Press Brands Lean On New Attribution Tech – Just Don’t Call It MTA – As Budgets Split To New Channels
A rose by any name will smell as sweet, sure. But attribution by any name doesn’t work the same.
Marketers are trying to figure out how their ad budgets are actually working for them. Just don’t call it multitouch attribution (MTA). Or perhaps don’t call it attribution at all.
Madan Bharadwaj, Co-Founder and CTO of Measured, a startup offering marketing measurement and incrementality testing (just don’t call it multitouch attribution), said he uses “attribution 2.0.” But that that nomenclature is being shot down too. The company is moving more toward framing campaign measurement as “contribution reporting” rather than attribution, he said.
“Contribution reporting” helps marketers understand that the analytics chronicle an overall channel’s contribution to sales, rather than attribution reports that assign credit to individual impressions or close the loop on specific customer journeys.
Parachute, the bedding and home décor brand, began working with Measured in late 2020 largely because of the company’s jaded (or experienced, if you prefer) take on data-driven attribution, said VP of Growth Ian Yung.
“One reason why I actually went with Measured as opposed to some of the other players was that they were likewise explicit in their belief that MTA [multitouch attribution] is not the best approach,” Yung said.
Call it what you want, the problem of channel-based incremental testing is becoming more important. Measured raised $21 million last week, as it expands in the post-attribution attribution category, alongside other startups like Triple Whale, which raised $24 million a month ago, and Northbeam that both pitch commerce and ad analytics for performance marketing.
One plus one equals 15
Parachute hired Yung as VP of Growth in early 2020, when the company was on the fence between building or renting an advanced ad analytics toolkit.
“[Measured] had done a lot of the work that was on my road map for a homegrown solution, so we decided to bring them on board,” Yung said.
Parachute’s problem was that the marketing performance data showing up in campaign reporting “cannot be true,” he said. “With what Google’s saying, what Facebook is saying, etc., it’s like one plus one equal 15, because we see that there aren’t that many sales coming in.”
One social media platform stuck out as an early win for Measured, according to Yung. Parachute was spending in the low six figures per month on the platform. “And they were obviously giving us reporting that it was very profitable.”
Running an incrementality test with Measured, the brand saw that it could cut that spend to zero with next to no impact on sales. Ouch. (The name of the social platform in question was not disclosed, except that it’s a publicly traded company.)
Podcast advertising is another category that Parachute rethought once it had a measurement testing regime in place.
Podcast attribution often banks on listeners redeeming a particular code, which under-credits the channel. “Podcasting is one [rarer] example where we have to take the reporting and increase what it has on our end to capture the true value,” he said.
Another channel that underreports conversions is TiKTok.
“We haven’t figured out exactly what the right playbook is with TikTok,” he said. “We’re maybe 50% to 60% of the way there in terms of how to best use that channel. We’re still trying to refine that last piece, which is the coefficient that we need to apply to truly capture the value of TikTok.”
Splitting the media pie
The clothing brand Faherty began working with Measured three years ago, starting with incrementality tests of Google, paid social advertising and direct mail. Since then, the company has brought in native display ads, newsletter and email advertising, its affiliate marketing program, streaming audio, traditional radio and TikTok, said founder and CEO Alex Faherty.
Before 2020, particularly prior to Apple’s iOS 14.5 rollout, many digital-native brands relied on Facebook and a Google search strategy to scale, he said, while other channels were relegated to the margins of the media plan.
“Now people are moving to a more diversified media mix,” Faherty said. Rather than Facebook and Instagram accounting for half or more of ad spend and most of the rest going to Google, and programmatic and other platforms contending for some 10-20% share, the new world of media buying probably has Google and Facebook chopping up half the pie, with more platforms or channels earning their own 10% or so slice, he predicted.
Incremental gains
Incrementality testing can reveal unexpected results, which occasionally can test the “art and science” approach by the brand marketer, Faherty said.
The Parachute brand saw a similar effect: one social channel with a multi-million-dollar annual budget was worth practically nothing and podcast ads, which look terrible in the analytics dashboard, actually pull more than their own weight.
For Faherty, one major question was the value of its print catalog – a glossy direct mail strategy the company invested heavily in early on.
“The science was telling us when we did incrementality measurements that the economics of the channel were not as good as we expected,” Faherty said.
The company shifted budget to digital channels rather than the catalog, which is expensive to print and ship. Rather than ditch the catalogue altogether, the company changed its approach to a brand marketing and retention play. Parachute repositioned direct mail from a performance-first channel driving new customers to a targeted offer for known customers – a shift in mindset and ROI expectations that put the channel more in line with its incremental contributions.
Podcasting, on the flip side, had poor attribution in the Google Analytics dashboard, but turned out to be a strong contributor when the company ran post-purchase surveys. There was no digital data point or trackable impression that credited podcasts with conversions, but it became clear that podcast ads read by the hosts resonated with potential customers and came up again and again in post-purchase surveys.
The host-read ads were quickly sinking in and helping shape shopper choices, he said. Just not in a way that was easily credited by attribution tech.
“That’s the art and science of showing what’s an ROI-positive channel,” he said.
A rose by any name will smell as sweet, sure. But attribution by any name doesn’t work the same.
Marketers are trying to figure out how their ad budgets are actually working for them. Just don’t call it multitouch attribution (MTA). Or perhaps don’t call it attribution at all.
Madan Bharadwaj, Co-Founder and CTO of Measured, a startup offering marketing measurement and incrementality testing (just don’t call it multitouch attribution), said he uses “attribution 2.0.” But that that nomenclature is being shot down too. The company is moving more toward framing campaign measurement as “contribution reporting” rather than attribution, he said.
“Contribution reporting” helps marketers understand that the analytics chronicle an overall channel’s contribution to sales, rather than attribution reports that assign credit to individual impressions or close the loop on specific customer journeys.
Parachute, the bedding and home décor brand, began working with Measured in late 2020 largely because of the company’s jaded (or experienced, if you prefer) take on data-driven attribution, said VP of Growth Ian Yung.
“One reason why I actually went with Measured as opposed to some of the other players was that they were likewise explicit in their belief that MTA [multitouch attribution] is not the best approach,” Yung said.
Call it what you want, the problem of channel-based incremental testing is becoming more important. Measured raised $21 million last week, as it expands in the post-attribution attribution category, alongside other startups like Triple Whale, which raised $24 million a month ago, and Northbeam that both pitch commerce and ad analytics for performance marketing.
One plus one equals 15
Parachute hired Yung as VP of Growth in early 2020, when the company was on the fence between building or renting an advanced ad analytics toolkit.
“[Measured] had done a lot of the work that was on my road map for a homegrown solution, so we decided to bring them on board,” Yung said.
Parachute’s problem was that the marketing performance data showing up in campaign reporting “cannot be true,” he said. “With what Google’s saying, what Facebook is saying, etc., it’s like one plus one equal 15, because we see that there aren’t that many sales coming in.”
One social media platform stuck out as an early win for Measured, according to Yung. Parachute was spending in the low six figures per month on the platform. “And they were obviously giving us reporting that it was very profitable.”
Running an incrementality test with Measured, the brand saw that it could cut that spend to zero with next to no impact on sales. Ouch. (The name of the social platform in question was not disclosed, except that it’s a publicly traded company.)
Podcast advertising is another category that Parachute rethought once it had a measurement testing regime in place.
