Measuring the Impact of a Covid Vaccine Campaign. An Interview with Brennan Lake, Senior Director of Research Partnerships & Data for Good at Cuebiq

How effective is the Ad Council and COVID Collaborative Vaccine Education Initiative? Cuebiq, a company that measures mobility will find out. Cuebiq and the Ad Council are partnering to ascertain how effective the ‘It’s Up To You’ campaigns are. They were created to educate Americans about the COVID-19 vaccines. 

Using foot fall and other traffic data, Cuebiq will measure the effectiveness of the campaigns in driving exposed audiences to vaccination centers. Metrics will include visit lift, the change in percentage of visitation to vaccine centers between those exposed to PSAs versus an unexposed control group, and incrementality, which represents incremental visits to frequently visited locations (such as pharmacies) above and beyond normal behavior. Results are expected by the summer. Brennan Lake, Senior Director of Research Partnerships & Data for Good, offered further details:

Charlene Weisler: Has Cuebiq done this type of research before?

Brennan Lake: Measuring the effectiveness of media campaigns in driving visits to brick and mortar locations is at the core of Cuebiq's commercial business. Alongside this, we've done extensive pro bono work through our Data for Good program in using privacy-preserving mobility data for analyzing behavior change throughout the pandemic. Therefore, it was a natural move for us to combine our work in COVID-19 research with our advertising technology to assist the Ad Council in measuring the effectiveness of their vaccine information campaign.

Weisler: What is the methodology for this study?

Lake: We utilize our sample of first-party mobility data, consisting of over 20 million anonymous and opted-in daily active users, in order to measure visitation trends to public vaccination centers, such as pharmacies and vaccine mega sites. Specifically, we created privacy-preserving segments of users who have been exposed to the Ad Council's PSAs, and compare their visitation behaviors to an unexposed control group that is demographically similar, in order to measure the visit "Uplift" resulting from campaign exposure.

We also use machine learning to compare 'normal' visitation patterns to current behavior in order to draw a causal link between exposure to a PSA and visits to vaccination centers - a metric known as "Incrementality".

Weisler: What are the challenges that you see?

Lake: As with any other campaign, we want to make sure that we can effectively verify real visits to the points of interest, differentiating them from the noise of 'passersby' within the mobility data. When attempting to infer something such as vaccination from visits data, this adds a layer of complexity, especially for multi-purpose venues such as pharmacies, where even if we can confidently point to visits, it may be the result of segments engaging in regular shopping activities rather than to get a COVID-19 shot.

In addition to applying campaign parameters - such as only looking at visitors who dwell at a location between 15 minutes and 1 hour - we can also use causal machine learning to distinguish between normal shopping behavior and true incremental visits that can be attributed to a campaign. For example, if I typically visit a pharmacy 4 times a month, but after being exposed to a campaign I make 5 or 6 visits, our neural network can pick up on these discrete changes over time, along with data from a control group, in order to reveal incremental visitation behavior.

Weisler: What is the main purpose of the study?

Lake: The main purpose of this study is to support the Ad Council in evaluating the effectiveness of their campaign in driving positive public health outcomes. While the main call to action of the Ad Council's "It's Up To You" campaign is to learn more about the COVID-19 vaccine so that you can make an informed choice to vaccinate, we also hope to see an increased vaccine uptake, especially among cautious, hesitant and skeptical segments.

Weisler: What do you hope to find?

Lake: Ultimately we hope to see a campaign that is successful in providing vital information to the general public, while also driving positive health outcomes through an increase in COVID-19 vaccine uptake. By better understanding which aspects of the campaign - such as content, creative, channel, geographic focus - are most effective at driving visits to vaccination centers, decision makers can better double down on what works, to get people the information they need to make an informed decision to get vaccinated, in order to protect them and their loved ones.

This article first appeared in www.Mediapost.com

 

The Coup D’etat in Media. Insights From the TV Data Summit

There has been a coup d’etat in media. Where Content used to be King, it has now been deposed and replaced by what Eric Shenk, Technical Director, Office of the CTO, Google Cloud Media noted at the recent TV Data Summit - “Audience is King.”

