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.

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.


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.

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.

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.

Which PPC metrics matter? Lessons from half a million keywords

Are your AdWords campaigns working… like, really working?

That might be a surprisingly hard question to answer. Anybody with an AdWords account can see if they’re getting clicks, and it’s not too hard to set up conversion tracking — but chances are that the reason you put money into AdWords was that you wanted to get money out.

In other words, you want your ad spend to produce sales.

As obvious as this statement is, actually determining how different factors in your AdWords campaigns affect sales can be fairly difficult. To try to shed more light on the subject, we recently conducted a study on how different variables affect ad performance at Disruptive Advertising (my company). We pulled data from well over half a million keywords and measured return-on-investment against dozens of variables.

In short, we wanted to answer the question: What predicts profitability in an AdWords account? Our findings may surprise you.

1. High CPC = low profitability

With any pay-per-click platform, the more clicks cost, the less profit you’ll make. However, many businesses are quick to argue that if a new sale is worth enough, it’s worth it to bid on keywords with expensive CPCs.

But do things actually work out that way?

In our study, we found that ROI rapidly drops off as your cost-per-click (CPC) increases. For example, take a look at data we pulled from a variety of e-commerce companies:

Now, for these companies, a sale was worth anywhere from tens to thousands of dollars, so you’d think that at least some of their keywords would perform well at a higher CPC. But it didn’t work out that way.

Even for expensive products, higher CPCs were directly linked to low ROI, to the point where paying more than $5 for an e-commerce click is like saying, “No, I don’t want to make money on this product.”

2. Long-tail keywords are a waste of money

Based on the above findings, it seems like long-tail keywords would be the way to go. After all, the longer the keyword, the less competition there is and the cheaper the click will be.

However, that only works up to a point.

When we looked at how keyword length affected ROI, we found that the most profitable keywords typically had 15 to 30 characters.

If you think about it, these findings make sense. Below 15 characters, you face one of two problems:

    The keyword is too non-specific and produces low-quality clicks, orThe keyword has good volume and intent but is way too competitive.

Above 30 characters (and especially above 40 characters), the searches are usually incredibly specific and have low conversion intent. For example, we once saw an AdWords account that had received 127 clicks from the search term “how do I remove the terrible smell from carpet that has been flooded using household ingredients.”

Despite all these clicks, this search term had never produced a single conversion. Why? Well, people who bother to type in a 96-character search term like this are usually looking for a very specific answer — the kind that you get on a forum or answer board, not a landing page.

3. More clicks don’t mean more conversions

If you have a conversion rate (CR) of 5 percent and a click-through rate (CTR) of 5 percent  for a given ad, it’s easy to assume that doubling your CTR will double your conversions. While that may be true in some situations, as a general rule, increasing your CTR actually tends to decrease your conversion rate.

Yes, you read that right.

In our study, higher CTRs were typically associated with lower conversion rates. Let’s take another look at that e-commerce data we were talking about earlier.

(Note: Since this is e-commerce, a single click sometimes leads to multiple sales, which is why a good chunk of our conversion rates fall above the 100 percent mark.)

As you can see in the graph above, as CTR improves, the conversion rate plummets. But why? Since people only click on ads that they think match their intent, wouldn’t a higher CTR lead to a higher conversion rate?

Unfortunately, that only happens if you are targeting the right audience with the right message. In many cases, CTR improves because you are targeting the wrong audience with the wrong message (or at least an unclear message). As a result, they think they’ve found what they’re looking for, only to end up on your landing page and discover that your business isn’t what they really want.

4. There is no silver bullet

Sadly, this is where the clear data ends. Although AdWords experts love to say, “Pull this lever and you’ll make more money,” it doesn’t work out that way in practice.

For example, let’s take a look at how well click conversion rate (percentage of clicks that convert at least once) predicts ROI:

At first glance, this graph looks great! I mean, look at that trend line. Clearly, the higher your conversion rate, the more profitable your campaigns will be, right?

While this graph looks compelling, there’s a problem. If you take a close look at the graph, it’s pretty clear that the dots don’t really follow the line. In other words, the trend line doesn’t do a very good job of predicting real-life results.

In statistics, we describe how well a trend line fits the data using R2 (R squared). In the case of the graph above, the R2 value is 0.31, which essentially means that the trend line is only accurate about 31 percent of the time.

In our study, we found that the best predictors of ROI were the amount of time spent on a page and the number of pages visited. That’s kind of a no-brainer — if you’re converting, you’re going to spend more time on the site and visit more pages. But it’s hard to use that data to improve campaign performance. After all, forcing someone to visit more pages and spend more time on your site isn’t likely to get them to convert.

