31.8.17

Instagram starts putting Stories, but not Story ads, on its website

The majority of people who use Instagram’s app every day check out its Stories feed. Now the Facebook-owned photo-and-video-sharing service is extending its Snapchat clone to its online audience.

Instagram has begun showing Stories to people who log into its website, the company announced on Thursday. While the Stories feed in Instagram’s app features ads, for now Instagram will not insert ads within the online version, according to an Instagram spokesperson.

People can now view others’ Stories on Instagram’s desktop and mobile site.

People will eventually be able to post to their Stories through Instagram’s mobile site, but not the desktop version, the spokesperson said.

The move to put Stories online appears focused on appealing to Instagram’s international audience. According to Bloomberg, more than 80 percent of the people who use its site live outside of the US.



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What's Your AMP Traffic Really Doing? Set Up Reporting in 10 Minutes

Posted by Jeremy_Gottlieb

The other day, my colleague Tom Capper wrote a post about getting more traffic when you can’t rank any higher. I was really pleased that he wrote it, because it tackles a challenge I think about all the time. As SEOs, our hands are tied: we’re often not able to make product-level decisions that could create new markets, and we’re not Google’s algorithms — we can’t force a particular page to rank higher. What’s an SEO to do?

What if we shifted focus from transactional queries (for e-commerce, B2C, or B2B sites) and focused on the informational type of queries that are one, two, three, and possibly four or more interactions away from actually yielding a conversion? These types of queries are often quite conversational (i.e. "what are the best bodyweight workouts?") and very well could lead to conversions down the road if you’re try to sell something (like fitness-related products or supplements).

If we shift our focus to queries like the question I just posed, could we potentially enter more niches for search and open up more traffic? I’d hypothesize yes — and for some, driving this additional traffic is all one needs; whatever happens with that traffic is irrelevant. Personally, I’d rather drive qualified, relevant traffic to a client and then figure out how we can monetize that traffic down the road.

To accomplish this, over the past year I’ve been thinking a lot about Accelerated Mobile Pages (AMP).

What are Accelerated Mobile Pages?

According to Google,

"The AMP Project is an open-source initiative aiming to make the web better for all. The project enables the creation of websites and ads that are consistently fast, beautiful, and high-performing across devices and distribution platforms."

What this really means is that Google wants to make the web faster, and probably doesn’t trust the majority of sites to adequately speed up their pages or do so on a reasonable timeframe. Thus, AMP were created to allow for pages to load extremely fast (by cutting out the fat from your original source code) and provide an awesome user experience. Users can follow some basic instructions, use WordPress or other plugins, and in practically no time have mobile variants of their web content that loads super fast.

Why use AMP?

While AMP is not yet (or possibly ever going to be) a ranking factor, the fact that it loads fast certainly helps in the eyes of almighty Google and can contribute to higher rankings and clicks.

Let’s take a look at the query "Raekwon McMillan," the Miami Dolphins second-round pick in the 2017 NFL Draft out of Ohio State University:

Screenshot of mobile SERP for query "Raekwon McMillan"

Notice how of these cards on mobile, two contain a little lightning bolt and the word "AMP?" The prevalence of AMP results in the SERPs is becoming more and more common. It’s reasonable to think that while the majority of people who use Google are not currently familiar with AMP, over time and through experience, they will realize that AMP pages with that little icon load much faster than regular web pages and will gravitate towards AMP pages through a type of subconscious Pavlovian training.

Should I use AMP?

There are rarely any absolutes in this world, and this is no exception. Only you will know, based upon your particular needs at this time. AMP is typically used by news publishers like the New York Times, Washington Post, Fox News, and many others, but it’s important to note that it's not limited to this type of entity. While there is an AMP news carousel that frequently appears on mobile and is almost exclusively the domain of large publishing sites, AMP results are increasingly appearing in the regular results, like with the Raekwon McMillan example.

I'm a fan of leveraging blog content on AMP to generate as many eyeballs as possible on our pages, but I'm still a bit leery about putting product pages on AMP (though this is now possible). My end goal is to drive traffic and brand familiarity through the blog content and then ultimately drive more sales as people are either retargeted to via paid or come back from other sources, direct, organic or otherwise to actually complete the purchase. If your blog has strong, authoritative content, deploying AMP could potentially be a great way to generate more visibility and clicks for your site.

