Lesson From Advertising Week – It’s The Data

When I think of autumn, I can't help but think of advertising week which is a jam packed series of overlapping events highlighting how our industry is innovating, evolving and transforming. At the end of it I always marvel at how much I have seen ... and how much I have missed because of time. But the one thing I have not missed (because it is ubiquitous) is the recent exaltation of data and analytics in our industry. I am thrilled by the recognition of the value of research as a strategic revenue driver.

So here are my research takeaways from Advertising Week and the OMMAs:

It's Not Big Data. It's Smart Data

Data by itself tells you nothing. It has to be put into context with all of the different datasets' inter and intra relationships. Too much data for data sake is problematic as David Tucker of UM noted "We have the capacity to know more about people today but it’s like boiling the ocean and data makes the ocean deeper. People don't say what they think and don't do what they say. We need more careful insights." But not having enough data is problematic as well as Claudia Perlich of Dstillery said, "Do you have enough data to go into the details?" So finding that optimum amount of quality, meaningful data will be the Holy Grail going forward.

Use Data to Look Ahead, Not Back

The use of data to forecast has never been more promising. Anush Prabhu of Deutsch explained, “Back 10 to 15 years ago we analyzed effect. Over the years, it has become how it will affect. We are looking forward with more data. We are looking at what is going on culturally. We can do and create things.” Traditional methods have been based on past performance - how a program rated in the past, for example, used to project future ratings. But now with machine learning, AI and expert algorithms, we may be able to better ascertain content attributes and target segmentations in such a way that even without prior actual performance, we can forecast the chances of its success.

Identify, Measure and Monetize –

The mantra, “If you can’t identify it, you can’t measure it. If you can’t measure it, you can’t monetize it” has been gaining in volume over the past year. Initiatives that have been calling for industry standards are gaining traction. For example, CIMM’s Trackable Asset Cross-Platform Identification (TAXI) was developed to cover the entire content identification spectrum - programming and advertising – as a way to verify exposure to assets as they travel across platform. CIMM’s Jane Clarke explained, “The way it is now, everyone has their own proprietary tag and code. There isn't an open and inter-operable standard. And so we just kept saying to ourselves, as with the UPC code, couldn't there be a UPC code for media? CIMM has been collaborating with Ad-ID and the Entertainment ID Registry (EIDR) along with the Society for Motion Picture and Television Engineers (SMPTE) to bring UPC code-like benefits to tracking assets through the media ecosystem. This will drive innovation not only for cross-platform measurement, but also for other automated innovation in digital TV.” The IAB’s Randal Rothenberg offered his view, “There is no universal coding system across platforms but we are closer to embedding Ad-ID in digital which will enhance measurement and inter-operability. This will be a major panacea to digital marketing community.” Nancy Hill from the 4As added, “Ad-IDs will not be a replacement for the ISCI code. The faster we get Ad-IDs implemented across the chain, the more relieved we will be. We are structuring norms and behaviors that allow us to do business and not contain innovation and creativity. We need to be able to grow profitable businesses over time.”

No One – In Digital or Traditional- Is Happy With Current Measurement Analytics

There are many executives from across the spectrum who are frustrated with the rate of change and implementation of audience based standard measurements. While there is “pressure for more measurable media” according to Anush Prabhu, "Analytics have a long way to catch up to what we are doing in digital" added Kevin Rettig from Accenture. MediaVest’s David Shiffman believed, “Everyone is creating their own solution for their own platform for their own needs. It doesn't serve the whole.” But there is hope, Shiffman added, “(comScore’s) Project Blueprint brings together various data streams. They have a convergence panel to understand how data comes together. They take a consumer oriented view - not channel by channel – and it has the potential to shift the conversation. There is excitement and hope around that initiative.”

The Future Belongs to the Nerds

The future looks bright for those of us who understand and work with data. Mediapost’s Steven Smith noted that “Trend lines have been more to analytics” while David Tucker said that “Opportunities have always been there. They are not new. What data allows us to do is find those moments more frequently. Data is unlocking and making solutions more visible for us.” Even conversations with clients have changed according to GroupM’s Harvey Goldhersz as they realize that "Everyone we made fun of in college will be our bosses." Oh do I hear music?

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 Bloomberg.com 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.