Category: Use Cases

Apple, Google, Privacy, and Bad Tech Journalism

 

Wait, did they just say Safari now blocks Google Analytics?

(Spoiler alert: it doesn’t)

At the 2020 edition of the Apple Worldwide Developers Conference (WWDC), Apple announced that the new version of MacOS (nicknamed Big Sur) would ship with version 14 of the Safari web browser – promising Safari would be more privacy friendly. Which is a great move and in line with the regulatory and digital marketing landscapes.

However, based on fuzzy, out-of-context screenshots shown during the announcement, some digital marketing publications started asserting that the new Safari would block Google Analytics.

[Narrator’s voice: it didn’t]

Here are some of the articles in question:

Within minutes, that poorly researched bit of fake news was all over social media.

So what really happened? Should you worry?

Cooler heads always prevail, so let’s take a step back and look closely at what really happened.

What is ITP and why does it matter?

The WWDC is generally the occasion for Apple to announce new features and key developments in their tech ecosystem from desktop and mobile operating systems to SDKs, APIs, and all that good technical stuff.

In recent years, Apple has used the WWDC to announce changes to the way they handle privacy in web and mobile apps, namely with initiatives such as ITP (Intelligent Tracking Protection), which is used in Safari, Apple’s Webkit-based browser on Macs, iPhones, and iPads.

In a nutshell, ITP restricts the creation and the lifetime of cookies, which are used to persist and measure someone’s visit on one site (first party, a.k.a. 1P) or across multiple websites (third party, a.k.a. 3P). ITP makes things more difficult for digital marketers because users become harder to track and target.

If we use Google Analytics as a comparison, ITP can “reset” a known visitor to a new visitor after only a couple of days, instead of the usual 2 years – assuming users don’t change devices or clear their cookies.

If we look at ITP with our privacy hat on, even collecting user consent will not stop ITP from neutralizing cookies.

ITP arrives at the right moment; just as online privacy starts to finally take root with pieces of legislation such as GDPR and ePrivacy in Europe, CCPA in California, LGPD in Brazil, APA/NDB in Australia, APP in Japan, PIPA in Korea, and a lot more being made into bills and/or written into law.

Arguably the above pieces of legislation allow for the collection of user consent prior to collecting. So we should not really be worrying about Safari potentially collecting information that users consented to, right?

That was not even a consideration in the aforementioned pieces on “Safari blocks Google Analytics.”

Does the new Safari really block Google Analytics?

(Second spoiler alert: it still doesn’t)

The most obvious way to show you is with a test. Luckily, I had MacOS Big Sur beta installed so I took a look under the hood – especially on the sites that published that “Safari blocks Google Analytics” story. Let’s fire up Safari and turn on developer mode.

Sure enough, Google Analytics sends a tracking call that makes it home to Google collection servers. Safari does not block Google Analytics.

Now let’s take another look at that new privacy report: it shows “22 trackers prevented.”

Wait, the list shows google-analytics.com?! Didn’t we just establish that Google Analytics tracking went through?

Let’s clarify: what the panel below shows are the domain names of resources loaded by the page that are flagged in the ITP lists as potential tracking vectors using third-party cookies.

Other than that, ITP plays its role in drastically reducing the Google Analytics cookie’s lifetime to just a week as shown below.

Let’s drive this point home again if needed: Safari 14 does not block Google Analytics.

ITP is enforced as per the spec by blocking third-party cookies and limiting cookies to a lifetime of a week at most.

So what’s the big impact?

As mentioned, ITP is primarily going to reduce the time during which a visitor is identified. After a week, ITP deletes/resets the user cookie and the visitor is “reborn”. Not a great way to study user groups or cohorts, right?

If you’re worrying about the impact of ITP on your data collection, may I suggest reading this awesome piece on ITP simulation by my colleague Doug Hall.

What is important to remember is that Apple is using ITP block lists built in partnership with DuckDuckGo, a search engine that has made a name for itself as a privacy-friendly (read: anti-Google). I, for one, have yet to see what their business model is but that’s a story for another post.

At any rate, ITP lists are meant to block cookies for specific domain names.