I must point out, however, that AMP doesn’t come without potential drawbacks. There are strict guidelines around what you can and can’t do with it, such as not having email popups, possible reduction in ad revenue, analytics complications, and requiring maintenance of a new set of pages. If you do decide that the potential gain in organic traffic is worth the tradeoffs, we can get into how to best measure the success of AMP for your site.

Now you have AMP traffic — so what?

If your goal is to drive more organic traffic, you need to be prepared for the questions that will come if that traffic does not yield revenue in Google Analytics. First, we need to keep in mind that GA's default attribution is via last direct click, but the model can be altered to report different numbers. This means that if you have a visitor who searches something organically, enters via the blog, and doesn't purchase anything, yet 3 days later comes back via direct and purchases a product, the default conversion reporting in GA would assign no credit to the organic visit, giving all of the conversion credit to the direct visit.

But this is misleading. Would that conversion have happened if not for the first visit from organic search? Probably not.

By going into the Conversions section of GA and clicking on Attribution > Model Comparison Tool, you’ll be able to see a side-by-side comparison of different conversion models, such as:

  • First touch (all credit goes to first point-of-entry to site)
  • Last touch (all credit goes to the point-of-entry of session where conversion took place)
  • Position-based (credit is primarily shared between the first and last points-of-entry, with less credit being shared amongst the intermediary steps)

There are also a few others, but I find them to be less interesting. For more information, read here. You can also click on Multi-Channel Funnels > Assisted Conversions to see the number of conversions by channel which were used along the way to a conversion, but was not the channel of conversion.

AMP tracking complications

Somewhat surprisingly, tracking from AMP is not as easy or as logical as one might expect. To begin with, AMP uses a separate Analytics snippet than your standard GA tracking code, so if you already have GA installed on your site and you decide to roll out AMP, you will need to set up the specific AMP analytics. (For more information on AMP analytics, please read Accelerated Mobile Pages Via Google Tag Manager and Adding Analytics to Your AMP Pages).

In a nutshell, the client ID (which tracks a specific user’s engagement with a site over time in GA) is not shared by default between AMP analytics and the regular tracking code, though there are some hack-y ways to get around this (WARNING: this gets very technically in-depth). I think there are two very important questions when it comes to AMP measurement:

  1. How much revenue are these pages responsible for?
  2. How much engagement are we driving from AMP pages?

In the Google Analytics AMP analytics property, it's simple to see how many sessions there are and what the bounce and exit rates are. From my own experience, bounce and exit rates are usually pretty high (depending on UX), but the number of sessions increases overall. So, if we’re driving more and more users, how can we track and improve engagement beyond the standard bounce and exit rates? Where do we look?

How to measure real value from AMP in Google Analytics

Acquisition > Referrals

I propose looking into our standard GA property and navigating to our referring sources within Acquisition, where we’ll select the AMP source, highlighted below.

Once we click there, we’ll see the full referring URLs, the number of sessions each URL drove to the non-AMP version of the site, the number of transactions associated with each URL, the amount of revenue associated per URL, and more.

Important note here: These sessions are not the total number of sessions on each AMP page; rather, these are the number of sessions that originated on an AMP URL and were referred to the non-AMP property.

Why is this particular report interesting?

  1. It allows us to see which specific AMP URLs are referring the most traffic to the non-AMP version of the site
  2. It allows us to see how many transactions and how much revenue comes from a session initiated by a specific AMP URL
    1. From here, we can analyze why certain pages refer more traffic or end up with more conversions, then apply any findings to other AMP URLs

Why is this particular report incomplete?

  • It only shows us conversions and revenue that happened during one session (last-touch attribution)
    • It is very likely that most of your blog traffic will be higher-funnel and informational, not transactional, so conversions are more likely to happen at later touch points than the first one

Conversions > Multi-Channel Funnels > Assisted Conversions

If we really want to have the best understanding of how much revenue and conversions happen from visits to AMP URLs, we need to analyze the assisted conversions report. While you can certainly find value from analyzing the model comparison tool (also found within the conversions tab of GA), if we want to answer the question, "How many conversions and how much revenue are we driving from AMP URLs?", it’s best answered in the Assisted Conversions section.

One of the first things that we’ll need to do is create a custom channel grouping within the Assisted Conversions section of Conversions.

