Time Series: NUVI’s newest groundbreaking feature.
We often get the question, “How can our brand’s social identity have any impact on actual day-to-day business in real life?” Many people see social media as simply a place to talk about cats and post pictures of the food you eat and the mess your kids make. They don’t see any correlation between something as simple as
140 280 characters in a tweet and their stocks and profit margins. Those of us in “the biz” are often surprised at this mentality because it seems like there is an overwhelming amount of evidence proving that social feedback can have an absurd influence on any brand or company *cough United Airlines.
Take the stock market for example. An extremely volatile, petty mistress that reacts to social sentiment, causing companies to potentially lose millions of dollars.
Just ask Snap.
While there is some disagreement (causation and correlation) as to whether or not a tweet from one of the Jenners sent the tech company into a downward spiral costing them $1.3 BILLION in lost stock, there is no disputing the power a major influencer can have on a brand’s bottom line.
Time Series Data
But how do you quantify that data? How do you accurately measure and analyze the correlation between something that happens on social media and the effect on your company? With Time Series, a brand-new premium feature of NUVI’s Monitors Enterprise, you can overlay any numerical data over time on top of your social mentions to get an accurate picture of influence. Going back to our previous example of the stock market, let’s take a look at Facebook’s most recent “faux pas” ( I googled it, it’s right) to see how the #deletefacebook campaign affected their stock prices.
In the screenshot above, you can clearly see the yellow line representing Facebook’s value on NASDAQ. It is easy to see when their stock prices plummeted like the walls of the Grand Canyon and you can also easily see when the social mentions with #deletefacebook began to spike thanks to WhatsApp founder and later Elon Musk. In this example, we can surmise that Facebook’s stock prices were directly impacted by the conversation calling for users to delete their accounts.
With this feature, decision makers no longer have to speculate as to whether or not a specific campaign was successful. If you are running a promotion on running shoes, you could take your sales data from the time of the promotion and overlay it on top of your social data to see if the money you spent advertising on social media resulted in an increase in sales. Here are just a few use cases where the Time Series feature provides additional insights.
Many brands are shifting their marketing priorities to leverage influencers but struggle to prove ROI. While Time Series won’t replace a full-blown data scientist, it will give you more granularity than you would’ve had otherwise. Let me explain. Let’s say you hire an influencer to promote your brand over the course of 4 months and give them specific URL’s and promo codes so you can track each specific sale that came in due to their social posts and interactions. You can then create a segment within Monitors Enterprise that isolates and analyzes all the posts, reach, spread, and interactions of each influencer. From there you can take your sales from that same time period and overlay it on top of your social data, giving you two very distinct visualizations. This will help you to see whether your influencer’s post had any impact on sales.
As you track specific mentions from influencers to monitor reach and spread, you no longer have to judge success simply by the number of shares, but can accurately attribute sales to specific posts and individual influencers.
Beyond retail, there are many use cases where a tool this powerful can provide invaluable insights. Within the wonderful world of sports, for example, it would give teams the ability to view how fan sentiment on social media corresponds to ticket sales over time. In another use case, the NFL could take Twitter data from the #takeaknee #boycottnfl campaigns (remember when that was a thing?) and then overlay ticket sales, advertising revenue, and viewership to get an accurate picture of whether people were actually changing spending habits.
In the gaming industry, it is important to understand the factors that influence gameplay both within the game itself as well as in the “real world.” With Time Series, a gaming company could take their gameplay data and compare it to their social data to see what people are saying about the game and look for patterns in conversation spikes and gameplay. In the case of sentiment, the gaming company might see a sudden spike in negative mentions that correlate to a drop off in gamers. This would let them know if there was an issue with the server or some other factor impacting user experience.
While there are many industry-specific use cases we could talk about, suffice to say we believe this groundbreaking tool will give businesses a completely different angle from which to analyze their data. As we’ve seen from multiple examples, “the times they are a changin” and social interactions have the power to impact brands large and small. One thing to keep in mind (here comes our obligatory disclaimer) is that we are not saying social media was the sole factor in Facebook’s epic decline. That probably had something to do with bad choices and a broken moral compass. But we are saying that social is not only an excellent measuring stick for public opinion but also an incredibly powerful platform for influencing perception, which in turn affects how/where people spend their money.
Want to more about our new Time Series feature or NUVI in general? Request a demo and a NUVI pro will be happy to answer all your questions.