Our Q&A series shines a spotlight on the biggest challenges, questions and trends in the programmatic marketplace with commentary from industry experts, clients and partners.

Today’s Q&A is with Jodie McAfee, Senior Vice President of Sales and Marketing at Inscape, a provider of automatic content recognition (ACR) technologies that enable advertisers and broadcasters to access minute-by-minute ad consumption trends.

A veteran of the TV and advertising industry, McAfee has used his expertise in advanced video advertising, interactive TV and content acquisition to launch advanced advertising at Samsung TV and has helped grow companies like Inscape for more than two decades.

 Q: There’s lots of buzz in the industry about TV automatic content recognition (ACR). What do marketers really need to know about how it works?

Simply, if you don’t use ACR data for TV marketing, you’re running on analog systems in a digital world, and it’s probably costing your company money, and making you slower and less accurate in your assessments.

ACR data from smart TVs delivers the cleanest, fastest and most comprehensive glass-level viewing data of internet connected TVs available. It’s also one of the least understood pieces of technology in the TV ecosystem.

ACR data obtained from smart TVs reflects what’s being watched regardless of input device. People increasingly consume content not just on linear TV, but on mobile devices, PCs, connected TV devices and smart TVs. ACR technology uses screen-level measurement to identify what programs and ads are being watched in near real-time. Without collecting personally identifiable information (PII), ACR technology can identify what show is being watched and what IP address the device is connected to.

From the perspective of business outcomes, having an anchor device in the home with an IP address attached to it opens up a stream of new possibilities.

Q: There are a number of different ACR solutions available. What makes them different from one another?

The first thing to know is that Samsung and Vizio comprise 72% of the smart TV market. Vizio’s data subsidiary Inscape, which accounts for roughly 20% of all connected TVs in America, is the largest single source of ACR data in the U.S., which is fast approaching the 10 million opt-in mark. The data is collected from all sizes and makes of TVs and is spread across all DMAs in the U.S, making it representative. Inscape delivers data on a second-by-second basis in raw form so the data can be used in a variety of ways and its fidelity can be verified quite simply.

Q: Are there any notable ACR trends or observations that marketers would be interested to learn about?

According to the IAB, more than half of U.S. adults now own a streaming-enabled television, up from one-third in 2015. By 2021, there will be 114.3 million smart TVs in the U.S., up from 81.2 million in 2017, according to eMarketer. Smart TVs are definitely coming into their own and TV[R]EV predicts that smart TVs will be in close to 75 percent of American homes by 2022.

Consumer behavior continues to shift away from linear, scheduled viewing toward on-demand, cross-platform content – meaning third-party viewing data is not enough. Both advertisers and content producers need access to the most accurate viewing data available: What’s actually happening on the screen. If marketers are using TV data that is heavily modeled, it’s bound to be messy, inaccurate and contain huge inefficiencies.

Q: Do all ACR providers have access to the same source of data, or is some viewership data unique to certain providers?

Not all ACR is made the same. Inscape uses a patented system that is more lightweight on the TV device, and delivers more accurate results because it maps multiple points of verification into the process. Some take the equivalent of a screen shot which gets messy.

Also, Inscape is the only ACR provider with access to VIZIO smart TV data, which is more than nine million opted-in TVs. Other ACR providers combine data from several smaller OEMs, and in some cases also include audio ACR from smartphone apps.

 Q: Finally, what are some key questions to ask prospective ACR partners?

 We like to point to a great list of questions prepared by our partner Viant, in their Introductory Guide to ACR Technology:

1. How does the provider link personal devices to household televisions?
2. What is the source of the provider’s data? TV manufacturers or Smart TV and mobile applications?
3. Does the provider model for scale? If so, what is their deterministic footprint?
4. Can the solution provider measure cross-device ROI along with TV tune-in?
5. Is the solution provider’s reporting delivered in real time?

Our Q&A series shines a spotlight on the biggest challenges, questions and trends in the programmatic marketplace with commentary from industry experts, clients and partners.

Today’s Q&A is with Matt Wong, VP of Channel Partnerships at PushSpring, a leading provider of data and insights for verified iOS and Android mobile app audiences. In his position, Wong is charged with helping clients effectively understand and leverage PushSpring’s offerings.

Q: Marketers know it’s important to reach audiences across all of their devices, but how essential is it to reach users specifically within their mobile apps?