In here, we need to:

  1. Click "Channel Groupings," select "Create a custom channel grouping"
  2. Name the channel "AMP"
  3. Set a rule as a source containing your other AMP property (type in “amp” into the form and it will begin to auto-populate; just select the one you need)
  4. Click "Save"

Why is this particular report interesting?

  1. We’re able to see how many assisted as well as last click/direct conversions there were by channel
  2. We’re able to change the look-back window on a conversion to anywhere from 1–90 days to see how it affects the sales cycle

Why is this particular report incomplete?

  • We’re unable to see which particular pages are most responsible for driving traffic, revenue, and conversions

Conclusion

As both of these reports are incomplete on their own, I recommend any digital marketer who is measuring the effect of AMP URLs to use the two reports in conjunction for their own reporting. Doing so will provide the value of:

  1. Informing us which AMP URLs refer the most traffic to our non-AMP pages, providing us a jumping-off point for analysis of what type of content and CTAs are most effective for moving visitors from AMP deeper into the site
  2. Informing us how many conversions happen with different attribution models

It’s possible that a quick glance at your reports will show very low conversion numbers, especially when compared with other channels. That does not necessarily mean AMP should be abandoned; rather, those pages should receive further investment and optimization to drive deeper engagement in the same session and retargeting for future engagement. Google actually does allow you to set up your AMP pages to retarget with Google products so users can see products related to the content they visited.

You can also add in email capture forms to your AMP URLs to re-engage with people at a later time, which is useful because AMP does not currently allow for interstitials or popups to capture a user’s information.

What do you do next with the information collected?

  1. Identify why certain pages refer more traffic than others to non-AMP URLs. Is there a common factor amongst pages that refer more traffic and others that don’t?
  2. Identify why certain pages are responsible for more revenue than other pages. Do all of your AMP pages contain buttons or designated CTAs?
  3. Can you possibly capture more emails? What would need to be done?

Ultimately, this reporting is just the first step in benchmarking your data. From here you can pull insights, make recommendations, and monitor how your KPIs progress. Many people have been concerned or confused as to whether AMP is valuable or the right thing for them. It may or may not be, but if you’re not measuring it effectively, there’s no way to really know. There's a strong likelihood that AMP will only increase in prominence over the coming months, so if you’re not sure how to attribute that traffic and revenue, perhaps this can help get you set up for continued success.

Did I miss anything? How do you measure the success (or failure) of your AMP URLs? Did I miss any KPIs that could be potentially more useful for your organization? Please let me know in the comments below.


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Marketing Day: Real-time attribution, location modifiers & AdSense User First beta

Here's our recap of what happened in online marketing today, as reported on Marketing Land and other places across the web.

Please visit Marketing Land for the full article.


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SearchCap: Google local pack mentions, Google Shopping reports & PPC evals

Below is what happened in search today, as reported on and from other places across the web. The post SearchCap: Google local pack mentions, Google Shopping reports & PPC evals appeared first on Search Engine Land.

Please visit Search Engine Land for the full article.


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Daily Search Forum Recap: August 31, 2017


Here is a recap of what happened in the search forums today, through the eyes of the Search Engine Roundtable and other search forums on the web.

Search Engine Roundtable Stories:

Other Great Search Forum Threads:



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Your account structure might be hurting performance. Here’s why (and how to fix it)

When it comes to managing AdWords, something I’ve come across time and again is that lots of accounts are oversegmented. I’ve seen AdWords accounts with almost awe-inspiring intricacy. No dimension unsegmented; no campaign setting untweaked; no minute negative keyword unadded. I think we’ve officially reached the point at which some of you are too good at your jobs.

Automation is better than it’s ever been. It’s so good, in fact, that it often beats oversegmented, even overengineered accounts. Campaigns can be segmented by devices, match types, audiences, geographies and more. Campaigns shouldn’t be segmented by all of those.

AdWords Smart Bidding looks at specific queries (and the context of those queries)

Overly segmented account structures are attempting to approximate something that Smart Bidding already does: bid to a user’s specific search query and adjust bids for devices, time of day and audiences to control the impact on the advertiser’s objective. AdWords Smart Bidding considers dozens of additional signals and the combinations of them, like mobile devices at nighttime in a specific area.

You don’t need to manually define each segment’s value if you’re accurately tracking your conversions in AdWords. Tell Smart Bidding what your end goal is, then track performance. You can stop using CPC bidding as a proxy for value; Smart Bidding can boil everything down to what really matters for you, whether that’s a CPA or ROAS goal.