Podcast attribution often banks on listeners redeeming a particular code, which under-credits the channel. “Podcasting is one [rarer] example where we have to take the reporting and increase what it has on our end to capture the true value,” he said.
Another channel that underreports conversions is TiKTok.
“We haven’t figured out exactly what the right playbook is with TikTok,” he said. “We’re maybe 50% to 60% of the way there in terms of how to best use that channel. We’re still trying to refine that last piece, which is the coefficient that we need to apply to truly capture the value of TikTok.”
Splitting the media pie
The clothing brand Faherty began working with Measured three years ago, starting with incrementality tests of Google, paid social advertising and direct mail. Since then, the company has brought in native display ads, newsletter and email advertising, its affiliate marketing program, streaming audio, traditional radio and TikTok, said founder and CEO Alex Faherty.
Before 2020, particularly prior to Apple’s iOS 14.5 rollout, many digital-native brands relied on Facebook and a Google search strategy to scale, he said, while other channels were relegated to the margins of the media plan.
“Now people are moving to a more diversified media mix,” Faherty said. Rather than Facebook and Instagram accounting for half or more of ad spend and most of the rest going to Google, and programmatic and other platforms contending for some 10-20% share, the new world of media buying probably has Google and Facebook chopping up half the pie, with more platforms or channels earning their own 10% or so slice, he predicted.
Incremental gains
Incrementality testing can reveal unexpected results, which occasionally can test the “art and science” approach by the brand marketer, Faherty said.
The Parachute brand saw a similar effect: one social channel with a multi-million-dollar annual budget was worth practically nothing and podcast ads, which look terrible in the analytics dashboard, actually pull more than their own weight.
For Faherty, one major question was the value of its print catalog – a glossy direct mail strategy the company invested heavily in early on.
“The science was telling us when we did incrementality measurements that the economics of the channel were not as good as we expected,” Faherty said.
The company shifted budget to digital channels rather than the catalog, which is expensive to print and ship. Rather than ditch the catalogue altogether, the company changed its approach to a brand marketing and retention play. Parachute repositioned direct mail from a performance-first channel driving new customers to a targeted offer for known customers – a shift in mindset and ROI expectations that put the channel more in line with its incremental contributions.
Podcasting, on the flip side, had poor attribution in the Google Analytics dashboard, but turned out to be a strong contributor when the company ran post-purchase surveys. There was no digital data point or trackable impression that credited podcasts with conversions, but it became clear that podcast ads read by the hosts resonated with potential customers and came up again and again in post-purchase surveys.
The host-read ads were quickly sinking in and helping shape shopper choices, he said. Just not in a way that was easily credited by attribution tech.
“That’s the art and science of showing what’s an ROI-positive channel,” he said.
Original Publisher
AdExchanger
Ready to see how trusted measurement can help your brand make smarter media decisions?
Press Facebook Advertisers Are Itching For Change As Bugs Infest Its Attribution Tech
Facebook marketer Rok Hladnik awoke last Thursday to discover that more than half of the 140 Facebook ad accounts he operates had been randomly turned off. The week before, the campaigns were overspending in the wee hours of the morning, when they should have been dormant.
2021 was the year of the cicada swarms in the US. But the bugs have come for the metaverse this year, apparently.
Hladnik, founder and CEO of a boutique performance agency that specializes in social media and DTC brands, is one of many Facebook advertising specialists who are dealing with a new, bug-ridden platform instead of the money-making, flywheel-spinning machine that they’re accustomed to using.
After the bugs crop up, the issues are usually resolved within a day after Hladnik’s agency, Flat Circle, surfaces the issue to its Facebook rep, he said. “They’re making backend changes and are responding to how that messes up campaigns.”
But when campaigns are derailed by bugs on the regular, trust is lost.
Facebook advertisers have treated the platform and Google as essentially “sources of truth,” said Madan Bharadwaj, co-founder and CTO of the ad attribution company Measured. But in the past six to 12 months, he said, “they’ve almost all accepted that that’s no longer the case.”
Facebook bugs put attribution and agency companies in a tough spot, though. Marketers are used to judging campaigns by Facebook reports. Nowadays, those reports may show dramatic fluctuations in targeting or return on ad spend. A couple years ago, those fluctuations would be a sign that something strange was happening with the campaign targeting or creative, or perhaps the landing page being linked to.
In other words, Facebook campaign reports pointed the marketer to something that they, not Facebook, should address.
But wild fluctuations are now the norm for Facebook attribution reports and may not say anything about the campaign, other than that Facebook is tinkering with its own machinery as it figures out a new attribution system.
“The biggest issue is communication,” Hladnik said.
Facebook is heads-down trying to fix the ad platform as gears and springs fly out of it like a cartoon pocket watch.
To be fair, Facebook did warn advertisers and ad tech partners that this year would be a mess and that it’s using more modeled attribution, rather than attributing actual conversions.
But Facebook can do more to help its partners through this difficult course correction, said David Herrmann, a social advertising consultant.
For one thing, it’s clear that when Facebook works on platform updates, their own tinkering causes a cascade of weird outputs in ad campaign reports, Herrmann said. Facebook can warn agencies or ad buyers which specific days it will work on platform upgrades, for instance.
“It makes it very hard to manage expectations [with clients],” Hladnik said, echoing Herrmann’s concerns.
Marketers are focused on meeting their goals and often aren’t hands-on practitioners aware of the nuances of different ad platforms.
If the ad buyer can alert the brand that Facebook is working on the backend and to anticipate strange results these days, it can relieve the tensions on some difficult, urgent calls when the reports come in with bizarre numbers.
Another big problem is the delay on reporting data. With its third-party pixel and SDK network, Facebook used to pick up practically every visit or conversion to another site or app. That data was fed in real time to campaign reports.
Now data comes in large batches that upload for thousands of accounts simultaneously every two or three days, Hladnik said.
Again, Facebook did warn advertisers to expect slow reporting and not to optimize campaigns without a few days to build up a level of data so that the platform can model results.
And some advertisers are less keenly affected. Larger brands, particularly with higher-priced items, are less affected by Facebook’s upheaval, Hladnik said.
Toyota’s profit margin does not hinge on the Facebook ad platform, and a massive brand with a diversified ad budget, like McDonald’s, is relatively unaffected by a two or three-day delay on reporting.
But the mechanics of Facebook’s ad platform are built into many ecommerce businesses. Startup or smaller niche brands succeeded on Facebook partially because they are big tinkerers themselves. They target carefully, change spend levels and optimize more often, because they need to slice and dice platform audiences to find those perfect prospects.
Facebook’s consistent response has been to be patient and, well, to slow down. In February, Facebook acknowledged that it was still underreporting attribution, but said it had cut the error margin from 15% to 8%.
Says who?
If every time the Facebook ad platform butterfly flaps its wings, a tsunami hits the attribution reports, then ad buyers are going to stop trusting Facebook data or promises of performance improvement.
The tools Facebook is building to fix the black box ad platform are an even darker box, Herrmann said. “What are they doing to earn the trust of media buyers or publishers?” Because Facebook doesn’t provide details on what’s being worked on or fixed in the background, even as that work swings ad campaign performance.
Even more than Google, Facebook has built its ad dominance on the idea that its data and algorithms are the best on the market, according to Hladnik. You didn’t have to trust Mark Zuckerberg; Advertisers trusted Facebook results.
“But that’s not the case anymore. You cannot trust the data,” he said. “It makes me question the data from before too.”