But what about all the other metrics we love to watch? How does modifying those metrics affect ROI?

As you can see above, the very best predictors of ROI are CTR and CPC. But even those factors only have R2 values of 0.27 and 0.19, respectively. A 27 percent and 19 percent success rate aren’t exactly the kind of wins you want to wager money on.

Now, that being said, these numbers are based on our whole data set. When you group companies with a $0.25 CPC and a $10 product with companies with a $25 CPC and a $1,000 product, your data are not going to be very consistent.

So, let’s try to simplify things. Instead of looking at our whole data set, let’s look at the R2 values for e-commerce keywords with very similar CPCs and see if that provides any additional clarity:

In this chart, I’ve assigned bronze, silver and gold medals to the top predictive factors in each CPC range. As you can see, hashing out the data in this way does improve the predictive value of each of these factors, but our best performer is still only accurate about 50% of the time.

So, regardless of what you may read out there, there is no “silver bullet” for AdWords performance. Improving your CTR, ad position or conversion rate might improve your ROI, but it’s a shot in the dark.


Really, when you get right down to it, every business and market audience is unique, which means that the only true “silver bullet” may be blood, sweat and tears. That being said, these data may be a bit of a relief to you.

After all, if improving these metrics doesn’t reliably improve ROI, that means you can spend less time worrying about your CTR and more time identifying new, creative ways to reach and influence your target audience. If you’re focused on creating profitable ads and campaigns, rather than improving surface metrics like bounce rate, you’ll probably end up with better results.

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

Omnichannel shoppers collide with Black Friday and Cyber Monday, setting new records

Black Friday and Cyber Monday continue to gain cultural significance across the US and the globe as shoppers and retailers deepen their relationships through enhanced technology, stronger/more personalized deals and a singular online-offline approach. As for 2017, all major metrics trended up, including click volume, mobile purchases, foot traffic and overall sales. Cyber Monday 2017 marked the biggest shopping day in US history, with over $6.59B in sales, including a record-breaking $2B in mobile sales.

Bing (my employer) also saw strong positive trends, with a YOY jump in clicks across Black Friday, Cyber Monday and the entire month of November. In the US, clicks were up 9 percent (cross-device) between Black Friday and Cyber Monday when compared with the same time period in 2016, and we also saw clicks up 12 percent YOY for the month of November. The rise in clicks is likely due to large retailers who extend Black Friday deals earlier and later — a trend US consumers have come to expect as retailers like Walmart and Toyota offered week-long Black Friday deals.

This increase in clicks YOY wasn’t just a trend we saw in the US, but also around the world, as Black Friday and Cyber Monday become a global phenomenon. Bing’s international clicks across all devices were up over 17 percent for Black Friday and 20 percent for Cyber Monday.

The holiday numbers also support a strong omnichannel approach throughout the 2017 season. According to Matt Shay, CEO of the National Retail Federation (NRF), 51 million Americans shopped exclusively in stores throughout the holiday weekend, 58 million Americans shopped exclusively online, and a majority 65 million shopped both, representing the new sweet spot for leading retailers.

The online, mobile and in-store experience needs to work in harmony if retailers are going to continue in the new economy. The NRF reported that over 174 million Americans showed up in stores over the holiday weekend as retailers wooed consumers with free coffee bars, foot massages and cosmetic samples. As the numbers show, these same shoppers went home to buy online, many of them making purchases on their phones. The Home Depot even reported seeing more mobile traffic than desktop.

Black Friday deals also popped up in some new places, such as the Amazon Alexa, where users could find early deals starting November 22 through voice shopping. In classic omnichannel form, Amazon leveraged their Whole Foods brick-and-mortars to promote their Alexa devices. Every retailer should be following suit, combining their online and offline forces for maximum impact.

Bing’s Black Friday to Cyber Monday search trends

I love digging into the query reports post-Black Friday and Cyber Monday to highlight a few trends and see what has changed in consumer behavior as users search for deals this holiday season. Here are the insights I uncovered based on search trend data from the 2017 Black Friday to Cyber Monday shopping period:

Don’t forget to add year-modified keywords

We continued to see the trend where consumers are adding the calendar year to their search queries when looking for specific deals and offers. The top Black Friday and Cyber Monday intent-related keywords can be summarized in the following query combinations:

‘Tis the season for tech and entertainment

As in previous years, we saw a surge in tech-related queries as consumers searched for the latest phones and gaming consoles. It’s no surprise to me that the most-searched-for tech items are the two that are almost impossible to find with a discount: the iPhone X and Xbox One X.