A simpler proposal

Your default campaign structure should be a lot more straightforward. This may sound insane, but here’s how I think campaigns should be organized:

  • Organize your ad groups around what ads you want to serve to groups of users.
  • Organize your campaigns around your objective and KPI.

Some aspects of campaign setup warrant separate campaigns — such as budgetary control and the countries/territories where you can actually sell your goods and services. There is no longer a need for additional campaigns to work around long-gone AdWords limitations surrounding bidding and messaging. Bidding has Smart Bidding. Ad text has ad customizers. Audience targeting benefits from both Smart Bidding and ad customizers.

One thing in particular that I want to highlight is separate campaigns or ad groups by match type. The AdWords system is set up to prefer the more specific keyword, and in those rare cases when it doesn’t, it’s to your benefit. A less specific keyword will trigger only if you’re projected to have a higher Ad Rank and a lower CPC. (You might even consider de-duplicating your match types of the same keyword in your account. That’s too big a topic to cover here.) Ultimately, what may seem like sloppy structure is actually saving you money.

If you have a set of high-performing keywords that deserve their own budget, you should break those out. That’s a case where it makes sense to make such a management decision. But that should be for your best stuff. Let performance dictate what gets priority.

The benefits of aggregated campaigns

An overly segmented AdWords campaign structure can actually be a serious barrier to performance.

1. Automation works better on large sets of information.

AdWords’ Smart Bidding can work on pretty paltry data. But it works even better when it has large amounts of insight to feed into its machine learning. Larger campaigns, including data across all different types of cross-device, cross-user-list, cross-time insights, tend to perform better. A bigger campaign is actually more likely to perform better when you fully embrace automation.

2. There are fewer ads to maintain.

Keeping up with your ads is a lot of work. The smarter you are about the amount of work you create for yourself, the more your work time is spent on finding and deploying great messaging. And the less time you have to spend making sure that you’ve copied/pasted your ads across all nine device-specific campaigns that advertise women’s tankinis to previous customers who reside in New England.

[Read the full article on Search Engine Land.]

Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.



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Why real-time attribution is (mostly) irrelevant, and what to do instead

The martech and ad tech industries love to talk about real-time. The context doesn’t matter — regardless of the circumstances, real-time must be better than delayed. Right?

The allure of real-time makes sense. We operate in real time these days, at work and at home, answering calls and emails as they come in, fighting fires as they arise, watching our customers and prospects browse websites and click our offers literally as it happens. The real-time perspective is certainly compelling and sometimes valuable from an operational point of view — but not always.

In fact, when it comes to marketing attribution, real-time results are far less important than right-time insights.

Forrester’s Tina Moffett articulated the concept of right-time insights in one of our meetings. It immediately resonated as an intuitive description of all the hype around real-time and something we had already worked into our product.

The truth is that most media doesn’t work in real time. Every channel works at a different pace and cadence of effectiveness. The length of time in market for each channel before it drives behavior varies dramatically. There are applications and channels in which real-time measurement makes sense (programmatic, largely), but the majority of the time, you have to give media some time to do its work.

A focus on right-time attribution changes the conversation from “how quickly can we get results” to “how do we get the insights and data to the channel at the right time, so that we/it can make a better optimization decision?”

When is the right time?

Again, that right time will differ for each channel. For programmatic, it does demand close to real-time input. Channels like video, and especially TV, on the other hand, perform better when optimized based on daily, weekly, biweekly or even monthly insights.

You need to give media in these channels a chance to make an impact. If you optimize too quickly, it simply won’t work. Just because a TV spot didn’t drive action today, you shouldn’t necessarily optimize it out.

Instead, by determining the right maturation cadence for each channel, you gain the ability to optimize strategically. That may mean moving money from publisher to publisher or changing contracts — decisions that require more time and thought than shifting budget from keyword to keyword.

In some cases, real-time isn’t even realistic. With a TV campaign, for instance, you may have 50 percent of your budget caught in an upfront. Even if you had real-time data to push to the network, what are you going to do with it? A right-time perspective enables you to work within your buying constraints.

[Read the full article on MarTech Today.]

Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.



