Tag Archives: SEM

PPC insights: Our top SEM columns of 2017

Though paid search has long since cemented its place as a pillar of digital marketing, changes in technology and consumer behavior have continued to reshape the PPC landscape and keep search marketers on their toes. In 2017, we saw the last of “standard” text ads in AdWords as expanded text ads, introduced in 2016, became the new norm. We also said goodbye to the literal definition of “exact” as Google expanded exact match targeting to include close variants.

Yet, on the whole, search marketers spent more of 2017 looking forward than dwelling on the past. Two of our most widely-read columns, penned by former Googler Frederick Vallaeys, were forward-thinking pieces that focused on how artificial intelligence (AI) and machine learning are driving innovation and automation in paid search.

This past year also saw a host of new feature releases, and with new capabilities comes the need to try new things — which is why so many of our top columns this year focused on testing. From ad copy testing to landing page testing, search marketers sought out resources to help ensure that their ads are reaching their full potential.

For these topics and more, check out Search Engine Land’s top paid search columns of 2017!

    The best-kept AdWords secret: AMP your landing pages by Frederick Vallaeys, published on 5/10/2017.Seriously, Google, can you just make exact match exact? by Daniel Gilbert, published on 3/21/2017.Attention search marketers: ALL keywords are branded keywords! by Larry Kim, published on 1/23/2017.10 AdWords ad copy testing ideas you can use right now by Jason Puckett, published on 3/14/2017.The AdWords 2017 roadmap is loaded with artificial intelligence by Frederick Vallaeys, published on 6/7/2017.3 free AdWords testing tools to adopt today by Todd Saunders, published on 3/7/2017.Three foolproof steps to excellent AdWords ads by Matt Lawson, published on 3/17/2017.This script creates Google Slides with AdWords data to automate your presentation-making by Frederick Vallaeys, published on 8/2/2017.The great big list of landing page tests to try by Amy Bishop, published on 5/2/2017.How artificial intelligence drives PPC automation by Frederick Vallaeys, published on 1/18/2017.

Using AdWords API to export to third-party ad networks will remain OK as Google keeps terms it adopted in FTC settlement

Though the part of Google’s antitrust settlement with the Federal Trade Commission that had them allow exports of AdWords data through its API expires tomorrow, Matthew Sucherman, Google’s VP and deputy general counsel, announced today that Google will keep the AdWords API terms and conditions as they are currently.

That means Google will continue to allow software that interfaces with its API to export AdWords campaign and ad data, so users will be able to continue mixing that data with other information and integrating it into other ad networks, such as Bing Ads.

“We believe that these policies provide continued flexibility for developers and websites, and we will be continuing our current practices regarding the AdWords API Terms and Conditions and the domain-by-domain opt-out following the expiration of the voluntary commitments,” Sucherman said.

Google explained that this requirement expires tomorrow, December 27, 2017, but they have decided internally to keep the terms and conditions as is.

Additionally, Google will continue to allow websites to keep their crawled content from appearing on Google.com-linked pages for Google Flights, Google Hotels, Google Shopping and in results returned for certain local queries. The provision enables a competing site to allow its pages to be included in web search results while keeping them from appearing on more directly competitive Google offerings — though opting out from the local results would apply globally.

Google wrote:

In 2012, Google made voluntary commitments to the Federal Trade Commission (FTC) that are set to expire on December 27th, 2017. At that time, we agreed to remove certain clauses from our AdWords API Terms and Conditions. We also agreed to provide a mechanism for websites to opt out of the display of their crawled content on certain Google web pages linked to google.com in the United States on a domain-by-domain basis.

We believe that these policies provide continued flexibility for developers and websites, and we will be continuing our current practices regarding the AdWords API Terms and Conditions and the domain-by-domain opt-out following the expiration of the voluntary commitments.

6 ways ad agencies can thrive in an AI-first world

Artificial intelligence (AI) and machine learning have long been part of PPC — so why are AI and machine learning all of a sudden such hot topics? It is, in part, because exponential advances have now brought technology to the point where it can legitimately compete with the performance and precision of human account managers.

I recently covered the new roles humans should play in PPC as automation takes over. In this post, I’ll offer some ideas for what online marketing agencies should consider doing to remain successful in a world of AI-driven PPC management.

Be a master of process

According to the authors of the book “The Second Machine Age,” chess master Garry Kasparov offered an interesting insight into how humans and computers should work together after he became the first chess champion to be defeated by a computer in 1997. In matches after his loss to Deep Blue, he noticed a few things:

    A human player aided by a machine could beat a computer.When two human players were both assisted by a computer, the weaker human player with a good process could beat the stronger player with an inferior process.

The first point is covered in my previous post, and it is the foundation for why smart PPC managers will learn to collaborate with AI rather than compete against it.

The second point got me thinking about some other scenarios where the winners aren’t necessarily the most skilled. Does the world’s most successful coffee chain have the best baristas? Do the most successful hotels employ staff who innately know how to make guests happy?

No. In almost any scenario where humans are a big part of the experience, success is achieved by having a clear mission that is supported by a really strong process and tools to achieve the mission.

