On days like this predictions abound. And most often those predictions come from the pundits, the ones “in the know.” But what if the real power of prediction is not in the opinions and the bias of pundits but in the data?
One the most amazing things about the internet is its ability to quickly determine the sentiment of large populations just by listening to what people are talking about. Of course, listening is nothing new. Anyone building a successful business will tell you that the single most important skill to develop and info into a culture is that of listening to the customer.
What if I told you that was wrong? Anathema, right? Customers always come first! That’s only partially true. The problem with always putting the customer first is that you build an echo chamber which reports that same old biased view of what you should be doing to grow your business based on what you have been doing, while growth comes not only from customer but from those who are not yet customers.
Companies often try desperately to hang onto customers when their overall business is shrinking and suffering, They put in place loyalty programs and incentives for customers to stay, but they are oblivious to the sentiment of the larger market which is fleeing to other alternatives. It’s like trying to give cabin upgrades to passengers of the Titanic–while it’s sinking!
Instead, what if you could listen to the entire market, current and potential, in order to direct your resources and align your decisions with where the growth was? What if you could predict the many ways in which the marketplace is changing but which no individual customer, focus group, marketing genius, or existing community of customers could adequately express?
That’s precisely the objective of social listening; to understand the collective sentiment of a marketplace based on what the data is telling your. It sounds simple but it’s amazing how few companies are doing it. Why not? Because we all want to believe that we are smarter than the market; that the data has nothing on us. Because, if it did, what would our value be?
Which brings me to the Oscars. (You knew I’d get there eventually!)
Using a listening analytics platform, Sprout Social captured data around the three major Oscar categories of best picture, best actor in a leading role, and best actress in a leading role in order to project tonight’s Oscar winners. Although this is just for fun, it’s a great illustration of how powerful social sentiment can be in understanding a market’s perspective.
In each category they scoured the web for the number of mentions and the positive versus negative mentions. The results are in some cases straight forward and in others fascinatingly close.
For example, the data shows that Call Me By Your Name is the projected winner among fans, garnering 152,880 total mentions, 64,758 positive mentions, 18,095 negative mentions and 46,663 net positive mentions (that’s the number of positive mentions less the negative mentions.) The Shape of Water and Lady Bird follow close behind with 48,039 and 34,268 positive mentions respectively. However, Dunkirk had more total mentions than Lady Bird, but just about 7,000 fewer net positive mentions. Although Get Out had more net positive mentions than Dunkirk!
None of that is likely to usurp Call Me by Your name, but from a marketing standpoint it provides insight into how close sentiment is about movies that may not be getting an Oscar but are none-the-less neck and neck in terms of popularity.
Even more fascinating is the ridiculously close net positive ratings for the category of Best Actress in a Leading Role as compared to the category of Best Actor in a Leading Role. Make your own inferences here but the bifurcation of opinions is at the very least a fascinating look at how polarized sentiment can become.
| Best Motion Picture | TOTAL MENTIONS | POSITIVE MENTIONS | NEGATIVE MENTIONS | NET POSITIVE MENTIONS |
| Call Me By Your Name | 152,880 | 64,758 | 18,095 | 46,663 |
| The Shape of Water | 115,578 | 48,039 | 12,304 | 35,735 |
| Lady Bird | 64,063 | 34,268 | 7,249 | 27,019 |
| Dunkirk | 73,586 | 33,085 | 12,988 | 20,097 |
| Get Out | 56,196 | 32,136 | 9,802 | 22,334 |
| Best Actor in a Leading Role | ||||
| Daniel Kaluuya (Get Out) | 89,552 | 37,152 | 4,698 | 32,454 |
| Timothée Chalamet (Call Me by Your Name) | 28,527 | 16,405 | 1,785 | 14,620 |
| Gary Oldman (Darkest Hour) | 15,057 | 8,337 | 2,573 | 5,764 |
| Best Actress in a Leading Role | ||||
| Margot Robbie (I, Tonya) | 2,007 | 593 | 589 | 4 |
| Meryl Streep (The Post) | 549 | 196 | 183 | 13 |
| Saoirse Ronan (Lady Bird) | 404 | 188 | 34 | 154 |
| Frances McDormand (Three Billboards) | 202 | 81 | 22 | 59 |
| Sally Hawkins (The Shape of Water) | 131 | 70 | 15 | 55 |
*Data provide by Sprout Social
So, will the data foretell tonight’s winners? The practical side of this specific scenario is that the 6,000 members of the Academy of Motion Pictures and Sciences who vote on the Oscars can do whatever they want, regardless of what the data says. Are they likely to reflect the broader demographic captured in the table above? Probably, but not necessarily.
Whatever the case, we are at a point when we need to spend more time listening to the data and less time in our echo chambers.