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
IRI – Beet.TV https://dev.beet.tv The root to the media revolution Thu, 29 Jul 2021 14:58:42 +0000 en-US hourly 1 https://wordpress.org/?v=5.8.7 How Live Sales Data Changes Course Of Ads In-Flight: IRI’s Pelino On LoopMe Case Study https://dev.beet.tv/2021/07/how-live-sales-data-changes-course-of-ads-in-flight-iris-pelio-on-loopme-case-study.html Thu, 29 Jul 2021 11:31:40 +0000 https://www.beet.tv/?p=75266 If you could see, in near real-time, how well an ad campaign was driving sales, you might be able to recalibrate it in “mid-flight”.

That is what IRI, a consumer-packaged-goods (CPG) purchase data provider, is helping ad-tech companies and their ad buyers do.

In this video interview with Beet.TV, Jennifer Pelino, EVP of omni-channel media at IRI, explains how it works – and how an IRI partnership with ad-tech firm LoopMe helped a beverage brand hit big results.

The source of sales data

Founded to capitalise on the advent of point-of-sale (POS) terminal scanners, IRI grew to ingest purchase data from consumer-packaged-goods retailers across the US.

“Because of the data set, the loyalty card data, the scale that we have, which is the largest of this kind in the world, we’re able to understand what a consumer purchased off of habitual products, like a beverage, or a toothpaste, or fruit roll-ups, whatever you may think of,” Pelino says.

“We send that information on a weekly basis to LoopMe, in this particular case, in a data-compliant way that allows them to use that information and their technology from an AI perspective to help inform which consumers should get their advertisements.”

Pelion says that allows users to ascertain, for example, whether they should find lookalike audiences of consumers who recently bought a particular product.

Outcomes and speed

It is one more example of two trends that are becoming more commonplace in advertising:

  1. Closing the loop with actual purchase data, to help ad buyers figure out outcomes and true campaign effectiveness, rather than traditional proxies.
  2. Speeding-up the provision of such data, so that campaign changes can be made before the campaign has even ended, in pursuit of better results.

That is what IRI’s data has enabled for a beverage company, which Pelino did not name, together with LoopMe.

Thirsty for results

“They were able to understand the in-store sales performance by the tactic, and then use that for their own AI technology advances to enable that corporate conversion and data into those in-flight decisions, helping them to make better outcomes,” Pelino says.

“What we found was that, when we delivered the mobile in-app and web inventory across display, rich media, mobile (and) video – using this very tactic of what we call IRI’s ‘campaign conversion fee’ – we were able to see extraordinary results.

“We saw increased dollar-per-household sales lift by 40% and an increase in the delivered return on advertisement of $1.28, which is pretty incredible during that timeframe when we see that the category average benchmark is about 12%.

“We increased that benchmark by 12% versus the overall carbonated beverage category sales lift. So, (they are) really incredible results because we’re able to optimise on sales versus vanity metrics.”

Want to replicate that success? IRI’s Pelino says having and smartly leveraging first-party customer data is crucial for brands.

You are watching “Outcomes-Based Advertising: Connecting Ad Exposure to Business Results,” a Beet.TV leadership video series presented by LoopMe. For more videos, please visit this page

]]>
Beet.TV
Accountability Is Knowing Who Consumers Really Are: IRI’s Mehta https://dev.beet.tv/2018/07/nishat-mehta.html Thu, 12 Jul 2018 01:55:40 +0000 https://www.beet.tv/?p=54322 CANNES – IRI has almost 400 million reasons why television should no longer be planned and bought based on traditional age/gender metrics and related proxies. That’s the number of consumer loyalty cards the company can access to discern what virtually every U.S. household purchases offline.

But until recently, data from those cards has taken a back seat to the traditional buying and selling of TV ad inventory. According to Nishat Mehta, President of IRI’s Media Center of Excellence, the industry had been on a trajectory that simply wasn’t sustainable.

“The notion of accountability starts with making sure that the consumer was receiving what we thought was best for them, and then second that what we think is best for them is actually based on accurate knowledge of who that consumer is,” Mehta says in this interview with Beet.TV at the recent Cannes Lions International Festival of Creativity. “And I think we had been following a path where neither of those was really being met. That ultimately leads to a consumer who is angry at the advertising industry and ultimately will shut us off.”

Mehta considers the new European Union GDPR initiative to be a “multi-year effort to clean up the industry” and the challenges of Facebook and other digital companies as paving the way for needed changes. Namely, to take lessons from digital targeting and bring them to TV.

“We believe very strongly in the notion of optimizing linear TV,” he says.

And while he’s hardly the first to suggest that age/gender demos for TV targeting are past their prime, IRI is offering “a set of capabilities focused around data and accurate data to the market that allow television to now be bought on sold on what people actually do rather than what we think they do.”