Hence, I believe that in the world of PPC agencies, a primary focus should be on building an amazing process and equipping the team with tools that make that process easy to follow. So as AI takes over some of the tasks in your agency, make sure your staff knows and follows the process for leveraging the technology to deliver results.

Accept that your old value proposition is toast

Consider how you convinced your existing clients to sign up with your agency. If your pitch included that you produce amazing results because you’re really good at bid management (something machines are getting really good at), you may need to tweak your positioning. You don’t want to make your main value proposition something that can be put on autopilot by anyone — and will hence become very difficult to price at a level that makes you successful.

That’s not to say that you should stop thinking about something like bid management altogether. Instead, you should offer skills that are complementary to the AI system rather than skills that compete against it.

Hal Varian, Google’s chief economist, gives the career advice to “become an indispensable complement to something that’s getting cheap and plentiful.” For example, become a data scientist because we’ll need more people to make sense of the data and to figure out how to turn new insights we get from more sophisticated AI into new strategies.

In the context of an ad agency, this makes a lot of sense. You want to be able to say you have great data scientists who can make sense of what the automated systems are doing and make solid recommendations for the next thing to test.

Determine your new value proposition

Do you know California’s largest agricultural export? I guessed wine, but the correct answer is almonds. How did this come to be? It turns out that almonds are easy to harvest mechanically; you basically have a machine that violently shakes the tree so the nuts fall down to be harvested. So farmers figured they could be more productive by using automation, and all of a sudden tomato fields across the state were turned into almond orchards.

But people want more than just almonds on their plates, so despite how automation moved an entire state’s economy in a certain direction, it also created opportunities for farmers who didn’t automate.

We can apply this analogy to paid search agencies. Thanks to advances in AI, it is a given that they will do a good job of managing bids, and it’s also assumed that this service will be cheap because technology has commoditized it.

Agencies, like farmers, can supplement their highly automatable service offerings with something that commands a higher fee. So figure out what will be your niche in things that are harder to automate. And think about why a client would want to hire you if you’re just as good as the next agency at managing bids. Figure out what additional services you are really good at that are harder to automate (for now) and can be used to win new business.

Be the best at testing because testing leads to innovation

Innovative agencies win awards, which makes it easier for them to land new clients and grow their business. But how can an agency be innovative in a world where a lot of the work is done by a handful of automated systems that produce similar results?

I believe economist Martin Weitzman’s recombinant view of innovation offers a possibility. Recombinant Innovation describes innovation as a process through which new ideas emerge as the combination of existing ideas. Thanks to better prediction systems using machine learning, it is now possible for agencies to test new ideas faster and to iterate faster. Hence, an agency that leverages machine learning for testing and has a really strong process will be able to out-innovate its competitors.

Innovation in an agency is to recombine ideas into valuable new ones. The problem with testing new ideas is that it used to take a lot of time. But thanks to technology, you can test more things more quickly, and the winning agencies will be those that are the fastest at finding new winners. And they can achieve this by prioritizing the most likely winners into the fastest process, with the best testing technology.

You need to monitor the tradeoffs between labor and technology

Business is a big optimization problem. As an agency owner, you balance labor (headcount), and capital investment (technology) to achieve outcomes with a target level of speed, quality and cost. As technology takes hold in more aspects of PPC management, knowing how to optimize the equation becomes critical.

What some advertisers fail to see is that there is no perfect technology (just as there is no perfect human employee), but if a technology gets you close enough to the desired result while freeing up your staff’s time to work on other things, that is a win.

We all hire people for our companies, even when we know that ALL humans make mistakes. But we hire the best we can because it gets us closer to our goals, even if not 100 percent of the way. So why should it be any different when we think about capital investments?

A former colleague of mine who is still at Google shared examples where advertisers told him that they would not use broad match because it resulted in some impressions for their ads on irrelevant queries. But when prodded further, they were unable to quantify the impact this had. In many cases, the additional clicks were negligible, while the time they could have saved by letting Google’s AI handle query exploration was significant.

In my view, this is a poor optimization of that account manager’s time. In exchange for a small sacrifice in targeting precision, they could have freed up billable hours worth hundreds of dollars.

Hire one extraordinary (wo)man

American philosopher Elbert Hubbard said that “one machine can do the work of fifty ordinary men. No machine can do the work of one extraordinary man.” And he was on to something. In engineering, a great engineer can do the work of 10 good engineers.

So, as more of an agency’s work gets done by machines and you need fewer humans to do repetitive work, having the smartest possible person to work on the tasks that remain will be more important than ever.

Conclusion

There’s never a boring day when working on PPC, mostly because Google pushes so many changes every year. But this year, AI is going to stir the pot and create some challenges unlike the ones we’ve been used to dealing with. Hopefully, some of the thoughts shared here will get you thinking about strategies for keeping your agency successful in a world of AI-first PPC.

Stay tuned for my next post in this series, where I’ll cover how the technology got us here and what we can automate today.

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

PPC 2017: Epic review of the biggest trends & updates in paid search

As 2017 draws to a close, let’s take a moment to catch our breaths and look back at the whirlwind that was PPC in 2017.