We’re also seeing search trends that point to this year’s hottest toys. Last year, Hatchimals were the toy du jour; this year, Fingerlings have taken over. There was also a surge in searches for Yu-Gi-Oh! Dueling Nexus.

It’s also the time of the year to be entertained, so it wasn’t a surprise to see the movie “Bad Moms Christmas” as one of the top new queries over the holiday weekend.

It’s not too late

There’s still time to make the most of the 2017 holiday season. Here are five quick ways you should be using search to leverage your omnichannel strategy:

    Get ready for Green Monday. The 2016 comScore data rated the second Monday in December, or Green Monday, as one of the busiest shopping days of the year. Be sure your campaign budgets are high enough to accommodate a likely spike in traffic on Monday, December 11.Watch your budgets: Make sure you account for high-traffic shopping days. 2016 comScore data showed a string of 27 consecutive billion-dollar shopping days between Thanksgiving and Christmas, up from nine consecutive billion-dollar days in 2015. If this trend continues, it is worth keeping an eye on campaign budgets between Thanksgiving and Christmas, paying special attention to your top traffic days for the 2016 holiday season to make sure you don’t run out of budget before the end of the month.Know your shipping cutoff dates. Make it easy for your customers to understand the deadlines for ground shipping, two-day shipping, next-day shipping, or even same-day shipping, so their gifts can make it on time. I pulled together the dates from USPS, UPS and FedEx for you in the graphic below:
    Use ad extensions to call out shipping cutoffs and promotions. No one likes buying holiday presents only to miss the cutoff by a single day. Be sure to clearly communicate your shipping requirements with customers, including placing it in ad copy and site extensions. It’s not too late to use countdown ads customizers in your ad copy to call out shipping cutoffs or to call attention to those last-minute holiday promotions.If available, advertise free store pickup. Most of today’s leading retailers are offering free store pickup as a solution for busy holiday shoppers. If applicable, advertise free store pickup in ad copy and site extensions, especially after shipping cutoff dates pass.

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

PPC agencies will play these 4 roles when automation takes over

Earlier this year, I wrote about how artificial intelligence (AI) and machine learning are driving automation in PPC and then again about how Google’s latest wave of AdWords innovations is driven largely by these same technologies.

As the move towards automation accelerates, how should agencies and PPC managers update their strategy? What processes will they need to remain competitive? And what can they really expect from automation tools in the market today? I’ll cover all these topics in a series of upcoming posts, so I’d love to hear your ideas. But today, let’s begin by looking at what roles humans and agencies will play in PPC.

1. Agencies will teach machines to learn

Now that machines can learn, they certainly will surpass humans, right? The reality is that machine learning is still very dependent on humans. We program the algorithms, we provide the training data, we even manipulate the training data to help the machine get it right.

Machine learning often requires structured data to learn from, and it needs a very well-defined problem to solve. We as humans will play a role for some time to define the problem and help shape the desired outcome by manipulating how the machine can “learn.”

For now, the machines need us to be its teachers. AdWords Quality Score only works because the wisdom of the crowds provides a massive set of data about queries and clicks that the machine can use to learn from.

Tesla’s autopilot works because thousands of drivers control their cars manually through tricky situations. Because they’re all networked, this helps the next Tesla better drive itself through that same spot.

In PPC, what we have learned from years of manually managing campaigns can be the basis for teaching computers how to respond in similar situations.

Teachers can’t teach everything, so a large part of what they do is help students ask better questions. As teachers to the computers, we should allow ourselves to ask more questions, because synthetic intellect doesn’t have the same human constraints for how quickly it can find answers.

Take Quality Score, for example — it is a machine learning system that can analyze hundreds of factors related to a search and find patterns of things that have a meaningful impact on CTR. Because it can analyze data so much faster, we can feed it seemingly random and unconnected data and let it tell us if this makes a difference.

Here’s a crazy question we once asked the Quality Score system: Does the lunar cycle impact CTR? While the answer isn’t what’s important (no, there was no correlation), what is important is that we were able to ask entirely new questions and quickly get an answer that helped make the system better.

But we should also prioritize the questions we ask based on human intuition. We don’t want to waste machine power by asking everything when we already know with a high probability that some answers won’t help us improve. Consider the following example: Ask Google Maps to calculate the best route from San Francisco to New York. Calculating every possible backroad will take a long time, and considering that we know highways tend to be faster than local roads, that calculation will almost certainly not yield a better result — so we can safely ignore that question.

2. Agencies will provide the creativity machines lack

The biggest value of an agency will be the ability of its employees to work collaboratively with automation.

