October was a massive month for video game sales with three of the biggest titles of 2018 dropped over the course of a few weeks. With Bethesda’s Fallout 76 launching in mid-November can we expect another weekend blockbuster and maybe even another record setting sales figure? Let’s see what the data says.
For context we should look back at 2018 to this point. Early in the year Ubisoft’s Far Cry 5 (released in March) was touted as having the biggest opening weekend of the year at around $310 million dollars in retail sales until another of Ubisoft’s hit series, Assassin’s Creed Odyssey, reported record breaking weekend sales in early October. Ubisoft hasn’t published sales figures for this title, so we will have to assume the dollar amount exceeds $310 million.
We don’t have to assume when we are talking about the next blockbuster game of October, Call of Duty: Black Ops 4. Activision reports that they pulled in over $500 million during its three-day launch weekend.
While that sounds like a ridiculous figure to beat, Rockstar Games did that just two weeks later with Red Dead Redemption 2. The smash hit of 2018 (so far) pulled in over $725 million during its launch weekend. That is a massive number and falls just behind Rockstar’s own Grand Theft Auto V ($800M) and Bethesda’s Fallout 4 ($750M) which earned their record numbers in their first 24 hours following launch.
In order for publishers to make that kind of money, video games must be crossing the line between cult fandom towards mainstream popularity, similarly to what we’ve seen with feature films. At Networked Insights, we have been using social conversation to predict box office success for years, but now we are turning to consumers to see what we can expect in the video game world.
If we look at the conversation volume of the three games above that launched in October, we see a total of over a million consumer conversations in the thirty days prior to their respective launches. The share of volume of those three looks like this:
Assassin’s Creed Odyssey: 19%
Call of Duty: Black Ops 4: 35%
Red Dead Redemption 2: 46%
When we took a look at their record weekend sales figures and calculate a similar share of volume, we see the following:
Assassin’s Creed Odyssey: 21%
Call of Duty: Black Ops 4: 32%
Red Dead Redemption 2: 47%
The similarity in their ratios can be very telling and is comparable to what we’ve learned from the world of film. Consumer conversation prior to launch can be a useful indicator of potential sales success and an excellent way to benchmark the progress of a campaign.
Now let’s look at what we can expect with Fallout 76 launching on November 14th. In the 30 days leading up to its launch this particular title has 63% more conversation volume than Red Dead Redemption 2.
63% more than $725 million would certainly be a record-breaking figure. Now, we can’t be sure that these figures will translate to a billion-plus dollar weekend but it’s a strong indicator of consumer interest and consumer interest often equals consumer dollars.
Fallout does have to contend with a Wednesday release date compared to the above titles which launched on a Friday, but it is interesting to note that the $750 million dollar 24-hour launch of Fallout 4 happened on a Tuesday.
As video games start to surpass all other entertainment titles as the most valuable of all time, it will be interesting to see if consumer interest has more room to grow.
Love, happiness, and desire might feel like natural emotions to associate with candy, but what about ‘success’, ‘remorse’, ‘amusement’ and ‘relief’? Using powerful AI to interpret what we say online, Networked Insights has spent the last decade perfecting its picture of how language translates to emotions, and how those strong emotions translate to actions, in this case, candy consumption!
By factoring in the volume and intensity of 38 emotions, we ranked how the nation really feels, state by state. And, well, as we might expect, emotions always reveal some very real curveballs!
Illinois is the most representative of the nation’s overall feelings ranking Snickers in the top spot, followed by Skittles and then Sour Patch Kids.
But Utah gets the warm and fuzzies for Ghirardelli, Minnesota just can’t show enough how much it loves Sweet Tarts, Montana is all about the Grandparent’s favorite, Werther’s Original, and Arkansas must be watching its figure with its passion for…. 5 Gum!
What does your state love? Check our complete ranking….