There wasn’t a big change that dominated the landscape like enhanced campaigns of 2013 or expanded text ads of 2016, but multiple trends created an atmosphere of constant, incremental change this year. However, if we were to dub 2017 the year of something in search marketing, it would clearly be the year of the machine. While machine learning and other forms of artificial intelligence aren’t new to search marketing, their use became pervasive in 2017.

Here’s a look back at the big developments and key trends that happened in PPC in 2017 that will continue to inform and influence our work in 2018.

Finally past the year of mobile, this was the year of AI in search

Sure, there is still work to do in improving mobile experiences and conversion rates, and we’ll continue to see Google, in particular, push its initiatives in this area: AMP for ads and landing pages, Purchases on Google and more. This year, the big shift was the extent to which machine learning and other forms of artificial intelligence permeated all things search.

Here are eight highlights of ways the search engines ingrained machine learning into their products. They cover everything from keyword matching to ads to audiences to spend pacing to attribution:

In March, Google made putty of the meaning of ‘exact’ in exact match, stretching it to include close variants of a keyword with different word order and/or function words.Ad rank thresholds got a machine learning infusion to take the context of a query into consideration when setting the bid floor.Google’s Smart display campaigns are nearly entirely powered by machine learning.Google’s data-driven attribution methodology is entirely AI-powered. It’s been in AdWords for more than a year, but it gained new attention with the introduction to Google Attribution.Google and Bing released new automated bid strategies: Bing’s Maximize Clicks and Google’s Maximize Conversions.Google’s move to let daily spend exceed up to 2x the budget? Yep, that, too, relies on machine learning to try to predict spend trends throughout the month.One flavor of Google’s custom intent audiences on the GDN uses machine learning to automatically create audiences based in part on inferred characteristics of an advertiser’s target customers.Bing Ads is testing AI-powered chatbot extensions in search ads.Dynamic Search Ads in Bing Ads came to the US and the UK.

Forget A/B testing, because machine learning

Another big, if more subtle, shift was in ad testing methodology. All year, Google has pushed advertisers to move away from the A/B testing model of running two ads per ad group and manually assessing performance.

If there was any doubt Google was serious about this, the move to limit ad rotation options in August put that doubt to rest. The change makes the push for advertisers to choose “optimize,” letting the machines choose the best ad to serve, that much more forceful. Google’s Matt Lawson laid out in a column last month the argument for having at least three ads in an ad group: Overall impressions will increase as Google’s algorithms will serve up the best ad based on the specific query. Advertisers shouldn’t even be evaluating individual ad performance under this new rubric, but rather at the ad-group level of performance, says Google.

To this end, Google rebooted its Ads Added by AdWords pilot in September. The ads suggestions test automatically generates additional text ads (for approval) in some ad groups. Again, the goal is to get more advertisers running more ads in their ad groups, even if Google has to do the work for them.

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Identity & audience targeting

Dovetailing with the rise of machine learning is the steady advance in audience targeting capabilities. Keyword intent may still be the calling card of search marketing, but audience targeting options continued to expand. The popularity of Facebook’s audience-focused, people-based marketing approach largely precipitated this shift over the years as Google has loosened the reigns on its user data and shifted to signed-in data for audience development and targeting.

Some of the big moves in audience targeting this year:

Bing Ads began testing in-market and custom audiences at the beginning of the year. In September, it announced there are now more than 70 in-market audiences available to target.Google introduced in-market audiences and similar audiences to Search and Shopping campaigns in March, and consumer pattern targeting and life events targeting for YouTube and Gmail in May.Google’s custom intent audiences debuted in November for display campaigns.More offline data can now be used for first-party audience targeting as well. Earlier this month, Google expanded its Customer Match offering to include the ability to build retargeting lists based on customer phone numbers and addresses, not just email addresses.Microsoft has begun integrating the LinkedIn Graph with the Microsoft Audience Intelligence Graph. We should expect audience targeting to come out of this effort in 2018.

Attribution & 0nline-offline tracking

With more channels, more devices, more campaigns and more technology in play, attribution isn’t getting any easier.  The biggest news on this front was, of course, the beta launch of Google Attribution. Announced in May, the product could upend the way many search marketers approach attribution, but the real impact won’t be seen until next year when the product rolls out more fully. Google Attribution aims to give users a bigger picture of how their channels and campaigns — at all stages of the funnel — are contributing to the bottom line.

The Google beauty of it is that the data can automatically feed back into AdWords or DoubleClick to inform bidding strategies. That’s the real motivation here; it’s not going to be the silver-bullet answer to everyone’s attribution challenges. From a Google campaign perspective, it will provide more cross-channel insights than AdWords or Google Analytics does currently.

The other big news in attribution this year largely revolved around online-to-offline conversions.

Google’s in-store sales measurement news was the most notable. In one approach, retailers can upload their loyalty or other customer email lists into AdWords. The other approach is powered by Google partnerships with financial vendors. In-store sales conversions will automatically show up in AdWords when enough conversion data is available. Google has said its vendor-supported program gives it coverage of 70 percent of credit card transactions in the US.Google’s store visits measurement extended to YouTube campaigns as of May, giving retailers insights into how effective their videos are at driving viewers to stores.Bing’s support for uploading offline CRM conversion data with a new Offline Conversion Import tool in September.Bing’s integrations with call-tracking systems to enable call conversion imports rolled out this month.