Chess grandmaster Garry Kasparov notes that when it comes to chess, teams of humans assisted by machines dominate even the strongest computers. In a 2005 experiment, Playchess.com launched a chess tournament in which participants could play in teams with other players and/or computers. According to Kasparov:

The chess machine Hydra, which is a chess-specific supercomputer like Deep Blue, was no match for a strong human player using a relatively weak laptop. Human strategic guidance combined with the tactical acuity of a computer was overwhelming.

Humans are still good at creative strategy — putting old ideas together in new ways and testing the results. The reason we don’t have Google’s computers writing all the ads for AdWords is that they all would end up looking the same — and then they would stop evolving because the machine would no longer have any variations to test.

Evolutionary algorithms, a subset of AI, are based on biological evolution, and they need access to variations to work well. And while they can create their own mutations, humans often still know the right shortcuts to come up with better ideas.

An advertiser on Facebook once submitted an ad that was a static image that shook a bit. This had a far better CTR than the same ad when it was completely static. It’s kind of a silly way to produce better CTR, but it’s a great example of humans trying something new that the machine probably wouldn’t have thought of because nobody had done this before inside the realm of the data it had access to.

3. Agencies will be the pilot who averts disaster

Self-driving cars are not “driverless” cars because there’s still a human behind the wheel to monitor the machine. That makes sense because not killing its passengers or others on the road is valuable enough to deserve some human resources.

In PPC, we’re fortunately not dealing with life-or-death scenarios; but we can still put a pilot in place to monitor the most important areas of automation. The trick is figuring out the 80/20 rule and saving the human involvement for the automations with the biggest potential impact.

I once audited an account that had completely tanked because the bid automation had correctly reduced bids after the launch of a terribly performing landing page. But while the landing page was quickly fixed by humans, nobody remembered to reset the bids, and the account spent months with subpar performance because its best keywords were lingering on page two of the search results.

The problem with many systems built today is that they have narrow goals that can fail due to self-reinforcing feedback loops that can cause a downward spiral:

bad performance →  bid down a bit → even worse performance → bid down some more → doom!

We can also look beyond what our own automations are doing to find weaknesses to exploit in our competitors’ algorithms. Remember that many automations are doing tasks that are well-defined, and this makes them predictable. For example, I once had to cross four lanes of traffic on my bike and was going to wait to let a car pass me first. But when I noticed it was a Google self-driving car, I went for the turn anyway because I knew the car had perfect vision and was programmed not to hit bicyclists. And since I’m sharing this story, things went well for me in that scenario.

Sometimes, we can learn from what the machine does. Lee Sedol, the world-champion Go player who was beaten by DeepMind’s AlphaGo computer, became a better player from the experience of losing to a machine. He, as well as many others watching the game, were perplexed by move 37 that the computer made. It was simply not a move any human would have played. But it was the move that set the computer up for the win, and now humans have added it to their own repertoire.

And sometimes your job as copilot is to see something that’s not there but that should have been. The book “How Not To Be Wrong” by Jordan Ellenberg tells the story of mathematician Abram Wald, who figured out what part of an airplane should be made stronger to resist being shot down by enemy aircraft during World War II. The data from planes that returned with bullet holes showed that there were more bullet holes in the fuel system than the engine. Scientists concluded that they should re-enforce the fuel system. But Wald argued that planes that were hit in the engine probably crashed and never returned, and this skewed the data.

Let’s put that into a PPC example. When you look at what leads to a conversion because you want to do more of that, maybe you should also ask what doesn’t lead to a conversion and do less of that. For example, high shipping fees may tank your conversion rate, but you wouldn’t find this out if you asked the wrong question.

4. Agencies will have the empathy machines lack

Even when computers will be doing every part of PPC management, they still won’t have the same human connection that you have with your clients. Understanding the nuances of your client’s business (which will help you come up with new ideas to test), understanding their fears about PPC, understanding their frustrations with the last account manager and so on. All this will help you have a more productive relationship with them.

One surprising profession that is leveraging AI is medical doctors. They simply can’t read as much of the existing research as Watson, so IBM’s supercomputer can be a magnificent diagnostician. But Watson may not be able to explain conditions to a patient, and it certainly will not have the empathy of a human when sharing potentially devastating news. There is still a place for doctors even when they have a supercomputer to help them.

And as PPC experts, a large part of our role will be to know which expert automations to test in an account. For bid management alone, there is an overwhelming number of options, ranging from Google’s free Portfolio Bid Strategies to upstart bid management companies that charge thousands of dollars for the promise of a slightly better result. Knowing what is available, what is worth testing and how to calculate the trade-offs is certain to be a large part of the value agencies provide.


Automation is taking over a lot of the tasks humans have historically done in PPC; but as this shift continues, there will be plenty of new opportunities for PPC experts and agencies to provide value to their clients.