Facebook marketer Rok Hladnik awoke last Thursday to discover that more than half of the 140 Facebook ad accounts he operates had been randomly turned off. The week before, the campaigns were overspending in the wee hours of the morning, when they should have been dormant.
2021 was the year of the cicada swarms in the US. But the bugs have come for the metaverse this year, apparently.
Hladnik, founder and CEO of a boutique performance agency that specializes in social media and DTC brands, is one of many Facebook advertising specialists who are dealing with a new, bug-ridden platform instead of the money-making, flywheel-spinning machine that they’re accustomed to using.
After the bugs crop up, the issues are usually resolved within a day after Hladnik’s agency, Flat Circle, surfaces the issue to its Facebook rep, he said. “They’re making backend changes and are responding to how that messes up campaigns.”
But when campaigns are derailed by bugs on the regular, trust is lost.
Facebook advertisers have treated the platform and Google as essentially “sources of truth,” said Madan Bharadwaj, co-founder and CTO of the ad attribution company Measured. But in the past six to 12 months, he said, “they’ve almost all accepted that that’s no longer the case.”
Facebook bugs put attribution and agency companies in a tough spot, though. Marketers are used to judging campaigns by Facebook reports. Nowadays, those reports may show dramatic fluctuations in targeting or return on ad spend. A couple years ago, those fluctuations would be a sign that something strange was happening with the campaign targeting or creative, or perhaps the landing page being linked to.
In other words, Facebook campaign reports pointed the marketer to something that they, not Facebook, should address.
But wild fluctuations are now the norm for Facebook attribution reports and may not say anything about the campaign, other than that Facebook is tinkering with its own machinery as it figures out a new attribution system.
“The biggest issue is communication,” Hladnik said.
Facebook is heads-down trying to fix the ad platform as gears and springs fly out of it like a cartoon pocket watch.
To be fair, Facebook did warn advertisers and ad tech partners that this year would be a mess and that it’s using more modeled attribution, rather than attributing actual conversions.
But Facebook can do more to help its partners through this difficult course correction, said David Herrmann, a social advertising consultant.
For one thing, it’s clear that when Facebook works on platform updates, their own tinkering causes a cascade of weird outputs in ad campaign reports, Herrmann said. Facebook can warn agencies or ad buyers which specific days it will work on platform upgrades, for instance.
“It makes it very hard to manage expectations [with clients],” Hladnik said, echoing Herrmann’s concerns.
Marketers are focused on meeting their goals and often aren’t hands-on practitioners aware of the nuances of different ad platforms.
If the ad buyer can alert the brand that Facebook is working on the backend and to anticipate strange results these days, it can relieve the tensions on some difficult, urgent calls when the reports come in with bizarre numbers.
Another big problem is the delay on reporting data. With its third-party pixel and SDK network, Facebook used to pick up practically every visit or conversion to another site or app. That data was fed in real time to campaign reports.
Now data comes in large batches that upload for thousands of accounts simultaneously every two or three days, Hladnik said.
Again, Facebook did warn advertisers to expect slow reporting and not to optimize campaigns without a few days to build up a level of data so that the platform can model results.
And some advertisers are less keenly affected. Larger brands, particularly with higher-priced items, are less affected by Facebook’s upheaval, Hladnik said.
Toyota’s profit margin does not hinge on the Facebook ad platform, and a massive brand with a diversified ad budget, like McDonald’s, is relatively unaffected by a two or three-day delay on reporting.
But the mechanics of Facebook’s ad platform are built into many ecommerce businesses. Startup or smaller niche brands succeeded on Facebook partially because they are big tinkerers themselves. They target carefully, change spend levels and optimize more often, because they need to slice and dice platform audiences to find those perfect prospects.
Facebook’s consistent response has been to be patient and, well, to slow down. In February, Facebook acknowledged that it was still underreporting attribution, but said it had cut the error margin from 15% to 8%.
Says who?
If every time the Facebook ad platform butterfly flaps its wings, a tsunami hits the attribution reports, then ad buyers are going to stop trusting Facebook data or promises of performance improvement.
The tools Facebook is building to fix the black box ad platform are an even darker box, Herrmann said. “What are they doing to earn the trust of media buyers or publishers?” Because Facebook doesn’t provide details on what’s being worked on or fixed in the background, even as that work swings ad campaign performance.
Even more than Google, Facebook has built its ad dominance on the idea that its data and algorithms are the best on the market, according to Hladnik. You didn’t have to trust Mark Zuckerberg; Advertisers trusted Facebook results.
“But that’s not the case anymore. You cannot trust the data,” he said. “It makes me question the data from before too.”
Original Publisher
AdExchanger
Ready to see how trusted measurement can help your brand make smarter media decisions?
Press Geo-Testing Deserves A Comeback
With less customer tracking and online data collection, advertisers are rethinking their ad targeting and attribution methods. The time has come to revisit a measurement approach that many marketers cast aside decades ago.
Geo-testing, once the gold standard of advertising measurement, fell out of favor as the internet gained popularity. The allure of digital marketing – insights so granular that advertisers could track the behavior of individuals as they traveled about the internet – relegated geo-testing to the role of a trusted, old-school measurement method for “non-addressable” campaigns.
Nowadays, even the MTA diehards have conceded that attribution tracking across the open web is not feasible. Meanwhile, in-market incrementality testing and experimentation on digital channels has gained traction as a measurement alternative. That’s in part because it can actually be accomplished; every programmatic ad platform provides some of the audience-building and measurement tools required for testing incremental ROI.
Understanding incrementality can help marketers reconcile conflicting attribution reports (such as from retargeting campaigns, site-side analytics or self-attributing walled gardens like Google, Facebook, Amazon and Apple). Even without attributing user-level conversions (cookie-style), incrementality experiments can accurately reveal how tweaks to a campaign or media channel impact business outcomes.
While optimizing media for incrementality has become a common objective, most marketers have stuck to running lift tests using a subset of their audience as the control group or testing on first-party audiences using CRM or CDP data. Geo-testing as a way to experiment for incrementality remains buried at the back of the toolshed.
There’s a strong case for dusting it off.
Geo-testing follows the scientific principles of controlled experimentation, but its test and control groups are defined by geographic regions, or geos, selected to have similar demographics (also known as matched-market testing). Anchored on source-of-truth transaction data from the business, geo experiments are cohort-based and don’t require user-level data to measure media’s incremental contribution to any metric that can be collected at the geo level.
Why the hesitation from advertisers? Geo-testing carries a reputation as overly complex, expensive and broad – compared to the cheap, easy scale of the web. It is true that geo-experimentation is deeply rooted in data science and was historically a manual, high-touch process. Identifying unbiased matched markets for geo tests requires a high level of detail. As the tests get more granular, data loss and noise increase and more matches are required to substantiate results. In the past, these costly experiments were rarely revisited for relevancy, and stale reports might wind up informing decisions for years.
But geo-testing has come a long way. While marketers were distracted by the potential of user-level tracking on the web, forcing MTA to accomplish something it never would, data scientists and academics around the world improved geo-testing methodologies to be more automated and efficient.
In recent years, independent reports from The University of Texas and The Journal of Economic Literature have advanced the applications of geo-testing. And platforms – namely, Google and Facebook – created open-source libraries dedicated to the practice. Advancements in the science have resulted in successful deployments of geo-testing at the DMA and even ZIP code levels.
