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.

April was a big month for Google Data Studio (GDS), with Google introducing some significant product updates to this already robust reporting tool.

For those not familiar with GDS, it is a free dashboard-style reporting tool that Google rolled out in June 2016. With Data Studio, users can connect to various data sources to visualize, and share data from a variety of web-based platforms.

GDS supports native integrations with most Google products including Analytics, Google Ads, Search Ads 360 (formerly Doubleclick Search), Google Sheets, YouTube Analytics, and Google BigQuery.

GDS supports connectors that users can purchase to import data from over one hundred third-party sources such as Bing Ads, Amazon Ads, and many others.  

Source: Google

1. Google introduces BigQuery BI Engine for integration with GDS

BigQuery is Google’s massive enterprise data warehouse. It enables extremely fast SQL queries by using the same technology that powers Google Search. Per Google,

“Every day, customers upload petabytes of new data into BigQuery, our exabyte-scale, serverless data warehouse, and the volume of data analyzed has grown by over 300 percent in just the last year.”

Source: Google

2. Enhanced data drill-down capabilities

You can now reveal additional levels of detail in a single chart using GDS’s enhanced data drill down (or drill up) capabilities.

You’ll need to enable this feature in each specific GDS chart and, once enabled, you can drill down from a higher level of detail to a lower one (for example, country to a city). You can also drill up from a lower level of detail to a higher one (for example, city to the country). You must be in “View” mode to drill up or drill down (as opposed to the “Edit” mode).

Here’s an example of drilling-up in a chart that uses Google’s sample data in GDS.

Source: Google

To drill-up by year, right click on the chart in “View” mode and select “Drill up” as shown below.

Visit the Data Studio Help website for detailed instructions on how to leverage this feature.

3. Improved formatting of tables

GDS now allows for more user-friendly and intuitive table formatting. This includes the ability to distribute columns evenly with just one click (by right-clicking the table), resizing only one column by dragging the column’s divider, and changing the justification of table contents to left, right, or center via the “Style” properties panel in “Edit” mode.

Source: Google

Detailed instructions on how to access this feature are located here.

4. The ability to hide pages in “View” mode

GDS users can now hide pages in “View” mode by right clicking on the specific page (accessed via the top submenu), clicking on the three vertical dots to the right of the page name, and selecting “Hide page in view mode”. This feature comes in handy when you’ve got pages you don’t want your client (or anyone) to see when presenting the GDS report.

Source: Google

5. Page canvas size enhancements

Users can now customize each page’s size with a new feature that was rolled out on March 21st (we’re sneaking this into the April update because it’s a really neat feature).

Canvas size settings can be accessed from the page menu at the top of the GDS interface. Select Page>Current Page Settings, and then select “Style” from the settings area at the right of the screen. You can then choose your page size from a list of pre-configured sizes or set a custom size of your own.

Source: Google

6. New Data Studio help community

As GDS adds more features and becomes more complex, it seems only fitting that Google would launch a community help forum for this tool. So, while this isn’t exactly a new feature to GDS itself, it is a new resource for GDS users that will hopefully make navigating GDS easier.

Users can access the GDS Help Community via Google’s support website or selecting “Help Options” from the top menu bar in GDS (indicated by a question mark icon) then click the “Visit Help Forum” link.

Source: Google

Conclusion

We hope that summarizing the latest GDS enhancements has made it a little easier to digest the many new changes that Google rolled out in April (and March). Remember, you can always get a list of updates, both new and old by visiting Google’s Support website here.

Jacqueline Dooley is the Director of Digital Strategy at CommonMind.

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Call analytics can be a touchy subject among some marketing teams, particularly those that have strained relationships with the sales team of their organizations. The tension between the two departments often leaves a gap between our teams that, when bridged, create valuable insights into cross-channel campaign effectiveness and sales results. Thanks to the rise of mobile in e-commerce, digital marketers need to incorporate call analytics into their reporting strategies to tell the whole story of the customer journey.

Go beyond basic call tracking

According to research from Forrester, customers who call tend to buy more, make purchases quicker and remain customers longer than customers from other channels. Customers who initiate an inbound phone call during the customer journey convert an average of 30 percent faster — and spend an average of 28 percent more.

Having a handle on customer sentiment will significantly improve your holistic digital strategy. You know what your customers “do” with your campaigns, but how do they “feel” towards your brand? What happened when they called? What was the salesperson’s impression of the customer’s attitude towards him or her? Understanding the conversational context in which the sales team engages with them can help you better understand these factors and identify signals of intent (or attrition).

Amanda Farley, partner at SS Digital Media, recommends that marketers with the bandwidth listen in to sales calls — with both positive and negative outcomes — to better understand the conversation that drove the result. “There is usually a disconnect between marketing campaigns and the people answering the phone,” she said. “The messaging on the ads might be clear about who a brand is, but it’s really about how phone calls are facilitated.” Establishing this practice, according to Farley, can create valuable learnings for sales and marketing teams and improve the experience for inbound callers.