Next time, I’ll cover new strategies and processes that will help bridge the gap between humans and artificially intelligent PPC machines.

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

Auction Insights 3: The final script

Who would have thought that Auction Insights could inspire an entire TRILOGY? Well, if you know AdWords, I suppose it’s not a huge shock that our original script has had to undergo a few adaptations over the last couple of years. Google does like to keep us PPC practitioners on our toes!

Changes to AdWords aside, it’s always nice to spruce things up. Optimization is an infinite process, after all. So, please read on for the latest script that puts the insight into “Auction Insights,” compliments of Brainlabs (my employer).

Basically, we’ve given the Auction Insights script a bit of an update. The latest version can:

take reports from the new AdWords interface (OMG YES!).try out defaults for column names, if those in the Settings sheet aren’t perfect (…WOO?).find out more about your competitors (NOW YOU’RE TALKING!).

What’s new?

New interface

New interface, new reports. You may not have noticed the difference, but there’s an extra line at the top with the date range. In the old version of the tool, it wouldn’t look far enough down the sheet to find the headings. And when you download campaign performance, there are a bunch of totals at the end that would make the old version overcount your stats. But the new version can tell what sort of report you’ve pasted in and cope with it; you can go back to not noticing the differences.

Something to note, though: In the old interface, if you downloaded a campaign report segmented by time and device, it would only give rows for time, device and campaign combinations that had traffic. In the new interface, it gives rows even when there are no impressions. This may be awkward to copy into the Performance sheet, and it may slow down running the tool. Speed things up by filtering out the zero impression rows before copying the data into the Performance sheet.

Also, you can’t mix and match reports from the old and new interfaces — they use different names for the device segments.

Default column names

The old interface says “Impressions,” where the new one says “Impr.” Sometimes, reports say “Interactions” to mean “Clicks.” It’s easy to miss when you have to update the column names in the Settings sheet — so now, if the names in the Settings don’t work, the script will try some of the English column names as a default.

Competitor settings

There’s a change to the list of competitors — you can just say “yes” next to the ones you want to include (as before), or you can give them a number. Competitors with a number will be shown in that order in the reports.

If you’ve got too many competitors to all show in the list on the Settings page, you’ve got two new options:.

First, you can choose to include all competitors in the data tables. It will still only include the top six in the chart, though. You wouldn’t be able to see anything if there were too many lines in there.But what if you don’t want them all, and you just want that one guy who’s not listed on the Settings sheet? You can keep the list from automatically filling, and then you can manually edit the list to include whoever you want to see.

How do I use it?

Enough blather. You’re here because you want to use this for yourself!

The first thing is to make a copy of the new template sheet. It’s got the script already embedded in it.

Fill in your data

Go to your AdWords account, select the campaigns you want to look at, and download the Auction Insights report, segmented by day, week or month. Copy it to the spreadsheet in the Auction Insights tab. Make sure you’ve included the headers.

(If you’re having problems with numbers or dates being wrong — for example, if Sheets is reading the day as the month or not recognizing numbers with decimal places — you may need to change the locale of the spreadsheet. To do this, go to File, click “Spreadsheet settings…” and select your country from the Locale drop-down. If you’re using Excel, also make sure the columns are wide enough to show the data when you copy them, otherwise you may find all your dates turned into #####.)

If you want separate device graphs, download the Auction Insights report again — but this time segmented by time period and device. Copy and paste that into the Auction Insights By Device sheet (again, make sure there are headers).

Lastly, if you want CTR, CPC, impressions or searches, then download a performance report for the same set of campaigns for the same date range, segmented by the same time period and (if you’re looking at device data) by device. Make sure there are clicks, impressions and cost columns — CTR, CPC and searches will be calculated from these. Copy this into the Performance Data sheet.

(If there are lots of campaigns, you may hit the limit for the number of cells in a Google Sheet. If that happens, then you can add up all the campaigns’ data for each day and device combination and copy that into the Sheet — just keep the column headers the same and have them on Row 2.)

Adjust your settings

From here, go to the Settings sheet. Some cells are filled in automatically — their text is in yellow. This includes the competitor names (listed in order of highest impression share), the device names and the column headings (both in the “Reports to Make” table).

The Names From Reports section at the top is used to make sure the script reads from the correct columns. Make sure that “Date” matches the name of the date column in your reports (which should be “Day,” “Week” or “Month” if the report is in English). Display URL Domain is the name of the column containing competitor names: “Display URL Domain” for Search campaigns or “Shop Display Name” for Shopping campaigns.

