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The debate around federal privacy laws and regulations has reached a fever pitch as consumers grow increasingly concerned about their privacy. States such as California are enacting strict and robust privacy laws on a local level.

As such, more thought is being placed into what a federal privacy law would look like and just how (and how much) it would protect consumers. A good source of inspiration for determining the appropriate approach to protecting your brand and your customers could be complying with the strictest policies. Not only is this a preemptive means of avoiding trouble but, more importantly, it will create the best and most trusted experience for your customers.

The top-down approach

It should come as no surprise that the General Data Protection Regulation (GDPR) is the strictest privacy regulation in force across the European Union. The fact that it covers such massive markets like the UK, Germany, France and the rest of the EU means that you can’t ignore it. The who in “who is covered” by the law is based on physical location: a French citizen residing in Los Angeles is not covered under GDPR; however, a Mexican expat living in Germany would be covered because they are a data subject in the EU.

That all sounds pretty straight forward, right? Not so fast. Imagine that both of these individuals have an @gmail.com address. How would you know where they are located or their national origin simply based on an email address with no geographical designation, as in an @Yahoo.fr top-level domain (TLD)?

Instead of focusing on playing a game of “Where in the World is Carmen Sandiego,” companies should focus on establishing policies that comply with the strictest privacy laws. Not out of fear of the heavy monetary burdens of non-compliance, but because it’s simply good for business. This is the new standard for how brands must handle and care for customer data. It also happens to be the law in a growing number of places around the world.

Let’s briefly review what consent means under GDPR: consent under GDPR has to be freely given, specific, informed and unambiguous. However, predating the GDPR, Europe had the 2002 e-Privacy Directive, which more directly dealt with electronic marketing and set the standard around consent. Double opt-in is a solid means of complying with the requirements of adequate consent and control for GDPR and the e-Privacy Directive. It’s important to note that a Directive does not apply directly to member states in Europe. Rather, an EU Directive is a requirement that every EU country enact laws at the member state level that implement the EU Directive. As a result, there are variations between member states, with some being stricter than others in how they implement the Directive. In the case of consent rules for electronic marketing, Germany tends to be the strictest by generally requiring a double opt-in. However, double opt-in is not the only requirement—things like pre-ticked boxes are anathema under GDPR — so you have to think through all of the ways that you are currently obtaining consent and if that consent passes muster with the various consent frameworks?

If this sounds like it’s too far afield for businesses outside of Europe, think again. Companies are willingly establishing double opt-in mechanisms for new subscribers. This approach ensures that wherever a customer resides, the consent is being obtained in a manner that is commensurate with global privacy laws.

But there’s another reason for this: uninformed consent is likely to breed higher complaint rates and certainly lower engagement. Recipients that don’t realize they have opted in to receive communications from a company that either purposefully or unwittingly obfuscates consent are far more likely to mark messages as spam. With inbox placement being such a user-driven, engagement-centric exercise, consent is at the heart of establishing and maintaining your email program.

Tangential to consent frameworks and privacy regulation, many companies are choosing to cull the oldest and lowest performing segments of their lists. This approach is a direct manifestation of the “less is more” approach to data management and email marketing. Being present in every inbox is not a recipe for success. Quite the opposite, actually — it creates risk that can affect your entire program.

The winds are shifting

States such as California are not waiting on the federal government to enact stricter privacy regulation. The FTC recently concluded its review of the 2003 CAN-SPAM law that controls the assault of non-solicited marketing. The conclusion of the 10-year review was that no changes were needed despite the massive evolution of the digital marketing space and the adoption of policies such as Canada’s Anti-Spam Law (CASL) and the GDPR in Europe. Essentially, the FTC concluded that the United States can remain an opt-out framework for email rather than moving toward an opt-in best practice.

During the 2018 election, Californians passed the California Consumer Privacy Act (CCPA) which brings California closer to a European framework than the FTC’s policies. The law is more focused on what happens to consumer data by controlling the sale of that data and giving consumers the option to prevent its sale and use.

Under CCPA, the responsibility of properly collecting, storing and handling consumer data now shifts to businesses that have significant data as part of or as a focus of their business. It allows Californians to determine what kind of data about them a business may possess, giving them access to that data and enabling them to opt-out of having their data sold. Businesses with revenues of $25 million or more will be forced to comply with CCPA, annually buy or receive for commercial purposes the PII of 50,000 or more persons or derive 50% or more of their annual revenue from selling consumer personal information. The law as it’s currently written is targeted at larger businesses where consumer PII is central to these businesses or represents a sizeable quantity of data.