Shopping keeps growing

Across the pond, Google got slapped with a giant antitrust fine by the EU for shutting competing comparison shopping engines (CSEs) out of Google Shopping. Google is contesting the fine, but in the meantime, Google Shopping is operating as a separate business unit and will compete in auctions against other CSEs for spots in the Shopping carousel in Google search results in the EU. (Crealytics’ Andreas Reifen and I each took issue with the ruling.)

Stateside, the influence of Shopping on retail search just continued to grow. At the year’s halfway mark, Merkle reported Google and Bing saw continued growth in shopping ad spend, outpacing that of text ads among retail clients. But there’s an elephant in the room, and its name is Amazon. Amazon loomed in terms of being a head-on competitor with its one-again-off-again presence in Google Shopping, in terms of the rapid and expanding build-out of ad offerings for merchants on its own site, as well as in the realm of product discovery and ordering via digital assistant.

For its part, Google continues to experiment with the way it displays shopping ads. Below is an example of an elusive Purchases on Google ad, but these ads also have a new “Quick view” feature that lets users learn more about the product and seller right from the search results.

Google continues to search for new places to extend Shopping ad inventory. At the end of May, it automatically opted advertisers into a test to show product ads on the Display Network.

Local, driven by mobile

Mobile, voice and digital assistants will continue to spur innovation next year, but perhaps in no area greater than local. Last year, Google said local searches are growing 50 percent faster than mobile search overall and account for one-third of mobile searches. Those habits are driving the development of search ad products aimed at connecting users to local businesses (thus the increase in online-to-offline attribution capabilities covered above). Merkle’s Andy Taylor covered the growing importance of local ad products for brick-and-mortar stores in his recent column.

Though not ad-related, Bing launched bots for local businesses in Bing Places in May that also work with Facebook Messenger and Cortana.Google rebranded and expanded its ad products for local service providers. Local Services by Google will be in 30 cities as of year-end.Google teamed with HomeAdvisor and Porch to offer local services discovery and lead generation through Google Assistant and Google Home.Location extensions and store visits measurement extended to YouTube in October.Text ads and Local inventory ads (LIA) began showing in local knowledge panels in Google search results.

Local inventory ads began showing in local knowledge panels in August.

Honorable mentions

We can’t close out a 2017 wrap-up without mentioning the new AdWords interface. There is a lot of grumbling about the new UI, which is expected to become the de facto interface at some point in 2018. Change isn’t easy, and there still isn’t enough parity or ease of use to have endeared it to many paid search managers who are in it on a daily basis managing campaigns. But every sign indicates Google is leaning into this new “experience,” not backing away. There are many, many features now that are only available in the new UI. That will only continue.

In further evidence that 2017 was one long year, some updates that feel much older than they actually are. Can you believe Google switched to the green outline Ad Label this year (February)? All Mac users got access to Bing Ads Editor in March. Google added historical Quality Score data in AdWords in May. Oh, and AdWords price extensions rolled out to all devices in March, and Bing merchant promotions in Shopping ads came out of pilot in the US in April.

That does it for 2017. After I wrote this piece, I looked back at how I concluded 2016’s year-end wrap-up: “Expect to see the trends we saw this year — audiences; attribution, including online-to-offline; mobile; and automation — continuing to influence change in the year ahead.”

Looking at that list of trends in terms of next year, I’d swap out mobile for local (mobile is foundational now) and add voice marketing to the mix. We are still in very early days with voice and digital assistants in terms of marketing potential, but I expect we’ll continue to see this area develop rapidly.

What you learn from talking with Google’s largest advertisers all day, every day

There’s a position at Google called “Chief Search Evangelist.” It’s evolved in the years since Fred Vallaeys filled that role, now focusing on meeting with our advertisers in person when they come to visit Google on-site. I think my job is pretty cool, but I must admit that the idea of talking search ads day-in, day-out with people at the cutting edge of their craft makes me more than a bit jealous. Nicolas Darveau-Garneau, who currently fills the role of Chief Search Evangelist, is the man whose job turns me a light shade of green with professional envy.

I learn so much every time I talk with Nick, so I thought it would be fun to sit him down and pick his brain about all of those meetings he gets to have. Here’s an edited transcript of the wide-ranging conversation we had recently about automation, growth, keywords and more.

Nicolas Darveau-Garneau, Chief Search Evangelist at Google

Lawson: What are the biggest trends that you’ve noticed when talking with top AdWords marketers?

Nick Darveau-Garneau (NDG): The best in the business have really figured out how to use automation and machine learning. Managing a search campaign should be partially automated these days, and there’s so much value you can unlock when you’re strategic about using automation. I’ve seen the most success here when people have a clear strategy, focusing on user experience and personalized marketing. Then they leave a lot of the detailed stuff to automation.

I consider this setup to be “semi-automated marketing.” Set the right KPIs, then let the machines do most of the work. You don’t need to worry about the results of individual tactics or specific keywords anymore. In fact, I see automated tools like Dynamic Search Campaigns and Smart Bidding largely outperforming manual optimizations.


Lawson: Semi-automated marketing. I like that. What does that look like in practice?