Even if Apple did decide to block Google Analytics altogether, how big a deal are we talking about? According to StatCounter, Safari accounts for roughly 18% of browser market share (as of June 2020). Let’s round this up to a neat 20%. That’s an awful lot of data to lose.

Arguably, Google Analytics wouldn’t be the only tracking solution that could be impacted. Let’s not forget about Adobe, Criteo, Amazon, Facebook, Comscore, Oracle—to name a few.

So if you keep implementing digital analytics according to the state of the art, by respecting privacy and tracking exclusively first-party data, you’ll be a winner!

Is it really just bad tech journalism?

Let’s get real for a moment. If tech journalists posting the story about Safari blocking Google Analytics knew about ITP, they wouldn’t have published the story – or at the very least with a less sensational headline. Even John Wilander, the lead Webkit engineer behind ITP spoke out against the misconceptions behind this “Safari blocks GA piece.”

This is unfortunately a case of bad tech journalism, where half-truths and clickbait titles drive page views. Pitting tech giants Apple and Google is just sensational and does not highlight the real story from WWDC: privacy matters and Apple are addressing it as they should.

In this, I echo my esteemed colleague Simo Ahava in that this kind of journalism is poorly researched at best, intentionally misleading at worst.

Most of the articles on this particular topic backtracked and offered “updates” but they got caught with their hand in the cookie jar.

To be fair, it is also Apple’s fault for using misleading labeling.

But is it so bad considering we’re talking about a beta version of a web browser? Ìf anything, Apple now has a few months ahead of them to make adjustments before Big Sur and Safari.

Beyond the fear, uncertainty and doubt, this kind of publication is symptomatic of an industry that is scared by the effect that privacy regulation is having on their business.

How is MightyHive addressing this?

While we at MightyHive have long been preparing  for the death of the cookie and digital ecosystem focusing on first-party data, we can appreciate that initiatives such as ITP can make a digital marketer’s life very complicated.

We strongly believe that the future of digital marketing lies in first party data, consent and data quality.

Cookies are on their way out but this does not mean the end of the world.

Need help navigating the ever-changing digital marketing landscape? Contact us for guidance!

Identifying Significance in Your Analytics Data

 
A few weeks ago I had the chance to help launch our new “Live with MightyHive” series. My colleague Myles Younger and I chatted about how to distill significance and causality from analytics data, and then how to act on those types of insights. You can watch the full episode and access the slide deck below.

If you want to chat further with MightyHive about advanced analytics solutions like these, please reach out to us at questions@mightyhive.com.

What is significance?

Making decisions based on data needs the support of a robust measure of confidence in the data.

Off the back of an event of some sort (campaign starts, new app feature, global pandemic), if we observe any change in our data we need to be confident the “thing” that happened was actually responsible for the change in data—not just a correlation. We need to be able to demonstrate that had this thing not happened, the data wouldn’t have changed.

Then we can infer a causal relationship between the event and the change in the data. Remember—it’s still a probability, we can never prove causality in a categorical sense, but we can be highly confident (and it’s way better than guessing!). We can remove emotion and unconscious bias from decision-making. We don’t eyeball data or use our gut—mathematics informs the decision making process.

Here’s the full chat and slides from last week’s “Live with MightyHive” episode (scroll to the end for the slides):

How does it work?

The technology behind the Google CausalImpact R package that was demonstrated in the episode constructs a Bayesian structural time-series model and then tries to predict the counterfactual.

Simply, the mathematical model uses data prior to the event to predict what the data would look like had the event not happened. Important: the prediction is actually a probabilistic range of values. If the historic data is noisy, then the accuracy of the prediction will change. See the screenshot below from the demo walk through linked above. In the image below, the blue shaded area is the prediction (synthetic control estimator) from the model. If the observed data falls outside the blue region, we have significance!

The blue region gets bigger with noisier data. The broader the blue region, the more extreme the observation will need to be in order to achieve a significant signal.

Using Google CausalImpact

You can use the CausalImpact package with as little as three lines of R. R Studio is open source or you could try it out using rstudio.cloud.