On smaller teams, dedicating a marketer to listen in on recorded phone calls might not be feasible. However, working with the sales team to provide visibility into your digital campaigns can be a step in the right direction towards understanding the context of inbound calls. Enabling the sales team with a process and the right tools to do this; for example, custom fields can be added to your CRM to capture the information.

More advanced organizations with systems already in place can take advantage of natural language processing features to perform on-call analysis of spoken words and phrases that have been identified as signals of conversion intent.

Create sentiment-informed campaigns

Analytics provide a healthy performance analysis, but they lack the contextual elements of what the customer’s experience with your brand was. Conversation analytics are an example of measurable insights that we can use to determine messaging, identify strengths and weaknesses, assess campaign effectiveness and measure customer sentiment.

Customer sentiment should be considered when you are developing segmentation strategies for email campaigns, designing landing pages and marketing automation. Messaging, for example, can be explicitly written to serve the individual’s needs based on their sentiment rating. If a salesperson indicates a customer has a negative experience, use the event as a trigger to initiate a win-back campaign — before the customer hangs up for good.

It’s all about the relationships

Our relationships with sales can present many challenges for organizations of all sizes — from using siloed platforms to being in different physical locations, it can be difficult to establish rapport with other teams. However, building that relationship is a critical element to optimizing and truly understanding call analytics and customer sentiment. Partnering with sales to clearly define and align goals improves the holistic sales and marketing strategy with the added layer of customer-data to help influence campaigns.  Adding the measurement of customer sentiment to this will provide new opportunities for your teams to share valuable insights, better understand customers and foster better relationships with them.

For over a decade, SMX® Advanced has proudly delivered an elite, unbiased, vendor-agnostic editorial program to thousands of search marketers from around the world.

But we also know how important it is to learn first-hand from the search engines you trust with your rankings and advertising dollars.

That’s why we’re thrilled to invite you to Seattle, June 3-5, to train directly with Google and Microsoft. Only SMX Advanced brings these two powerhouses together in one place. Check out what’s in store:

Exclusive Keynotes & Sessions

The SEM track will kick off with an in-depth keynote conversation about the future of search marketing and advice for staying competitive in an increasingly automated landscape — featuring Search Engine Land’s editor-in-chief, Ginny Marvin, Nic Darveau-Garneau, Chief Search Evangelist for Google, Vaishali De, Partner Group Program Manager for Microsoft Advertising Engineering, and Lynne Kjolso, VP, Global Search Sales & Support for Microsoft Search Advertising.

Then, it’s time for insightful, tactic-rich SEO and SEM sessions, including…

• Google & Bing Talk Spam & Penalties: Want a behind-the-scenes view of how Google and Bing determine what’s good and what’s bad? Join Fili Wiese, former Google Search Quality team member, and Frédéric Dubut, who leads the anti-spam team at Microsoft, for a candid conversation on how both engines are fighting spam and handling manual penalties.
• What’s New With Schema & Structured Data: Cata Milos, Senior Program Manager at Manager, will join Max Prin, Head of Technical SEO at Merkle, for a look at advanced structured data tactics that ensure your sites rank well by making content accessible to search engines. You’ll also get advice for how to future-proof content to avoid getting left out of the voice search conversation.
• The Evolution Of Branding: Brand To Demand: Helen Provost, Google, Account Manager, will share brand-new insights why branding is more important than ever, quantify the value of digital brand advertising in the path to purchase, and provide actionable guidance on how to create a branding media plan on a limited budget using machine learning and automation for scale.

Learn With Google

Join the Google Ads team Tuesday, June 4 for full-length sessions exploring some of the most crucial aspects of successful account and campaign management. Check out some of the sessions in store:

• Managing Large Accounts With Google Ads Power Tools
• Understanding Your Creative Potential In Google Ads
• Delivering Fast, Assistive Experiences To Supercharge Your Google Ads Performance

Microsoft Networking & Solutions

You’ll catch Microsoft Advertising (formerly Bing Ads) in a few different places:

• Meet up Monday evening, June 3 for a special Microsoft-hosted networking event about inclusion and diversity in the workplace.
• Attend the 2019 Search Engine Land Awards Ceremony & Afterparty on Tuesday evening, June 4, sponsored by Microsoft Advertising, for a fantastic evening celebrating the search community.
• Come by the Solutions Track on Wednesday, June 5 for two exciting training sessions with the Microsoft Advertising team.

Choose Your Ideal Pass

Book before Monday, June 3 to save up to $300 off on-site rates! Pick the pass that suits your goals and budget and register now.

• All Access: All sessions, keynotes, networking, and amenities.
• All Access + Workshop Combo (best value!): The complete SMX experience, plus your choice of an immersive, full-day workshop.
• Networking & Search Engine Land Awards: Full access to the Expo Hall and networking events, plus sponsored sessions (including Learn with Google and the Microsoft Advertising sessions mentioned above!), downloadable speaker presentations, and more.

Register now!

See you in Seattle!

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