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Lookalike modeling breathing new life into old channels

Lookalike modeling isn’t new. It’s been a mainstay of the ad tech industry for years, used to help advertisers expand digital audiences while maintaining relevancy of targeting. The principle is simple. Brands want to attract new visitors to their site. What better way to do this than to identify prospects who resemble existing visitors (or customers)?

What is new is the dazzling variety of ways in which digital marketers are deploying lookalike modeling techniques to enhance the return on investment across marketing channels — both online and offline.

With more data than ever before on user journeys and behaviors, increased adoption of platforms (like customer data platforms and data management platforms) to centralize and analyze that data, and growing ubiquity of machine learning tools and techniques, lookalike modeling is breathing new life into old channels.

What is lookalike modeling?

Customer-centric businesses have long recognized that the best way to acquire new visitors is to focus on users who resemble their existing visitors (or better yet, high-value customers). For digital marketers looking to drive traffic and conversions, this long meant identifying and purchasing media against audiences based on a small number of static demographic attributes. Your recent site visitors are statistically more likely to be females, aged 18-29? Perfect — serve display advertisements to similar audiences elsewhere on the web!

The problem is that demographic segment-based targeting, while enabling advertisers to reach audiences at scale, isn’t a great proxy for relevancy. Women aged 18-29 are a diverse demographic, only a subset of whom are likely to be interested in a brand’s offering. As a result, performance can tend to show a steep drop-off as audience size increases.

Enter lookalike modeling, a form of statistical analysis that uses machine learning to process vast amounts of data and seek out hidden patterns across pools of users. Lookalike modeling works by identifying the composition and characteristics of a “seed” audience (for example, a group of recent site visitors or high-value customers), and identifying other users who show similar attributes or behaviors.

By analyzing not just demographic but behavioral similarities — e.g., users who have demonstrated similar browsing patterns — lookalike modeling enables advertisers to leverage powerful and complex data signals to find the perfect audience.

Why does it matter?

Lookalike modeling is a trusty tool in the digital media arsenal — and it’s quickly becoming indispensable to other channels as well. The convergence of ad tech and CRM (customer relationship management) — powered by platforms that enable advertisers to go well beyond cookies and CRM professionals to gain visibility into the digital journeys of known users — has made it possible to build lookalike audiences of unprecedented sophistication.

[Read the full article on MarTech Today.]

Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.



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Branch now offers its Deep Linked Email solution on a majority of ESPs

Let’s say you open an email on your phone about a new travel package to Italy. You click on a link in the email, and it takes you right to a screen in the Hipmunk travel app with the specific flight and hotel info.

That’s a key scenario for Branch’s Deep Linked Email solution, now available via eight additional Email Service Providers following an announcement this week by the Palo Alto, California-based company.

Branch said the new integration with the eight providers — Blueshift, Epsilon, Mailjet, Mailgun, PostUp, Sailthru, Vero and Zeta Global — means that its solution is now available on a majority of ESPs (email service providers), given that it is already offered on providers like SendGrid and Oracle Responsys.

Using the Deep Linked Email dashboard, a marketer can configure whether a click in the email link takes the user to an installed app, to the screen in the appropriate app store to download the app if the app is not installed, or to a related web page. With the new ESP partnerships, Branch is also announcing easier ways to configure deep linking settings in its dashboard.

If the email link is clicked on a desktop, the user is taken to a desktop web page. If the path is to the app download screen in an app store, the appropriate screen inside the app is automatically opened after the app is installed.

Branch CRO Eric Stein told me that this app-install-to-correct-screen path is not available on Apple’s deep linking solution, Universal Links.

Additionally, he said, Universal Links’ click traffic and attribution stats, showing the path a user took to a sale or other action, are not always available for all email clients. Branch’s solution, he said, tracks link clicks and attribution on all clients, while “link wrapping” that many ESPs otherwise provide to track Universal Links often breaks the link connection to an app.

Google’s comparable App Links for Android, he said, only works on Android 6 and above, while older OS-based devices — representing about half of all Androids — require a different solution.

Linking from email to apps can be an important path for marketers. A Criteo study found that conversion are more than 300 percent higher in native apps than in mobile web, and Movable Ink report says that 69 percent of emails are opened on mobile devices.



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Google says we don’t need no stinking location modifiers… or do we?