Be advised, if you install the CausalImpact package locally, due to dependencies, you’ll need at least v3.5 of R. I updated Linux on the Chromebook to get the latest version of R and R Studio via this very useful article and the package installation was very straightforward.

There’s another option thanks to Mark Edmondson from IIH Nordic. Mark wrote a great Shiny app front end for CausalImpact that’s free to use, so you can explore significance in your own GA data.

Using significance to establish causality and take action

We used the package to analyse client data to confidently answer key business questions that arose regarding KPI changes since the UK was locked down.

As well as considering YTD data (setting the ‘event’ as Jan 1), we use pre- and post-lockdown (Mar 9) date periods. Data shows clear patterns in purchase behaviour for retails sites. Media sites appear to exhibit explosive growth. However, the specifics regarding growth areas of content are highly informative—not what you’d expect to see by just eyeballing the data from afar.

For retail and media clients, the ability to identify current and future growth areas with confidence is a highly valuable tactic. At a strategic level, the forecast output from CausalImpact is highly actionable in driving campaign content, budgets, and timing.

While tactics for the current global situation include “managing,” there is a clear near for preparation as well. Making decisions on current data and using forecasts with confidence proves to be valuable for our clients.

Additional Resources

Thank you for reading! The slides from the episode can be accessed here:
 

Watch the CausalImpact R package introductory video here (mandatory viewing!):
youtube.com/watch?v=GTgZfCltMm8

Remember to sign up here for future Live with MightyHive episodes:
livewithmightyhive.splashthat.com

Managing COVID-19 Brand Safety in The Trade Desk

 

Introduction

In the third part of our series about how advertisers can ensure brand safety while still supporting publishers during the global pandemic, we are sharing best practices for several major programmatic buying platforms. As one of the largest independent media buying platforms, with a focus on transparency, openness, global scale, and advanced TV, The Trade Desk is an important part of an advertiser’s strategy looking to reach consumers globally. 

Through a three-step process, you can confidently set up campaigns avoiding sites that peddle in misinformation and sensationalist content that can appear during global crises, while still supporting reputable news sites.

Step 1: Site/Category Blacklists

Working with trusted partners to ensure brand adjacency is more important than ever. The Trade Desk allows advertisers with a list of trusted partners to block specific websites/apps as well as specific content categories.

There is no limit to the number of sites that can be added to the blacklist and these lists can be shared across an entire advertiser for usage with every campaign.

the trade desk block

Step 2: Pre-Bid Technology

The next precaution advertisers can take is to enable pre-bid targeting and only bid on traffic that falls within certain parameters. For example: block fraudulent traffic, bid only on ads likely to be in a user’s view, or target pages related to relevant contextual categories. Note: this is not currently supported for connected TV campaigns. 

The following pre-bid targeting vendors are available:

  • DoubleVerify
  • Grapeshot
  • Integral Ad Science
  • Moat
  • Peer39

Each vendor offers a unique list of category exclusions including:

  • Site content
  • Content rating
  • Keyword targeting
  • Invalid traffic/fraud

ttd ad targeting

Step 3: The Trade Desk + Quality Alliance™️

In addition to the aforementioned vendors, The Trade Desk also offers Quality Alliance™️ as a viewability targeting solution in desktop web and mobile web environments, for both display and video. Where viewability can be measured, this solution will also work in-app.

The Trade Desk includes enriched reporting metrics to allow for more sophisticated analysis against inventory that was categorized as fraudulent (Eg. Adware/Malware Impressions, Sophisticated Nonhuman Data Center Traffic, etc.). This helps advertisers further optimize media spend by giving them a better understanding of risky inventory.

In Conclusion

We know brand safety is highly subjective and mission critical when the direction of global recovery changes on a daily basis. We hope this guide provides a quick review of steps you can take, or ensure your partners are taking, to make sure your ad dollars are reaching the users and supporting the content you deem appropriate. 

MightyHive clients can reach out to their account teams for more guidance on how to implement these tactics within campaigns. If you’re not already a MightyHive client, contact us. We’d love to talk.

Check out our full brand safety series here:

Managing COVID-19 Brand Safety in Amazon DSP

 

Introduction

In the fourth part of our series about how advertisers can ensure brand safety while still supporting reputable publishers during the global pandemic, we are sharing best practices for several major programmatic buying platforms. 