We recommend that all campaigns be run across devices to message users within the media they consume most – mobile applications being an important part of this mix, given they comprise more than 90% of our time on mobile devices, according to eMarketer.

 Q: What can be learned from understanding which mobile apps users are downloading?

Installed applications tell us a lot about a user’s interests, hobbies and attributes.

Apps can be highly personal and reflect interests or associations not easily found in other data sets without PII or registration data. One’s travel loyalties, retail and entertainment preferences or frequent hobbies are a few items easily identified through applications.

For instance, if a device has a specific airline app installed, the owner is extremely likely to have flown that airline or be a member of the airline’s loyalty program. There are also “archetypal” apps, which one would only have installed on their device if involved with a particular activity or life stage. An example would be a pregnancy tracker, with the logical assumption being that a user would only download this app if actually planning for or expecting a child.

Q: How should that information influence media buys?

Apps tell us a lot about their users and ownership information should be used as part of the media planning process. The ability to target based on one’s preferences or interests is extremely compelling and acts as a definitive attribute to qualify users into a particular audience.

For planning purposes, we recommend understanding the life stage and additional interests or related categories of a user, which would qualify them for a particular audience. Conquesting a competitive brand’s mobile application is often the immediate opportunity that comes to mind for marketers. However, while that is one tactic to use, it’s not the only effective option for the campaign.

Think about an insurance provider who is looking to gain new users. It would be easy to create an audience targeting competitive insurance providers, but how often does one really switch insurance companies? If this is the only audience on your plan, there’s a high likelihood you won’t attain the results you’re looking for. Instead we recommend also using life stages – for instance, targeting devices with apps that indicate life changes such as engagement or marriage, having a child or buying a house, which are all activities that might encourage someone to review their insurance needs and seek a new provider.

Q: What is unique about PushSpring’s partnership with Viant’s DSP Adelphic?

Adelphic and PushSpring’s partnership allows for custom audience creation with seamless media execution. The ability to create custom segments leveraging the PushSpring Audience Marketplace and easily execute across Adelphic’s platform (potentially adding additional layers of targeting) gives advertisers a unique way to leverage two best-in-class platforms with transparent, custom data and media options.

Q: As we look ahead to 2019 and beyond, what do you see as the biggest upcoming developments or trends for data?

First: leveraging first-party data

While not necessarily new, I’m very excited about the ongoing investment that advertisers, marketers and brands are making to incorporate first-party data into their marketing efforts. Leveraging CRM/first-party data alongside best-in-class third-party data provides broader options for segment creation and leveraging a brand’s organic customer base, allowing more intelligent engagement with all types of customers.

We also expect to see various types of look-a-like models being created from CRM seed data, with the objective of acquiring new customers who “look like” current ones, and building segments from unique seed sets to compare tactics.

Second: all the data…

People are complicated. We’re multi-dimensional, have various interests and all act individually. This complexity has affected the way advertisers think about identifying audiences, as using one targeting tactic isn’t always as impactful as leveraging multiple data types, and accounting for individual preferences or differences. For any advertiser, finding audiences that are both targeted and scalable is a constant balancing act. At PushSpring, we see an increasing number of advertisers leveraging multiple types of data instead of limiting themselves to just one data source. The ability to combine different targeting tactics allows true scale while maintaining the integrity of the desired audience.

So, you’re considering bringing your programmatic efforts in-house. That’s great! In-housing can help you save on costs, increase ROI and keep control of your data – and that’s just a few of its benefits.

But it can also raise some important questions, starting with a big one: How do you build your programmatic team? Attracting top talent is often one of the biggest hurdles brands face after making the decision to in-house programmatic. We’re here to help.

Below, the top interview questions to ask any prospective programmatic hires, and what can be learned from their answers.

Q: What kind of ad execution experience do you have, and was it on the demand side or supply side?

Why ask: You want to make sure, first and foremost, that any experienced programmatic hire has expertise in running media, either at an agency or in-house at another brand. Qualified candidates will understand auction dynamics, including supply and demand economics and real-time bidding.

Q: Which platforms are you comfortable with?

Why ask: Your interviewee should be able to talk competently about the DSPs, SSPs and ad servers they have worked with in the past. This will help you get an idea of the breadth of their experience and whether it matches up with your plans.

Q: Have you had experience working with a data management platform (DMP) or handling data in any way?

Why ask: Data is often extremely important in digital advertising, and must be handled securely as it is transferred between multiple entities (client to DMP to DSP, for example). You should be certain any hire has the capability to effectively manage large pushes of data so that no data loss occurs in the process, that way you can ensure the deterministic nature of your data remains intact.

Q: What kind of reporting experience do you have?

Why ask: Reporting is going to be very important as you bring your programmatic efforts in-house. Make sure any hires understand reach and frequency management, so that you can effectively make data-driven decisions – including making optimizations on the fly.

Q: Do you have experience managing creative?

Why ask:  Managing creative is so much more complex these days because advertisers no longer work with simple JPEG or GIF files. Instead, most display ads are JavaScript or HTML, and most video ads come in the form of VAST URLs/VAST tags. Make sure your prospective hire has a working knowledge of tag and pixel management so there are no issues with the creative flighting process.

Practically everyone understands first-party data, the information that you collected directly and own. The same can be said for third-party data, which lives at the other end of the spectrum: data from multiple external sources that you’ve purchased through an aggregator. The concepts behind both are straightforward and relatively intuitive.

But when it comes to second-party data … well, things aren’t as clear. But second-party data is valuable and should play a role in your advertising strategy. In a way, second-party data is the ideal balance between scale and precision. Allow us to explain.

In a perfect world, everyone would have a ton of first-party data available. After all, it’s valuable and fully transparent, as opposed to third-party data, which is often probabilistically determined and can raise questions about source, methodology, definitions and so forth. Unfortunately, however, first-party data doesn’t always scale. And that’s where second-party data can help you bridge the gap.

The best way to think of second-party data is as someone else’s first-party data. To put it simply, second-party data is any data purchased directly from the source. There’s no middle man, which means more validation, more transparency and more overall trust. As opposed to third-party data purchased from an aggregator, there’s accountability with second-party data. You know where exactly where it comes from, and you know who’s on the hook if things don’t work out right.

You can get second-party data by forming partnerships directly with other businesses, and plenty of marketers do. Viant’s data marketplace includes second-party data, as well, and always has.

Wondering just how Viant incorporates second-party data? When Viant acquires data from our partners, it’s matched one-to-one with our own audience data of 250 million registered users. When you leverage data through Viant, you can think of that data as our own first-party data, with attributes appended from companies like Experian, Acxiom and others to enrich our people-based consumer identity profiles. Our data comes right form the source and we take the extra step to validate it, something most others don’t.

The distinction between data types is more important to understand now than ever before, as cookies and probabilistic data continue to lose favor across the market. When evaluating data sources, it’s critical to recognize exactly what kind of offerings any potential partner is offering, so that you end up with data you can trust.

For more answers to questions about data type, Viant’s device graph and more, reach out to a specialist today

Before he was a Technical Producer at Viant, Adelphic’s parent company, Andy Neitzert spent four years in the Air Force in Texas, Florida and Missouri. Neitzert originally joined the service as a way to move away from home (like most 18-year-olds!), but soon realized the experience was much more than just a job.

In honor of Veterans Day, Neitzert discussed his four years in the Air Force, working with a B-2 Bomber and how civilians can best honor those who’ve served.

Q: Why did you decide to serve your country, and how did you decide on joining the Air Force?

Initially the reason was selfish. I was 18, I wanted out of my parents’ house and I didn’t want to have to spend any money or learn anything new to do it. Obviously, just a few weeks later those reasons had changed. The reason I chose the Air Force was because while I was pondering how to get out of town, I attended an Aerosmith concert where I sat next to two Airmen. They sold me on it by simply telling me I didn’t have to think about what I wore or have any job security concerns – coupled with the generous bonus I would receive upon completion of technical training.

Q: What was your role and what were your primary responsibilities?

I was what was called an Aerospace Maintenance Journeyman. Which, simply put, was an aircraft mechanic. I was assigned to a specific B-2 Bomber (The Spirit of Alaska) and I would do everything from keep up its paperwork to changing the oil to giving it a bath. I was also the one who marshalled the aircraft when they launched (the guy with the wands who salutes the pilot).

Q: Where did you travel while serving?

Although I fought to travel as much as possible, I only was able to see Texas, Florida, then Texas again, before finally settling in glorious Missouri. Which, coincidentally, was thousands of miles from my requested station. But, as luck would have it, the B-2 Bomber lives in Missouri.

Q: When you look back on your time in the Air Force, what stands out the most?