NDG: A lot of it is straightforward work that I already imagine people are doing. Smart Bidding (Target CPA and Target ROAS, in particular), Data-Driven Attribution, Dynamic Search Ads. And they work well together, so use them all.

I’ve also seen plenty of companies have success by buying into automation with their ads. The faster people realize that ad testing is a thing of the past, the better off they’ll be. Optimize your ad rotation, enable as many extensions as you can, and add a bunch of ads to your ad groups. Using optimized rotation uses the most appealing ad at the time of each auction, for each individual customer. I know you wrote about this recently on Search Engine Land, so just add that link and tell people to read it.

Bottom line: Use the entire search machine learning stack together.


Lawson: One of the more controversial things I’ve heard you talk about before is keyword selection. What’s your preferred method?

NDG: I don’t think my opinion should even be considered controversial. Once you believe in machine learning like I do, I think it’s easy to believe in this. And it’s simple, really: Buy all the relevant keywords.


Lawson: All of them?

NDG: Yep. All of them. Look, there’s no need to carefully select our keywords anymore. The machine will automatically figure out which of those work for us. I mean, when you’re using Smart Bidding, you’re already setting bids on a query-by-query basis. If that query sees OK performance, the algorithm will set OK bids. If that query works great, you’ll set very competitive bids. And if one query doesn’t work that often, the bids will be set accordingly. That even includes cases where your bids are so low as to effectively pause that keyword. If things change, think [about] your conversion rates or even the competition on that keyword/query, then you’re eligible to try out that auction again.

Some advertisers are also being more aggressive and use a lot more broad match because Smart Bidding sets bids at the query level, not the ad group level.


Lawson: And Smart Bidding isn’t the only tool to use with your keywords. You’re a big believer in audience targeting, too, right?

NDG: Oh, absolutely. It works really well. You want to power all of that bidding with your most important audience signals. Smart Bidding considers your audience lists, so feed those lists into your campaigns. You can stop worrying about bid modifiers, as Smart Bidding looks at audience along with a ton of other stuff. Just like ad testing is outdated, audience bid adjustments are irrelevant if you’re using Smart Bidding.


Lawson: There’s that semi-automated marketing again. As people get used to handing some control over to the machine, what are the things they should pay special attention to?

NDG: I mentioned the strategic stuff like customer experience already, and that’s incredibly important. Really focus on improving the customer experience. The most successful advertisers have high conversion rates relative to their competitors. Stay ahead of the pack by using tools like AMP for AdWords, parallel tracking, one-click signup and one-click buy. The better your conversion rate, the higher your ceiling as a marketer.

Something else I think is important is KPIs. One of the key issues that differentiates top advertisers is the KPIs they select. It’s almost like an evolutionary scale. You might start with doing what you can on a fixed budget, then you graduate to a CPA target, then you evolve to a sales ROAS and eventually a profit-margin ROAS. And the ideal final state is cash flow based on lifetime value.

Once you’ve got the right KPIs in place, and once you’re measuring those KPIs effectively, there’s really no limit to what you can do.


Lawson: You mentioned measuring KPIs effectively. What does that look like?

NDG: It’s about data. The best way to improve your account is to understand its performance as fully as possible, so share data with your agencies and platforms as much as possible. Smart Bidding gets better as it understands the value and life cycle of your conversions as completely as possible.

Many advertisers start with simple conversion data, and from there they evolve to revenue-based conversions. And that’s true even if you’re selling something with a long sales cycle. The next level up involves sharing your margin-per-conversion. Revenue is great, but revenue doesn’t consider your bottom line. You want to be as profitable as possible, which is why I love when advertisers talk to us about margin. Finally, the cream of the measurement crop has started forecasting lifetime value of their customers. With those forecasts, they can optimize toward profitability farther out in the future than that one short-term sale.


Lawson: I know you’ve talked about profitability with customers a whole lot in the past. What’s the focus of those conversations?

NDG: It’s growth. Focus on growth. Don’t obsess over a low CPA or a high ROAS. Look at your business as a whole and see if you’re more profitable today than you were yesterday. Think of it this way: You can get 10 conversions at a $10 CPA, or you can get 15 conversions at a $20 CPA. You might be making more money at the higher CPA. Can we add a chart to this interview? Is that possible? (Note: here’s a re-creation of what NDG drew on the board.)

CPAConversionsMarketing CostMargin (@$50/conv.)ProfitCPA goal$1010$100$500$400Profit goal$2015$300$750$450

This is a super simple example, but for me, I take the second option every time. It’s only $50 more profit. But if you’re not willing to take that $50, you need to change your approach. Because once you get that extra $50, you’ll get into the mentality of how to get the next $50. And the next and the next.


Lawson: That makes sense, but not every conversion is worth the same.  How do you think about that?

NDG: That’s when forecasting LTV (lifetime value) comes into play.  Companies who can forecast the LTV of each customer they acquire at or near the time of acquisition significantly outperform their peers. Imagine being able to forecast the three-to-five-year cash flow of every new customer you acquire with good accuracy and setting your marketing KPI for customer acquisition as a percentage of that profitability. You’ll be investing something like $100 to acquire a customer worth $1,000 and $300 for a customer worth $3,000. By bidding higher for better customers, these advertisers get a much higher percentage of these top customers.


