Text is an integral part of our social media experience. Through text, we communicate and share thoughts with our community. There are two main forms: dynamic and static text. Dynamic is real-time content that is shared by users in short form mediums (comments, tweets, reviews). Meanwhile, static text is long-form content often found in blogs and email communication. Both of these forms offer valuable information about user sentiment, current trends, audience intention, and interests.
Social media text analytics is a technique that analyzes “hidden business insights from textual elements in social media content.” Since there is so much text on social it is important to be very strategic in your search. This week, I used Sprout Social to conduct a Twitter keyword analysis. Since I have a large interest in entertainment marketing, I decided to focus on a specific film to observe the community’s behavior throughout the campaign. The movie I focused on is Pixar’s Lightyear, which was released this summer.
I chose five keywords that help define the film and were likely to be brought up when audiences were discussing their thoughts. The keywords are Chris Evans, Lightyear, Pixar, Sox, and Toy Story. After choosing the words, Spout provided three main reports.
Keyword Volume
The first is the keyword volume, which demonstrates through graphs how often the keywords were used on Twitter over a year. This graph was extremely helpful because it demonstrated clear spikes when the film was talked about most. The largest spike occurred in June, which is when the film was released in theaters. The keyword that performed the best that month is Lightyear. This is understandable because it is the title of the movie, plus it is the name of the protagonist. The large spike demonstrates that the marketing campaign picked up during June in hopes of driving audiences to the theater.
The next highest keyword of that month was Chris Evans. Evans voices Lightyear and is a very popular actor with over 16 million followers on Twitter. I recall him trending following the movie’s red carpet premiere, his trip to Disneyland, and the release of the film. His popularity showcases that content that highlights the cast is likely to perform well.
The third best-performing keyword in June was Sox. This is a robot cat character in the film that acts as Buzz Lightyear’s sidekick. This character provides comedic relief and was well loved by audiences. Unlike the previous keywords, Sox remained popular from March to August rather than spiking only in June. Therefore, audiences maintained their excitement about Sox making content about him a strong contender for sustained posting.
Pixar was the fourth most popular during this month, but it did have a large spike earlier in the year in February and March which was when the trailer dropped. This leads me to infer that audiences were sharing their thoughts on this movie being Pixar’s first movie back in theaters. Since not much knowledge was known about the film, Pixar’s brand identity was its largest selling point.
Finally, Toy Story was mentioned the least. Even though Lightyear served as an origin story for the franchise, the lack of Toy Story references likely led to it being mentioned the least. This demonstrates a slight flaw in the marketing since it failed to enamor the Toy Story fans.
Share of Volume
The next graphic Sprout Social provides is the share of volume for each keyword. This refers to how much of the total volume each keyword takes up. Throughout the campaign, Sox was mentioned the most, taking up 28% of the volume. Although it didn’t spike in popularity like the other words, the character remained a consistent topic of conversation. The second most talked about overall was Pixar. Pixar is home to many popular family films, therefore its mentions may be due to both Lightyear and its past titles. Lightyear and Chris Evans take up very similar amounts of volume which is likely because conversations spiked when the trailer and film were released rather than year-round. Toy Story was the lowest at 10% which shows that connections between the films weren’t enough to start conversations.
Stats by Keyword
The final analytics that is provided is stats by Keyword. These provide the average tweets per day, the total volume, and the growth trend. Lightyear at a 400% increase in growth demonstrates that the campaign successfully informed audiences about the film. All the other increases make sense as conversations would grow as information about the film was released. The only keyword that decreased is Pixar which could be attributed to the fact that Lightyear wasn’t as popular as past Pixar films have been, such as Turning Red and Luca.
Overall, the information provided by Sprout Social was very beneficial in deciphering audience interest and trends. When compared with marketing campaign major events, it demonstrates which initiatives successfully got audiences talking. Plus, the share of voice demonstrates the elements of the movie that fans talked about the most. Based on the insights, I would focus on highlighting Sox and cast content rather than focusing on the ties to past Pixar franchises.
Sources
Khan, Gohar F.. Creating Value With Social Media Analytics: Managing, Aligning, and Mining Social Media Text, Networks, Actions, Location, Aps, Hyperlinks, Multimedia, & Search Engines Data (p. 130). CreateSpace Independent Publishing Platform. Kindle Edition.
Zote, Jacqueline. “Twitter Analytics: How to Analyze and Improve Your Twitter Marketing.” Sprout Social, 15 Sept. 2022, https://sproutsocial.com/insights/twitter-analytics/.