Why have audiences taken over the prime consideration in media? Part of the answer is the primacy of data in the consumer journey. With access to first, second and third party datasets, marketers and programmers can more easily and efficiently parse who is motivated, who is engaged and who is ready to transact. But how can we know which datasets are relevant, what might be missing and how to best analyze the results?

Here are some takeaways from the TV Data Summit:

The Impact of Data

The availability of data has led to a seismic philosophical change in the media pipeline. The focus used to be on delivering audiences to advertisers. But now, with audiences more in control of their viewing choices, companies need to consider what triggers their choice and attention.

For Radha Subramanyam, Chief Research and Analytics Officer, CBS, her company’s world class global content, brand championship in a safe environment with a passion for innovation is all tied together with cutting edge analytics supported by data. In looking at the ad marketplace today, she noted that data can be used by targeting demographics to gain mass reach and brand awareness, from data enabled TV to target optimization and in addressable for one to one messaging.

For Shenk, “Data is everything,” touching all aspects of the media business. But, currently, it is highly fragmented, residing in silos within companies and behind walled gardens with frenemy companies.  As best as one can, data needs to be collected, transformed, analyzed, visualized and then the best decisions must be made from the insights.

Consumers Are in Charge

Larry Allen, Vice President Ad Innovation and Programmatic, Turner, noted the shift in focus from the client to the consumer. “TV is under siege,” he warned, and said that while advertising strives to make the experience better for the client, “what if it is alienating the consumer?”  We need to “put them front and center.”

He explained that the current ad model is not working because there is too much frequency, not enough relevancy and too mass. “Really long ads can work depending what you are trying to achieve,” he noted and added, “We have new customer engagement metrics to improve our understanding of what is happening. We want to put ads in front of people that make sense. So they don't avoid them.” To that end, Turner embarked on consumer journey research to find out what builds affinity for content. Turner identified consumer content needs and the path they took to make decisions. “This can make things more contextually relevant in real time,” he stated, “and it can be leveraged. But it is hard to scale today and it is a long term horizon project.”

The Challenge of Measurement

The wide possibilities that data brings to the media business is offset by some of the challenges it creates. “Measurement to business outcomes has been challenging,” admitted Julie DeTraglia, Head of Research, Hulu. Tracking content across screens, calculating co-viewing on shared platforms and establishing an industry standard cross platform measurement are all worthy goals that require a joint industry effort between companies that often compete.

CIMM, now part of the ARF, has been focused on establishing a universal content labeling code to ads and programming. This initiative is beginning to gain traction. Jane Clarke, Managing Director and CEO, CIMM noted that there is, “a lot of support for data but sometimes data produces different results because there is no national dataset. We need to understand what is under the hood.”

Initiatives like OpenAP have enabled frenemy companies to work together to bind datasets together to segment audiences for sales.  For Haile Owusu, Senior Vice President, Analytics, Decisions and Data Sciences at Turner, the focus is on algorithmic output. “We forecast bulk audience flows and the ability to probe intra-show behavior, identifying components of the content for additional churn,” he explained. He is also working on the blending of linear and digital consumption by coupling Iinear TV viewing with viewing on devices and to messaging on the app.

Conclusion

Data and analytics, fueled by machine learning and artificial intelligence, will make the media business more efficient and targeted. If frenemy companies can work together, the opportunities offered by data will multiply and the challenges it presents will be subtracted. The TV Data Summit has put all of the innovative approaches out there. Now is the time for the industry to move forward.

This article first appeared in www.MediaVillage.com

Programmatic Advertising and AI: Insight From MediaPost’s Marketing AI Conference

Among the various means of buying media content, programmatic launched as one of the few forms that fully embraced advancing technology—and it’s artificial intelligence (AI) that’s helping to bring about that profound technological change.

At MediaPost’s recent Marketing AI conference held in Manhattan, media experts explored the impact that this protocol will have on buying, selling, agencies, commerce, customer experience, and marketing. Here’s insight from some of the featured speakers.