Lawson: I know you’ve got to take off to a summit. Any parting words for anybody who reads this?

NDG: Relax. Once you get comfortable navigating the world of semi-automation, you have to resist the temptation to micromanage. Hundreds or even thousands of small decisions were just removed from your plate, so you now have more time to think about the big, important items. Strategy, user experience, how to focus on being a marketer.

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

Google is testing images in search text ads

Google is running a new image test in search ads.

An image from the landing page appears to the right of the description area of the text ad. Sergey Alakov tweeted a screen shot of the ad test over the weekend.

@GinnyMarvin @rustybrick landing page image pulled into an ad. New? pic.twitter.com/GkQBliAxEl

— Sergey Alakov (@sergey_alakov) December 16, 2017

A Google spokesperson told Search Engine Land, “We’re always testing new ways to improve our experience for our advertisers and users, but don’t have anything specific to announce right now.”

Alakov is based in Toronto, Canada. I have not been able to replicate it, and it’s not clear how widespread the test is or what verticals are included besides automotive.

Google has gone through several iterations of testing images in search ads over the years. Currently, it is beta testing images in Sitelink extensions in a feature called Visual Sitelinks. Last year, Google launched large format mobile ads for automotive makers featuring a carousel of images of car models.

Supercharge your email marketing with Google AdWords

I have a confession to make.

The odds of my instantly deleting one of the many marketing emails I receive each day are about as good as Tom Brady and the Patriots making the playoffs — meaning it’s pretty likely to happen.

Unfortunately for all you email marketers out there, I’m not alone. According to email marketing service MailChimp, the average email open rate across industries is below 25 percent, with a click rate of 2 to 3 percent. That means that, on average, you’d need to send 100 emails to get two or three people to take any action. All that time and energy spent crafting the perfect email marketing campaign will be wasted if you don’t create a complementary strategy to get more sales from your hard-earned email list.

The good news is that you can use Google AdWords as your complementary strategy by simply leveraging the existing data you have on your email subscribers. Let’s dive into the best ways to make that happen.

Learn the ins and outs of Customer Match in AdWords

Customer Match in AdWords might be the greatest secret weapon for email marketers that Google has to offer. It allows you to target or exclude your existing customers on Google Search, Display and YouTube by simply uploading your customer email list to AdWords. Think of it as another way to nurture your sales leads besides sending them more emails.

The best thing about Customer Match is that it’s not that difficult to get up and running. Here’s what you need to do to get started:

Click on the “Wrench” icon in the top right corner of your AdWords Dashboard.Click on “Audience Manager” under the Shared Library section.Click on “Audience Lists” from the Page Menu on the left.Click on the blue “+” button to create a new audience list.Select “Customer List.”Choose the option to upload a plain text data file or a hashed data file.Choose your new file.Check the box that says “This data was collected and is being shared with Google in compliance with Google’s policies.”Set a membership duration (this should be determined by the types of customers that make up the list).Click “Upload and Create List.”

Please note that these instructions are for the “new” version of the AdWords dashboard. If you’re interested in Customer Match but are still using the “old” version of the AdWords dashboard, see here for more instructions.

Segment your email list

Now that you have a better understanding of Customer Match, let’s take a look at how you might want to slice and dice your email list to more effectively target your sales leads on AdWords.

Take a look at the following email audience segments we use at AdHawk (my company) for a moment:

New and engaged email subscribers who have not become customers.Email subscribers who have not opened an email recently.Email subscribers who are existing customers and would be a good fit for an upgraded product or service.

Each of these email audience segments has an entirely different relationship with our business and needs to be messaged to differently. If you have a similar breakdown of your marketing emails, you can repurpose your email list segmentation for your AdWords campaigns via Customer Match. This will allow you to tailor the messaging of your ads for each segment, and as a result, help to nudge your sales leads farther down your funnel.

Create a different AdWords strategy for each segment of your email list

Once you have your email audience segments in place, it’s time to develop a unique AdWords strategy for each segment.

I’m going to use the three email audience segments noted above as examples. Your approach might be different, and that’s okay. Just make sure you’re not using general ads for every email audience segment you have on your list.

Converting new and engaged email subscribers

When a new lead signs up to learn more about AdHawk, our team goes into “educate” mode. The goal is to get them to see the value of our product and services as quickly as possible so we can move them down the funnel.

Our “Welcome” email flow takes the first steps in educating our leads, and it performs pretty well compared to the industry average. But our secret weapon emerges when we take a list of our “new” sales leads and turn it into a Customer Match campaign in AdWords.

Here’s what a typical flow for this segment looks at AdHawk:

Step 1: Potential customer signs up to learn more about AdHawk.Step 2: After signing up, the potential customer receives the first email in the “Welcome” email flow, with a call to action to book a time with our sales team.Step 3: A Customer Match segment is created for all “new” prospective customers that didn’t take action on the first email in the “Welcome” email flow.

By using a Customer Match segment for all new and engaged AdHawk sales leads, we’re able to bid up on more generic keywords that would be too risky to bid up on for a general search campaign. We’re also able to create Gmail Ads with a similar look and feel to our “Welcome” emails series that prompt a strong customer recall.

