Big Data and Social Media Help NASCAR Lap the Competition

In 2009, NASCAR was in an unenviable spot. The economic recession, a changing media landscape and several other factors crashed down simultaneously on the racing company. “Rising fuel prices hit our fans badly,” explained Sean Daugherty, the company’s Director of Digital and Social Media Engagement. “Our fans travel more than 100 miles on average to attend our races, so increases in fuel prices have a direct impact on race attendance.”

This is how Daugherty opened his portion of a recent webinar titled How NASCAR is Using Social Media to Deliver a Dynamic and Engaging Fan Experience. The presentation was held in collaboration with HP, the company’s partner for much of the hardware and software its Marketing Communications department uses today.

Fast forward to 2014, and NASCAR is in a much better position. Race viewership is at an all-time high, the largest media deal in the sport’s history is in place through 2024, and pillar partner companies are renewing to long term agreements. So what happened? According to Daugherty: unprecedented research, a large investment in technology and a dedication to using live data and social media to offer fans a more engaging experience. Here’s a behind-the-scenes look at how the company is doing just that.

Fan and Media Engagement Center

Fan and Media Engagement Center

NASCAR has developed a technology “headquarters” unlike anything else in sports or entertainment. Unveiled in Charlotte, the Fan and Media Engagement Center is a 500-square foot room with several 46” HD screens and three workstations. This hardware, and the HP “analytics engine” that supports it, allow the company to track and better understand the conversations trending across social, traditional and broadcast media that impact their industry. They then leverage that information to provide live updates to the team on the ground during each race and distribute detailed and customized analytic reports to key stakeholders after the checkered flag waves. These groups include its teams, tracks and partners.

Nascar Big Data

Live Interaction and Engagement

Just as important as their impressive infrastructure and software are the creative ways NASCAR uses its gained insights to drive an engaging, memorable experience for fans and viewers. During all races in NASCAR’s 3 national series, the Fan and Media Engagement Center is bustling. A team watches a live broadcast of the race and engages fans by answering questions and live tweeting from the official NASCAR social media handles. They keep an eye on live trending topics and fan sentiment during the race, dive deeper into topics that gain traction and relay insights to teams and drivers’ social media managers so they can live tweet and post on Facebook more effectively throughout and after each race.

Where the Rubber Meets the Road

Another impressive benefit of harnessing real-time clustered data is the ability to recognize when mistakes are made or negative comments are being shared. For example, during their most recent All-Star race, which is an exhibition race where drivers are re-ordered based upon fan voting and fan rules, a broadcast graphic was aired displaying the driver order incorrectly. “Even though the cars were in the correct running order on the track, it seemed like the wrong driver ended up winning the race,” recalled Daugherty.

Fans reacted negatively and reporters portrayed it as a big deal saying NASCAR had a firestorm on its hands. “Well we went back and analyzed the data and found that the issue was only 3 percent of the overall conversation around the race at that time,” Daugherty shared. “So, what the media portrayed as a firestorm was really just a blip on the radar and in an instance where we may have continued to issue a statement and extend that news cycle, we were able to, in this case…take no action and not extend that news cycle and let our broadcast partner handle that response.”

How Can Your Company Reap Similar Benefits?

Data collection, analytics and social media are driving value for companies across all industries and specialties, not just motorsports racing. If you’re interested in learning how the proper mix of marketing, analytics and cloud solution services can help your company win big, spend a few minutes browsing our website or contact us directly to discuss your unique business model and requirements.

The Necessary Evil of Targeted Ads and How to Eliminate Them

Targeted ads are simply the cost of doing business on the Web. It takes billions of dollars to build and maintain sites like Google and Facebook, and we don’t pay anything to use them. Parting with some private information and agreeing to tolerate some ads is our end of the bargain.

The industry of collecting, aggregating and brokering personal data is known as “database marketing.” The second-largest company in this field, Acxiom, has 23,000 computer servers that process more than 50 trillion data transactions per year, according to The New York Times. It claims to have records on hundreds of millions of Americans, including 1.1 billion browser cookies, 200 million mobile profiles and an average of 1,500 pieces of data per consumer.

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Even with all the information that is gathered, some companies still make mistakes and haven’t polished their marketing techniques.  

Farhad Manjoo of Slate shares some examples of poorly targeted campaigns from his coworkers. One colleague, he mentions, was stalked for weeks by Warby Parker, a spectacle retailer after he’d ordered a try-on pair. Another coworker purchased a couple of bras from Soma Intimates using her home computer. Then, back at her work, Soma began peppering her with ads showing half-naked women to anyone who happened by her desk.

My co-worker Adam recently looked up a pair of Asics sneakers for himself and was targeted repeatedly by ads at work. If these companies spent a little more time and energy on learning about who they are targeting their ads to, they would realize that even though showing the ad to Adam during work hours keeps it in his mind, he would not be buying the shoes at that time.

This particular marketing tactic is called “remarketing.”

The theory is that once you’ve visited a certain company’s site but failed to buy anything, you’ve expressed enough interest to make you a target for more ads. You’re the one who got away and if the company is persistent enough, maybe they can get you back!

Capture

Omar Al-Hajjar, Indochino’s ad manager, told the e-commerce news site GetElastic that every time his firm increases the amount of ads it shows to people who have visited the site, its traffic and sales go up. “Users don’t seem to mind,” he said.

If you don’t like being targeted by these ads, there is a simple fix. You can install several different ad blockers onto your computer. See if your browser has ad-block extensions. Google Chrome has AdBlock and Facebook Customizer (by Adblock Plus) so you can remove all the annoying ads. Sites like Disconnect.Me are a fast and easy approach to searching privately using your favorite search engine.