The Changing World of Media Buying

While AI has been in the conversation for a while, “the hype is starting to get real,” according to Ross Fadner, director of event programming at MediaPost. “There are more efficient products, and questions are arising as to how AI is being applied and what it means.”

There is talk that technology like machine learning and AI will replace humans in a variety of media jobs, but author Ken Auletta questions whether that is really true. Ultimately, “you have to rely on humans and not on machines,” he stated.

Trust is a large factor in how we balance the use of targeting data and the legacy...

Read the full article on the Videa blog.

Welcome the Fourth Industrial Revolution. The TV of Tomorrow Offers an Exciting and Dystopian Future.

Where is TV headed? What is the TV of tomorrow? That was the question on my mind while attending the TV of Tomorrow conference held in NYC last week.

Many issues are hitting the industry now. “People are trying to aggregate data in order to organize the KPIs and monetize them while understanding all of the barriers involved how to bring all that data together,’” noted, Tracy Swedlow, Editor-in-Chief of ITVT and Founder of the TVOT Conference. In the realm of social media, many companies are grappling with “YouTube and their changing algorithms, libraries that are being de-monetized and the creation of greener pastures,” she added. 

One thing is clear; the TV ecosystem of today will definitely not be the TV ecosystem of tomorrow. Millennials are cord-nevers who didn’t grow up in a world of TV networks. Don’t expect them to change their habits as they age. And they don’t see the media landscape the way older viewers do. As Helen Katz, SVP/Global Director of Media and Insights, Publicis Media, explained when she asked her daughter what her favorite TV channels were, replied, “What is a TV channel?” 

For those of use with years invested in the industry, the changes discussed at the TVOT are at once exciting and dystopian. Here are my takeaways:

Increasing Technological Dominance

This drumbeat of technological change is leading to what Stein Erik Sorhaug, VP Product Strategy, Vimond, terms the Fourth Industrial Revolution where, through artificial intelligence (AI), we will drive human behavior and human thought. AI, as applied through Machine Learning, has the future capability to craft the most engaging content, map the most effective media plan and measure everything everywhere through the consumer journey. Ideally there will be room for both AI and human input where computers "create an inference layer" according to Mika Rautiainen, CEO/CTO, Valossa Labs, followed by "human curators editorially creating playlists and new channels," Sorhaug added.

Skill sets need to keep pace

Certain jobs could disappear in this new media ecosystem or will require different skill sets. "No question that people in yesterday's supply chain will be wiped out," stated Dave Morgan, CEO, Simulmedia, "marketing managers today don't have hard science background and will lose jobs to those who do." Swedlow suggested future media mavens, “create their own channel with their own ideas for original content. There will always be an opportunity for great content with real personalities and people who have a compelling story to tell.” 

Measurement Still a Challenge

“The lines between linear and digital are blurring,” explained Jenny Burke, SVP Sales Strategy, NBCU, “so we are concentrating on content; distributing it to whatever platform the consumer prefers.” How can this consumer journey be best measured? Aaron Fetters, SVP National Agencies and CPG Business, comScore, noted that, “times are changing and measurement must change with it. We need to future proof measurement with the growth in IoT, OTT and wearables.” But how can we accomplish this when there are walled gardens and silos of data and no industry standard content identification system in place? Until we can agree on the best way to track content, through content identification and ACR, full cross-platform measurement will continue to be a challenge and will become more complex.

OTT is Growing and Cuts Out the Advertiser

Ignore the influence of OTT at your peril. “Four major OTT services account for 80% of viewing time in OTT households with Netflix at 39%,” stated Katz. And it is growing. Since much of OTT is subscription based, this can shut out advertising. Fetters added, “We see that viewers are spending 25 hours per month with Netflix on their TV screen and that is 25 hours per month that is not available to advertising. We need to find ways of adjusting the advertising plan to reach those households.”