Geo-testing is now more accessible, and the costs are more palatable, to the point where it can be a mainstream marketing strategy once again. While geo-testing will never be the most surgical measurement option, for a tactic like prospecting – which has increased in cost, especially with major walled gardens – it can be the best option available.
The ongoing stream of data privacy policy updates threatens even some first-party data collection. Many fingers are crossed that one of the 80 or more organizations working on a solution to the identity crisis will create a workable standard – but waiting for that to happen is a bad idea. Marketers have only just begun to see the fallout from Apple’s AppTrackingTransparency framework and, even with Google Chrome’s delay of third-party cookie deprecation, media mix blind spots are growing at a rate that most brands can’t afford to ignore.
In anticipation of more tracking restrictions and the eventual 2023 expiration of cookies, we expect marketers and platforms will continue to embrace experimentation as the way forward. Now is time to make geo-testing a part of those initiatives – to claw back some clarity and make media investment decisions based on reliable insight. I’ve even heard from some brands that several platforms, including Google and Facebook, are now developing and recommending geo-testing tools for advertisers.
Modern marketers who dismiss geo-testing as an outdated tool for brands that spend heavily on TV or radio will lose out on significant growth potential. Geo-testing is an important piece in the complete testing toolset because trusty, reliable geo will continue delivering valuable insights regardless of what the future holds for identity resolution, user tracking, and data access.
Modern marketers who dismiss geo-testing as an outdated tool for brands that spend heavily on TV or radio will lose out on significant growth potential.
With less customer tracking and online data collection, advertisers are rethinking their ad targeting and attribution methods. The time has come to revisit a measurement approach that many marketers cast aside decades ago.
Geo-testing, once the gold standard of advertising measurement, fell out of favor as the internet gained popularity. The allure of digital marketing – insights so granular that advertisers could track the behavior of individuals as they traveled about the internet – relegated geo-testing to the role of a trusted, old-school measurement method for “non-addressable” campaigns.
Nowadays, even the MTA diehards have conceded that attribution tracking across the open web is not feasible. Meanwhile, in-market incrementality testing and experimentation on digital channels has gained traction as a measurement alternative. That’s in part because it can actually be accomplished; every programmatic ad platform provides some of the audience-building and measurement tools required for testing incremental ROI.
Understanding incrementality can help marketers reconcile conflicting attribution reports (such as from retargeting campaigns, site-side analytics or self-attributing walled gardens like Google, Facebook, Amazon and Apple). Even without attributing user-level conversions (cookie-style), incrementality experiments can accurately reveal how tweaks to a campaign or media channel impact business outcomes.
While optimizing media for incrementality has become a common objective, most marketers have stuck to running lift tests using a subset of their audience as the control group or testing on first-party audiences using CRM or CDP data. Geo-testing as a way to experiment for incrementality remains buried at the back of the toolshed.
There’s a strong case for dusting it off.
Geo-testing follows the scientific principles of controlled experimentation, but its test and control groups are defined by geographic regions, or geos, selected to have similar demographics (also known as matched-market testing). Anchored on source-of-truth transaction data from the business, geo experiments are cohort-based and don’t require user-level data to measure media’s incremental contribution to any metric that can be collected at the geo level.
Why the hesitation from advertisers? Geo-testing carries a reputation as overly complex, expensive and broad – compared to the cheap, easy scale of the web. It is true that geo-experimentation is deeply rooted in data science and was historically a manual, high-touch process. Identifying unbiased matched markets for geo tests requires a high level of detail. As the tests get more granular, data loss and noise increase and more matches are required to substantiate results. In the past, these costly experiments were rarely revisited for relevancy, and stale reports might wind up informing decisions for years.
But geo-testing has come a long way. While marketers were distracted by the potential of user-level tracking on the web, forcing MTA to accomplish something it never would, data scientists and academics around the world improved geo-testing methodologies to be more automated and efficient.
In recent years, independent reports from The University of Texas and The Journal of Economic Literature have advanced the applications of geo-testing. And platforms – namely, Google and Facebook – created open-source libraries dedicated to the practice. Advancements in the science have resulted in successful deployments of geo-testing at the DMA and even ZIP code levels.
Geo-testing is now more accessible, and the costs are more palatable, to the point where it can be a mainstream marketing strategy once again. While geo-testing will never be the most surgical measurement option, for a tactic like prospecting – which has increased in cost, especially with major walled gardens – it can be the best option available.
The ongoing stream of data privacy policy updates threatens even some first-party data collection. Many fingers are crossed that one of the 80 or more organizations working on a solution to the identity crisis will create a workable standard – but waiting for that to happen is a bad idea. Marketers have only just begun to see the fallout from Apple’s AppTrackingTransparency framework and, even with Google Chrome’s delay of third-party cookie deprecation, media mix blind spots are growing at a rate that most brands can’t afford to ignore.
In anticipation of more tracking restrictions and the eventual 2023 expiration of cookies, we expect marketers and platforms will continue to embrace experimentation as the way forward. Now is time to make geo-testing a part of those initiatives – to claw back some clarity and make media investment decisions based on reliable insight. I’ve even heard from some brands that several platforms, including Google and Facebook, are now developing and recommending geo-testing tools for advertisers.
Modern marketers who dismiss geo-testing as an outdated tool for brands that spend heavily on TV or radio will lose out on significant growth potential. Geo-testing is an important piece in the complete testing toolset because trusty, reliable geo will continue delivering valuable insights regardless of what the future holds for identity resolution, user tracking, and data access.
Original Publisher
AdExchanger
Modern marketers who dismiss geo-testing as an outdated tool for brands that spend heavily on TV or radio will lose out on significant growth potential.
Ready to see how trusted measurement can help your brand make smarter media decisions?
Press How Facebook Is Overhauling Its Attribution Standards To Deal With Apple’s ATT
This is part one of a two-part deep dive series on the changing face of attribution.
Facebook’s had a tough time of it recently.
There was the explosive Wall Street Journal Facebook exposé, whistleblowing on Capitol Hill and the stock market’s reaction, which shaved tens of billions off Facebook’s valuation in a single day.
But Facebook is also grappling with another major headache: the loss of signal and what that means for its ability to measure ads and conversions.
No longer made to measure
The Facebook ad platform – which always seemed able to forge ahead regardless of scandals or rough headlines – has been put through the ringer this year due mainly to Apple’s AppTrackingTransparency (ATT) framework, which launched in 2020 and has steadily rolled out over the course of this year.
From a user perspective, ATT is the new consent request Apple requires for any non-Apple app in order to track users for marketing and other purposes.
The ATT update is particularly damaging to Facebook because Facebook derives a great deal of value from having its SDK plugged into so many outside apps and from its attribution pixels littered liberally across the web. Facebook – and each of those third-party apps – must now get permission from every user, or that user data flow will be blocked by the operating system.
Losing visibility into iOS is a big deal. Apple device owners generate multiple times more revenue than Android users through in-app payments and subscriptions – but they also have access to a top-notch camera. Facebook, whose ad platform includes Instagram, has a vested interest in staying close to this lucrative segment of the market.
In short, Facebook’s attribution system cannot simply move ahead without the iOS user data it’s losing. That is why over the past year, and even in the last month, Facebook has made important changes to its attribution standards.
Facebook is pushing advertisers to use its Conversions API, a server-side developer toolkit for user data and measurement that allows advertisers to send web events from their servers directly to Facebook.