But consent is only the tip of the iceberg when it comes to GDPR. How data is stored, handled, transferred and minimized are all major facets of GDPR. CCPA is similarly focused on the sharing and selling—and in some cases collection—of data of California residents, while broadly expanding consumer rights and access to their data. The short answer is that personal data and our ability to keep our data private are becoming increasingly more important. The right to privacy is a basic human right according to European law, which ideologically is different than how we think about privacy in the United States—but the world is changing, and that change is being driven in part by the seemingly unfettered collection of PII and the outcries against it.

Data has enabled the success of a myriad of businesses and spawned a vast array of technologies that inform us about everything from how our cars perform to how we sleep. However, it’s impossible to discuss the benefits of big data without mentioning data breaches, scandals and the vast ocean of personal data that are all driving significant changes in not only our marketplaces but in legislative houses around the world. Both India and Brazil recently created privacy frameworks of their own. These changes outside of first world countries are foretelling important milestones to take into account when considering the kind of compliance framework that will guide your opt-in practices, data handling and user access methods.

A prudent approach is to ask your legal counsel and seek specific privacy counsel and support to determine how your business might be affected by the coming changes. One thing is certain: this is not the world wide web of the 90s. We are in a new age, and the world is creating new laws to tackle challenging problems that have risen through the storing and analysis of huge data sets. The only question is: how will your business follow suit?

Opinions expressed in this article are those of the guest author and not necessarily Marketing Land. Staff authors are listed here.

In 2017, Google agreed to provide refunds to selected advertisers using DoubleClick Bid Manager (now called Display & Video 360) where ads were served on sites that had fraudulent or invalid traffic. Reportedly, hundreds of marketers were eligible, but a class-action lawsuit by AdTrader asserts that Google improperly withheld those refund payments, according to the Wall Street Journal (WSJ)

Prior agreement to refund ‘platform fee.’ When the fraud was initially discovered, Google said it would repay its “platform fee,” which typically represents between 7% to 10% of the total value of the ad spend. Some marketers expressed dissatisfaction with the refund scheme. However, according to the WSJ, “Google said it wasn’t in a position to return money that had already flowed from its buying tool to third-party online ad marketplaces where publishers were selling ad space.”

AdTrader initiated the class action suit against Google in California federal court, arguing that Google had “illegally appropriated” promised advertiser refunds. The lawsuit alleges that Google never actually issued any refunds, after reclaiming money from publishers accused of having inflated or fraudulent traffic.

Alleged failure to pay $75 million. Unsealed court documents reviewed by the WSJ apparently reflected that Google had not paid as much as $75 million in potential refunds tied to “ad marketplaces that Google itself owns and fully controls: AdX and AdSense.”

Various third analyst and monitoring firms have estimated ad fraud amounts to more than $16 billion globally. Other reports have different figures. A range of U.S. estimates, including from the Association of National Advertisers, assert that brands will lose between $6 and $7 billion this year on fraudulent (non-human) traffic.

Why you should care. The AdTrader lawsuit is still in process and seeks class certification for agencies and advertisers that used DoubleClick Ad Exchange (AdX) and AdSense during the relevant time frame. It also seeks triple damages and punitive damages as well as injunctive relief against Google. AdTrader accuses Google of being a monopolist and positions itself as a champion of advertiser interests. You can read more detail on the legal and factual claims in AdTrader’s blog post and court complaint (.pdf).

Back in the days when I was learning PPC, one of the two biggest growing pains I had were:

1. Learning the difference between segmenting campaigns out to maximize efficiency
2. Reaching the point where the juice is no longer worth the squeeze

Rather than creating clutter and a burdensome account to manage, I’ve since learned to make use of everything I can to speed up my workflow and free up bandwidth to focus on things that actually make a difference.

IF functions are a versatile means to tailor your ads to users in real time, using either the type of device they’re browsing on or the audience segment they belong to as signals to serve up specialized ad copy. The right message at the right time can make all the difference between a conversion or another bounced visitor. Search marketing is rapidly moving towards heavy automation and personalization, so IF functions are helpful because they’re a simple way to keep your seat at the table.

