Visualizing Your Data
Visualizing Your Data
FAQ - Visualizing Your Data
Which Chart or Graph is Right for YouYou have the data and you have the questions. Meaningful charts and graphs are what you strive for but sometimes you cannot decide which would best convey your data for the answers you seek. TapAnalytics helps answers these questions and this article will help you decide which would be the best charts for the type of data you want to utilize to answer your questions.
Stranding your data in isolated, static graphs limits the number of questions you can
answer. Let your data come alive and be the centerpiece of decision making by using it to tell your story. You can combine related charts. Add a map. Provide filters to dig deeper on the impact for the business and get the insight and answers to questions in front of your eyes.
Which chart is right for you?
Transforming data into an effective visualization (any kind of chart or graph) is the first step towards making your data work for you. In this article you’ll find best practice recommendations for when to create these types of visualizations:
- Line Chart
- Bar Chart / Stacked Bar Chart
- Pie Chart
- Top Performers
- Big Number
- Geo Chart
- Funnel Chart
- Combination Chart
- Gauge Chart
Sometimes you want to include your additional insights or have a visual graphic image that you want to display to support your data. This option is great for really getting your story through by allowing you to tell clients your analysis of the data.
When to use Media options:
- You have made your desired graphs, but you want to help lead your clients to the correct answer to the problems they are facing. This media option can allow you to write out your findings to convey what your chart/graph is trying to tell the end user.
- Liven up your graph with images that would show which products or advertisement is being analyzed. An example use case would be uploading images of two advertising campaigns in which your chart or graph is showing.
- Including the data point totals in your analysis if your chart/graph breaks down items
- If you do not have a comparison chart/graph for a time period, you can add the previous period's numbers to inform clients about growth
- Include any calculations or noteworthy footnotes that you may have done to visualize your data
Line charts are one of the most frequently used chart types. Line charts connect individual numeric data points. The result is a simple, straightforward way to visualize a sequence of values. Their primary use is to display trends over a period of time.
When to use line charts:
- Viewing trends in data over time.
- Examples - Engagement growth over a monthly period, website page views during a month, revenue growth by quarter
Also consider Area Charts:
- Shade the area under lines. When you have two or more line charts, fill the space under the respective lines to create an area chart. This option can be selected at the top of the line chart section when building your widget. This informs a viewer about about the relative contribution that line contributes to the whole.
Bar charts are also one of the most common ways to visualize data. It's quick to compare information, revealing highs and lows at a glance. Bar charts are especially effective when you have numerical data that splits nicely into different channels so you can quickly see trends within your data.
Bar Chart / Stacked Bar Chart
When to use bar charts:
- Comparing data across channels
- Examples - volume of likes, comments, and shares or website traffic by origination site
- Include multiple bar charts and group them next to one another on your dashboard. This helps the viewer quickly compare related information instead of flipping through a bunch of spreadsheets or slides to answer a question.
- Use stacked bars or side-by-side bars. Displaying related data on top of or next to each other gives depth to your analysis and addresses multiple questions at once. One can simply do this by selecting the stacked bar chart option.
Pie charts should be used to show relative proportions – or percentages – of information. Pie charts are one of the most commonly mis-used chart type. If you are trying to compare data, leave it to bars or stacked bars. Don’t ask your viewer to translate pie wedges into relevant data or compare one pie to another. Key points from your data will be missed and the viewer has to work too hard.
When to use pie charts:
- Showing proportions
- Examples - Percentage of budget spent on different campaigns, demographic channels from a survey, breakdown of video view percentage
- Limit pie wedges to six. If you have more than six proportions to communicate, consider a bar chart. It becomes too hard to meaningfully interpret the pie pieces when the number of wedges gets too high.
Like a table overview? Top performers will give you an organized table overview of your top performers. This table will give you a great insight and power to include multiple metric columns for a table comparison.
When to use top performers:
- When you want to organize performance of multiple Data Sources by specific performance metrics.
- Examples - Would be having top performers of new followers or new fans, or a breakdown of a page session's metrics.
- Utilizing top performers to break down sessions adding metrics to compare versus goals.
Sometimes you just want a big overall number for specific metrics. Big numbers will give you the overall totals of what you are interested in as a quick overview. Visually, big numbers are great eye catchers.
When to use big numbers:
- The best way to utilize big numbers is for a top view look at your metrics.
- Examples - Having the total number of followers, number of likes, number of clicks, or number of impressions
- Including big numbers at the top of your dashboard would be one of the best ways to have your clients see totals for their time-frame
Geo ChartWhen you have any kind of location data - whether it's postal codes, state, abbreviations, country names, or your own custom geocoding - you've got to see your data on a map. This chart can visually give you an idea of the geographic location your data is coming from. So demand the same informative view from your data.
When to use maps:
- Showing geocoded data.
- Examples - Pageviews by country, product revenue by state, custom sales territories
- Layer bubble charts on top of maps. Bubble charts represent the concentration of data and their varied size is a quick way to understand relative data. By layering bubbles on top of a map it is easy to interpret the geographical impact of different data points quickly.
Funnel ChartThe funnel chart is used to visualize the change and reduction of data as it passes from one phase to another. Data in each of these phases is represented as different portions of the whole process from start to end.
When to use funnel charts:
- If you have data that tracks people's usage from a starting point to a completion point, funnel charts will be your best way to visualize how far a user progresses to completion.
- For example, at the top of the funnel you will have all the users coming to your site. However, you really care about how many of those users make it to the checkout page to submit an order. Funnel charts are a great way to track users and allow you to focus on where your users get lost in transition. You can then strategically plan to maximize you completion goals.
Combination ChartTo emphasize different types of information in a chart, you can combine two or more chart types in that chart. For example, you can combine a bar chart with a line chart for an instant visual effect that might make the chart easier to understand. Visually, you can see two charts in one.
When to use combination charts:
- You should utilize combination charts when the range of values for different data series in your chart varies widely, or when you have mixed types of data. This way, you can plot one or more data series from a different chart type on a secondary axis.
- Your metrics should be related to one another and one metric's scale does not overshadow your second metric. For example, if you utilize a metric whose scale is in the thousands and a metric in the hundreds, you will be limited in seeing correlation.
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