that can affect how your audience interprets your visualizations, are your choices of size, color, font, and the language used within a presentation. You should also be able to identify some basic tools that will help you create visualizations. Let's go through some of the types of charts and discuss what they're best used for. One of the most common and recognizable visualizations, is the pie chart. Pie charts are visually appealing and are seen everywhere from business reports to newspapers and magazines. A pie chart is a good choice if you have three or less fields. For example, when charting the gender of respondents. So, let's take a moment and discuss why you don't want to use a pie chart for let's say, if you had, 12 different particular fields or categories. Think about a pie. If you're cutting it into 12 slices, they're getting kind of small, and it's also going to be more difficult for your reader to understand each of those slices. So, sometimes we've seen really bad pie charts where you have these itsy bitsy slices, and it's really hard to read. Again, it's all about how can the viewer see the information, and easily understand what you're trying to communicate? Let's also talk about column charts. Column charts are quite common when displaying business data. In a column chart, each column represents a category of information that you want to represent. The columns in a column chart are oriented vertically. A column chart is a good choice if you have five or less fields. For example, charting the age of survey respondents. Let's talk about the differences between when to use a bar chart, versus when to use a column chart. The most important thing to think about is, how many particular categories do you have? Are you only charting let's say, four or five particular categories, or do you have a much longer list? For example, you might test a product and there would be 10 features in that list. Then, you have to think about how are you going to format that data and those respective lists on your PowerPoint presentation? Now, in a bar format, you can actually just use the list of features like this. And then the bars will go like that. In a column chart, you're going to have the columns like this, and the list is going to be below. Now if you think about it, there's less real estate at the bottom of a PowerPoint presentation page than you can use here. In this case, when you have a lot of data fields, you might want to do a bar chart because it will be easier to place the information on the side of the bar as opposed to trying to squeeze it below the column chart. Okay, let's talk about histograms. Now histograms are often more typically used in scientific research, less so in marketing research. But, it's still an important type of chart. Now, really, what you want to do with a histogram, is you want to be able to represent the distribution of data. So, in some cases a histogram really is just like a column chart. But you're typically looking at the distribution of an entire audience. So for example it could be listing the specific age categories of the consumers that you spoke to. Now, in this example that I will show you, this is a histogram that charts the salaries of employees. Histograms are very good ways of distributing information. In this case, you can see that the salaries follow a general bell curve. Now, Scatter Plots. Again, scatter plots are often used a lot more in scientific research, but they do have some functionality in market research as well. Scatter Plots show the relationship between two variables. Typically, they are used to show how one variable can affect another, and thus, the correlation between the two. Statisticians typically use scatterplots to show if variables are correlated. For example, there might be a correlation between price and a consumer's interest in a particular subscription service at that price. Line charts can be used to display information trending over a period of time. Typically, line charts will have the same time scale across the bottom of the chart the X axis, and the units being measured on the line on the left the Y axis. If you're trending information over time, a line graph is helpful. For many of the technology companies that I work with, they often talk about a Hockey Stick Curve. And that basically means that a product is taking off. You have a very, very, very, slow growth and then poof, the Hockey Stick. Let's also talk about colors. Colors are really important. Even if you've chosen the optimal chart for your data, your choice of color can have an impact on how audiences will interpret your visualization. For example, if you are charting things that are positive, you might want to utilize the color green, as this signifies good or go. Conversely, red is a good color for something that is negative. Think about a stoplight. Fonts, fonts are also very important. Your font choice can have an impact on the effectiveness of your deliverable as well. First and foremost, make sure you use fonts that are easy to read. Times New Roman, and Helvetica and Courier, are simple but clear and easy to read. Consider how your font size affects your presentation. For example, if you're presenting to a large group of colleagues in a conference room, you probably don't want to use a very small font such as ten point, or less, because it will be very difficult for them to read from across the room. However, if you are writing a one page memo, a font size of 10 would be appropriate. Now that you know some basic rules about choosing the appropriate visualization, you need to somehow create that visualization. While some research firms have design specialists devoted to designing research deliverables, others may rely on basic software tools. At the most basic, excel has a robust set of tools that can be used to create a wide range of charts. One of the best aspects of the most recent version of excel, is that it will suggest particular charts and also has a wide range of templates. It's pretty easy, within five minutes, to see various layouts and types of charts. Now, when you're using excel, it's very tempting to get creative and want to use a variety of colors and formats. But, what you'll find is that that will be confusing for your reader or your viewer. What you wanna do is pick one particular style, or maybe just two or three particular styles if you have a lot of data to present, and use them consistently throughout your presentation. There are also a variety of companies that sell different types of presentation software and templates. For example, there's a company called Prezi, which has student and business trials, and helps you create visually stimulating presentations. There are also a variety of infographic templates available, including Piktochart chart, Visme, and then Venngage. If used appropriately, data visualizations can have a great impact on the effectiveness of your presentation. It comes down to understanding your data set, and choosing the appropriate way to represent it. And, with so many tools available to help you build your charts. You can create some very appealing visuals without having to be a graphic designer yourself. Remember, visualizations ultimately make your findings more interesting, and easier for your audience to understand.