Converting unengaged email subscribers

Converting unengaged email subscribers can be a huge pain in the butt. They’ve stopped engaging with your emails, so the worst thing you could do is continue to bash them over the head with more emails.

Here’s the flow we use to re-engage leads that have left us hanging:

Step 1: Potential customer signs up to learn more about AdHawk but does not engage with our emails for 30 days.Step 2: A Customer Match segment is created for all “unengaged” prospective customers.Step 3: A Remarketing campaign is created to target prospective customers that have not converted after 30 days.Step 4: We tailor the Customer Match and Remarketing ads to promote a special offer.

This group is the least likely to convert, so any new business scraped up is a huge win! It’s important to educate these stale leads on what we do and remind them why they signed up in the first place.

Upselling existing customers to a new product or service

Most marketers are so intent on attracting new business that they often forget that there is a wealth of opportunity under their noses. Don’t sleep on marketing to those that have bought something from you in the past! We use our existing customer segment to promote new features or products we feel they will be a good fit for.

Here’s the flow we use to target existing customers:

Step 1: A Customer Match segment is created for our “Existing Customers.”Step 2: We further segment this list by renewal date to ensure that customers see our ads when their contract is up.Step 3: Tailor the ads to promote additional services we offer that our customers are not leveraging.

We’ve structured our flow this way because our product runs on a subscription basis. If you’re selling physical goods that can be repurchased often, break down your segment by the products your customers have shown the most interest in. That way, you can tailor your ads to the specific products you believe would resonate most with them.

Final thoughts

Are you leveraging AdWords as part of your email marketing strategy? If you are, I’d love to learn more about what strategies you have used that have been successful.

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

Google Ad Grants policy changes include 5% CTR minimum, up from 1%

Google is making changes to Ad Grants, the AdWords program that provides search advertising grants of up to $10,000 per month to non-profits.

As first reported by Robert Brady on the Clix Marketing blog, advertisers and agencies began receiving email notification this week extolling the fact that more than 35,000 non-profits participate in the Google Grants program and news that it is lifting the $2 bid cap when campaigns use Maximize Conversions bid strategy.

That news was then followed by a set of links to updated policy pages. On those pages Brady discovered several other significant changes.

The biggest update is a new requirement for accounts to maintain a minimum 5 percent click-through rate (CTR). That’s an increase from a 1 percent CTR minimum. Accounts that miss that threshold for two consecutive months will be suspended. Accounts in jeopardy of being canceled will be “alerted through in-product notifications if your account is at risk of falling below 5 percent CTR with educational resources offered to improve.”

Other updates include:

Non-profits cannot buy branded keywords they don’t own.Keywords must have quality scores of 2 or higher.Campaigns must have at least two ad groups with at least two ads running in each.Accounts also must have at least two sitelink extensions active.

The new policies go into effect on January 1, 2018 — just weeks away. Of the short timeline, Brady writes, “…  asking nonprofits to make such significant changes on such short notice (only 17 days from email send before these go into effect) is just bad customer service. And if they try to say that one email and a few notifications in the interface are enough, then they don’t understand how busy nonprofits are.”

Last year, Google wound down the Grantspro program, which was the premium Google Grants offering for non-profits spending between $10,000 and $40,000 per month.

The vicious cycle of ROAS targets is killing your business

Your marketing team is hard at work tweaking ads and landing pages to drive efficiency and hit the targets set for them by the C-suite. And those targets are more than likely ROAS-related.

But, for two reasons, these ROAS targets are actually causing a lot of damage:

    ROAS usually doesn’t take incrementality into account, which incentivizes marketers to turn on retargeting or brand campaigns to meet their targets while hardly generating any tangible results.It sets incentives to sell more low-margin products to mainly existing customers because this type of second-class revenue is cheaper to get.

If, like most companies, you’re focused on growth and new customer acquisition, you need to ditch ROAS-based KPIs, come up with a new metric and include incrementality before it’s too late.

This is what you get if you ignore incrementality

When we talk about “incremental sales” as a digital marketing KPI, we’re talking about how much a specific marketing campaign or channel contributed to increasing sales revenue. So, if a search or shopping ad led to a sale that wouldn’t have happened otherwise, that’s an incremental sale.

Return on ad spend (ROAS) takes into account purchases from users after clicking on an ad. At first glance, that sounds reasonable. It seems like that measure would tell you how good an ad is at driving revenue.

But what ROAS usually doesn’t tell you is whether or to what extent those sales would have happened anyway (without showing ads). In other words, ROAS doesn’t account for incrementality.

Imagine you’re shopping for high-priced luxury products; you put them in the shopping basket, but then decide to wait another few days to think about whether it’s worth spending the money. Then you see your favorite products following you all over the web, and at some point, you’re intrigued to click through. Finally, the day after, you buy. This happens hundreds of thousands of times every day.

Our industry now understands — much better than a couple of years ago, at least — that a significant number of these people would have bought the items anyway, even if they hadn’t seen the ad.

You’re probably thinking, “OK, sure, but how big a deal is incrementality, really?” It turns out it’s quite a big deal. Based on our internal client testing here at crealytics, we’ve found the following:

If you’re a multibrand retailer (e.g., Kohl’s or Staples), brand searches will usually drive no more than 1 percent incremental sales.Display retargeting often hovers around 5 percent incremental sales when tested properly.Search retargeting rarely gets higher than 20 percent incremental sales.