As one of the fastest-growing DSPs, Amazon DSP specializes in exclusive first-party audience data sets and unique owned and operated web and advanced TV properties, alongside robust brand safety safeguards. Through a quick two-step process, advertisers can ensure their campaigns avoid risky sites and content that can be particularly hard to avoid during a global crisis, when the volume of breaking news and misinformation challenges even the savviest advertisers. 

Step 1: Site/App Whitelist in Amazon DSP

Advertisers with a list of trusted partners and properties should turn to Amazon’s whitelist features first. In order to positively target domains/apps, advertisers must input a minimum of 50 domains. 

It’s also worth noting that Amazon requires 50+ domains in consideration of its private marketplace (PMP) offering, which is an alternative/parallel option for open exchange whitelists. PMPs provide higher priority access to premium inventory and are a viable alternative to secure placements with premium publishers.

amazon domain targeting

Step 2: Brand Safety Targeting

Pre-bid filtering is another powerful option advertisers have in Amazon DSP to keep ads dollars away from content they deem unsuitable for their brand. Once an advertiser has selected the properties on which ads will appear, pre-bid filtering provides another layer of security around the specific content categories the brand will appear next to. Amazon has a robust mix of third-party brand safety integrations including:

amazon 3p prebid

DoubleVerify

Web content category exclusion; authentic brand safety (custom brand safety profiles that can be ingested via audience ID through DoubleVerify’s platform)

double verify

Oracle Data Cloud

Custom Grapeshot segments determined by brand safety controls in the Oracle Data Cloud Context UI

oracle data cloud

Integral Ad Science

Web content category exclusion

integral ad science

NOTE: All third-party verification is currently free for advertisers, which is a unique benefit in comparison to other demand-side platforms

Over-The-Top (OTT) targeting

Content ratings and genres: With advanced TV offering, Amazon DSP allows advertisers to select the ratings and genres of the content ads will be placed on, allowing a level of granularity that can protect spend and improve control.

ott

In addition to these capabilities, Amazon enables its own safeguards to monitor and review third-party sites and apps for unsafe content. If a third-party site or app is identified as unsafe, it is blocked from advertising.

In Conclusion

We know brand safety is highly subjective and mission critical at a time like this. We hope this guide can provide a quick review of steps you can take, or ensure your partners are taking, to make sure your ad dollars are reaching users and supporting the content you deem appropriate. 

MightyHive clients can reach out to their account teams for more guidance on how to implement these tactics within campaigns. If you’re not already a MightyHive client, contact us. We’d love to talk. If you’re not familiar with Amazon DSP yet, read our explainer here.

Check out our full brand safety series here:

Managing COVID-19 Brand Safety in Xandr Invest

 

Introduction

In the second part of our series on how advertisers can ensure brand safety while still supporting publishers during the global pandemic, we have open-sourced our brand safety best practices for several major programmatic buying platforms. 

With a unique focus on first-party data, advanced TV and premium inventory access, Xandr Invest is an important tool for advertisers looking to reach consumers during these trying times. 

Through five specific steps, you can set up your campaigns to avoid risky sites and content that can appear during global crises, which is particularly important if you’re managing your own spend.

Step 1: Category Targeting

Xandr provides two types of category targeting for advertising: universal and custom.

  • Universal categories are defined by Xandr and made available to all users
  • Custom categories are defined by specific sellers to be applied across specific “slices” of their inventory (e.g. a news site filtering certain types of content)

The custom category is particularly relevant for advertisers who want to continue to support quality news outlets, but only on specific pages or sections of a publisher’s website or app.

xandr category targeting

Step 2: Blacklists

Built on the foundation of the AppNexus DSP, Xandr Invest’s blacklists are built on the foundation of one of the longest-standing buying platforms. In addition to these protections, Xandr also automatically applies its own platform blacklist.

