Author Archives: Reid Wegley

I am continuously experimenting with big data and learning the intricacies of how data can be used, utilized and integrated into the workflow of nearly any industry, task or project. Which is why I am intrigued by the ability to make slight changes to advertising strategies or content or even slight manipulations to an algorithm that ensure a business is achieving its business goals.

I am looking forward to sharing this fascination on May 28 when I and marketing author Bryan Heathman will be the featured guests for a University of Washington seminar. We will be discussing data-driven marketing with the Foster School of Business’ Master’s Degree candidates and Bryan will be sharing the experiences he’s learned through his work using big data for various marketing initiatives.

In anticipation of this opportunity to meet with the marketing innovators of the future, we put together the following Q&A to explore the role big data plays in marketing:

•  How do you define data-driven marketing and what makes it different from traditional marketing?
  • Ed Sarausad: Traditional marketing relies more on intuitive “gut feelings” to make decisions on price/product features/promotional initiative/placement choices. Data-driven marketing relies on statistical models (often from econometrics) to make decisions.
  • Bryan Heathman: Traditional marketing, meaning the analysis of historical data from a marketing initiative, often begins 15-60 days after the marketing event (trade show, syndicated ad, coupon drop, direct mailing, etc.). Managing business decisions from the rearview mirror is a thing of the past with up to the minute data-driven marketing tools.
• What is the key to success? Is it a KPI or is it something that’s intangible?
  • ES: Key is a data-driven culture, one that doesn’t ignore human intuition—but strikes the right balance of utilizing advanced metrics and data but also on checking that the numbers align with a humanized brand.
  • BH: The magic of data driven marketing is in creating visual simplicity with a sea of inbound data. Success comes from the ability to see results combined with subject matter expertise to interpret important mathematical correlations.
• How does the concept of “big data” factor into today’s marketing campaigns?
  • ES: Signals from social traffic and conversion require processing of high-volume, high-variety and high-velocity data. Turning these data into actionable outcomes for the campaigns is key. If you know a specific segment of customers (identifiable via Facebook demographics) respond well to specific promotional offer versus another, you can continuously feed that learning into the next promotion. Considering a promotional calendar with holidays and multi-cultural events, there’s a reason to have a promotion (Game of Chance, 2 for 1, or 50% off) every month and often times multiple times a month. The intelligent promoter will want to know what promotion to choose for the right segment at the right time. Often times, these offers are made in near real-time to prevent churning of customers.
  • BH: As more commerce moves to ecommerce channels, real-time data analytics of terabytes of data is moving the forefront of the marketing mix.
• What is possible today that wasn’t possible three years ago?
  • ES: Dealing with terabytes of data in real-time is now possible. Making it actionable with measurable business outcomes (marketing ROI) is the next wave.
  • BH: Real-time data analytics is now on the horizon for marketing departments of B2B and B2C companies. Imagine the power of real-time sales revenue data combined with advertising spend, to track the ROI of a marketing campaign.
• What will be possible three years from now that is not possible today?
  • ES: The future is about automating decisions based on real-time data collection. Businesses will be able to react to social, market or environmental signals with the best possible response, which real market data will enable.
  • BH: Moving real-time business decisions beyond the realm of ecommerce and into sales channels with traditionally slow reporting, such as warehouse clubs or 3^rd party parts distributors.
• What is the top skill for today’s students to refine before they enter the post-college world?
  • ES: Tying Statistics/Quantitative Methods to Strategy is the most important. We used to talk about “data telling the story”, but the truly convincing Quantitative Marketers tell the story with the data—armed with the know-how of the statistician or econometrician. For example, the results of a complex latent variable model can be summarized in an easy-to-understand infographic, which tells the marketer, “Oh, I’m talking to the wrong customer segment completely, or I’m sending them the wrong message at the wrong time.”
  • BH: Apply your knowledge from the classroom into the corporate world. Companies are hungry for students who bring a fresh perspective to the marketplace. Get an internship while you are studying, which will help give students perspective into post-college pursuits.
• What is one danger of data-driven marketing?
  • ES: Ignoring human intuition when the data is simply incomplete or appropriate to take business action. This happens when we haven’t accounted for everything in our prediction model.
  • BH: Improper programming/modeling in automated decision making can be detrimental to profits. Also, loose management oversight on complex programming can be equally dangerous.

