Margins and Paddings Update

During the National Football League’s biggest weekend, it’s often the commercials that take center stage. It’s every advertiser’s dream. The world as your audience. But how do advertisers capitalize on the opportunity and connect with viewers? Advertisers are responsible for developing memorable content and messages that resonate with their audiences. This year, we saw our fair share of light-hearted commercials and those that tugged at our emotional heart strings. And most of them were discussed the next morning at the water cooler. So who did this year’s commercials resonate with? Based on 10 of the more talked about commercials during this year’s Super Bowl, we categorized them into two segments: emotional and light-hearted. We leveraged our Social Media Analysis to dig a bit deeper into the core demographics and social behaviors of the consumers who engaged with these brands. Interestingly, nearly three times the number of social media users engaged with brands associated with emotional commercials rather than the brands tied to more humorous TV spots. The emotional heart strings (Airbnb, Audi, Budweiser, Coke and Lumber 84) Our analysis revealed more than 52 percent of the consumers who interacted  with these brands on social media were women, and nearly 28 percent fell between the ages of 26 and 35. Moreover, these consumers were 15 percent more likely to be single than the average social media user. They were also 1.91 times more likely to reside in Wahington D.C. The analysis also showed consumers who engaged with these brands were 2.69 times more likely to fall within the life stage Experian refers to as “Urban Edge” based on the company’s Mosaic® lifestyle segmentation system. People in this segment tend to be younger, up-and-coming singles, who live big city life styles near the top metropolitan markets. The types of social media handles these consumers were more likely to follow, included sports organizations, soccer teams and leagues, and magazine brands. Additionally, the hashtag these consumers were more likely to talk about than the average social media user was #travel, while they were more likely to mention @nytimes in social media posts. Commercials with a funny bone (Bai, Buick, Kia, Mr. Clean and T-Mobile) While there were some similarities in the core demographics of both segments of social media users, there were some slight variations. More than 54 percent of social media users who engaged with the brands tied to the light-hearted commercials were men. These consumers were also 26 percent more likely to be single than the average social media user, and 1.55 times more likely to reside in Washington (state). Consumers who engaged with these brands were 1.74 times more likely to fall within the life stage “Heritage Heights.” These are often single people and families with modest incomes who live settled lives in urban apartments. The types of social media handles these consumers were more likely to follow, included NFL and football enthusiasts, WWE, and technology influencers. Furthermore, the hashtag these consumers were more likely to talk about was #sweepstakes, while they were more likely to mention @shawnmendes than the average social media user. Quite frankly, each consumer is different. What peaks their interests and motivates them is unique to every individual. It’s up to marketers to understand who their customers are, and how to engage them in an impactful and meaningful way. And social media data provides them with a remarkable view into their preferences and opinions. Through our data and insights, we’re able to help marketers tap into who their customers are and how they behave. Marketers can take this information and optimize content for future marketing campaigns and deliver messages that resonate with their target audiences. The Big Game is only once a year, but marketers should “game plan” year round. It’s those marketers who will come out on top. To learn more about how marketers can leverage social media data, visit https://www.experian.com/marketing-services/targeting/marketing-measurement/social-media-analysis.html        

  I’m the Head of Utilities in Experian’s Energy and Water Sector. I handle a very specialized form of fraud called “energy theft,” where an individual or business steals electricity by tapping a line or bypassing the energy meter. Back in 2010, the process for handling this type of fraud was broken. Few companies bothered investigating instances of theft; they just accepted the pervasive issue as a cost of sale. This fraudulent activity was costing energy consumers approximately £30 per year, while putting countless homes and offices at risk, since faulty wiring for gas and electricity often leads to house fires or even explosions. Energy regulators decided the time had come for energy providers to crack down on the practice. My team and I at Experian were invited to a consultation to discuss how to use data and innovative techniques to end energy theft. The model we suggested was adopted as the preferred approach, and in the last year the project has been implemented across the entire industry in the UK. Our model combines data from the big energy companies with Experian’s own database to identify which residential or business properties may be stealing energy from the network. We can determine this by comparing energy consumption trends with information on how many people actually occupy the property. With both data sets, we can determine the amount of energy we believe the property should be consuming. If the energy consumption is lower than it should be on a particular piece of property, we look at fraud and credit data sets to see if the case qualifies as a genuine instance of low consumption (such as an older woman living alone), or if someone is perpetrating theft. We send that information back to the supplier so they can prioritize it for investigation. Through this program, I’ve helped protect countless homes and saved consumers from having to pay for energy they’re not using. I love that what I do not only gives me the opportunity to be creative in how I use data, but also helps protect businesses and everyday people. Read more #ExperianStories from our colleagues around the world.    

Today we are living in a world of data. It is everywhere, affecting many aspects of not only how our businesses are run, but our individual lives. It is growing in value and becoming more significant with each year. When used correctly, it has the potential to make positive changes. The challenge is that while data is everywhere, we don’t always trust it. While many businesses today say that data is driving new opportunities around increasing revenue and better serving their clients, the level of accuracy within their data is lacking. According to new Experian Data Quality research, less than half of organizations globally trust their data to make important business decisions. That level of doubt is causing 52% of organizations to rely on educated guesses or gut feelings to make decisions based on their data. That lack of clarity is causing businesses to not only operate with less efficiency, but 73% of c-level executives indicate that inaccurate data is undermining their ability to provide an excellent customer experience. While many are making strides to try to improve the quality of data and the trust level, they are often hindered by departmental silos and a lack of consistency across data sources. Much of that comes down to basic communication and an ability to talk about data. Departments lack understanding of how information is used across an organization or what the true impact is of poor data. In my discussions across the industry, it is clear that data lacks a consistent, meaningful language. We tend to focus on the level of pure accuracy levels, rather than the effect to the business or the customer. Data strategies need to more closely relate to defined business goals, outcomes and use cases, rather than just a data policy that sits within a vacuum. In the year ahead, we expect that many businesses will make strides within their data management programs and improve the quality of data. However, for those programs to be successful, they need to tie to broader business objectives. In those instances, developing more trusted data will certainly pay off. To learn more, check out the new global data management benchmark report.