Setting up IF functions

The process of setting up IF Functions is painless. You could easily set one up in the time it will take to finish this article, regardless of your comfort level with Excel formulas. And if doing it on Excel is too daunting, you can set them up directly in the Google Ads UI under the Ads tab.

The basic logic is as follows

{=IF(condition is met, show this text):If not, show this text}.

So, if you wanted specific messaging for users on mobile, the logic runs something like this:

IF the user is ON a mobile device, show mobile-friendly CTA. If not, show the general CTA.

To put that in the basic formula

{=IF(device=mobile, Call Now!):Get a Quote.}

Another common usage of IF statements is serving specific offers to specific audience segments.

The basic formula for audience-based IF functions is

{=IF(Audience IN(audience name), Audience-specific copy.):General copy}

To put the above into a sentence: “If a user is IN this specific audience segment, serve them this specific copy. Otherwise, serve this more general copy.”

Suppose you were running a tiered promotion, where Club Members were eligible for an additional 15% discount on top of a 30% off sale, that text would look something like this:

Shop Now for{=IF(Audience IN(ClubList),45%):30%} Off!

Or, if your nurture campaigns weren’t entirely broken out and you wanted to move recent visitors into booking a consultation, you might have something like:

{=IF(Audience IN(Returning Visitor 7 Days), Book Your Consultation Today!):Download Our Free Guide.

Take note that you can target multiple audience segments in the same IF function. However, you are still limited to two copy options. The syntax is the same, just with your audiences separated by commas in the Audience IN section –

{=IF(Audience IN(Segment1,Segment2,Segment3)Learn More!):Get a Quote.}

If you’re feeling overwhelmed by keeping track of all of those brackets, commas, and colons, you can also build IF functions directly in the Google Ads UI. Simply add an open bracket in an ad field, anywhere from the headline one to URL paths one or two (note that ad customizers in Final URLs are not supported) and let the system walk you through putting it together.

Things to note while using IF functions

• The character limits for each field still apply (but only for the ad text defined in your functions).
• Symbols in the function’s ad text options like quote marks (both single and double), commas, and colons will need to be preceded by backslashes (\) for the function to work properly. For example, rather than “SearchEngineWatch’s” your function copy would read “SearchEngineWatch/’s.”

Using IF functions for fun and profit

Although IF functions don’t offer as many options to customize ads as using a business data feed, the options they do provide are staggering.

Shaping expectations based on device type is a must. While mobile browsers have come a long way in recent years, filling out long forms on a small screen with no keyboard is a slog, and desktop users might not have the same propensity to turn into brick and mortar visitors.

Tailoring your copy for devices isn’t a replacement for setting realistic device bid modifiers and taking cross-device/cross-channel conversions into account. But it is another way to squeeze more efficiency out of your ad budget.

Beyond device-type, the real power of IF functions come from the ease with which you can target specific audience segments. If you have a large enough CRM list to make customer match audiences viable for search, great. If your lists aren’t quite big enough, have no fear, you can create details of the possible audiences in Google Analytics and import it to Google Ads, the options are endless.

Bonus: Countdown ads

Countdown ads are yet another feature that is effective and easy to use but tend to fly under the radar. Beyond highlighting promotions, I’ve seen success in highlighting shipping windows (keep that in mind for the holiday shopping season), special events (for example, store openings), and more. Just like the other customizers available, countdowns can be put anywhere in an ad except for the URL.

The syntax is pretty straightforward

• Specify a date in Year/Month/Day, pick a time in Hour:Minute:Second
• Specify the language you’re targeting, and how many days you’d like the countdown to run

In the below example, the countdown will end at midnight on June 7, 2019, after starting seven days prior

{=COUNTDOWN(“2019/7/7 12:00:00″,”en-US”,7)}

The future is now

Running a successful paid search campaign has always required knowing who your customers are. Ad customizers make reaching the right user with the right messaging easier, and at scale. IF functions are easy inroads towards better tailoring of your users’ experiences towards their needs. It gives you more control over your ad copy than dynamic keyword insertion or responsive search ads, with a lower likelihood of matching to undesirable search queries than dynamic search ads. And with less setup needed than the Ad Customizer feeds, IF functions ultimately give savvy search marketers a powerful tool to boost performance.

Have any queries or interesting functions you know? Share them in the comments.

Clay Schulenburg is Director of SEM at PMG.