You shouldn’t need to change anything else if your reports are in English, but if you’re using a different language, you’ll need to update some additional elements — most are column names, and “You” is what the Auction Insights report shows as the domain/display name when it gives your performance.

The Formatting section is used to format the data. Feel free to replace the date format (e.g., with dd-MM-yyyy or MM/dd/yyyy) and the currency symbol. (Note that the script won’t do any currency conversion for you!)

The Stats To Report section lets you pick which extra statistics go in the data tables and which go into charts. Put “Yes” in the relevant cell to include a stat. Some things to note:

You can only add, at most, two stats to the chart. If you select more, then only the first two are included.Note that if you want something in the chart, it has to be in the table (because that’s where the chart gets its data from).If you haven’t copied anything into the Performance Data sheet, this section will be ignored. You can just leave all of these blank.“Searches” is (approximately) the total number of available impressions. It is calculated as impressions divided by impression share; as the impression share is rounded, it is not a precise figure, especially if your impression share is low.

Competitor Settings can be used if you have too many competitors to fit in the Competitors To Include section.

Set “Include all competitors” to yes if you want all competitors in your reports (regardless of what’s marked with a “Yes” in the the Competitors To Include section).Set “Auto refresh the list” to “No” if you want to be able to change the Competitors To Include section manually. If you don’t want all competitors, but there’s a name you want included that’s missing from the list, stopping the auto refresh means you can replace the names in the list yourself.Be careful — the names have to match what’s in the Auctions Insight report. If you mistype a name, it won’t show up in reports.If this is set to “Yes,” then the competitor list will automatically update whenever the spreadsheet is edited, and you’ll lose any changes you’ve made there.)

The Competitors To Include section should have an automatically filled list of competitor display domains, drawn from the Auction Insights sheet. Put a number next to the names to have them appear in your reports in a specific order, or put “Yes” if you don’t mind the order. Leave the space next to them empty to ignore them.

All selected competitors will be in the data tables.To prevent the charts from being too crowded, only the first six selected competitors are included.

The Reports To Make section lets you pick which reports are generated. The top row is filled out automatically with the column headers from the Auction Insights sheet (because the columns will be different if you’re looking at Shopping rather than Search campaigns, or if your report is in another language).

The Total row gives you a report of your and your selected competitors’ performance (alongside your selected stats) for all devices. This uses data from the “Auction Insights” sheet.There are then three rows for devices, using the names from the “Auction Insights By Device” sheet. Putting a “Yes” for these rows gives you a report of your and your selected competitors’ performance (alongside your selected stats) for the named device.The last row is Compare All Devices, which gives you your total average performance and performance segmented by device. This report does not include competitor data.You can’t make a Compare All Devices report for columns like “Position above rate,” as they don’t have any data on your performance.

And then run the script!

When you’re all ready, hit the “Click Here To Generate Reports” button. You’ll need to give authorization the first time you do this so the script can run. Your reports should all be generated, one report per sheet. If there are any issues, there should be a message box to say what the problem is.

Note that if you’ve run the report before, it will delete and remake any of the reports you’ve selected — so make sure you save the output somewhere!

If you’ve made a load of sheets, and it’s all too much, you can delete everything except the template sheets with the “Delete Reports” button.

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

How your website redesign can sabotage your paid search efforts

Recently, my PPC agency almost declined to take on a new client because the client’s website was so severely outdated. The site looked bad, was difficult to use and didn’t have an easy way to convert prospects. But when we learned that the client was in the process of redesigning this website, we agreed to move forward.

This scenario suggests that when clients announce a website redesign, it’s good news for PPC. But is it? Well, yes and no. Yes, because updated websites that work well and inspire trust can help our paid search efforts.

But no, because website redesigns can also end up sabotaging paid search programs — at least temporarily. Experience tells us that redesigns rarely run smoothly from a PPC perspective. Inevitably, there will be problems we’ll need to fix.

In this article, I’ll walk through what can go wrong with website redesign from the vantage point of PPC professionals. By knowing these problem areas in advance, you and your marketing team can anticipate and avoid some of the most common issues.

Where things can go wrong in website redesigns

Unfortunately, it’s not unusual for elements and functions that are critical for paid search advertising to get dropped somewhere during the redesign process. We usually see this with phone numbers, trust signals, tracking codes, thank-you pages and forms.

1. Phone numbers

Sometimes the client’s phone number, which was prominently displayed at the top of every old web page, is absent from new pages. Or, if it’s still present, it’s smaller in size and more difficult to spot.

Here’s an example:

This image is the top portion of a client’s new webpage. But where did the phone number go? Originally, it had a prominent position at the top of every page. But now, users have to click the “contact us” button to find it. Why force visitors to take this extra step?

