One-to-One Marketing. The World of Data Science at KDD

The recent Knowledge Discovery and Data Mining conference in NYC this past week gave me a good look inside the belly of the data beast and I was humbled. I realized that the world of data science was moving faster than we in the media industry realize and the challenge that faces us now is insuring that our data systems and protocols keep up with the these new advancements.

In fact, data science is being applied in a range of pro-social efforts today and the KDD conference highlighted many worthy efforts in support of people and society. Microsoft’s Eric Horvitz, for example, spoke of how data is being used in transportation – monitoring wind patterns to help lower the carbon footprint and mitigate the impact of storms as well as monitoring cell phone usage in under developed countries to help pinpoint natural disasters like earthquakes to facilitate aid. Data science is also expanding in medicine to lower hospital infection rates and reduce inpatient recidivism. Horvitz explained, "The value of data is to increase and enhance your decision making" no matter what industry you target.

One aspect of new data analysis that struck me as applicable to the media industry is “rich representation” which enables the user to dynamically tag elements in a video. It involves some facets of facial recognition, body parts, clothing, items, landscape identification and other features. In this way a video can be more easily categorized by elements in the content. This capability will enable content owners to more fully and accurately categorize the elements in their content and might even enable a more granular way to measure small but discernible facets of content for performance success.

Another analytical application for media is real time speech translation which has improved dramatically in the past 5 years. It is now possible to translate conversational speech in real time, even Skype to Skype, which opens up possibilities for faster global distribution of content.

Further, applications like adaptive diversity (a form of data mashing), transductive learning (a type of machine learning), consensus modeling (used for mining data to optimize group recommendations) and collaborative filtering (used in recommendation engines) can be applied to media content selection in a variety of ways; performance prediction models, program scheduling that enhances audience flow, recommended content selection by viewing segments and the ability to create and refine those segments.

Some prescient companies like are using data science to construct custom consumer segmentations using a disparate selection of data sets including, according to VP Technology Pat Moore, the origination network, device use, traffic flows which are then used to create graph models to match users with similar features for a specific advertiser.  

View the short interview with Moore here:

Claudia Perlich, Chief Scientist at Dstillery, uses data science in consumer targeting, seemingly getting to one-to-one marketing. She explains, “I develop algorithms that utilize data to make marketing more focused and ultimately more effective for our clients. Specifically, I apply machine learning and predictive modeling techniques to distill billions of individual events of consumer behavior into an audience of prospective customers.  Every day, we analyze billions of data points generated from where people go on their devices and with their devices.  Instead of trying to bucket people into demographic or behavioral groups, we evaluate every consumer individually with respect to this specific sequence of actions to detect potential product interest and then identify the precise moments and channels for a brand’s message. We buy an impression only when we know the consumer is likely to engage. This allows us to be incredibly selective …. While others bid on 45% of impression inventory, we bid on only 3%. This approach is individualized to every brand or product, and it’s also individualized to every consumer on the other end.”

I suspect that this is just the beginning. And unless we as an industry consistently make an effort to understand the expanding capabilities of data science - machine learning, artificial intelligence and data mashing for example- we will fall short of optimizing our data for viewership, cross platform, POS and ROI measurement uses. Of course data intelligence, like everything else in our industry today, is evolving quickly but we should at least begin to include the basics of data science in our media and marketing research conversations so we are not leading from behind.


The Business of Games. Q&A with Michael Gluck

Michael Gluck, Founder of VG Market, always wanted to be in the video game industry and has been preparing for this career for many years.  Gluck started his own research-oriented company to serve the video game industry by recruiting gamers to give first hand feedback for new and established games. In this fascinating interview, Gluck talks about the gaming industry, what makes the perfect game, how his company measures game satisfaction and success, game monetization, landscape and global implications. He also looks ahead to predict how the media landscape will look in the gaming sector in the next few years.

There are six  videos in this interview:

Subject                                                 Length (in minutes)
Background and VG Market                        (5:13)
Start Up and Gaming Market                      (6:48)
Game Truisms and Platforms                      (5:10)
Demos and the Perfect game                     (4:34)
Monetization and Global Gaming             (6:28)
Predictions and Connected TV                   (3:33)

Charlene Weisler interviews Michael Gluck who talks about his background and VG Market in this 5:13 minute video:

CW: How have you seen the gaming market evolve since you first started?

MG: I started my company in 2007 and at that point in time, 90% of my business was console gaming. There was Playstation, Xbox or a computer. So we tested box products. Moving into 2008, we started to test on the mobile phone for the first time. We were one of the first research companies to start in on that. It was a new field and we were in the position as a video game research company to start the testing for mobile phone games. And at that point in time, the mobile phone games we were testing were all pay for download. You would go to the app store, you would pay $4.99 or $7.99 or $9.99 and you would get your game and play it until it was over. The sequel would come out and you would buy the sequel. So what started as console gaming only, moved into console and pay-by-app phone game. And then the following year, we started to get into Facebook game and more mobile game testing. Then we started to see a new free-to-play model. In fact, we were in the room doing the research on one of the first free-to-play games in app purchases and people were terrified. They were thinking – we just made this game, we are not going to charge for it, we are going to give it away and hope that people buy it? We were in the room having these conversations when these executives were talking about- is this something we really want to try? What if no one buys anything in the game? We just spent all this money building it and giving it away for free. There was a lot of fear around that. But then we dipped a toe in and it was successful and then over the next year or two everything started to go that way and I saw my business change from console to pre-paid app and then free app with in-app purchases and then Facebook gaming and then mobile gaming. Everything became free to play and today, more than half of my business is mobile gaming.

VG Market's Michael Gluck tells Charlene Weisler about his company's back story. He also gives an excellent overview of today's Game Market in this 6:48 minute video:

CW: Games probably differ by platform but are there any truisms for gaming success across any platform?

MG: Fun game play is important regardless of the platform. The game has to be fun. The graphics don’t necessarily have to be great depending on the platform. You can have a lower graphics quality game or even a menu text based game that can do quite well depending on the country, depending on the target audience.  It can make more money than a game that took years to produce with the highest level of graphics – just a simple game on your phone with lower graphics. So graphics is certainly not a truism. But fun game play is. So a hook that grabs you and makes you want to come back. Something that has a mechanic in it that compels you to play again and again. That is true regardless of the platform.

Replay-ability is also important. So once I have gone through the experience, is it fun to come back and repeat the process? Is it new, fun and different each time I come back? Does it have a life span? User interface is also something that is important regardless of the platform. If it is not intuitive to play on your phone, if it is not intuitive to play on your play station or your computer, chances are someone is going to drop out early.

Audio is something that depends on the platform. You can have a simple loop on a phone game that isn’t much to listen to in the background but it can still be successful versus on a higher production game, they are looking for audio recorded by full orchestra and it has to be published on a soundtrack – a whole different level of audio.

What are game truisms and how do games vary by platforms? Michael Gluck shares his perspective with Charlene Weisler in this 5:10 minute video:

Charlene Weisler interviews Michael Gluck who talks about game monetization and global gaming in this 6:28 minute video:

Different games attract different demos. Michael Gluck talks about demographics and what makes the "perfect game" in this 4:34 minute video:

In this final video, Charlene Weisler interviews Michael Gluck who offers some thought on the future of the media landscape and also the imapct of connected TVs in gaming in this 3:33 minute video: