Deprecated: Return type of WP_Theme::offsetExists($offset) should either be compatible with ArrayAccess::offsetExists(mixed $offset): bool, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-theme.php on line 554

Deprecated: Return type of WP_Theme::offsetGet($offset) should either be compatible with ArrayAccess::offsetGet(mixed $offset): mixed, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-theme.php on line 595

Deprecated: Return type of WP_Theme::offsetSet($offset, $value) should either be compatible with ArrayAccess::offsetSet(mixed $offset, mixed $value): void, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-theme.php on line 535

Deprecated: Return type of WP_Theme::offsetUnset($offset) should either be compatible with ArrayAccess::offsetUnset(mixed $offset): void, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-theme.php on line 544

Deprecated: Return type of WP_REST_Request::offsetExists($offset) should either be compatible with ArrayAccess::offsetExists(mixed $offset): bool, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/rest-api/class-wp-rest-request.php on line 960

Deprecated: Return type of WP_REST_Request::offsetGet($offset) should either be compatible with ArrayAccess::offsetGet(mixed $offset): mixed, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/rest-api/class-wp-rest-request.php on line 980

Deprecated: Return type of WP_REST_Request::offsetSet($offset, $value) should either be compatible with ArrayAccess::offsetSet(mixed $offset, mixed $value): void, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/rest-api/class-wp-rest-request.php on line 992

Deprecated: Return type of WP_REST_Request::offsetUnset($offset) should either be compatible with ArrayAccess::offsetUnset(mixed $offset): void, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/rest-api/class-wp-rest-request.php on line 1003

Deprecated: Return type of WP_Block_List::current() should either be compatible with Iterator::current(): mixed, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 151

Deprecated: Return type of WP_Block_List::next() should either be compatible with Iterator::next(): void, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 175

Deprecated: Return type of WP_Block_List::key() should either be compatible with Iterator::key(): mixed, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 164

Deprecated: Return type of WP_Block_List::valid() should either be compatible with Iterator::valid(): bool, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 186

Deprecated: Return type of WP_Block_List::rewind() should either be compatible with Iterator::rewind(): void, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 138

Deprecated: Return type of WP_Block_List::offsetExists($index) should either be compatible with ArrayAccess::offsetExists(mixed $offset): bool, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 75

Deprecated: Return type of WP_Block_List::offsetGet($index) should either be compatible with ArrayAccess::offsetGet(mixed $offset): mixed, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 89

Deprecated: Return type of WP_Block_List::offsetSet($index, $value) should either be compatible with ArrayAccess::offsetSet(mixed $offset, mixed $value): void, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 110

Deprecated: Return type of WP_Block_List::offsetUnset($index) should either be compatible with ArrayAccess::offsetUnset(mixed $offset): void, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 127

Deprecated: Return type of WP_Block_List::count() should either be compatible with Countable::count(): int, or the #[\ReturnTypeWillChange] attribute should be used to temporarily suppress the notice in /home/superbeet/dev.beet.tv/wp-includes/class-wp-block-list.php on line 199

Deprecated: DateTime::__construct(): Passing null to parameter #1 ($datetime) of type string is deprecated in /home/superbeet/dev.beet.tv/wp-includes/script-loader.php on line 333

Deprecated: trim(): Passing null to parameter #1 ($string) of type string is deprecated in /home/superbeet/dev.beet.tv/wp-includes/class-wp.php on line 173

Deprecated: ltrim(): Passing null to parameter #1 ($string) of type string is deprecated in /home/superbeet/dev.beet.tv/wp-includes/wp-db.php on line 3030

Warning: Cannot modify header information - headers already sent by (output started at /home/superbeet/dev.beet.tv/wp-includes/class-wp-theme.php:9) in /home/superbeet/dev.beet.tv/wp-includes/feed-rss2.php on line 8
Kelly Metz – Beet.TV https://dev.beet.tv The root to the media revolution Tue, 28 Sep 2021 05:26:05 +0000 en-US hourly 1 https://wordpress.org/?v=5.8.7 Nine Things We Learned From Our CTV Data Series presented by Sabio https://dev.beet.tv/2021/09/nine-things-we-learned-from-our-ctv-data-series-presented-by-sabio.html Tue, 28 Sep 2021 12:00:45 +0000 https://www.beet.tv/?p=75913 In recent years, the prevalence of audience data has revolutionized the ability to target digital advertising.

But now the set of capabilities and consequences produced by that data is changing shape.

What will the future look like? That is what “Data: Powering CTV for Marketers,” our recent Beet.TV leadership series presented by Sabio, set out to uncover.

In these highlights, hear the takes of nine advertising executives on the issue.

1. Mobile brings a TV boost

Joao Machado, marketing SVP at Sabio, a company which powers connected TV ads using mobile data, says the combination is a win.

“The mobile device is the perfect mirror of a person’s affinities, their likes, where they are in their life stages,” Machado says. He wants to “couple it with the promise of what CTV digital television offers”.

Reborn, QR Codes Are The Glue Between Mobile & TV: Sabio’s Machado

2. TV is getting richer

When it comes to new-wave TV, AJ Kinter, head of advanced video strategy at Publicis Media Exchange (PMX), says the opportunities are burgeoning.

Kinter draws a distinction between “programmatic CTV” and “direct CTV”. “Since the CPMs have started to become much closer to programmatic CTV, you now have a linear, addressable TV and programmatic CTV kind of range in the same type of CPM,” he says.

Data Tell Story of Changing Viewership Habits: PMX’s AJ Kintner

3. Fusing media and mobile

Device data needs to inform media buys. That is why Aziz Rahim, Sabio CEO, says his company also started an app analytics division.

“Sabio is focusing on the media aspect of the industry, providing a deeper, unique targeting, reach and capabilities, and then along with creative capabilities,” he says. “The App Science side is to provide agnostic analytics and insights on CTV and OTT, along with mobile campaigns.”

After IDFA, Mobile Is Identity Gold For CTV: Sabio & App Science’s Rahim

4. Double-down on de-duplication

Ad buyers need to avoid exposing consumers to the same ad across multiple devices, says Dave Kersey, executive media director at GSD&M.

“Duplication is certainly a challenge in the industry,” Kersey says. “(We need to be) understanding the entire consumer journey across all video platforms.”

Mobile Data Help to Avoid Ad Duplication: GSD&M’s Dave Kersey

5. Data helps post-pandemic ad recovery

At MBuy, a unit of Mediaocean, media strategy and operations SVP Michael Parent is using data to welcome back travel brands that want to resume spending.

“We’re taking the data that we’re getting — everything from geography to programming to dayparts to the response that we’re getting,” Parent says.

CTV Data Provide More Insights for Ad Targeting: MBuy’s Michael Parent

6. Real-time duplication monitoring

At Sabio’s App Science, EVP Helen Lum says ad duplication is starting to worry more ad buyers.

“I think a good way to solve for that is actually to track and reduce that duplication and monitor that reach and frequency across partners and publishers, so that advertisers can reinvest those wasted dollars in real-time for their buys,” Lum says.

CTV Offers Faster Data Insights Than Linear TV: App Science’s Helen Lum

7. Mobile is the key to e-commerce

Mobile is evolving toward becoming an e-commerce driver for TV ads, says Jeff Liang, head of digital product at WPP’s MediaCom.

“We’ll eventually get to a point where we’ll be able to allow for comparison shopping on CTV and give consumers the ability to transact within that single remote device rather than driving people to their mobile phones,” Liang predicts.

Mobile Data Enable Audience Targeting on CTV: MediaCom’s Jeff Liang

8. Understand TV & mobile together

It’s no longer an “either-or”. Kelly Metz, managing director of linear activation at Omnicom Media Group, says ad planners must understand how consumers use mobile and TV in tandem.

“The way we choose to manage that or support that from a planning perspective is by emphasizing holistic campaign planning and holistic campaign measurement,” she says.

Mobile, TV Data Provide Holistic Audience Insights: Omnicom Media Group’s Kelly Metz

9. TV can target the right patient

The ability to target TV ads can revolutionise healthcare advertising, according to Starcom’s EVP Melissa Gordon-Ring.

“We can double-down on things like connected television or addressable television, and have a higher likelihood of reaching our patient in their household, versus hoping that this is the right target audience for us to be purchasing against,” she says.

Mobile Data Support Personalized Healthcare Marketing: Starcom’s Melissa Gordon-Ring

You are watching “Data: Powering CTV for Marketers,” a Beet.TV leadership series presented by Sabio. For more videos, please visit this page.

]]>
Beet.TV
Mobile, TV Data Provide Holistic Audience Insights: Omnicom Media Group’s Kelly Metz https://dev.beet.tv/2021/05/mobile-tv-data-provide-holistic-audience-insights-omnicom-media-groups-kelly-metz.html Thu, 27 May 2021 12:34:24 +0000 https://www.beet.tv/?p=74036 LOS ANGELES – Marketers can harness a combination of TV viewership and mobile usage data to gain a better understanding of how to engage consumers. Those insights are crucial to developing a media plan and making adjustments as needed.

“Consumers are watching TVs and engaging with their mobile phones simultaneously as they’re engaging with our ad experiences,” Kelly Metz, managing director of linear activation at Omnicom Media Group, said in this interview with Beet.TV. “The way we choose to manage that or support that from a planning perspective is by emphasizing holistic campaign planning and holistic campaign measurement.”

With many consumers watching TV while looking at their smartphones at the same time, advertisers have more sources of data to help understand how their ads are seen.

“All of that factors into mobile data, TV data coming together to derive insights and make those better planning decisions and measurement decisions,” Metz said. “The use case for mobile data is to have more effective plans. We need to understand mobile ad exposure in the home to truly understand influence of the advertising campaign and the influence of the different screens.”

Advertisers have reason to be optimistic about the pace of innovation, though Metz cautions that the amount of data generated by consumers can create conflicting signals.

“There’s a certain realization that signals will never be in perfect harmony. Anyone who’s ever dealt with data, and we know big data really well, frequently you get conflicting signals,” she said. “It’s about really embracing the fact that signals will contradict. Signals will be bad, and you have to have the right data infrastructure and approach and the flexibility to be able to address that.”

The pandemic led to a dramatic shift in viewing habits, with many people sampling the programming on streaming platforms as they spent more time stuck at home. The cord-cutting trend accelerated as more households connected their TVs directly to the internet.

“We were prepared for these changes. We just expected them to happen at a slower rate,” Metz said. “The key is to focus on that cross-screen consumer engagement, and to enable planning insights across screens.”

While audience data are vital to media planning, marketers also need to be mindful that they’re using the information in a way that’s considerate of consumers.

“You’ve got to start with the right data. You’ve got to clean that data, and you’ve got to make sure that you’re 100% compliant with everything the consumer would want you to do, to be respectful of that data use,” Metz said.

You are watching “Data: Powering CTV for Marketers,” a Beet.TV leadership series presented by Sabio. For more videos, please visit this page.

]]>
Beet.TV
During Turmoil, Out-Spend Your Rivals: VideoAmp’s Metz https://dev.beet.tv/2020/07/to-soar-out-of-covid-19-out-spend-your-rivals-videoamps-metz.html Mon, 13 Jul 2020 11:52:21 +0000 https://www.beet.tv/?p=67470 US digital ad spend will slow from a previously-projected 17% growth this year to just 1.7%, as brands tighten their purse strings amid the COVID-19 pandemic, according to eMarketer.

But some executives think bold spending at a time when rivals are cutting back could help some brands emerge out of this period in the lead.

“Right now, what is really, really necessary is to understand how your competitors are approaching the same challenge, how they’re executing in linear, so that you can make better decisions about what you’re going to do,” says Kelly Metz, VP Product Marketing at VideoAmp.

“Everyone in this industry knows that those who advertise in downturns come out of the downturn in a much better place with much higher market share.”

Optimize investment

That is why VideoAmp just launched Competitive Insights, a platform which lets ad buyers see the effectiveness of their own TV ad spend, as well as that of their rivals.

In Competitive Insights, ad buyers can see the household reach and frequency of linear TV ads by target audience, plotted against selected competitors. They can compare their spend against rivals and use those insights to further optimize their linear TV investment.

For Metz, understanding your share of voice, and acting on it, is about getting smarter.

“In the time of COVID … you’ve got your advertisers sitting on the fence… do they buy? Do they not buy?,” she says.

“So I think now, more than ever, you inside the agency need to be using this type of data to advise your clients when to be in market and when to be out of market. You need to understand what’s happening vis-a-vis the entire competitive set.”

Linear smarts

VideoAmp’s offer is one way in which software and data these days is bringing smarts to even linear TV ad buying and measurement.

Metz hopes the system will include digital ad buying. But that’s a “future goal”. For now, it leverages set-top box and other TV viewing data that VideoAmp says it “commingles”. That includes linear TV datasets plus spot schedule and spend data from Kantar.

Such tools can help ad buyers understand details including audience by show, day part and network.

“Instead of women (aged) 18 to 49, they are able to actually understand women who own dogs, as an example, and target them very specifically and understand how their campaign’s performing specifically against that target,” Metz says.

Finding spend

If such efforts can increase effectiveness, they may encourage sustained spending in the marketplace. After all, linear ad channels are reckoned to fare worse than digital channels through the pandemic.

EMarketer forecasts buyers’ new reluctant and lack of long-term planning ability will wipe 27% of the this year’s US TV ad sales upfront season, some $5.5 billion.

“In H2, brands will cut a significant share of TV upfront ad spending due to difficult economic conditions,” according to the company.

“Without clarity into whether business operations will be stable later in the year, brands are planning less of their TV buying in advance, which normally gives advertisers about half a year to plan a campaign, and will likely rely on inventory purchased within much shorter time horizons (scatter and digital).”

How Has the US Upfront TV* Ad Spending Forecast Changed? (billions, 2018-2022)

]]>
Beet.TV