The Long Game - Sports Analytics and Social Media Insights | Harnham US Recruitment post

The Eagles just took down a Super Bowl dynasty, the New England Patriots. They did it with a quarterback only three games in before the Bowl. In 2002, the Oakland A's in a bid for the Championship won 20 consecutive games with, as quoted in the movie Moneyball, "an island of misfit toys." Football, baseball, basketball, whatever the sport, New York is the home for league headquarters. The New York Metro area is one of only two cities in the country to boast eleven sports teams in the five most important professional leagues. Here, numbers, stats, and algorithms are just as important as plays, training, and wins. Okay, so wins are important. But, how do you get there? How do you know your play will hit a home run or make a touch down? It's in the numbers, the data. Even fan engagement can offer insights across social media channels - every channel, fuel to the win, plus of course great players, well-trained, who go for the win.

Sports Get Social (Media)

Sports have always been social; a place for friends and family to gather and cheer on their favorite team. In the age of digital, sports teams and their players join the social media landscape to better engage with fans and businesses are paying attention.

Social media value in sports translates to the transfer of power of popular players and teams to products. Something like the athlete on a cereal box, but on a much wider scale. For customized up-to-the minute dashboard analysis, companies spend anywhere from $50,000 to $100,000 to determine their social media measurements. Comparing their mentions, fan reach, engagement and so on to see how they measure up against other teams and players within a specific location or sport.

As social media continues to preoccupy marketing and advertising executives in sports, decision-makers are digging deeper. They want to know what's working, what isn't, what to focus on, who's being reached, and how effective their efforts are. Data is weighted depending on the sport, but across the board social media is quickly becoming one of the most important ways to speak to sports fans.

Sports Marketing Insights

Though TV, radio, and in the seats are still valuable and viable, the sheer magnitude of social media fandom is on the rise. Wherever you are, you can check your favorite teams scores, find player stats, and compare notes with others around the world. The key selling point for marketers? Instant feedback.

Marketers now have instant access to what's working and what isn't when it comes to social media. They'll know immediately whether a brand campaign is successful or not and can gauge its effectiveness via comments and critiques. Insights via these channels allow businesses to see at once what might take them hours or days to compile via polls, surveys, or focus groups. Fan engagement insights are invaluable to not only launch follow-up campaigns, but to ultimately have user-generated content to spur engagement.

In play, a team's success is measured on the scoreboard, but in social media channels, teams, players, and brand successes are measured with fan engagement. Though not everything can be controlled, we would be remiss in not mentioning analysis of pain points and injury reduction through machine analysis.

Pain Points

While ultimately, coaches decide who is at risk for injury and must make the determination to keep them on or take them off the field, they must first understand the computer-generated analysis. As seasons progress, fluctuations in a player's fitness and appetite for risk determine the probability of injuries.

This type of analysis requires a level of computation only machines can process. But, if coaches don't understand what they're reading, they can't make informed decisions. They need to know such variables as how the predictions and analysis were calculated as well as the exact effects of analytics on performance. They need to trust the numbers generated by the machine, then combine that with their domain knowledge and experience to make their decisions.

Predictive injury analysis, fan engagement, brand awareness, and sports business executives can all benefit from insights gained through analytics. Marketing insights help to propel successful campaigns into the limelight and this knowledge helps to feed everyone's bottom line.

Join the Club

Multiple revenue streams such as match day, broadcasting, commercial, and now digital are driving sports teams' executives and clubs to a healthy bottom line. Fan data segmented by any number of factors include age, location, and gender while store sales and season ticket holders can be monitored to understand where and when sales are being made. Clubs use this information in their marketing campaigns to decide the best place for their stores based on demographics and fan behavior. By analyzing these results they can even boost ticket sales based on past results to balance profit margins through predictive analytics.

The potential for analytics in sports has been utilized prodigiously in every sport from baseball to football to basketball and everything in between, yet its benefits are still up for debate. Data-driven insights offer a glimpse into the inner workings of teams as one unit, can help prevent injuries, as well as help individual players improve their game. When the dynamics come together the return on investment can be huge. Though the data must be translated for humans to understand, most sports clubs recognize data can create insights humans can't replicate.

Analytics may offer immediate insight once played, but investment in analytics is a long game. Affecting everything from player recruitment to injury prevention to business decisions, for some the debate of its benefits remain. Yet, as the jocks claim the money and fame, the back-office nerds are developing algorithms to help businesses determine everything from player picks to ticket prices.