This is where data from the nearly 400 million loyalty cards come in, representing about 110 million households. “We have significant penetration across virtually every household in the U.S. about the types of products that they actually purchase in the physical world,” says Mehta.

Asked to summarize his Cannes experience, he thinks it’s shifting more toward adtech and “a little bit away from the actual advertisers. I hope that’s not a trend we see going forward. I hope we do see some balance coming back.

“I think we need to continue to remind ourselves who we work for. At the end of the day, it’s the consumer represented by the advertiser and if we don’t watch out we’ll lose track of that.

This video is part of a series produced by Beet.TV at Cannes Lions 2018 about advertising accountability presented by Mediaocean. Please find more videos from this series here.

]]>
Beet.TV
Initiative’s Gilbert: As Live Content Grows, Digital Mirrors Linear TV https://dev.beet.tv/2018/05/adam-gilbert.html Thu, 10 May 2018 09:24:57 +0000 https://www.beet.tv/?p=51911 Premium content, a multitude of new partnerships and how brands can create authentic resonance with consumers are the “common threads and themes” that Initiative’s Adam Gilbert takes away from the Digital Content NewFronts 2018.

He also traces the arc of a digital content ecosystem that is in a sort of “retrograde” phase as live content becomes more prevalent amid the decline of linear television viewing.

“The mantra of the week: premium content at scale. Original content being produced by publishers, really in response to cultural trends,” Gilbert, who is Head of Digital, Midwest, says in this interview with Beet.TV.

It’s premium not just in the various big-name publishers that are generating content but also in the “production values that is elevating this content to a premium level.”

While many content partnerships were announced at this year’s NewFronts, they were accompanied by other collaborations, for example publisher-to-publisher and publisher-to-platform.

“As well as even partners such as Hulu trying to hold themselves more accountable through the likes of measurement partnerships with Nielsen, IRI as well as others,” says Gilbert. “That to me as a marketer, as an advertiser, as an agency lead is critical to defining success for the future ahead of our clients and brands.”

He also heard “the loud and continued cry towards personalization and creating authentic resonance with consumers, ultimately helping to also ensure brand safety along the way.”

Gilbert’s perspective includes a view of the marketplace for live content that for him suggests a “retrograde” of how the digital marketplace has been built and where it’s going.

“Digital video has really been build off of traditional both long-form and short-form content that gets uploaded and then lives in perpetuity,” he says.

This stands in contrast to linear TV, which has largely been live and which still draws “a wealth” of live audiences.

“In order to draw more audiences away from linear and traditional channels to digital platforms, we are seeing the likes of ESPN, Twitter and Facebook live. We also heard it last night at YouTube’s Brandcast is they’re continuing to double down with YouTube TV. So I expect we’ll continue to see that grow in the years ahead.”

This video is part of Beet.TV’s coverage of the Digital Content NewFronts 2018. The series a co-presentation of Beet.TV and the IAB. Please see additional videos from the series on this page.

]]>
Beet.TV
‘Bullish On Data Marketplace,’ Dentsu Aegis Adds IRI To M1 Platform https://dev.beet.tv/2018/04/anthony-laurenzo.html Wed, 04 Apr 2018 21:44:52 +0000 https://www.beet.tv/?p=50809 While there’s no shortage of data available for enhanced consumer targeting, some advertisers still cling to gross rating points and broad demographic targets. “Some clients are opting in a little bit more than others,” says Anthony Laurenzo, SVP, Non-Linear Video, Dentsu Aegis. “We’re starting a slow evolution away from age and gender demography to more strategic targets and even guaranteeing those strategic targets in certain instances.”

Dentsu Aegis has gone full throttle on its custom platform, M1, the most recent data integration being with IRI. As announced early last month, M1 will now allow custom audience creation utilizing IRI Verified Audiences and/or IRI ProScores audiences linked to first- and/or third-party data.

In this interview with Beet.TV, Laurenzo explains why he is bullish on current and emerging data sources like automatic content recognition.

“Audience buying is definitely where we want to get to as an industry. Anybody you speak to on both sides of the desk would probably say our reliance on age and gender demographics for transactional purposes is really outdated,” Laurenzo says. “We have all this data that can tell us who’s watching what content, why can’t we transact on those more granular targets?”

Agencies are still “very much held accountable” to segments like adults 18-49 and the price at which they can transact for gross rating points. “It’s ‘as long as you get me this price on this demographic then you’re doing okay’ versus I want you to buy the audience that we need to hit and then if that audience then goes and makes some sort of action.”

Laurenzo says there’s no shortage of audience-based television advertising inventory in the marketplace. “Every network group has their own audience-based platforms that we can leverage and they’re making a lot of inventory available through those platforms.”

The question is what’s the right data to use and when would you use it, according to Laurenzo.

“There are a lot of partners now with ACR technology and I think that’s great,” he says, citing Vizio, Samsung, Samba and Alphonso. “It’s really changing the game in terms of measurement.”