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A Reddit thread on Wednesday called attention to many Facebook Groups’ privacy settings being changed to “secret.” The post generated more than 450 comments, with rumors that many Groups had been attacked by a spammer posting violating content that resulted in the Groups being removed by Facebook. Group admins were doing their best to avoid the issue to by switching their Group’s privacy settings to “secret.”

A Facebook spokesperson confirmed to Marketing Land that it had, in fact, mistakenly taken down a number of Facebook Groups, but was working to resolve the issue.

“We removed several Groups from Facebook after detecting content that violated our policies. We since discovered that this content was posted to sabotage legitimate, non-violating Groups. We’re working to restore any Groups affected and to prevent this from happening again,” said a Facebook spokesperson.

Why we should care

Any marketers who are managing a Group as part of their Facebook strategy need to review content within the Group to make sure it is clear of abusive or extremist content that violates Facebook’s community standards. This issue should also serve as a warning that Groups are just as susceptible to being hacked as any other owned platform and must be monitored accordingly.

With Facebook making Groups the “center” of its app, the platform offers marketers a powerful tool for organic engagement with their followers. But building membership numbers and a loyal following via a Group can take time and effort, and the last thing a brand wants to see happen is their Group removed by no fault of their own.

Even worse, a hacked Group that posts spammy, offensive content can do major damage to a brand’s reputation when Group members are served extremist or abusive content. Just like with any other aspect of managing your brand’s social channels, its crucial Group admins stay on top of the conversations happening within their Group.

More on the news

• Facebook currently has tens of millions of active Groups on Facebook and more than 400 million uses that belong to a Group.
• During this month’s F8 Developers Conference, Facebook introduced a new personalized activity feed within the Groups tab, along with a redesign of the tab to make it easier to find within the app. Facebook also launched a new discovery tool that recommended Groups based on a user’s interest.
• Facebook CEO Mark Zuckerberg told the F8, “Groups are at the heart of the experience,” and Facebook later confirmed users may start seeing more content from the Groups they belong to in their News Feed.

There’s a science behind what engages shoppers and gets them to purchase and new visual search tech implementations promise to exploit that and reinvent ecommerce as we know it.

A shopper’s decision to buy products is more influenced by the primal brain areas and less from the analytical side. Us humans are hard-wired to our emotions which spring from the same areas of the brain, the right side, that processes and reacts to visual stimulation. In the early days of mankind, it’s largely how our ancient ancestors survived in the wild.

Similar to Facebook’s emoticons it rolled out as “reactions” in 2016, our modern emotions emerge from four core feelings, happy, sad, afraid/surprised (“wow”), and angry/disgusted, based on research conducted by the Institute of Neuroscience and Psychology at the University of Glasgow.

Smart marketers can appeal to our right brains that communicate in feelings and respond to images that increase conversions and sales because people tend to act based on emotions. Most of the purchase decisions people make are emotional, not practical. Retail shopping therapy is, perhaps, an offshoot of this science-based truth.

When it comes to shopping, decision-making, and conversions, another experiment conducted by the George Washington University and UCLA, found that playing to the emotional side of our brains is a far better strategy than using too many facts and figures that appeal to the decision-making areas of the brain.

The researchers found that ads that use logical persuasion (for example, “this car gets 42 miles to the gallon”) scored lower for conversions than those that “seduced” people by circumventing “consumers’ conscious awareness by depicting a fun, vague or sexy scene”.

Visual search will revolutionize ecommerce and SEO

The rise of visual search is powered, in part, by people’s desire to discover products and brands, and it’s playing out now in the new trend of shopping on social media channels such as Instagram and Pinterest that’s spreading most quickly amongst millennials as the next big thing.

Yet, “creating technology that can understand images as quickly and effectively as the human mind is a huge undertaking”, wrote Adam Stetzer in a trend piece on visual search last year. “Visual identification is a natural ability made possible through a wonder of nerves, neurons and synapses. We can look at a picture, and in 13 milliseconds or less, know exactly what we’re seeing”.

Google is making rapid advancements tied to the increasingly visual nature of the search for ecommerce. For example, in early March it rolled out a new pilot program to digitally connect retailers and consumers, who can now make purchases from results of Google Image searches.

For the pilot’s launch, Google cited a figure that 50 percent of online shoppers said images of the product inspired them to purchase. Google is currently testing its “Showcase Shopping” ads on what it calls “a small percentage” of traffic with select retailers, surfacing on broad queries such as “home office ideas”, “shower tile designs”, and “abstract art”.