And the company is also advocating geo-testing as a new attribution model – mainly because testing by zip code or market doesn’t require user-level tracking by the advertiser.
Even so, there’s no disguising the impact that this loss of user data is having on Facebook’s measurement systems.
Facebook’s attribution crunch
Facebook’s attribution policy changes demonstrate the steady diminishment of its overall data intake.
Aggregated Event Measurement, for example, a protocol that Facebook introduced to address Apple’s iOS 14 updates, limits the number of trackable “conversion events” to eight. That may not register as a big deal to people who aren’t in the weeds on Facebook attribution, but advertisers might use dozens or even hundreds of conversion events across campaigns.
Any domain an advertiser uses for ad click-throughs – a merchant’s homepage, say, as well as specific product pages – requires a conversion event for campaign analytics. And to layer in Facebook’s conversion-based optimization, advertisers must commit at least four of their conversion events to that metric. Add-to-cart would be its own conversion event, as would checkout initiation. Advertisers might have different conversion events set for content marketing or blog pages than they do for product sales or their main service page.
That doesn’t leave a lot of wiggle room.
Facebook attribution windows have also taken a hit. Facebook used to have so much data coming in, advertisers could optimize campaigns on the fly or create practically endless lookalike audiences, even with granular targeting parameters (e.g. women aged 18-35 in midwestern cities who like to travel and follow cosmetics brands).
But Apple’s iOS 14 also zeroes out first-party tracking data in certain cases.
App-install page attribution windows are limited to one day during which a user can be retargeted or attributed to the ad that drove the click. Advertisers previously could attribute on 28-day windows for ad clicks or use 7-day view-through windows to track whether a user who visited a site also saw an ad.
Facebook advertisers have reduced spend by about 30% on average. But the biggest hit has been to advertisers that sell items in the hundreds or thousands of dollars range, said Rok Hladnik, a Facebook performance marketing consultant.
The longer attribution windows were prized by big-ticket sellers because expensive purchases often include more research or consideration beforehand. [Then again, they weren’t ideal for everyone.]
The data slowdown
What Facebook’s attribution changes often mean in practice are optimization and analytics come at a slower pace.
“Consider waiting a minimum of 72 hours or the full length of the optimization window” before optimizing campaigns, wrote Graham Mudd, Facebook’s VP of product marketing, in a blog post last month on new measurement practices.
A call for Zen-like patience is a big change from the go-go-go optimization mentality that elevated Facebook’s ad platform.
Mudd also suggested that advertisers “analyze the campaign, not the creative.”
That might sound like a rather bland, even hokey, nugget of wisdom, but it represents another momentous shift for Facebook. An important differentiator for Facebook has been its ability to test so many ad permutations and targeting parameters. Sometimes dozens or even hundreds of tweaks to ad copy or creative elements might be running and testing simultaneously, all of it optimized based on conversions within specific audience categories – and all happening while a campaign is in flight.
Now, Facebook recommends all similar campaigns – any ads driving to the same page, for instance, or ads that use similar creative – be consolidated.
Whereas in the past a brand may have targeted men versus women, for example, or music ticket-buyers versus sport fans, by making changes to the ad creative and a campaign’s attribution goals, Facebook now suggests combining these targets into a single campaign. By consolidating those campaign branches, advertisers lose the scalpel-like targeting they’re used to but have a larger pool of conversion data for Facebook to create statistically significant attribution models.
Facebook’s solutions
The upshot of all this change is that Facebook is grappling with how to continue to operate effectively – essentially, how to do more – with less data.
One of the things Facebook has done is to nudge (or in some cases full-on force) advertisers into channels that improve Facebook attribution.
For instance, if an advertiser optimizes a campaign based on site conversions or any in-app events, that campaign is automatically added to Targeting Expansion, a product launched last month that serves a portion of the budget to new types of users outside the advertiser’s pre-set targeting parameters.
Facebook advertisers are accustomed to campaigns expanding outside campaign seed audiences. Because there was so much user-level data available, the Facebook algorithm could spot lookalikes everywhere. Now, Facebook must work harder to coax advertisers out of their original campaign audience sets in order get its optimization flywheel moving again.
Facebook is also incentivizing shopping campaign options that create more data.
Last year, the company launched Shops, a Facebook storefront brands can set up on the platform or via an integration with Shopify. Facebook recently began offering ad discounts for brands to send traffic to Facebook Shops, as opposed to their own sites, Hladnik said.
First-party ecommerce data is extremely valuable for Facebook. Amazon’s attribution isn’t handicapped by ATT because it sees so much transaction data, not just web browsing or user events in other apps.
But Facebook Shops is no Amazon, and because they don’t convert as effectively, Hladnik said, advertisers aren’t sold despite the discount.
Another priority for Facebook is geo-testing. Facebook is privately testing market-based user measurement in its data clean room, said Madan Bharadwaj, co-founder and CTO of the attribution firm Measured. Geo-testing will be “the gold standard” for Facebook and other platform attribution, he said, because it demonstrates a campaign’s incremental contribution to sales without tracking individuals.
Geo-based attribution models “seem to be the promised silver bullet” for campaign attribution, tweeted growth marketing consultant Michael Taylor after a Facebook client webinar on attribution changes.
Although Facebook gets less data from individuals on iOS devices, the supply is still large enough to attribute based on what it sees in a market or zip code.
The only other option is to temper advertiser expectations
For example, Facebook’s latest measurement update is to pre-campaign audience reach forecasts and its “estimated daily results” metric, which provides advertisers with an expected reach projection for the upcoming day based on their budget and goals.
Now, those estimates come as a range, instead of a hard number. The estimates will also start to come down, since Facebook can’t easily distinguish between when a campaign retargets an Apple device owner and when it reaches a new user.
Geo-testing will be “the gold standard” for Facebook and other platform attribution because it demonstrates a campaign’s incremental contribution to sales without tracking individuals.
This is part one of a two-part deep dive series on the changing face of attribution.
Facebook’s had a tough time of it recently.
There was the explosive Wall Street Journal Facebook exposé, whistleblowing on Capitol Hill and the stock market’s reaction, which shaved tens of billions off Facebook’s valuation in a single day.
But Facebook is also grappling with another major headache: the loss of signal and what that means for its ability to measure ads and conversions.
No longer made to measure
The Facebook ad platform – which always seemed able to forge ahead regardless of scandals or rough headlines – has been put through the ringer this year due mainly to Apple’s AppTrackingTransparency (ATT) framework, which launched in 2020 and has steadily rolled out over the course of this year.
From a user perspective, ATT is the new consent request Apple requires for any non-Apple app in order to track users for marketing and other purposes.
The ATT update is particularly damaging to Facebook because Facebook derives a great deal of value from having its SDK plugged into so many outside apps and from its attribution pixels littered liberally across the web. Facebook – and each of those third-party apps – must now get permission from every user, or that user data flow will be blocked by the operating system.
Losing visibility into iOS is a big deal. Apple device owners generate multiple times more revenue than Android users through in-app payments and subscriptions – but they also have access to a top-notch camera. Facebook, whose ad platform includes Instagram, has a vested interest in staying close to this lucrative segment of the market.
In short, Facebook’s attribution system cannot simply move ahead without the iOS user data it’s losing. That is why over the past year, and even in the last month, Facebook has made important changes to its attribution standards.
Facebook is pushing advertisers to use its Conversions API, a server-side developer toolkit for user data and measurement that allows advertisers to send web events from their servers directly to Facebook.