2. Trust signals

Other times, the phone number will remain but trust signals are removed. Elements such as testimonials, certification badges and affiliations are either missing or only present on select pages.

Why do we care about phone numbers and trust signals as paid search pros? Because they have an important role to play in paid search. Making it more difficult for prospects to call you or removing elements that give prospects the confidence to do business with you will negatively impact your paid search efforts.

Additionally, we care about these elements being present on every page because we can’t assume that new prospects will start on your home page. They might start on a product page, service page or FAQs page. So we need phone numbers and trust signals to be present on those pages, too.

3. Tracking codes

Tracking codes return data that allow us to know exactly what’s going on with an account. We use these data to direct and refine our paid search efforts.

Without data from tracking codes, we’re essentially running accounts blindfolded. Yes, we can still make decisions based on our experience and knowledge, but those decisions will always be our best guesses. With tracking data, we can make decisions based on what’s actually happening.

Which codes are we most concerned about? At least these four:

Google Analytics code: This code tells us where your website traffic is coming from and when you’re getting it. It also tells us what visitors are doing when they get there and what technology they’re doing it with. This information is critical to paid search campaigns. For example, if we see that most users are converting via mobile, then we might focus our advertising efforts on mobile.Remarketing code: As the name suggests, we need remarketing code to run remarketing campaigns. (This isn’t a deal-breaker, however. We can also set up remarketing lists via Google Analytics.)Website call metrics code: We use website call tracking tags to track PPC visitors who call you once they land on your website.AdWords conversion code: AdWords conversion tracking shows us what happens after customers click your ads. It allows us to track the action we want visitors to take, whether that’s completing a form, downloading a white paper or something else.

I can see how these codes might get removed or corrupted in the course of redesigning a website. But at the same time, the impact of losing these codes is very real.

The sooner the problem is spotted, the sooner it can be corrected. But often, it’s not caught until the marketing team looks at its data and realizes something is off.

4. Thank-you pages

Unfortunately, it’s not unusual for website redesigns to do away with thank-you pages. These are pages that are returned to users after a contact form is submitted, confirming that the message has been sent.

Instead, visitors get a single thank-you line that appears on the contact page. It often looks something like this:

There are a few problems with this approach. First, it may leave visitors wondering whether their message went through. That single line of text is easy to miss.

Second, it’s a lost opportunity! Thank-you pages are a great place to put additional content to further engage visitors.

Third, we often use thank-you pages as a place to put tracking code. With no thank-you page, we have to resort to event tracking, which isn’t as simple as adding codes to thank-you pages (and can sometimes lead to errors).

5. Forms

Some website redesigns do away with contact forms entirely and replace them with email address links. This isn’t good.

Using email links seems like an outdated approach. Technically, we can still track these links via event tracking. But this can get tricky, and we sometimes run into technical issues.

When website redesign problems get worse

Even when things go bad with website redesigns, we can usually get back on track relatively quickly if we’re aware of the issues and the web design team is responsive.

But sometimes, things can go from bad to worse. In some cases, it can take weeks — or even months — to fix problems. And sometimes we can’t get the changes we need, so we end up developing workaround solutions.

For example, remember the client that replaced their contact forms with email address links? For technical reasons, we weren’t able to track when visitors clicked the link, and we couldn’t convince the web development team to put the forms back in place. We ended up developing landing pages for each page that contained an email address.

Sometimes, problems are ongoing. For example, we have one client where the developer does a backend refresh regularly. Every single time, our tracking code gets stripped from the web pages. Needless to say, this gets old real fast.

And sometimes, we see website design issues on the horizon. For example, one of our PPC clients redesigned their site last month. When we saw the new site, we were surprised to see it was HTTP and not HTTPS. We raised this issue with the designer, pointing to the announcement that Chrome will start adding “not secure” warnings to non-HTTPS pages.

The designer’s response? “We’ve scheduled that for later.” Oh boy. In the meantime, we’re holding our breath. Because nothing will shoot down a paid search program faster than a website with “not secure” messaging.

So what’s the solution to these problems of website redesign? It’s to give serious consideration to the requirements of paid search as part of website redesign.

When I raised this question with Stephen Merriman at cre8d Design, our Group Twenty Seven go-to web designer, he responded with the following:

One of the steps I do just before migrating a completed website is to hunt through the existing site for any tracking codes and such to make sure nothing important gets removed. I also double-check with the client to see if there is anything they haven’t mentioned so we don’t experience issues.

Stephen Merriman

Which, in my opinion, is exactly the right response!