Certainly, the visual search trend will impact the programmatic ad industry’s innovations for future offerings. Advanced AI and computer imaging will be two core technologies that power dynamic personalization and highly customized ads that boost campaign performance tied to consumer’s visual search behaviors. For instance, it enables offering up winter jackets in the shopper’s favorite colors as fall approaches, or quickly serves up visually or stylistically complementary dining sets to match a new dining table or tablecloth search or purchase.

Adtech leaders’ R&D programs have already begun to focus on new AI-powered marketing innovations, including research and development from Facebook, Google, and Pinterest, and new strategic partnerships such as the one announced by Amazon and Snap last year.

Shoppable visual ads take off on social media platforms

The powerful combination of influencer marketing, using emotional buying triggers we’re hard-wired to respond to, and the highly visual nature of popular social channels such as Instagram and Pinterest have sparked the fast growth of shoppable ads on social media platforms.

Many industry watchers are betting that Instagram and Facebook will lead the pack here. Late last year, Salesforce predicted that Instagram will grow 3X faster than overall social-traffic boosts, citing data from Cowen & Company that 30 percent of internet users reported purchasing a product they discovered on Facebook or Instagram.

The overall trend of social media’s impact on purchase behavior is well-documented. As many as 76 percents of consumers have purchased a product they’ve seen in a brand’s social media post, per data from Curalate.

Influencer marketing and consumers’ purchase of products, as a result, is nothing new. For example, many kids who grew up in the 1970s and their parents bought Wheaties back then based on the cereal’s “Breakfast of Champions” campaign because they were inspired to be like Bruce Jenner after his decathlon triumph at the 1976 Montreal Olympics.

While the mediums have changed, and we can now click on ads and have products delivered within the same day, and be much more granular in terms of micro-influencers’ campaigns that pinpoint targets and conserve campaign budgets, the psychology of why it works is the same.

New platforms such as Shopify make it easy for brands and merchants of all kinds to create engaging, highly connected sites that are helping to energize the social aspects of the web.

Large companies such as Amazon, Pinterest, and Instagram have done an excellent job of figuring out consumer sentiment, emotions, and online behaviors. We’re getting much closer to narrowing down to a “segment of one“, a trend that many retailers today are focused on in order to increase the personalization of advertising and improve the experience for consumers so that promotional offers to purchase products become more like a personal shopper catering to them instead of a pushy salesperson who annoys them to the point of departing the store.

And if Pinterest is any indication with more than 600 million visual searches each month, and fact that image-based Pinterest ads have an 8.5 percent conversion rate, the role of visual search in helping to capture our attention, personalize the advertising experience, and seduce us to buy is here to stay as ecommerce and SEO evolve around it.

Gary Burtka is Vice President of U.S. operations at RTB House, a global company that provides retargeting technology for global brands worldwide. He can be found on Twitter .

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Facebook’s Lookalike Audiences have long been a favorite ad targeting tool for advertisers, allowing marketers to use Custom Audience lists to find like-minded users on the platform. Advertisers can select their Lookalike Audience size from 1% to 10% — the smaller the audience size, the more closely the results will match the source list.

Many advertisers have relied on the laser-focused capability of 1% Lookalike Audiences since the launch of the ad targeting tool all the way back in 2013, but some are no longer seeing the results they once experienced.

What’s happening with 1% Lookalike Audiences?

“We have used 1% Lookalike audiences since it has been available, and we were pretty happy with the results,” said Pierre-Olivier Carles, CEO of the social media marketing agency Digidust. Carles said his agency’s best campaigns were based on Pixels’ data rather email databases or FB Pages audiences.

“The beauty of the 1% Lookalike targeting was to help us reach the right people even when the demographics were not obvious,” said Carles, “We don’t feel it works anymore unless you can build that audience on the Pixel — but in that case, your website has to provide enough traffic to make it accurate, especially as you don’t want to base that Lookalike Audience on older visits to keep pace with your market.”

Gil David, a Facebook ads specialist and founder of Run DMG, said he’s noticed a drop in results during the past three to four months.

“Lookalike performance dipped somewhat after Facebook stopped using third-party data for a while last year, but began to return a few months after,” said David. “However, now 2% and 3% Lookalike Audiences seem to be the best and I’ve also had higher — 4% and 7% — doing well in some accounts.”