And the company is also advocating geo-testing as a new attribution model – mainly because testing by zip code or market doesn’t require user-level tracking by the advertiser.
Even so, there’s no disguising the impact that this loss of user data is having on Facebook’s measurement systems.
Facebook’s attribution crunch
Facebook’s attribution policy changes demonstrate the steady diminishment of its overall data intake.
Aggregated Event Measurement, for example, a protocol that Facebook introduced to address Apple’s iOS 14 updates, limits the number of trackable “conversion events” to eight. That may not register as a big deal to people who aren’t in the weeds on Facebook attribution, but advertisers might use dozens or even hundreds of conversion events across campaigns.
Any domain an advertiser uses for ad click-throughs – a merchant’s homepage, say, as well as specific product pages – requires a conversion event for campaign analytics. And to layer in Facebook’s conversion-based optimization, advertisers must commit at least four of their conversion events to that metric. Add-to-cart would be its own conversion event, as would checkout initiation. Advertisers might have different conversion events set for content marketing or blog pages than they do for product sales or their main service page.
That doesn’t leave a lot of wiggle room.
Facebook attribution windows have also taken a hit. Facebook used to have so much data coming in, advertisers could optimize campaigns on the fly or create practically endless lookalike audiences, even with granular targeting parameters (e.g. women aged 18-35 in midwestern cities who like to travel and follow cosmetics brands).
But Apple’s iOS 14 also zeroes out first-party tracking data in certain cases.
App-install page attribution windows are limited to one day during which a user can be retargeted or attributed to the ad that drove the click. Advertisers previously could attribute on 28-day windows for ad clicks or use 7-day view-through windows to track whether a user who visited a site also saw an ad.
Facebook advertisers have reduced spend by about 30% on average. But the biggest hit has been to advertisers that sell items in the hundreds or thousands of dollars range, said Rok Hladnik, a Facebook performance marketing consultant.
The longer attribution windows were prized by big-ticket sellers because expensive purchases often include more research or consideration beforehand. [Then again, they weren’t ideal for everyone.]
The data slowdown
What Facebook’s attribution changes often mean in practice are optimization and analytics come at a slower pace.
“Consider waiting a minimum of 72 hours or the full length of the optimization window” before optimizing campaigns, wrote Graham Mudd, Facebook’s VP of product marketing, in a blog post last month on new measurement practices.
A call for Zen-like patience is a big change from the go-go-go optimization mentality that elevated Facebook’s ad platform.
Mudd also suggested that advertisers “analyze the campaign, not the creative.”
That might sound like a rather bland, even hokey, nugget of wisdom, but it represents another momentous shift for Facebook. An important differentiator for Facebook has been its ability to test so many ad permutations and targeting parameters. Sometimes dozens or even hundreds of tweaks to ad copy or creative elements might be running and testing simultaneously, all of it optimized based on conversions within specific audience categories – and all happening while a campaign is in flight.
Now, Facebook recommends all similar campaigns – any ads driving to the same page, for instance, or ads that use similar creative – be consolidated.
Whereas in the past a brand may have targeted men versus women, for example, or music ticket-buyers versus sport fans, by making changes to the ad creative and a campaign’s attribution goals, Facebook now suggests combining these targets into a single campaign. By consolidating those campaign branches, advertisers lose the scalpel-like targeting they’re used to but have a larger pool of conversion data for Facebook to create statistically significant attribution models.
Facebook’s solutions
The upshot of all this change is that Facebook is grappling with how to continue to operate effectively – essentially, how to do more – with less data.
One of the things Facebook has done is to nudge (or in some cases full-on force) advertisers into channels that improve Facebook attribution.
For instance, if an advertiser optimizes a campaign based on site conversions or any in-app events, that campaign is automatically added to Targeting Expansion, a product launched last month that serves a portion of the budget to new types of users outside the advertiser’s pre-set targeting parameters.
Facebook advertisers are accustomed to campaigns expanding outside campaign seed audiences. Because there was so much user-level data available, the Facebook algorithm could spot lookalikes everywhere. Now, Facebook must work harder to coax advertisers out of their original campaign audience sets in order get its optimization flywheel moving again.
Facebook is also incentivizing shopping campaign options that create more data.
Last year, the company launched Shops, a Facebook storefront brands can set up on the platform or via an integration with Shopify. Facebook recently began offering ad discounts for brands to send traffic to Facebook Shops, as opposed to their own sites, Hladnik said.
First-party ecommerce data is extremely valuable for Facebook. Amazon’s attribution isn’t handicapped by ATT because it sees so much transaction data, not just web browsing or user events in other apps.
But Facebook Shops is no Amazon, and because they don’t convert as effectively, Hladnik said, advertisers aren’t sold despite the discount.
Another priority for Facebook is geo-testing. Facebook is privately testing market-based user measurement in its data clean room, said Madan Bharadwaj, co-founder and CTO of the attribution firm Measured. Geo-testing will be “the gold standard” for Facebook and other platform attribution, he said, because it demonstrates a campaign’s incremental contribution to sales without tracking individuals.
Geo-based attribution models “seem to be the promised silver bullet” for campaign attribution, tweeted growth marketing consultant Michael Taylor after a Facebook client webinar on attribution changes.
Although Facebook gets less data from individuals on iOS devices, the supply is still large enough to attribute based on what it sees in a market or zip code.
The only other option is to temper advertiser expectations
For example, Facebook’s latest measurement update is to pre-campaign audience reach forecasts and its “estimated daily results” metric, which provides advertisers with an expected reach projection for the upcoming day based on their budget and goals.
Now, those estimates come as a range, instead of a hard number. The estimates will also start to come down, since Facebook can’t easily distinguish between when a campaign retargets an Apple device owner and when it reaches a new user.
Original Publisher
AdExchanger
Geo-testing will be “the gold standard” for Facebook and other platform attribution because it demonstrates a campaign’s incremental contribution to sales without tracking individuals.
Ready to see how trusted measurement can help your brand make smarter media decisions?
Press Apple’s IOS 14 Is Causing Major Changes To How Facebook Does Measurement
Marketers funnel money into Facebook because Facebook can prove ROI.
Put $1 in, get more than $1 out. It’s a simple narrative.
But Apple’s iOS 14 changes are chipping away at Facebook’s ability to measure and demonstrate performance.
And Facebook is reacting by “making wholesale changes to what kind of data and reporting they will offer back to advertisers,” said Madan Bharadwaj, CTO of marketing attribution and incrementality testing company Measured.
Signal loss
In mid-February, Facebook quietly posted a blog noting that it would no longer support holdout tests to measure conversion lift or enable A/B tests that include a control group for self-serve conversion lift studies.
A few weeks later, on March 1, Facebook reps alerted ad buyers by email that it plans to disable store visits optimization and reporting, as well as related beta products, including store visits lifts studies and Custom Audiences for store visits. That change is effective April 1.
“It’s my sense that Facebook is doing a tremendous amount of housekeeping,” said an agency executive who asked to remain anonymous. “Their tools that rely on off-Facebook data signals have to change.”
Heavy lifting
But these changes aren’t coming out of nowhere.
Facebook hinted back in August, when it shared initial guidance on how to prepare for iOS 14, that it would likely no longer be able to measure mobile app installs and other app events from iOS 14 devices in conversion lift tests.