Alabama — (1st) Reese’s (2nd) Twix (3rd) Kit Kat
Alaska — (1st) Snickers (2nd) Sour Patch Kids (3rd) Twix
Arizona — (1st) Skittles (2nd) Sour Patch Kids (3rd) Big Red
Arkansas — (1st) Twizzlers (2nd) Skittles (3rd) 5 Gum
California — (1st) Air Heads (2nd) Twizzlers (3rd) Sour Patch Kids
Colorado — (1st) Skittles (2nd) Snickers (3rd) Twix
Connecticut — (1st) Almond Joy (2nd) Twizzlers (3rd) Smarties
Delaware — (1st) Reese’s (2nd) Twizzlers (3rd) Snickers
Florida — (1st) Twix (2nd) Skittles (3rd) Jolly Rancher
Georgia —(1st) Skittles (2nd) Twix (3rd) Twizzlers
Hawaii — (1st) Kit Kat (2nd) Sour Patch Kids (3rd) Big Red
Idaho — (1st) Butterfinger (2nd) Hershey’s (3rd) Red Vines
Illinois — (1st) Snickers (2nd) Skittles (3rd) Sour Patch Kids
Indiana — (1st) Reese’s (2nd) Hershey’s (3rd) Twix
Iowa — (1st) Baby Ruth (2nd) Kit Kat (3rd) Snickers
Kansas —(1st) Jolly Rancher (2nd) Sour Patch Kids (3rd) Skittles
Kentucky — (1st) Swedish Fish (2nd) Skittles (3rd) Sour Patch Kids
Louisiana — (1st) Airheads (2nd) Skittles (3rd) Smarties
Maine — (1st) Red Vines (2nd) Starburst (3rd) Twizzlers
Maryland — (1st) Reese’s (2nd) Swedish Fish (3rd) Skittles
Massachusetts — (1st) Hershey’s (2nd) Reese’s (3rd) Snickers
Michigan — (1st) Starburst (2nd) Skittles (3rd) Twizzlers
Minnesota —(1st) Tarts (2nd) Tootsie Pops (3rd) Starburst
Mississippi — (1st) Snickers (2nd) Skittles (3rd) Starburst
Missouri — (1st ) Hershey’s (2nd) Twix (3rd) Reese’s
Montana —(1st ) Kit Kat (2nd) Werther’s Original (3rd) Jolly Rancher
Nebraska — (1st) Hershey’s (2nd) Reese’s (3rd) Snickers
Nevada — (1st) Skittles (2nd) Jolly Ranchers (3rd) Smarties
New Hampshire — (1st) Butterfinger (2nd) Snickers (3rd) Milky Way
New Jersey — (1st) Snickers (2nd) Hershey’s (3rd) Reese’s
New Mexico — (1st) Snickers (2nd) Twix (3rd) Kit Kat
New York — (1st) Sour Patch Kids (2nd) Snickers (3rd) Skittles
North Carolina — (1st) M&Ms (2nd) Snickers (3rd) Reese’s
North Dakota — (1st) Skittles (2nd) Starburst (3rd) M&Ms
Ohio — (1st) Airheads (2nd) Skittles (3rd) Smarties
Oklahoma — (1st) Skittles (2nd) Twix (3rd) Kit Kat
Oregon — (1st) M&Ms (2nd) Reese’s (3rd) Snickers
Pennsylvania — (1st) Twizzlers (2nd) Kit Kat (3rd) Jolly Rancher
Rhode Island — (1st) Butterfinger (2nd) Hershey’s (3rd) Twix
South Carolina — (1st) Kit Kat (2nd) Hershey’s (3rd) M&Ms
South Dakota — (1st) Tootsie Pops (2nd) Andes (3rd) Snickers
Tennessee — (1st) Twix (2nd) Snickers (3rd) Reese’s
Texas —(1st) Sour Patch Kids (2nd) Skittles (3rd) Jolly Rancher
Utah — (1st) Skittles (2nd) Snickers (3rd) Ghirardelli
Vermont — (1st) Starburst (2nd) Skittles (3rd) Jolly Rancher
Virginia — (1st) Reese’s (2nd) Hershey’s (3rd) Kit Kat
Washington — (1st) Sour Patch Kids (2nd) Skittles (3rd) Snickers
West Virginia — (1st) Snickers (2nd) Sour Patch Kids (3rd) Smarties
Wisconsin — (1st) Snickers (2nd) Reese’s (3rd) Skittles
Wyoming — (1st) Kit Kat (2nd) Jolly Ranchers (3rd) Reese’s
Learn more about using emotions to help your brand conduct audience research or find new segments of audiences for targeting: Why We All Need A “LOVE / HATE” Relationship With Targeting Data)
Strong emotions lead to strong actions, making emotional analysis an intriguing capability in digital marketing.
In the run-up to the 2016 Presidential election, like most good data companies, Networked Insights wanted to make a prediction on the outcome to demonstrate their capability. And just like other tech companies (and the pollsters as it turned out!), they were getting readings that jumped back and forth by the hour. It was too close to call and the data was very inconsistent.
Networked Insights specific capability in this area is conversational data analysis. Simply put, that means they look at what is said online from which they can determine the intent, emotions, and sentiments behind those statements. When you have an election that is particularly useful because what someone writes is akin to an unprompted confession — unlike the pollsters who have to ask the question ‘who are you voting for’, Networked Insights learns it without asking, therefore getting a more honest insight.
Still, though, 6 weeks to go, the data would not reveal who the ultimate winner was going to be — until the data science team hit on a fascinating idea — to look at negative emotions, not positive. Whilst the LIKEABILITY and LOVE to both Clinton and Trump were too similar to make accurate predictions from, the strength of DISLIKE and HATE was polarizing, and 6 weeks out from election day, they were later proven to have accurately called 49 out of 50 states.
For marketers, strong emotions as a signal of intent might just be the next big thing, and for us marketers, the good news is that there is a crazy amount of emotion projected online, and therefore scaleable data for most targeting criteria.
It’s surprising to me that in 2018 brands and agencies are still forced to work with targeting data that has no real science behind it — ‘auto intender’ segments are often based on one visit to a car auction site, or ‘home buyers’ from being tagged on a property site, even if they are just looking at the value of their own home.
With emotions, we have a much more immediate message.
“I HATE MY CABLE” signals that competing Cable companies and streaming services should be engaging that individual.
“I AM GOING TO GET A BIGGER PLACE” should get realtors, furnishing stores and mortgage advisors frothing at the mouth.
So far Networked Insights (under the umbrella of audience.ai) has been able to match emotions to a wide range of intents. Once a need is identified the data science team will produce customized segments, and upload them to the DMP or DSP of your choice for easy activation.
Every one of you reading this that runs digital marketing programs has a data need that has gone unmet. Try them. The team is very consultative and available on email@example.com.
Whether they want to or not, some of the world’s biggest brands have recently stumbled into politically charged social conversations.
Our audience.ai research report takes a look at the data behind the brand boycott hype, using millions of online conversations, classified 25,000 ways across 50 different emotions to gather an accurate, holistic view of the issue.
Why? We’re so busy telling consumers that they should be interested in our brands that we’re not paying enough attention to who they are and what they already naturally care about.
Customers are complex, and in order to succeed, brands need to better understand them as people – embracing analytics to better understand their affinities, emotions, and what drives their behavior, so that they can create more relevant and effective content.
Download our Guide to Audience Building to find out more.
audience.ai research found that people going through pivotal life events like graduation, marriage or starting families are more likely to have similar interests and affinities than those in similar demographic targeting groups based on age, gender or income.
For the study, audience.ai examined millions of conversations through the lens of five significant life stages to understand how audience interests, conversations and brand preference differ from life stage to life stage.
Check out what we discovered, like how recent graduates differ from retirees in the media they consume or how new parents differ from affluent professionals in the brands they love or why millennials and retirees may have more in common than expected.
In 2016, businesses wasted $347 billion globally on marketing campaigns because they simply did not work. How is that possible? Their campaigns were not relevant. Why? They didn’t capitalize on technologies that achieve personalization at scale. More than simply surviving, brands and agencies must be relevant to their customers. When compared to cookies or demographic targeting, combining artificial intelligence with public conversational data offers marketers a deeper data set and a more holistic view of their audience, which means better targeting.