Tell us about your experience with persistent ads. Do you feel like they are following you wherever you go? How have you dealt with them? Let me know in the comments below!

Math is Becoming Your Biggest Ally in Online Campaigns

When I was in the third grade, I cheated on my 7’s multiplication tables (sorry, mom and dad) and I’ve been cursed ever since with the inability to succeed in math. That same year, I achieved something slightly more noble and had a short story published in a children’s magazine. It was then that I realized I would manifest my destiny through creative writing rather than spend my life crunching numbers and manipulating equations. And yet here I am, about to justify the relevance of math and how it is molding my industry I work in.

Algorithms in Simple Terms

Kevin Slavin, an assistant professor and founder of Playful Systems at MIT Media Lab, said in his 2011 TED Talk that algorithms “acquire the sensibility of truth because they repeat over and over again, and they ossify and calcify, and they become real.” In layman’s terms, an algorithm is a mathematical code that is entered into a computer program by computer scientists that obtains “big data” from you, me and any other stranger on this Earth online.

KEvin Slavin

Breaking Down “Big Data”

Big data can be defined back to 2001 when industry analyst Doug Laney separated it into three parts: Volume, velocity and variety.

  • Volume: Ranging from transaction-based data to data from social media that is so large it is challenging to analyze it.
  • Velocity:  The speed at which all this information is being shifted through.
  • Variety: Numeric data in traditional databases, information from applications, videos, e-mail, and beyond.

What the Pros are Doing

These three parts of big data are changing business operations for companies like Facebook, Google and Netflix because it’s aiding in better decision making. For instance, toward the end of 2013, Facebook replaced their News Feed algorithm from EdgeRank to Story Bumping. Story Bumping deciphers all the posts a specific user has seen and moves all the unread stories to the top. Netflix has their head in the cloud, literally. They are improving their online recommendation engine through “deep-learning” algorithms through Amazon’s cloud service. And can you even imagine your daily life without Google? Google computer scientists unveiled their newest search algorithm called Hummingbird that provides direct answers to complex questions.

HummingbirdHow to Use Big Data

Through all these different complex algorithms being created by, in my opinion, geniuses, big data is revealing insightful information about populations, segmented audiences and individuals. Social media account managers like myself are using this information to tailor how our brands target and nurture consumers to increase ROI.

Now here is a two part equation I can understand:

Computer scientists + Algorithms = Big Data

Big Data ÷ Analytics = Tailored campaigns for consumers that increase ROI

Want to chat about deciphering big data or school me on new and emerging algorithms? I welcome the conversation! Follow me on Twitter @whatupTUT or leave a comment below.

Marketing With Big Data

Wouldn’t it be nice if you could know exactly what your customers need before they start looking for it? That thought is now a reality with big data.

Big data is a large collection of your customers’ data (or potential customers) from both internal and external sources. This data includes digital sources such as social media, CRM and web behavior, but also includes traditional channels such as phone records, financial records and shopping habits. All of these things help you understand your customers in a unique way by analyzing their patterns and buying behaviors.

Think about big data like this. Imagine that you’re at a party and you see someone that you haven’t seen in awhile. Last time you talked, you told them about your new job promotion and that you just adopted a dog. When you run into them months later at a party, they ask you how your new job is going and inquire about your dog. This person remembered what you last spoke about and you two already have somewhat of a relationship. This concept should carry over into business, and businesses should have this same rapport with their customers.

Less than 10% of of marketers say they are currently using what data they have in a systematic way, while 71% of marketers say they plan to implement a big data analytics solution in the next two years. Why? Because you can give customers information before they even know they need it and engage with them in a personalized manner. Using big data, you’ll be able to give people the right kind of recommendations and a perfectly tailored message for where they are in the customer journey.

So how do you use big data for marketing? There are four steps to follow:

1. Listen. This step is where you monitor your customers’ social media, buying history, mobile activity and more. For example, let’s say you’re a restaurant that uses a POS system to put in orders, make reservations and take payments. Listen to the information you get from the POS system, including what your customers are ordering each night, how often they come in, what nights you sell the most wine, how much a customer is typically spending and so on. Every move your customer makes, you should be listening.

2. Gather and Analyze Data. Before you try to analyze your data, figure out what the problem is that you are trying to solve. What areas of your business need to be improved? Are you trying to predict customer behavior? Do you want to analyze your customers’ eating habits? Decide what you are trying to figure out before digging through the data. While you are bringing data together and analyzing it, understand the right message for each customer. Data analytics can be done with software tools that are commonly used for predictive analytics and data mining.

3. Assemble the Message. Now that you have analyzed your data, it’s time to transform it into a message to a target audience. Cut out all the information that you don’t need, because a lot of the data you collect won’t matter. When assembling the message, remember that you are using big data to to send a specific message to a specific group of people…this is not meant to be a message for broad demographics. This message should be used to create a meaningful interaction between the consumer and your business, so create different messages to target different audiences.

4. Deliver the Message. Once your message is targeted and put together, you have to get the message out to your target audience. Check to make sure that you have a responsive email design to deliver the correct message to someone on an iPhone versus an Android. Each message should be tailored correctly to the device being used; this is where customer segmentation comes into play. Delivering the message doesn’t only correspond to email, it can be used to help determine specials and coupons. For example, if you own a restaurant and notice that a large amount of your customers love IPA, you can “deliver the message” that you know what they want by creating an IPA special such as $3 pints of IPA on Thursdays. Whatever your message might be, you need to get it out to your target audience in the correct manner.

Use big data to stay one step ahead of your customers. Your business can start to make data-driven strategic decisions to understand your customers in a unique way and deliver a product/service that they need or want in a personalized way.