Is 2%+ the new sweet spot?

David said the 2% and 3% audience size seem to be optimal for the campaigns he’s managing right now. He also has found success layering two different 1% Lookalike Audience lists on top of each other.

“I would always continue to test 1% Lookalike Audiences because, with the way Facebook ads are, they could suddenly make a comeback, but I’m much more likely to start off with 2%+ now or layering two 1% lists on top of each other,” said David.

Carles said his agency used to test the broader Lookalike Audience ranges, but never got the results they wanted. He plans to keep using the 1% Lookalike targeting, but only when the products or messaging is highly specific.

“For example, we work with a chain of restaurants, and our goal is not to build brand awareness but to bring more people to each of their locations. In that particular case, the 1% Lookalike Audience that we base on their email databases works fine when we narrow it based on the location of the restaurants,” said Carles.

Too popular or not enough privacy?

David believes the lack of results happening with 1% Lookalike Audiences is the outcome of the ad targeting tool being promoted as a type of “hack” for advertisers new to the platform who assume 1% audiences will automatically perform better — which leads to more crowded 1% audience pools.

“There has also been a general trend of broader audiences performing better, these would generally start off with a larger size than the standard 2.1 million people in a U.S. 1% Lookalike Audience — so that would also have an impact too,” said David.

Carles see it as part of a bigger trend and a clear sign of what’s to come in terms of Facebook advertising.

“Many industries — like politics or real estate — now have specific terms of use to protect people’s privacy, and I guess Facebook has updated its algorithms for Lookalike Audiences to take that trend into account. I think we will see these restrictions increase in the future,” said Carles.

He points out the paradox Facebook advertisers are currently faced with — that the platform has more data than ever, but it’s no longer available to marketers. “I am not saying it is bad — and privacy definitely matters — but it’s a fact.”

Not the end, just a new beginning

Carles doesn’t believe 1% Lookalike Audiences will pick back up.

“More businesses are running more campaigns, and the real estate in users’ timelines, Stories, Messenger, etc. is not an infinite resource and can be quickly saturated,” said Carles.

On top of a saturated market, there is also the coming ‘Clear History’ tool which lets users disconnect their off-Facebook activity from their profile, potentially limiting the amount of ad targeting data available and impacting Lookalike Audiences of all sizes.

The bigger picture here is that Facebook is undergoing major shifts that will impact marketers who have long relied the platform’s unparalleled ad targeting capabilities. The diminishing returns advertisers are seeing from 1% Lookalike Audiences may just be the tip of the iceberg as the company transitions to a privacy-focused messaging platform.

Marketers may feel like they are coming to the end of an era in terms of Facebook’s ad targeting goldmine, but the consequences of having access to such a goldmine have come at a cost in terms of user privacy and data security. Consumers are growing weary of social platforms as they become more aware of how their information is collected and how it used for ad targeting purposes — a shift that could significantly impact their online behavior and how they engage with brands. These changes in campaign results may not be “the end” of ad targeting — but potentially mark a new beginning for brands and how they build relationships with their audiences.

Search advertising has seen consistent growth over the last year in all the key metrics among advertisers. Here’s everything you need to know.

It’s been a good year for paid search and anyone working in the industry. Benchmarking can help us understand where we are and what we should consider as success in our work. Kenshoo has released its Q1 2019 Quarterly Trends Report to look at the latest trends in social and search advertising. The results are very encouraging for search and we’re looking at the key stats here.

An increase in spending and impressions

It’s interesting to see that there has been a drop from the last quarter both in the spending and the impressions in paid search. More specifically, there was a 16% decrease in spending and an 18% decrease in impressions. It’s not surprising though as Q4 is usually the busiest quarter of the year with the biggest spending at the end of year campaigns.

When it comes to the comparison from Q1 2018 to Q1 2019 from Kenshoo, there has been an 11% YoY increase in paid search spending and a 36% increase in the impressions.

This means that search marketers increased their budget from 2018 to 2019 while also seeing the appropriate success in the increase of impressions.

What does a drop in CTR and CPC mean?

According to Kenshoo’s report, there has been a 25% YoY decrease in click-through rate (CTR) and also an 11% YoY decrease in CPC.

The significant drop in CTR could possibly reflect the growing competition and increased spending and impressions. It would even possibly affect an advertiser’s quality score in ads. It should not be alarming though if we also consider the drop in cost per click.

