The Super Bowl and You: What to do with all that new data?

This year, an estimated 123.7 million people watched the Super Bowl. 120 million of those viewers watched the broadcast on CBS, making it the biggest audience for a single network live telecast ever. And for only the second time in history, the game went into overtime. All that, plus the flurry of social media engagement that happens during the game, means that advertisers will (hopefully) get a truck-load of engagement – and with that engagement comes a truck-load of data. 

Chances are, your data infrastructure is designed to handle the amount of data you’re collecting and moving regularly. This makes sense – why pay for a massive U-Haul when you’re just moving a desk? And on a day-to-day basis, that’s how it should be. 

But high-traffic events like the Super Bowl, a concert announcement, or a ticket release can easily break a system. Here are some ways to handle massive influxes of data gracefully, efficiently, and effectively:

1. Know that the data deluge is coming

As both Benjamin Franklin and your high school math teacher have (probably) said, an ounce of prevention is worth a pound of cure.

The most important way to keep your system intact is to make sure you’re prepared to handle any predictable data influx, and you know what’s coming

It’s easy to find out when the Super Bowl is coming, or when high-demand concert tickets will be released to the public. Making sure your data team is apprised of marketing campaigns or product drops that will result in a lot of traffic is an important part of keeping things running smoothly.

2. Design a scalable infrastructure (and know how scalable it is)

To address the U-Haul Problem and keep from paying for a giant data warehouse you don’t normally need, your system needs to be flexible.
Fortunately, this is now much easier to do than it was ten years ago. We’re in a golden age of cloud-based infrastructure, and it’s far more possible to create systems that can adjust to fit changes in data flow.

The next step, though, is to have an understanding of how “stretchy” your system is in practice. When figuring out how stretchy your infrastructure needs to be, you can ask questions like:

  • If we get an enormous amount of data very quickly, will we be able to handle it?
  • Will we be able to scale our system on the fly?
  • How much space can we add, and how quickly can we add it?

Understanding the capacity and capabilities of your system is key to keeping you afloat when a data flood comes.

3. Understand why you’re collecting data in the first place

When big data events happen, a common impulse is to collect as much data as possible, and figure out how to use it later. After all, it’s better to have too much than too little, right?

But if you don’t have a plan for the data you’re collecting, you may end up with a giant pile of information that will be incredibly daunting (and maybe even expensive) to sift through. And it may be so massive that it’s not possible to do much with it at all. 

Instead of coming up with a plan retroactively, know what information you want and what you plan to do with it before any big data event. This will allow you to be more thoughtful about your data pipeline, and any data points you want to flag. Being strategic about what you collect in the first place will ensure that you’ll get the most out of your data.  

4. Figure out where your new data is going to go

Once you’ve come up with a strategy for your data, you might discover that it won’t get along with your existing database. Maybe it’s not categorized in the same way, or maybe you want to use it very differently.

Rather than dumping new data into the same system, it’s important to figure out whether it will play nice with your old data. You may be able to incorporate it directly, but you also may need to create something new to accommodate it. 

5. Make sure everyone understands your shiny new data

You’ve built a data collection strategy, decided how you’re going to store it, and you’re ready to dig in. The next question is – will your analysts understand it?

Especially if you’ve created a whole new system, or you’ve collected a ton of data from an unexpected event, your analysts need to be able to recognize patterns and spot outliers.

This can be done by carefully organizing what you collect, or by using a program like Pickaxe MIX that’s designed to analyze unique events within the historical context of your other data. However you do it, ensuring that analysts have what they need to process this new information is key to making it useful.

6. Know how you’re going to relate to the new people you’ve engaged

You’ve suddenly gotten a bunch of publicity, and a ton of new people have signed up for your service or are engaging with your communication channels. How are you going to make sure new subscribers stay interested after that initial publicity bump has faded? 

For example: say you’re a subscription-based service that sends beauty boxes with select makeup products to subscribers. An intern on your social media team makes a hilarious tweet about Travis Kelce that goes viral, and a ton of people visit your site and sign up for your newsletter. If you send those people your usual messaging about lip gloss, they might be completely uninterested, and churn quickly. 

Coming up with an alternate plan for content is a way to ensure that this new cohort sticks around longer than they would have otherwise. For example, instead of pushing the lip gloss, you might offer a promotion on gift subscriptions, and encourage new followers to buy a few months of the service for the makeup wearers in their lives. (And if that engagement happens during the Super Bowl, you may even make it a Valentine’s Day deal.)

7. Have a plan for the unexpected

This year, when the Super Bowl went into overtime, the amount of views and engagement that advertisers received increased significantly. Only one other Super Bowl has ever gone to overtime, so even though it was somewhat predictable, it’s definitely a unique event.

Even if you’ve got every other precaution mentioned above in place, truly unpredictable bumps will happen. Maybe a tweet goes viral, or one of your products becomes part of a TikTok trend – events like that might lead to a sudden spike in engagement that your team will have to handle without warning.

Your system needs to be able to adjust to handle the unexpected. Maybe that’s ensuring scalability, thinking through contingency plans, or having a series of gameplans ready to go. 
High-traffic events like the Super Bowl can easily break a system. Here are some ways to handle massive influxes of data efficiently, and effectively.

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