What is your company’s legacy? Can you quantify it, predict it, or use it? Is your understanding of your legacy the same as your customer’s? By utilizing data and technology, these questions are quickly answered and turned into powerful tools for your business. For an example of how to explore your legacy and understand how it impacts your business today, enter Arnold Schwarzenegger.
“Stick Around”
Throughout the 1980s and 1990s, Arnold was one of the most recognizable action heroes in film, starring in now classic movies such as Terminator (1 and 2), Predator and Total Recall. By using automated web crawling and APIs, Arnold Schwarzenegger’s movie legacy can be quantified through aggregated scores like those found on RottenTomatoes.com, IMDB.com, and MetaCritic.com, as well as through qualitative sources such as movie reviews. Each movie is given a “legacy score,” and attributes of these movies are assigned this score.
By itself this is a powerful tool that can be used to gauge consumer’s opinions of your business, decisions, or products, but can this knowledge also be used to understand how customer perspectives influence decisions you might make in the future or products you should develop?
“I’ll Be Back”
In an effort to understand the effect that Arnold’s existing legacy had on his current standing in the public eye, the same technology used above for his old movies was applied to his most recent movie, The Last Stand. To create a connection from the past to the present, movie reviews for The Last Stand were scanned for attributes of old movies (for example, “T-1000” for the movie, Terminator). After a match was found to exist, the sentiment of the current review was compared to the average sentiment score of the movies being referenced; if The Last Stand review referenced John Connor, aliens and Danny DeVito, the legacy scores of Terminator 2, Predator, and Twins were averaged, then compared to the sentiment score of The Last Stand review.
Your results, give them to me, now.
A statistically significant, positive relationship was found to exist between the aggregate legacy scores of the movies being referenced to the movie review of The Last Stand. The higher the legacy scores of the movies being referenced, the higher the movie review score for The Last Stand. Additionally, a significant relationship was found to exist between the number of times previous movies were referenced to the sentiment of the movie review. The more times a previous movie was referenced, the lower the movie review for The Last Stand.
I eat big data for breakfast.
This type of data modeling can be predictively used in conjunction with marketing efforts. For new movies, messaging and creative can be tested calling to mind some of Arnold’s most well received movies in an attempt to create a connection between those movies and his new one.
Now, imagine ways in which your own business can use this information and process. Say, for example, you are planning on launching a new product in the next 18 months. Previous product launches for you and your competitors can be examined to determine not only how they were perceived then, but also how those products and marketing efforts continue to affect opinions about your business today. Attributes that had
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