Domain/App Audit Flags are a unique Xandr feature that automatically flags sites/apps on your list that may not meet brand safety criteria, such as not exposing the actual URL.

appnexus blacklist

Step 3: Brand Safety Segments

Brand safety segments are a powerful tool to direct your ad spend to specific sections of a publisher’s property. These are broken out as their own category under line item settings. 

Segments from third-party providers can be added on as additional filters for targeting and include standard options such as page content, content rating, etc.

Available third-party providers:

  • comScore
  • DoubleVerify
  • Grapeshot/Oracle Data Cloud

Step 4: Brand Exclusions

Xandr also offers a unique feature where you can block certain brands from serving ads in slots on the same page as your ads.

This can be used as an extra level of defense if there are certain brands you do not want to be associated with (competitive companies, questionable companies, etc.).

brand exclusions

Marketers have the option to set up other category exclusions at the advertiser level, which will then cascade down to all line items under it.

category exclusions

Step 5: Supply-Side Platform Targeting

As supply-side platforms take different approaches to the supply-path optimization and specialize in different formats, selecting the SSP you buy media through becomes more important. Through the integration with Xandr Monetize, Xandr’s supply-side platform, advertisers can set up custom sell-side filters in addition to the standard buy-side filters.

Advertisers have the option to filter out inventory without Ads.txt support from the buy-side, a useful control that eliminates resellers not adding value for your supply chain.

xandr advanced targeting

In Conclusion

We know brand safety is highly subjective and mission critical at a time like this. We hope this guide can provide a quick review of steps you can take, or ensure your partners are taking, to make sure your ad dollars communicate the value your brand has to offer during this crisis, while finding ways to support publishers doing important work. 

MightyHive clients can reach out to their account teams for more guidance on how to implement these tactics within campaigns. If you’re not already a MightyHive client, contact us. We’d love to talk.

Check out our full brand safety series here:

Managing COVID-19 Brand Safety in Display & Video 360

 

Introduction

For more than half a decade, digital marketers have been concerned about their adverts appearing against content not aligned to their brand’s values. This fear is rational. Whether it is extremist content or fake news, being seen adjacent to the wrong content can erode brand equity that took years to build. The COVID-19 crisis has increased concerns amongst many marketers. Because of this, MightyHive has decided to open-source our guidance on brand safety for marketers.

In this post, we’re addressing users of the programmatic buying platform Google Display and Video 360 (DV360) and the Google Campaign Manager ad server.

Through a three-step process, you can set up your platforms to avoid high-risk websites and non-brand safe content that arise during crises like COVID-19. Crucially, we will tell you how to catch anything that might slip through the net—especially important if you’re still outsourcing buying.

Step 1: Positively Target Brand Safe Domains

Low-quality and fake news articles have the potential to misinform the public. Now —more than ever— it is important to support quality news. Advertisers can do the right thing by supporting journalism and protect their brand equity by actively avoiding content that seeks to divide or misinform internet users.

“Website and App Targeting” (whitelisting) allows programmatic buyers to do just this. By using this feature at a line-item level within DV360, buyers can positively target content that is considered to be brand safe such as email, professional news, e-commerce sites, and price comparison engines.

Historically, programmatic buyers have raised concerns about scale when adopting this approach. These concerns can be mitigated. We believe advertisers who continue to use domain blacklists (which exclude websites/apps that they know to be risky) should reconsider this approach, due to changes in the operating environment.

New high-risk sites appear every day, making it impossible to update targeting regularly enough to include every domain that may pose a risk to your brand. This means a buyer is much better off positively targeting sources they know to be high-quality and brand-safe and that do not share misleading or sensationalist news.

Step 2: Avoid Unsafe Content In Brand-Safe Domains

Domain whitelists help brands avoid the very worst content out there. However, even with brand-safe sites like news, there will be content that risk-averse advertisers will not want to appear against. This is especially true in times of crisis.

DV360 has three tools programmatic buyers can use to avoid unsafe content:

  • Sensitive Category Exclusions
  • Digital Content Labels
  • Keyword Exclusions

The first feature is “Sensitive Category Exclusions.” This feature allows an advertiser to exclude content that has the potential to be particularly risky to a brand. Of note given the circumstances is the ability to exclude ‘Tragedy’ and ‘Shocking’ content:

Beyond filtering out the riskiest content using this feature, MightyHive recommends buyers use the “Digital Content Labels” feature that is available within DV360. This is a free tool provided by Google, which can be implemented within campaigns at a line-item level. It classifies content along a range from ‘suitable for all general audiences’ up to ‘suitable for mature audiences only.’