Last week, Google declared that the “near me” search query and other “geo-modifiers” (e.g., ZIP code, city name) were, if not dead, then certainly not worth spending your valuable SEO time worrying too much about:

In September 2015, we shared that “near me” or “nearby” searches on Google had grown 2X in the previous year. Now, just two years later, we see that behavior has continued to change. Make no mistake, people still use ”near me” to discover places of interest around them. But we’re now seeing a shift toward dropping location qualifiers (like zip [sic] codes, neighborhoods, and “near me” phrasing) in local searches, because people know that the results will automatically be relevant to their location — thanks to their phone. It’s kind of magical. In fact, this year, search volume for local places without the qualifier “near me” has actually outgrown comparable searches that do include ”near me.” [see data] Over the last two years, comparable searches without “near me” have grown by 150% [see data].

But, as you can see through Google Trends, it’s not just that “implicit” local search queries (searches for local places without the local qualifier) are growing rapidly — it’s that they have always had a much higher base volume as well.

So, we get it — the search term “tacos” is a better term to target than “tacos costa mesa.” However, Google treats implicit/explicit/”near me” searches differently. Just look at these different results (searches were all done from the same location with an incognito browser):

Tacos (located in Costa Mesa, CA)

Tacos

Tacos Costa Mesa

Tacos Costa Mesa

Costa Mesa Tacos

Costa Mesa Tacos

Tacos Near Me (located in Costa Mesa)

Tacos Near Me

While there’s overlap, literally none of the results above are the same. That tells us that Google evaluates all of these queries differently. Not only that, but according to our 2016 Local SEO Ranking Factors study (2017 version coming soon), it looks like Google is looking at different ranking factors as well.

Here’s how various factors correlated with high rankings in the Local Pack for implicit and explicit local search queries:

Explicit v Implicit Local SEO Ranking Factors

So, this requires a more holistic approach to location-based SEO. Local SEO isn’t just about fixing data accuracy problems, it’s about making sure that clients are effectively optimized for the myriad terms and paths that will generate them business.

[Read the full article on Search Engine Land.]

Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.



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Google launches AdSense User First beta to test if fewer ads & better targeting can make more money for publishers

A small number of AdSense and AdMob publishers started receiving invitations to Google Adsense’s User First beta program this week.

The goal at this stage is to test new ways for publishers to make more revenue with fewer, hopefully more effective, ads and reward publishers who prioritize the user experience The program is meant to reward publishers that provide a good user experience — measured by site speed, ad layouts that generate high quality-clicks and low rates of users muting ads on the site — with priority access to new features. From the program page:

You were invited to this beta program because you offer your visitors a good web experience, e.g., your pages are fast-loading or your users are happy with the ad layout on your site. With this beta, by meeting certain requirements, you’ll get early access to new features designed to help boost your revenue and provide your visitors with better ad experiences.

Initial experiments

The feature testing will revolve around the goal of helping AdSense and AdMob publishers generate more revenue from fewer ads.

Targeting

The experiments will aim to go beyond the ad relevancy and personalization already aimed at signed-in users on the Google Display Network: “Your visitors who are signed into Google will see ads that they’ll want to engage with more.”

Ad load optimization 

Google hopes to find the optimal formula for showing fewer, more targeted ads while driving more revenue: “User First will start optimizing your ad load to create an even better experience for your visitors.”

To be eligible for the program, publishers must run only AdSense ads on their sites: “In addition, in order to adequately optimize the ad load on your site, we’re only able to provide the benefits on sites that serve only AdSense ads.” 

That means publishers won’t be able to plug into any other ad network or exchange to fulfill inventory while part of the beta program. The network exclusivity gives Google control to adjust ad load with this test group to better understand the impact on the user experience and publisher revenue.

As the beta develops, participants will get early access to additional features and new ad formats.

Publishers in the program will get access to a scorecard on the AdSense home page showing how they stack up against the qualifying criteria. They can opt out of the beta at any time.

This program is separate but of a theme with the Better Ad Standards the company announced it would uphold earlier this year. As part of that effort, Google will stop showing ads in Chrome that don’t comply with the Coalition for Better Ads standards, starting in early 2018.



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[Report] Who owns the flights market in search?

Which brands dominate the US flights market in search?

A new report by Pi Datametrics has analyzed the entire US flights market to discover the most organically valuable search themes and players with the greatest share of voice across the market.

The search data was collected from across Google US with a view to identifying the search terms with the most commercial opportunity over the last four years, and trended to reveal demand peaks and declines across the travel industry.

