I ran a Crosstab analysis this morning to find out how people are feeling about some of the 2016 Republican presidential candidates across issues like the economy, the deficit, unemployment, and health care. And, for fun, I threw in hair.
The chart, which shows net sentiment scores for these candidates over the last six months, uncovered some interesting comparisons on the basis of real issues. But hair is still a surprisingly important issue in the presidential election, accounting for 3.5% of the total mentions in my analysis, more mentions than on the federal deficit and just below the total mentions on the economy.
In the hair race, predictably, Donald Trump’s flip got a relatively high net sentiment score of 46, while Rick Santorum knocked it out of the park with a perfect 100. Carly Fiorina’s hair got a flat 0 and Mike Huckabee, sadly, did not fare well at all with a -100.
Politics and hair aside, the Crosstab analysis is a handy tool for cutting through social media clutter to quickly and clearly identify key themes and see how your brand or product stacks up against those of your competitors. Similar to Excel pivot tables, the Crosstab lets you set up a two-dimensional comparison of multiple topics against multiple themes to look at mention counts, net sentiment, passion intensity, and other metrics. With the help of additional filters, you can extend the analysis to three or more dimensions and drill down even further.
The Crosstab provides vital information for your marketing strategy. It can tell you a lot about who might be interested in your product or idea, segmenting data by location, geolocation, color preference, positive or negative insight terms, or any category that might be of interest. So if you’re an automobile manufacturer and curious about how your brand compares to that of your competitors on different continents, across each quarter of last year, or on the basis of things like design, price, and innovation, you’ll find answers using the Crosstab.
Defining Themes for Crosstabs
Before you can run a Crosstab analysis on topics, you need to define themes that reflect the categories on which you want to compare. Here are some examples of how to create themes for common use cases:
- To compare topics by keyword, use the Include Terms In the 2016 Republican Presidential candidate example, I created the Employment theme by including the terms “employment,” “unemployment,” “jobs,” and other related terms, the Federal Deficit theme by including the terms “deficit,” “national debt,” and so on.
- To compare topics by geographical area, use the Include Geos For example, create theme 1 by including United States, theme 2 by including Europe, and so on.
To compare topics across time periods, create themes containing the Date Range filter. To create themes for Q1-Q4 of last year: Create theme 1 with a custom date range of January 1-March 31, 2014, theme 2 with a custom date range of April 1-June 30, 2014, and so on.
- To compare topics by insight, use the Sentiment Drivers For example, create theme 1 with a sentiment driver of Positive -> Emotions -> and specify the terms “love,” “want,” etc.
Setting Up a Crosstab
After you’ve defined themes, you can set up a crosstab in a few clicks. You simply select your topics in the analysis strip, set a date range, and click Apply…
…then use the funnel icon to add your themes. You can add up to 60 topic/theme combinations, such as 30 topics and 2 themes or 4 topics and 15 themes.
You can extend your analysis to include additional dimensions by adding more themes using the Themes global filter or adding other filters, such as Gender (which is currently not supported in themes), as well as applying different chart types. The example below looks at the Republican candidates again on the basis of mention count by female authors:
Other Crosstab Examples
The examples below provide some additional ideas for how you can use the Crosstab to drill down into your data.
This crosstab compares the Apple Watch and competitors across themes set up with Include Terms filters for battery, price, and design.
This chart compares post counts for positive/negative emotions and behaviors for five airline companies:
This example compares passion intensity for four retailers on the basis of five languages (the topics have a Language filter value of All Languages). Each theme uses the Include Language filter to include a different language.
The example below compares net sentiment for four fast food companies based on five different source types. Each theme uses the Sources filter to specify a single source type.
The following example compares potential impressions for the six top authors posting about the #SocialListening hashtag. Each theme uses the Include Authors filter to include a top author.
Top image from Bobbi Vie