Want to join our club? We specialize in digital and analytics recruitment and currently have an opening in our roster for a Lead Marketing Scientist with a data-rich sports media firm in New York. For a list of all our current vacancies, check us out here.

For the East Coast team please call 212-796-6070, or email newyorkinfo@harnham.com.

For the West Coast team call 415-614-4999 or email sanfraninfo@harnham.com.

A Data Engineer is a Unique Blend of Data Professional

From startup and small business to large enterprises, each type of business requires a unique blend of Data professional. Though in today’s world, much of the Data being gathered, catalogued, and analyzed happens both in the Cloud and on a hard drive, each type of business has a different need, budget, goals, and objectives. But there is one thing each and every business will have in common. At the heart of the Data team will be a Data Engineer. The Three Main Roles of a Data Engineer This is an analytics role in high demand. It is a growing and lucrative field with steps and stages for nearly every level of business and education experience. For example, a Data Scientist interested in stepping into a Data Engineer role might begin as a Generalist. In all, there are three main roles for each level and type of business – Generalist, Pipeline-Centric, and Data-Centric. Let’s take a quick look at each of the roles with an eye toward the type of person who might be the best fit: Generalist – Most often found on a small team, this type of Data Engineer is most likely the only Data-focused person in the company. They may have to do everything from build the system to analyze it, and while it carries its own unique set of skills, it doesn’t require heavy architecture knowledge as smaller companies may not yet be focusing on scale. In a nutshell, this might be a good entry point for a Data Scientist interested in upskilling and reskilling themselves to transition into a Data Engineering role.Pipeline-centric – This focus requires more in-depth knowledge working with more complex Data science needs. This type of role is found more often in mid-sized companies as they grow and incorporate a team of Data professionals to help analyze and offer actionable insight for the business. In a nutshell, this role creates a useful format for analysts to gather, collect, and analyze each bit of Data at each stage of development.Database-centric – This role is found most often in larger companies and deals not only with Data warehouses, but is focused on setting up analytics databases. Though there are some elements of the pipeline, this is more fine-tuned. In a nutshell, this role deals with many analysts across a wide distribution of databases. A Fine Balance Between Technical Skills, Soft Skills, and Business Acumen While it’s important for anyone filing this role to have deep knowledge of database design as well as a variety of programming languages, its equally important to understand company objectives. In other words, once the groundwork is laid and the datasets established, it’ll be important to explain what it is the business executives need to know to make the best decisions for their business. Knowing how and what to communicate to executives, stakeholders, and your Data team also means understanding how to best retrieve and optimize the information for reporting. Depending on your organization’s size, you may need both a Data Analyst or Scientist and a Data Engineer. Though this is less likely in medium and larger enterprises. On the flip side, in order to understand the business’ needs, you’ll also need to be good at creating reliable pipelines, architecting systems and Data stores, and collaborating with your Data Science team to build the right solutions. Each of these skills are meant to help you understand concepts to build real-world systems no matter the size of your business. One Final Thought… Do you like to build things? Tweak systems? Take things apart and see how they work, then put them back together better and more efficient than before? Then Data Engineering might be for you. Are you a business who knows you’re ready to scale up and hire a Data professional? We have a strong candidate pool and may have just the person you need to fill your role. Are you a candidate looking for a role in big Data and analytics? We specialize in junior and senior roles. Check out our current vacancies or contact one of our recruitment consultants to learn more. For our West Coast Team, call (415) 614 - 4999 or send an email to sanfraninfo@harnham.com. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to newyorkinfo@harnham.com.

by Thomas Daughtrey

11. June 2019

The Harnham 2019 Data & Analytics Salary Guide Has Arrived

We are thrilled to announce the launch of our 2019 Data & Analytics Salary Guide. With over 1,500 respondents across the USA, this year’s guide is our largest and most insightful yet. Looking at your responses, it is overwhelmingly clear that the Data & Analytics industry is continuing to thrive. This has led to an incredibly active market with 72% in the US willing to leave their role for the right opportunity. Salary expectations remain high, although we’re seeing that candidates, on average, expect 10% more than they actually achieve when moving between roles. We’ve also seen a change in the reasons people give for leaving a position, with a lack of career progression overtaking an uncompetitive salary as the main reason for seeking a change. There also remains plenty of room for industry improvement when looking at gender parity; the US market is only 23% female, falling to 17% in Data Engineering roles and 16% in the Data Science space. In addition to our findings, the guide also include insights into a variety of markets and recommendations for both those hiring, and those seeking a new role. You can download your copy of the guide here.

by Stephanie Brooks

10. June 2019