The drop in the cost per click means that search marketers are seeing an improved return on investment in their campaigns.

A combined analysis of CPC and CTR in every campaign can help us understand the different ways we can measure success in search advertising and how each metric can help us improve our efficiency.

Mobile search ads are on the rise

There is an increasing number of people relying on their smartphones when performing searches. Thus, it’s not a surprise that there has been an increased number of mobile searches from Q1 2018 to Q1 2019.

Mobile search ads are also increasing and they currently take 50% of search spending in Q1.

It is actually the third consecutive quarter that we see this balance between mobile and desktop search spending.

As for CPC, mobile CPCs are still lower than desktop being at $0.42 in Q1 2019. There has been a decrease of 12% from Q1 2018, which highlights the efficiency of mobile search ads.

Search marketers understand that we are heading towards a mobile-first world so there will be an even more increased focus on mobile search and finding solutions to create the most efficient ads.

Apple Search Ads saw a big growth

Apple Search Ads can be very successful if you want to promote your app. A large number of people rely on search when looking for the right app. This means that search ads in the Apple Store can have a big impact on your app’s popularity.

Kenshoo introduced Apple Search Ads to their platform in Q3 2018 and since then they’ve seen a 90% increase in their spend from advertisers.

A combination of excitement but also the understanding that Apple search ads can make your app promotion easier and more effective led to this growth and it seems to be only the beginning.

Overview

What we can learn from Kenshoo’s Trends Report is that search advertising is evolving but it’s still at a very encouraging stage.

It’s important to keep track of the latest trends and what could potentially affect our success. For example, search marketers cannot ignore the rise of mobile consumption and how it affects the spending and the results on the search ads.

Also, the drop in CTR and CPC indicates a hidden opportunity that more advertisers could explore.

The growing interest in the search industry is going beyond Google. One of the latest growing trends has to do with Apple Search Ads and we are expecting to see more of them over the next quarters.

A good way to maintain your success in the search ad industry is to monitor and benchmark the rates that will bring you closer to understanding what’s perceived as success and what can be improved.

Look at the stats and the trends that are more relevant to your work and start exploring how you can improve your own ad success through them.

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SAN FRANCISCO – A trend that has been building for several years came to the forefront this week at Google Marketing Live, the company’s annual conference for advertisers. The initiative? Automated campaign types that deliver ads across multiple Google properties.

What started with Universal App Campaigns (now App campaigns) in 2017 to automate app promotion ad delivery and creative messaging across multiple Google properties has become the model for new Google Ads campaign types.

App campaigns are held up as the model for this approach, but if we go back even further, Google’s relatively short-lived mouthful Search Network With Display Select campaign type — which launched in 2013 and used an algorithm to extend Search campaigns to GDN placements predicted to perform well for its small budget advertisers — could be seen as the original harbinger of where we are today.

The idea of running Search and Display together in one campaign will still make many advertisers shudder. But most of the new campaign types don’t give advertisers the option to opt out of channel inventory. That, Google will say, was a tactic necessary in a pre-machine learning powered world. Machine learning may be overhyped, but it underpins nearly every aspect of campaigns and will continue to grow in importance.

Where Search was once the hub of AdWords, it’s becoming just one of the spokes in Google Ads.

One campaign, multiple channels

This is the latest rundown of campaign types and ad formats that can (or will soon) run across multiple Google properties:

• App campaigns, launched in 2015. Google announced last week at I/O that App campaigns can now run on YouTube — on the YouTube home feed and in in-stream video inventory — in addition to Search, GDN, YouTube, AdMob and Google Play.
• Smart campaigns, launched in June 2018, it was the first new campaign solution under the Google Ads branding. Designed for small businesses, ads run across Google.com, Google Maps and the Google Display Network (GDN).
• Local campaigns, introduced in 2018. Ads run across Search, YouTube, Maps and GDN. Last week, Google announced new inventory on Maps for Local campaigns.
• Discovery campaigns, announced this week, will launch later this year (read our coverage of the new discovery ads). Announced Tuesday, Discovery campaigns will run across the YouTube home feed, Gmail promotions and social tabs and Google Discover on mobile, the content feed on Google’s homepage. Google has been testing the ads in Discover for several months.
• Showcase Shopping ads, launched in 2016. These multi-image Shopping ads run on Search and, announced this week, will soon extend to Google Images, YouTube and Google Discover, Google said Tuesday.
• Shopping campaigns. Standard PLA formats have run in Google Images since 2016. As with Showcase Shopping ads, these ads will also be eligible to appear on YouTube and Google Discover beginning the week of July 15, 2019 when opted into the Search Network.
• Google Shopping Actions, launched in 2018. Shopping ads from retailers that enable users to buy products via Google’s universal checkout through the Google Shopping Actions program can already surface on Google Assistant and Search. Soon their ads will show on Images and YouTube as well.