When an iOS 14 user opts out of tracking, Facebook has said it will honor that choice across browsers and devices, which means Facebook won’t be able to track the behavior of the control groups over time.
“This is a significant decision proactively made by Facebook to honor a user’s privacy consent, but it has widespread negative impact across all of Facebook’s advertising products and, markedly, to attribution,” said Bharadwaj, who noted that he’s heard chatter that Facebook is working on a way to estimate attribution for non-consented users.
For now, advertisers can still run an A/B test without a holdout to see which ads perform best, or to run a brand survey test to measure the incremental effect of Facebook ads on awareness, perception and/or recall.
Facebook is working on a new measurement methodology called Aggregated Event Measurement (AEM) which is modeled off of Apple’s Private Click Measurement and will allow for the measurement of web events from iOS 14 users by aggregating performance data at the campaign level.
AEM is not fully baked yet, though, and by design is more limited than previous measurement tools. (And for those hoping to use Facebook’s Conversion API as a workaround, which allows ad buyers to send offline events and web events from their server directly to Facebook for cross-platform measurement, Facebook has said that events sent to Facebook via the Conversion API will also be processed in accordance with the limits set by AEM. So, no dice.)
Bigger picture: as it becomes more difficult to measure actions off platform, Facebook will increasingly start to look inward, said Jennifer Eenigenburg, VP and digital media director at Rain the Growth Agency, a DTC-focused performance shop.
“We expect to see Facebook go into overdrive developing products that keep actions on the platform,” Eenigenburg said, pointing to Facebook Shops and Shops on Instagram.
Real world problems
Facebook once hoped to expand its off-platform measurement purview into the real world.
In 2017, Facebook tested a tool that used GPS, WiFi and Bluetooth signals that would tell retailers if someone walked into a store after seeing a Facebook ad.
But according to the email Facebook sent to ad buyers on March 1, store visits optimization and reporting and related measurement products were “not able to drive meaningful business outcomes at scale over time” and were only ever applicable to a relatively small number of eligible advertisers.
In other words, using location services to connect store visits to ad exposure works great if you’re a big box retailer in the suburbs surrounded by a large parking lot, but not if you’re located in a mall or a city with people streaming past your storefront on the sidewalk. The GPS just isn’t accurate enough to tell if someone entered your location.
Also, using location data to track offline interactions is dicey from a privacy perspective. Apple has been more aggressive in general with opt-in for background location sharing.
With that in mind, it’s likely that Facebook’s sunsetting of store visits optimization and reporting is more related to the tool’s inability to break through with enough advertisers rather than a direct casualty of Apple’s iOS 14 changes. Not that iOS 14 didn’t play a role.
“There’s a slogan I heard from a VC once: Never miss out on a good crisis,” said Maor Sadra, CEO and co-founder of INCRMNTAL, a startup focused on incrementality testing and measurement.
What’s happening with iOS 14 on a macro level “gives Facebook an opportunity to kill something that had low penetration anyway, so there was no point in keeping it,” Sadra said.
But although store visits optimization and reporting is being scrapped, Facebook will still allow advertisers to target ads to people within a certain radius of store locations.
There are a few catches, however.
This capability only works if an advertiser uploads its CRM file to Facebook, actually has a CRM file to share (not all advertisers know who their customers are), can handle the technical challenge of a daily upload … and is comfortable sharing their entire CRM file with Facebook, including non-Facebook users.
Facebook did not respond to a request for comment about discontinuing store visits optimization and reporting.
This is a significant decision proactively made by Facebook to honor a user’s privacy consent, but it has widespread negative impact across all of Facebook’s advertising products.
Marketers funnel money into Facebook because Facebook can prove ROI.
Put $1 in, get more than $1 out. It’s a simple narrative.
But Apple’s iOS 14 changes are chipping away at Facebook’s ability to measure and demonstrate performance.
And Facebook is reacting by “making wholesale changes to what kind of data and reporting they will offer back to advertisers,” said Madan Bharadwaj, CTO of marketing attribution and incrementality testing company Measured.
Signal loss
In mid-February, Facebook quietly posted a blog noting that it would no longer support holdout tests to measure conversion lift or enable A/B tests that include a control group for self-serve conversion lift studies.
A few weeks later, on March 1, Facebook reps alerted ad buyers by email that it plans to disable store visits optimization and reporting, as well as related beta products, including store visits lifts studies and Custom Audiences for store visits. That change is effective April 1.
“It’s my sense that Facebook is doing a tremendous amount of housekeeping,” said an agency executive who asked to remain anonymous. “Their tools that rely on off-Facebook data signals have to change.”
Heavy lifting
But these changes aren’t coming out of nowhere.
Facebook hinted back in August, when it shared initial guidance on how to prepare for iOS 14, that it would likely no longer be able to measure mobile app installs and other app events from iOS 14 devices in conversion lift tests.
When an iOS 14 user opts out of tracking, Facebook has said it will honor that choice across browsers and devices, which means Facebook won’t be able to track the behavior of the control groups over time.
“This is a significant decision proactively made by Facebook to honor a user’s privacy consent, but it has widespread negative impact across all of Facebook’s advertising products and, markedly, to attribution,” said Bharadwaj, who noted that he’s heard chatter that Facebook is working on a way to estimate attribution for non-consented users.
For now, advertisers can still run an A/B test without a holdout to see which ads perform best, or to run a brand survey test to measure the incremental effect of Facebook ads on awareness, perception and/or recall.
Facebook is working on a new measurement methodology called Aggregated Event Measurement (AEM) which is modeled off of Apple’s Private Click Measurement and will allow for the measurement of web events from iOS 14 users by aggregating performance data at the campaign level.
AEM is not fully baked yet, though, and by design is more limited than previous measurement tools. (And for those hoping to use Facebook’s Conversion API as a workaround, which allows ad buyers to send offline events and web events from their server directly to Facebook for cross-platform measurement, Facebook has said that events sent to Facebook via the Conversion API will also be processed in accordance with the limits set by AEM. So, no dice.)
Bigger picture: as it becomes more difficult to measure actions off platform, Facebook will increasingly start to look inward, said Jennifer Eenigenburg, VP and digital media director at Rain the Growth Agency, a DTC-focused performance shop.
“We expect to see Facebook go into overdrive developing products that keep actions on the platform,” Eenigenburg said, pointing to Facebook Shops and Shops on Instagram.
Real world problems
Facebook once hoped to expand its off-platform measurement purview into the real world.
In 2017, Facebook tested a tool that used GPS, WiFi and Bluetooth signals that would tell retailers if someone walked into a store after seeing a Facebook ad.
But according to the email Facebook sent to ad buyers on March 1, store visits optimization and reporting and related measurement products were “not able to drive meaningful business outcomes at scale over time” and were only ever applicable to a relatively small number of eligible advertisers.
In other words, using location services to connect store visits to ad exposure works great if you’re a big box retailer in the suburbs surrounded by a large parking lot, but not if you’re located in a mall or a city with people streaming past your storefront on the sidewalk. The GPS just isn’t accurate enough to tell if someone entered your location.
Also, using location data to track offline interactions is dicey from a privacy perspective. Apple has been more aggressive in general with opt-in for background location sharing.
With that in mind, it’s likely that Facebook’s sunsetting of store visits optimization and reporting is more related to the tool’s inability to break through with enough advertisers rather than a direct casualty of Apple’s iOS 14 changes. Not that iOS 14 didn’t play a role.