There is also a category for content that hasn’t yet been labeled. It is critical to exclude content that hasn’t been labeled by Google for two reasons:

  1. When a site is new, Google does not have enough data to classify its content. It can take up to a month to classify a site. Whilst a site’s content may not be objectionable to most audiences, it might not be suitable given the increased stress, fear, and anxiety audiences are feeling. During extraordinary times, erring on the side of caution makes sense.
  2. Sometimes Google doesn’t know the exact domain in a bid request because a publisher “masks” a URL. In these cases, Google cannot create a Digital Content Label for the URL. The content might be fine, but advertisers are running the risk of serving ads alongside sensitive content.

The final lever programmatic buyers can use to help avoid non-brand safe content in brand safe domains is “Keyword Exclusions.” Keyword Exclusions can be seen as the last line of defense. It is a blunt tool which, if misused, can impact scale. However, adding keywords such as ‘coronavirus,’ ‘covid-19,’ ‘death,’ and ‘intensive care’ can protect risk-averse clients from appearing against such content.

Step 3: Block Content That Slips Through The Net

One of the key benefits of contract ownership is direct access to your buying platform. If you have taken this step, it is easy to check your brand safety settings are implemented correctly and protect yourself from a myriad of brand safety risks.

But what should an advertiser who has not taken control of their DSP contracts or who outsources some of their buying do to ensure they are protected?

The long-term answer is take more control. In the short term, you can request that the “Standard Content Classifiers” feature is implemented in your Campaign Manager Network.

Standard Content Classifier settings allow you to block risky content including Tragedy and Sensitive Social Issues across all buys (including those made outside DV360). There is no additional charge to implement this feature.

MightyHive recommends using Standard Content Classifiers instead of targeting a whitelist. If a marketer chooses to use a whitelist and implement Standard Content Classifiers, the whitelist will prevail, leading to ads served on a whitelisted domain even if it contains content classified as Tragedy, Sensitive Social Issue, etc.

It is critical to remember that if you implement brand safety measures solely in your ad server, a blank ad will be served against content deemed risky by Google’s classification engine and you will still be charged for the space. Make sure your settings in your ad server and your buying platform are aligned to prevent serving blank ads.

In Conclusion

What is and isn’t considered brand-safe will vary from brand to brand. We hope these measures provide you with some clear and tangible ways to address brand safety. MightyHive clients can reach out to their account teams for more guidance on how to implement these tactics within your campaigns. If you’re not already a MightyHive client, contact us and we’d love to talk.

Check out our full brand safety series here:

WEBINAR: How Do Sophisticated Marketers Think About Measurement?

 

Recently, MightyHive and Google set out to answer some questions about sophisticated programmatic advertisers’ best practices:

  • How are they building new connections to customers?
  • What discoveries are emerging from data and analytics?
  • How are marketers pushing technology to do more?

To foster an exchange of ideas about today’s most sophisticated marketers, MightyHive and Google collaborated on How Do Sophisticated Marketers Think About Programmatic & Measurement Maturity? Chris Brook, Director of Client Solutions at MightyHive, co-hosted alongside the Google Marketing Platform Customer Success Team.

“First-party data isn’t a tool, it’s the toolkit.”

— Chris Brook, Director of Client Solutions, MightyHive

Chris focused on the KPIs top marketers are using to determine the lifetime value (LTV) of a customer. He shared that the best insights are derived from a wide variety of first-party data sources (CRM, POS systems, customer loyalty programs, etc.) combined with user-data that is generated by owned web properties. Chris also touched on important issues facing sophisticated marketers today, such as new privacy regulations and the benefits of dynamic ad serving.

The webinar concludes with a walkthrough of how personalized, dynamically-generated promotional content for the Netflix series “Narcos” was able to cut production costs by 40% and boosted clickthrough rate by 60%.