From last click to customer journey campaigns

These new solutions aren’t actually called customer journey campaigns, but that’s the case Google is making: that it can offer marketers full-coverage opportunities to reach potential customers from discovery to consideration to sale.

Search had long been seen as a bottom of the funnel channel. This was in part a function of measurement limitations, and Google has been pushing marketers to move beyond last click for years now to drive investment in upper funnel search marketing. It stopped being the default campaign attribution model in AdWords in 2016.

I asked about this shift from single channel to multi-channel, full funnel campaigns at a press briefing with Google executives Monday. Sissie Hsaio, VP for mobile app ads, said there are two things driving this change. First obviously is that Google has access to many surfaces where people are in different modes of intent and discovery, Hsaio said.

“This makes it easier to reach consumers in different modalities of intent.” Second, said Hsaio, is the ability for machine learning to find users and tailor messaging and creative assets based on those modes of intent. These two concepts are coming together and getting applied to meet different advertiser and user needs, Hsaio concluded.

Beyond search intent plus. Keyword search intent was the original money signal that made Google Search ads so successful. There wasn’t a better intent signal out there, until Facebook came out with audience targeting based on interests, web and app activity, demographics and other signals and algorithms that could match ads against that those signals. Google has quickly moved from keyword-focused targeting to supporting various types of audience targeting that incorporates a slate of interest and behavioral signals it captures from across its properties. Intent is still the core of search, but Google has been stripping away keyword targeting controls (with more to come), and it’s entirely possible to run Search campaigns based on other signals and no keywords at all.

“Intent signals used to consist of two- to three-word search queries,” said Prabhakar Raghavan, Google’s SVP of ads and commerce, when I asked him about this shift in an interview Tuesday. “The click was Nirvana.” Marketers have since become more sophisticated, he said, and machine learning has advanced to be able to attribute intent in different phases of the funnel.

Anticipating consumer needs. Google America’s President Allan Thygesen, said this omnichannel approach will help marketers “anticipate” where their users will be, what they’ll be looking for, what questions they’ll be asking and problems they’ll be trying to solve. Attribution may never be perfect, but there are enough directional metrics that can be stitched together to help marketers get better at anticipating consumer needs to create better full funnel strategies. “This is a shift as profoundly disruptive as mobile,” said Thygesen.

Measurement and privacy

“Perfect multi-touch attribution isn’t yet a reality, but we shouldn’t let the perfect be the enemy of the good,” said Thygesen. Google’s measurement efforts have been made more complex by GDPR and CCPA privacy regulations and looming potential for federal regulations in the U.S., which Google is actively lobbying to influence.

Google Chief Business Officer Philipp Schindler and Thygesen were fairly candid about the need for better cross-channel measurement and were optimistic Google is getting closer to solutions that do better, but there was some expectation-setting.

“It is in all of our interests while ensuring highest bar for privacy so it might take longer for us to deliver tools you need,” said Schindler. “Doing this is very hard even for the best data scientists in the world.”

Raghavan said he’s encouraged by many of the developments happening with computational advancements in the cloud. He noted that Ads Data Hub, “while you can think of it as a platform, there are things falling into place that allow us to form attribution-like computations without exchanging data. And I think that’s a huge advancement technically.”

Google hammered the privacy messaging. By its telling, the company’s tarnished reputation on privacy is a function of it not being more open about how it has thoughtfully approached data segmentation for years. “The wealth of the data is really used for personalizing consumer experiences far more than the little fraction that’s used for advertising,” said Raghavan.

It’s trying to walk a tenuous line between what Schindler described as a commitment to offering “full visibility” for marketers while protecting user privacy.

Raghavan said, “The thing we think about hardest here is how you can get this level of ad click modeling of consumer behavior and conversion behavior without compromising user trust.” Conversion modeling is being done for users that opt out of tracking in their account settings or block cookies. It does not show marketers any reporting breakouts on modeled versus attributed conversions.