Channels that drive the highest number of incremental sales are also generally more expensive. So, if you set ROAS targets without taking incrementality into account, marketers will have to look for cheaper sources of revenue. Usually, they will see themselves in a situation where “Search Brand” is already split out and treated separately because of the obvious lack of incrementality. So, where do marketers find the revenues they need?

The revenues which are least incremental are usually the cheapest, and therefore, marketers often try to increase the volume of display or Facebook retargeting first. Search retargeting is also a great way to hit targets without really having a substantial impact on the business. And the best part about search retargeting is that it’s hidden in the overall search numbers — you have to really zoom into AdWords to see what percentage of the revenue is coming from people who might have bought without spending ad money.

The vicious circle of ROAS targets

Let’s assume you’ve tested the incrementality of your most important marketing channels, and you’re factoring in the findings when measuring the success of your campaigns. Instead of setting traditional ROAS targets, you now refer to incremental ROAS.

In this case, ROAS should no longer be an issue, right?

Sadly, no. In reality, it’s still a big issue which silently destroys performance even at some of the savviest retailers.

How performance marketing targets are set

In most retail companies, marketing budgets are set by finance looking at the historical performance of past advertising campaigns. They know ROAS is a bad indicator for bottom-line profitability, so they go ultra-granular, take the numbers from some internal tracking system — usually based on last-click attribution — and analyze the profitability of every single order, taking into account contribution margins after COGS, shipping, packaging, payment costs and so on.

If bottom-line profitability differs from the internal financial planning, ROAS targets and budgets are adjusted accordingly. Marketing is then incentivized to hit the new targets while not exceeding the budget constraints.

What marketers will do to hit their targets

In order to hit these ROAS targets (including incremental ones), performance marketers will tend to sell more low-margin products to mainly existing customers because these sales deliver the best ROAS.

One simple way to sell to existing customers is by using Customer Match to target known customers. If revenue is the criterion and not margin, bidding systems will automatically allocate the budget where revenue can be found at the cheapest price. Areas of the assortment which have low margins will look better because there is usually less competition.

So, what happens in the next budgeting cycle? Finance will again zoom down to the most granular level, take all the orders and analyze profitability. They will notice that for some strange reason, profitability and new customer rate are down again. As a result, they will tighten the ROAS target.

If you see ROAS targets in your company, it’s very likely that you could easily do much better. If, in addition, you hear that ROAS is not reflecting incrementality, you’re really missing out on a huge opportunity.

Setting better targets and testing incrementality

In order to set performance marketing targets that are beneficial to the bottom line, you first need to find the exact incrementality levels for each of your marketing channels.

Very quickly, incrementality tests are implemented by defining a test and a control group. The test group sees ads, the control group doesn’t. You then analyze the revenues generated by the two groups over time. Incrementality presumes that the test group that sees the ads will generate more revenue than the control group. How much more defines your incrementality.

Once incrementality levels have been established, marketing and finance can work together to align on which metrics they want to use to measure progress. I always recommend customer lifetime value (CLV) or margin.

By using a profit-driven metric, you remove the ability to hit targets by selling low-margin products; and by taking incrementality into account, you make sure that hitting those targets gets you incremental gains.

The only way to enable marketers to really drive what matters is to give them access to order profitability and margins in such a way that they can use them in their bidding tool. This will undoubtedly require some technical integration, but it will deliver an unparalleled return.

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

AdWords advertisers can use phone numbers & addresses for Google Customer Match targeting

Google has added more ways for businesses to target their known customers with AdWords campaigns. As of this month, advertisers can upload phone numbers and mailing addresses for Customer Match retargeting and similar audiences.

Launched in 2015, Customer Match lets marketers upload lists of customers or other proprietary lists —  newsletter subscribers, for example — into Google AdWords to target (or exclude) search and display ads to those users. Until now, Customer Match only supported email list uploads.

As with email data, Google attempts to match phone number and mailing address information with user-provided data in Google accounts.

Hashed email addresses and phone numbers are matched up with Google’s own hashed strings to find matches. The matches are then added to marketers’ Customer Match lists.

For mailing address matching, Google says it “joins hashed name and address data for Google accounts to construct a matching key. After you’ve uploaded your list with hashed customer names and addresses (don’t hash zip and country data), Google constructs a similar key based on your data and then compares each key on your list with the keys based on Google accounts. If there’s a match, Google adds the corresponding Google account to your customer list.”

Here’s a Google illustration of how Customer Match works from the back end:

Source: Google

Advertisers can use Customer Match for targeting those matched customers across all Google properties, including search text and shopping ads, display, YouTube and Gmail. The lists can also be used to create similar audiences for targeting on YouTube and Gmail campaigns.

Phone and mailing lists can be uploaded via the AdWords API or in the new AdWords interface. The Audience Manager is located in the Shared Library, which is accessed by clicking on the wrench icon in the upper-right navigation.

The addition of phone numbers and mailing addresses opens up more opportunities for marketers that don’t have large sets of email addresses to leverage their own first-party data — from catalog and call center sales, for example — in Google campaigns.