I look back on my time in the service much like many look back on high school: I could have been better at what I did. I could have been more active in my career instead of myself. In the end, the experience was amazing. I wouldn’t take it back for anything. It did take me a long time to acknowledge the actual effect my time in the served had on me, even though I never left the country.

Q: Is there anything you learned during your service that has helped you succeed in your role at Viant?

Military culture is very, very, very different from the open-office culture at Viant. You had orders, rules and regulations you had to follow. We had to wear the same thing every day and it had to be worn the same way every day. Your physical appearance down to your weight could determine a promotion. My time between the Air Force and Viant was interesting, though. I went to college, worked in interesting and fun career fields and never really had a structure that I didn’t make myself. So Viant is a good blend of what I’ve experienced over the last 20 years and I appreciate that.

Q: What does Veterans Day mean to you?

Veterans Day to me means taking the time to honor those whom I feel did more than I should have. I was 18-22 while I was in the service, and although it was only four years, they were formative. My “college years” were formed very differently from most. So I take this time to honor those who joined for unselfish reasons and fought for an unselfish cause.

Q: What do you recommend as the best way for civilians to observe Veterans Day?

There really isn’t one catch-all for honoring our veterans. Everyone looks back on their time differently. Some don’t want to talk about it, while some only want to talk about it. Some don’t consider themselves worthy of being honored. Some complain about how easy people have it today, mostly in part to the sacrifice they’ve made. So, in the end, if all you do is Google what is going on in Veterans’ lives today, there’s an endless list of issues they face as well as causes and organizations in place to help them on their varying paths. Find one that speaks to you and read up on it. Volunteer, donate, tell a friend. It all helps.

If you’re looking to contribute this Veterans Day, Andy’s favorite veterans charities are America’s Vet Dogs, which provides and trains service dogs for veterans, and Vet Tix, which donates tickets to veterans to events that help them remain engaged in their communities

Increasing the scale of viewable inventory is one of the biggest challenges facing today’s advertisers.

But did you know that machine learning can help solve it? In fact, our machine learning offering can increase viewable scale by 4x.

You’ve likely heard a lot about machine learning in recent months, as it’s among the industry’s hottest topics. Below, a taste of just how it can help increase viewable inventory and what you should know before considering whether to adopt it.

Q: What is Machine Learning?
Machine learning is the application of artificial intelligence to make data-driven predictions or decisions. By giving computers access to data, machine learning provides the ability to recognize patterns and learn the appropriate response for the future. The computer is able to perceive environments and take action to maximize the chance of successfully achieving a designated goal.

Q: What is Artificial Intelligence?
Artificial intelligence is the ability for computers to perform tasks that are traditionally considered ‘cognitive’ or representative of human intelligence such as decision-making, problem-solving, learning, visualization, language translation, and speech interpretation.

Q: What are the benefits to Machine Learning Viewability?
With a deeper understanding of each incoming bid request, Machine Learning Viewability aims to increase scale of viewable inventory when compared to using an IAS segment alone.
By increasing viewable impressions, advertisers are increasing the overall impression volume that are known to be visible and thereby likely to be seen by consumers. Additionally, by knowing how many ads are actually being seen allows advertisers to more precisely measure ad performance.

Q: What is Adelphic Machine Learning Viewability?
Adelphic, Viant’s DSP, utilizes machine learning to drive KPIs based on historical patterns and insight into performance to train real-time decisioning. Adelphic’s Machine Learning Viewability will determine whether an incoming bid request is desirable with likely access to a viewable impression by leveraging historical training and feedback related to previously observed, known viewable impressions.

According to eMarketer’s newly released report “U.S. Programmatic Ad Spending Forecast Update 2018,” programmatic advertising is digital display advertising. As we near the end of this year and beyond, the amount of spend dedicated to programmatic is only expected to increase.

Something else that is on the upswing as well? The movement toward in-housing, in which brands are bringing some or all of their programmatic efforts under their own rooves. It’s a conversation that won’t be going away anytime soon, according to on Schulz, CMO of Adelphic’s parent company Viant.

“More companies are building their sophistication outside of channeling their budgets,” Jon Schulz said. “They’re moving toward more holistic budgets. Since many media channels are digital, there’s measurement and attribution they can use to understand how it all works together.”

Schulz said he expects this to continue as brands look to centralize buying efforts and measure their endeavors more holistically.

Read more at eMarketer.com