He cautions that despite the plethora of data available, “It’s muddy. Not all the data’s perfect. You have to really go through the methodology of how they’re collecting everything. But I’m actually bullish on the data marketplace.”

This video is part of a series The New Marketplace for Television Advertising, presented by dataxu. Please find more videos from the series here.

]]>
Beet.TV
IRI’s Mehta Helps Alphonso Follow TV Viewers To The Store https://dev.beet.tv/2018/03/iris-mehta-helps-alphonso-follow-tv-viewers-to-the-store.html Mon, 12 Mar 2018 20:07:13 +0000 https://www.beet.tv/?p=50233 SAN FRANCISCO — Often, the end goal for a TV advertisement is to drive a consumer to purchase a product in a store. But what if the point of purchase was the start, not the end, of the whole strategy?

That’s a question IRI, a marketing data company, is posing to advertisers.  Founded to capitalise on the advent of point-of-sale (POS) terminal scanners, IRI grew to ingest purchase data from consumer-packaged-goods retailers across the US.

At this point, it takes data from almost every POS transaction in the country, through knowledge of 350 million loyalty cards from 107 million households.

“We have multiple retailers in each household – it’s not just your grocery spend, but it’s your drug spend, it’s your specialty alcohol spend, it’s some of your club spend,” says IRI’s Nishat Mehta, in this video interview with Beet.TV.

What does that mean for brands? Mehta pitches that data as a chance to “measure whether or not they’re advertising actually worked, and what components of it worked best”.

Last year, IRI struck a deal with Alphonso, a company whose technology helps brands use internet-delivered TV advertising to spark interest – and track an actual offline purchase later down the line.

“We now have a panel of roughly about 14 million households for which we actually know their purchase behavior, and their television viewing behavior,” Mehta adds.

“That gives us an opportunity… to get down to the smallest of brands, to the fewest of exposures, to the lowest of frequencies, to the long tail of networks. Identifying …when (consumers) actually go to a store the following weekend to by their peanut butter, did the ad for Skippy actually have an impact? Is it that this household needs three views of the ad before it actually has an impact?

“Advanced TV certainly means that TV is not going anywhere soon.”

This video is part of a series produced in San Francisco at the RampUp 2018 conference. The series is sponsored by Alphonso. For more videos from the series, please visit this page.

]]>
Beet.TV
Alphonso And IRI Data Match Produces Scale For TV Attribution, Informs Digital Campaigns https://dev.beet.tv/2018/03/raghu-kodige.html Wed, 07 Mar 2018 17:57:59 +0000 https://www.beet.tv/?p=50165 SAN FRANCISCO – Matching IRI purchase data for 100+ million households with television ad exposure data from Alphonso’s 34 million household penetration produces “the missing piece” of multi-touch attribution. What finishes the puzzle is 12 million common households and more ways that TV can help to inform digital.

“We’re seeing a full circle here where digital used to influence TV,” says Raghu Kodige, Alphonso’s Chief Product Officer & Co-Founder.

Kodige was one of the speakers at this week’s RampUp 2018 conference by LiveRamp, which drew nearly 3,000 attendees. In this interview with Beet.TV, he details some of the work Alphonso has been doing with IRI, which has the largest database of shopper loyalty data.

To determine how television ads are working, Alphonso used the occasion of the 2018 Super Bowl to do some research based on data from a year earlier leading up to and including Super Bowl 2017. It involved a few different brands that were regular Super Bowl spenders.

For McDonald’s and Dunkin Donuts, Alphonso used location data to track post-ad store traffic. Working with IRI, it was able to attribute TV ad exposure to SKU movement, looking for lift before and after the big football game.

“We were trying to identify what kind of trends you see prior to the Super Bowl and after the Super Bowl. It was pretty exciting,” says Kodige.

One of the things that stood out was the amount of spending by Dunkin Donuts to influence Hispanic audiences on Spanish-language TV networks, particularly in the months ahead of the Super Bowl.

“We saw almost a twelve percent increase in foot traffic to Dunkin Donuts in the three weeks following the Super Bowl, which I thought was pretty significant considering that the Super Bowl reaches such a wide audience.”

Alphonso and IRI announced their data partnership in February 2018.

Alphonso’s research also uncovered insights into things like optimum TV frequency.

The 12 million households common to IRI and Alphonso produce data that facilitates TV tune-in attribution and sales attribution “down to the creative level,” says Kodige. If a brand is testing multiple creative iterations, “within a few weeks we start seeing this data flow into our dashboards with the IRI partnership” so that creative optimization can be done while the campaign is still in-flight, he adds.

The scale is such that it fills the gap in true, multi-touch attribution, according to Kodige. “The missing piece in most of these studies that have happened to date is the absence of large scale TV data.”

This video is part of a series produced in San Francisco at the RampUp 2018 conference. The series is sponsored by Alphonso. For more videos from the series, please visit this page.

]]>
Beet.TV