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

2-step methodology for dealing with PPC performance downturns

The most important thing I’ve learned from my 15 years of PPC experience is that sooner or later, account performance will take a downturn. When that day comes, we must be prepared to deal with the consequences of performance not meeting expectations. These consequences could range from stakeholders losing trust in your abilities to receiving ultimatums to “fix performance or else,” and worst-case scenario, someone else being brought in to take over the paid search program you’ve spent so much time and energy building.

Performance downturns can be very stressful and put you on the defensive. However, having a solid methodology for responding when performance is bad can help instill confidence that you have what it takes to turn a negative performance situation into a positive one.

This article discusses a two-step methodology for confronting underperformance in a way that helps you garner trust with your stakeholders and instill confidence in your ability to manage PPC accounts through the tough times.

Step #1: Diagnosing the problem

Clients and stakeholders need to have confidence in those managing their paid search program. When performance takes a downturn, they depend on their account manager to tell them what the problem is. If an account manager cannot demonstrate they understand what the problem is, then why would the client/stakeholder have any confidence that the account manager can solve their performance issues?

How do we go about diagnosing the root cause of a problem? Diagnosing a problem requires diligent research to pinpoint:

when a problem first began to occur.what key metrics are lagging and thus leading to the performance downturn.

Putting the methodology into practice

I’m currently dealing with an account performance issue that is causing this month’s performance to lag in terms of lead volume. I ultimately identified the issue as a drop-off in brand keyword traffic. How did I discover that brand traffic was the source of this issue? I did it by analyzing the following key metrics:

CPCs: Accountwide cost per click spiked dramatically from October to November. This was my first indication that a traffic pattern shift occurred.Conversion volume: AdWords pixel conversions were down significantly month over month.CTR: Click-through rate also dropped significantly.

The sudden drop-off in conversion volume and CTR, along with a spike in CPCs, led me directly to consider recent brand traffic performance. Typically, this account I manage has very steady traffic patterns with steady CPCs and conversion volume. As I dove further into brand campaign performance, I saw that branded impressions and clicks dropped dramatically, which caused CPCs to spike and volume to drop. Because of the brand traffic performance drop-off, cost per conversion increased dramatically due to the account’s over-dependence on non-branded traffic.

Further digging into the account, I discovered that branded traffic dropped suddenly at the end of October. This information allowed me to focus on specific changes made to the account during that period. I ultimately discovered several high-traffic branded keywords were paused in error as part of an overall optimization. These keywords were unpaused and bids readjusted. Traffic and conversion volume is now recovering.

As you can see from the example above, it took quite a bit of research to arrive at the problem’s root cause. Once a problem has been identified, it’s time to move on to the next step.

Step 2: Communicate what the performance problem is and recommend solutions

Throughout the course of my career, I’ve seen a lack of understanding and communication be the downfall of many business relationships. I’ve witnessed PPC account managers fundamentally not understand the performance problems they’re facing, ignore the fact that a problem even exists and fail to address problems head-on with their stakeholders. Allowing any of these things to happen quickly erodes trust.

To maintain your credibility as a PPC expert, it’s imperative that you do the following when there’s an underperformance issue:

Own the fact that an underperformance issue is occurring. Denying or minimizing an issue will make your stakeholders angry. Owning the issue helps convey that you understand how urgent the problem is.Communicate the issue verbally, in written form and through visual means to demonstrate that you’ve made the effort to be fully transparent and that you’re willing to educate your stakeholders as to what the problem is.Explain in full detail your recommendations for fixing all underperformance issues you’ve identified. Never leave stakeholders with just the problem. They depend on and expect their account manager to offer solutions that will lead to improved performance. Our stakeholders view us in a similar regard to doctors when their accounts aren’t healthy. How would you feel if a doctor diagnosed you with an ailment but didn’t recommend any course of treatment? This is how clients feel when they’ve been informed of an underperformance problem but not offered any guidance regarding how to get their account back on track.

Clear communication and context helps remove fear. Oftentimes, stakeholders become emotional and lash out because they feel their account manager doesn’t grasp the gravity and urgency of a situation. It’s our job as account managers to take the lead in eliminating fear of the unknown by providing as much background information and context as possible regarding an underperformance problem’s root cause, and propose sufficient courses of action for remedying the situation.

Final thoughts

No matter how hard we try, we’ll never be able to avoid the inevitable performance downturn. However, what we can do is be prepared for how we’ll respond when this time arrives. Fully understanding root causes of performance issues, developing the appropriate solution and decisively communicating all of this to our stakeholders is crucial to successfully surviving performance downturns.

It’s easy to be liked and respected when everything is going well. The real test comes when things are not going according to plan. Going through the fire of underperformance and successfully coming out on the right side of it will help build your credibility and your stakeholders’ trust in you.

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