We’re looking forward to sharing our experiences with the students at the University of Washington. We know that there’s a tremendous future for utilizing not only traditional KPIs in marketing initiatives, but by utilizing historical data sets, integrating algorithm approaches and the ability to make real-time decisions, there’s significant change underway for the marketing world.

By Ed Sarausad

Tracking down the trillions of dollars that flow through the virtual and brick and mortar casinos around the world is a monumental task. In a world where seven-figure bets are common, how does a casino ensure that the source of its income is above the boards?

With US regulators on the verge of requiring casinos to verify the source of the funds behind large wagers, the ability to investigate customers sensitively and discreetly is a new skill that gaming companies are developing.

Banks and other financial institutions have long had anti-money laundering processes in place to help prevent fraud. Subject to a litany of regulations, these institutions are accustomed to researching their customers to ensure both party’s assets are protected. The gaming industry has a history of literally and figuratively protecting the sources of its income; potentially it could be challenging to investigate players that disproportionately boost the bottom line. But, through the use of several similar processes and tactics, gaming companies can align with the financial sector and protect themselves and their customers.

A global threat

Gaming companies around the world face the threat of being an unwitting part of a money-laundering scheme. A recent survey from PwC found that 37 percent of companies in Hong Kong and Macau, mainly banks and casinos, had experienced money laundering in the past two years. The global average according to the study was just under 11 percent.

This meant that Hong Kong had the highest reported rate of money laundering in Asia and the ninth highest globally, behind Britain, South Africa, the Czech Republic, Russia, Zambia, Australia, Kenya and Ukraine.

There is significant incentive to ensuring that the funds being gambled in casinos are legit. In August, Sands Casinos incurred a $47 million fine for lapses in its money laundering controls. And reports indicate that additional Vegas companies are under investigation. But, how can gaming companies protect themselves?

Process alignment

In banking, the key assets for research are massive data sets of public and proprietary information that span property records, criminal records and internal databases that the banks utilize. In the gaming industry, the technologies such as facial recognition, RFID monitoring of chips and in-depth record keeping are no secret. But aligning this data collection processes with the investigation teams is where the efficiencies can be identified.

Ensuring that the analysis of the available data is fueled by common data entry technologies, and that the investigation teams are aligned on how to allocate resources and even a standard for which the results are judged are all vital. In addition to that, here are three tips gaming companies can utilize while investigating suspected money laundering activity:

People: a team with members that are at the top of their respective fields is vital. The ability to work with global banks, governments and regulatory agencies to identify risk, fraud and operational weaknesses comes with experience.

Process: eliminating wasted time, resources and money can be achieved through an organized process that plays to the strength of the team. While every institution has unique processes, Alacer has seen great results from its Lean Kaizen approach and Six Sigma expertise that enables streamlined procedures and added efficiency for bottom line results.

Technology: efficient systems rely on process-driven technology. Alacer has built custom system solutions that mirror AML processes, focusing the power of big data technologies and advanced analytics to identify, investigate and combat money laundering and fraud with integrated solutions.

If you’re working in the gaming industry, aligning yourself with not only the latest technologies, but also the most efficient processes possible are vital.

Is your company monitoring for money laundering activities? It should be and the Alacer Group can help do it well. You can learn more about our anti-money laundering activities now.

by Ed Sarausad

The United Kingdom is getting serious about big data. George Osborne, Chancellor of the Exchequer and Second Lord of the Treasury, has announced that the government will establish a fund to ensure Britain leads the way in big data and algorithm research.

The new research center, the Alan Turing Institute, will be funded by the Department for Business, Innovation and Skills and will report to the science minister. The institute will focus on ways to collect, organize and analyze large sets of data.

Just who was Alan Turing? He was a brilliant scientist well-known for his codebreaking work during WWII, including being the person to help break Germany’s “Enigma” codes; it is said that his work shortened the duration of the war by at least two years. His mathematical theories also formalized the concept of algorithms that are the foundation of today’s computer science. But his achievements were overshadowed by a sexual indecency conviction in 1952 which caused him to lose security clearance. He committed suicide in 1954.

His conviction would be considered unjust and discriminatory today (he was gay). After a number of public campaigns, including an e-petition that garnered over 37,000 signatures, he was finally given a royal pardon in December 2013.
Naming the institute in his honor is a small recognition for his enormous contributions to modern computers and today’s explosion of interest in big data. But it’s a start.