“There’s a slogan I heard from a VC once: Never miss out on a good crisis,” said Maor Sadra, CEO and co-founder of INCRMNTAL, a startup focused on incrementality testing and measurement.
What’s happening with iOS 14 on a macro level “gives Facebook an opportunity to kill something that had low penetration anyway, so there was no point in keeping it,” Sadra said.
But although store visits optimization and reporting is being scrapped, Facebook will still allow advertisers to target ads to people within a certain radius of store locations.
There are a few catches, however.
This capability only works if an advertiser uploads its CRM file to Facebook, actually has a CRM file to share (not all advertisers know who their customers are), can handle the technical challenge of a daily upload … and is comfortable sharing their entire CRM file with Facebook, including non-Facebook users.
Facebook did not respond to a request for comment about discontinuing store visits optimization and reporting.
Original Publisher
AdExchanger
This is a significant decision proactively made by Facebook to honor a user’s privacy consent, but it has widespread negative impact across all of Facebook’s advertising products.
Ready to see how trusted measurement can help your brand make smarter media decisions?
Press As Marketers Tire Of Last-Click And MTA, Incrementality Testing Finds Its Niche
Data-driven marketers don’t like last-click attribution, which simply credits only the final impression that drove a conversion. And they aren’t buying multitouch attribution (MTA), an involved process where each touchpoint in a campaign is tracked and assigned specific credit.
So where does the media measurement pendulum settle between those options?
For some attribution experts, the answer to that question is incrementality testing.
“What we saw was that incrementality testing was landing as the best methodology to inform these questions considering the blind spots in MTA,” said Trevor Testwuide, co-founder and CEO of the media measurement startup Measured.
Testwuide knows a thing or two about MTA. He co-founded and was CEO of Conversion Logic, one of the few remaining independent attribution tech vendors, and before that was VP of sales at Visual IQ, an attribution vendor acquired by Nielsen in 2017.
MTA models aim to track each impression and individual in a path to conversion, then allocates credit to specific publishers, vendors or media channels. But major platforms like Google or Amazon have taken steps to disable user-level third-party measurement. And traditional marketing categories like direct mail and linear television, don’t sync well with digital attribution, Testwuide said.
As marketing dollars retreat to these attribution “blind spots,” he said advertisers are falling back on incrementality testing, which uses cohorts and control groups to evaluate specific media channels without tracking individual users or impressions.
Mapping every user and impression isn’t feasible, said Alex Faherty, CEO of the fashion startup Faherty Brand. He said the company focuses on channels as a whole instead of user-level tracking.
Faherty Brand worked with Measured last year, and found that during the holidays it’s most effective to over-index on prospecting and channels like Facebook or Google, because people are in the mood to shop and they don’t need heavy branding or retargeting to turn a browser into a purchaser, he said.
That may seem like a minor adjustment, but Faherty said right-sizing budgets by season makes a big difference considering 40% of the company’s marketing budget is spent in Q4.
MTA is expensive and “creates more questions than it answers,” said Alyssa Perry, senior director of marketing of FabFitFun, a beauty product subscription service that uses Measured for incrementality testing.
“This felt like a way to get actionable insights without the heavy price tag or burden on our resources,” she said.
FabFitFun tried incrementality testing to evaluate its retargeting budget. Over the course of 2018, Perry said the brand started cutting back retargeting campaigns for certain control groups. The team found that on average, someone who visits the site and converts will do so within three days. It then halted all retargeting after a week to easily eliminate waste.
Retargeting budgets are the low-hanging fruit for incrementality tests, since they typically get the last-click credit from a campaign.
Soft Surroundings, a women’s fashion brand and another Measured client, dramatically scaled back retargeting since it adopted incrementality tests late last year, said marketing director Gail Buffington.
“The numbers said we could cut a lot, but it still makes you nervous,” she said. Incremental tests were a good way to taper budgets month to month, she said, since cohorts being tested didn’t show a drop in demand without retargeting reminders.
Now Soft Surroundings is bringing incrementality tests to its print budget, because the brand produces its own magazine to send to prospects and known customers.
“I suspect our catalogue gives more bang for our buck than we can directly measure,” Buffington said. “So I want to dig in to that and understand the incremental lift when we send someone a magazine.”
MTA is expensive and creates more questions than it answers
Data-driven marketers don’t like last-click attribution, which simply credits only the final impression that drove a conversion. And they aren’t buying multitouch attribution (MTA), an involved process where each touchpoint in a campaign is tracked and assigned specific credit.
So where does the media measurement pendulum settle between those options?
For some attribution experts, the answer to that question is incrementality testing.
“What we saw was that incrementality testing was landing as the best methodology to inform these questions considering the blind spots in MTA,” said Trevor Testwuide, co-founder and CEO of the media measurement startup Measured.
Testwuide knows a thing or two about MTA. He co-founded and was CEO of Conversion Logic, one of the few remaining independent attribution tech vendors, and before that was VP of sales at Visual IQ, an attribution vendor acquired by Nielsen in 2017.
MTA models aim to track each impression and individual in a path to conversion, then allocates credit to specific publishers, vendors or media channels. But major platforms like Google or Amazon have taken steps to disable user-level third-party measurement. And traditional marketing categories like direct mail and linear television, don’t sync well with digital attribution, Testwuide said.
As marketing dollars retreat to these attribution “blind spots,” he said advertisers are falling back on incrementality testing, which uses cohorts and control groups to evaluate specific media channels without tracking individual users or impressions.
Mapping every user and impression isn’t feasible, said Alex Faherty, CEO of the fashion startup Faherty Brand. He said the company focuses on channels as a whole instead of user-level tracking.
Faherty Brand worked with Measured last year, and found that during the holidays it’s most effective to over-index on prospecting and channels like Facebook or Google, because people are in the mood to shop and they don’t need heavy branding or retargeting to turn a browser into a purchaser, he said.
That may seem like a minor adjustment, but Faherty said right-sizing budgets by season makes a big difference considering 40% of the company’s marketing budget is spent in Q4.
MTA is expensive and “creates more questions than it answers,” said Alyssa Perry, senior director of marketing of FabFitFun, a beauty product subscription service that uses Measured for incrementality testing.
“This felt like a way to get actionable insights without the heavy price tag or burden on our resources,” she said.
FabFitFun tried incrementality testing to evaluate its retargeting budget. Over the course of 2018, Perry said the brand started cutting back retargeting campaigns for certain control groups. The team found that on average, someone who visits the site and converts will do so within three days. It then halted all retargeting after a week to easily eliminate waste.
Retargeting budgets are the low-hanging fruit for incrementality tests, since they typically get the last-click credit from a campaign.
Soft Surroundings, a women’s fashion brand and another Measured client, dramatically scaled back retargeting since it adopted incrementality tests late last year, said marketing director Gail Buffington.
“The numbers said we could cut a lot, but it still makes you nervous,” she said. Incremental tests were a good way to taper budgets month to month, she said, since cohorts being tested didn’t show a drop in demand without retargeting reminders.
Now Soft Surroundings is bringing incrementality tests to its print budget, because the brand produces its own magazine to send to prospects and known customers.
“I suspect our catalogue gives more bang for our buck than we can directly measure,” Buffington said. “So I want to dig in to that and understand the incremental lift when we send someone a magazine.”
Original Publisher
AdExchanger
MTA is expensive and creates more questions than it answers
Ready to see how trusted measurement can help your brand make smarter media decisions?