ATSC 3.0 Brings TV into the New Age

Although still in the arena of the engineering wonks, the advent of ATSC 3.0 will prove to be a game changer for local TV. This new protocol will, as Swedlow explained, “enable regular digital television over the air – local television and every other broadcaster - to be able to explore the relationship between linear over-the-air and interactivity on-demand.” How fast and how profound ATSC 3.0 will be depends on timing – when will all of the new chips be installed? It will take a while, she explained, because there is no deadline by the government, “but I think it will pick up steam,” she concluded.

We have to be “savvy enough to take advantage of all of these new technologies because everything will be interactive. There will be shows that will be voice activated and there will be shows that will require you to interact with another person or deal with blockchain to monetize your content,” explained Swedlow. The best advice I can give is to embrace change and be nimble. The future of television will demand more of us but it will be an exciting journey.

This article first appeared in www.Mediapost.com

Carpe Datum at Gigaom

Have you heard of Gigaom? Me neither. But after attending their truly fascinating Data Structure Conference in NYC I think that a solution to true seamless cross platform media measurement may be at hand.

At Gigaom there were many innovative, ground breaking tech companies that seemed to have the capability to improve on the current measurement of media and consumer behavior through the use of artificial intelligence, machine learning, data blending and data discovery tools. And many of these companies have the ability to merge on one user interface all platform, device, app, software and site data and run it all in or close to real time. Today’s tech environment facilitates storytelling and data visualization to better leverage business intelligence which is exactly what we in the media space are seeking. Needless to say I was impressed by just about everyone I spoke to. Some of the innovative companies represented at Gigaom Data Structure are in this video:

Data Blending

Let’s begin in the area of data blending. According to a recent Gigaom Research study (Sector Roadmap: Data Discovery in 2014) “Data blending is the term used to describe the performance of analytics on a collection of data sets, each emanating from a different data source.” They say that data discovery products currently on the market are now capable of real time or close to real time data blending allowing users to pull in data, quickly mash it up and analyze it. Some companies like cloudera offer the ability to serve many different types of user workloads with access to the same data set within a single interface. This interface, according to CEO Tom Reily, “can manage all types of analytics and identify trends in customer experience.”

So I am thinking, can we take television data (Nielsen, STB or other), online, mobile and tablet (name your sources) and maybe even print, retail or transactional data and place it all on one interface and data blend? I know there are some companies offering this capability now in our industry but with limited datasets and outputs that still seem to be fairly silo’ed.

Artificial Intelligence

AI still seems very futuristic to me but in fact is fairly common in applications today. Some firms, such as alchemy api are in the business to “make computers more human” according to CEO Elliott Turner and others like Watson Solutions’ Stephen Gold offer “cognition as a service.” But what does this really mean for media? I think the possibilities are endless. We may be able in finally pinpoint how a viewer fully interacts with a piece of content, including the soft measurements of sentiment and engagement. We may even be able to use AI to predict which pieces of content are most effective at driving human behavior whether for tune-in, reaction, affection or to create a call-to-action.

Machine Learning

Combined with a level of AI, machines can be programmed to learn from experience. In this way data can be mined more efficiently and with greater precision to create software applications. Tim Tuttle of Expect Labs explained, “We built mind meld to listen to conversations and find information for you. Now we want to take that technology and apply it to any data you have." Think of Siri who seems to retain knowledge with each interaction. Siri is just the tip of the iceberg in machine learning capabilities. At some point we may rely solely on the machine to map out data insights. I hope I am retired by that time.

Data Discovery Tools

Donald Farmer, VP Product Management, Qlik believes that “When it comes to big data understanding we are in the Dark Ages.” This is exacerbated by unnatural interfaces that once had a purpose under old media but no longer apply. Farmer gave the example of the keyboard QWERTY system that was originally set up to avoid the typewriter keys from jamming. We still use this unnatural keypad interface even though our devices today do not have the problem of typewriter keys jamming up. How to we advance from old legacy systems and processes?

This and many other questions are a part of a huge data surge that impacts many businesses, including ours in media. Attending the Gigaom lets me know that we in media are not the only ones grappling with processing, measurement, analysis and data wrangling issues.