‘International’ flights: Trended search themes | May 2016 – May 2017

Image source: Pi Datametrics Market Intelligence

So what does the data show, and what can marketers learn from it about the state of the flights market?

The difference between organic value and search volume

Trended search volume data is a strong indication of research and demand phases, but to determine when a search is most likely to actually convert, Pi has applied their proprietary Organic Value Score.

Search volume alone doesn’t always indicate value. Pi’s Organic Value Score averages out all of the metrics critical to conversion – including adword data – to reflect the true value of individual search terms, and their overarching search themes.

Looking at the search volume graph (above) in isolation, ‘Latin America & Caribbean’ appears to be the one of the most important search themes to focus strategy on within the ‘International flights’ market.

But, if we overlay commercial value, the data tells a slightly different story. ‘Latin America & Caribbean’ devalues significantly, while ‘Europe & Middle East’ retains its competitive edge.

Share of voice: Top sites across the entire ‘Flights’ market

Date: 7th June 2017 | Top 20 sites

Image source: Pi Datametrics Market Intelligence

Using a datapool of the most valuable ‘International’ and ‘Domestic’ search terms, Pi generated a vast snapshot of the entire US ‘Flights’ market (12,286 sites), to reveal the players dominating the industry.

Kayak own the US ‘Flights’ market

Kayak perform best both internationally and domestically, closely followed by Tripadvisor – which has recently transformed into an integrated review / booking site.

Here are just a few key insights:

  • The top 3 performers own 57% of the entire ‘Flights’ category.
  • All ‘Others’ beyond the top 20 own 10.1% of the ‘Flights’ market. Kayak, alone, owns more than double this.
  • The top 11 performers consist of online travel agencies, aggregators or integrated review and booking sites. These sites own 86% of the entire market.
  • An airline doesn’t appear until position 11, and only owns 0.6% of the category.

Image source: Pi Datametrics Market Intelligence

Which airline groups own the entire ‘Flights’ category?

  • Priceline Group owns 33.5% of the entire market – that’s four times more share than the entire remaining market, beyond the top 20
  • Expedia Inc owns 25.6% of the entire market
  • All ‘Others’, beyond the top 20, own a tiny 7.7% of the market
  • Airline providers can use this market share data to establish the best aggregators to resell their ‘Flights’

When combined, Expedia Inc and Priceline Group own nearly 60% of the entire US ‘Flights’ market. This is astronomical, and has created an ‘illusion of choice’ across the digital travel landscape.

  • Priceline is the 6th largest internet company by revenue ($10.64bn USD).
  • Expedia is the world’s 10th largest internet company by revenue ($8.77bn USD).

These revenue statistics just prove the success of their digital duopoly.

What can marketers and SEOs in the travel industry learn from the data about the most valuable search terms? Knowing their most valuable content gives businesses the foresight to dictate strategy.

From Pi’s trend chart, we can see that Europe and Middle Eastern flights have the highest Organic Value across the US ‘International flights’ market.

Aggregators, airlines and integrated booking sites can use this data to plan marketing activity around the most valuable flights.

Why is the online flights market so heavily dominated by just two companies?

Priceline group and Expedia own significant search real estate, and dominate the flights industry.

We can’t know exactly how these groups achieve their success, but we can presume that each brand prioritizes search throughout the business.

What’s more, these groups have an array of interrelated digital assets, which provide greater opportunity for comprehensive link infrastructures. This would only serve to boost their presence across the search landscape.

Based on the data, we can also see that online travel agencies, aggregators and booking sites decisively outrank airlines themselves in almost all cases. So why is this?

Based on their business offering, aggregators and OTAs offer a variety of content covering all areas of the flights market.

As direct providers, airlines may have less opportunity to match this offering, which could in turn impede market share.

The full report can be downloaded from the Pi Datametrics website.



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Earth Networks CMO says martech delivers a lasting first impression within the prospect experience

Earth Networks CMO Anuj Agrawal has more than a decade leading marketing strategy for B2B data and organizations focused on SaaS (software as a service).

“I’ve lived and learned what it takes to drive customer acquisition, identify cross-sell opportunities and maximize retention,” says Agrawal. The CMO says his background spans all different levels of business maturity, working with everyone from venture-backed organizations to later-stage companies.

In his current role, Agrawal oversees all marketing and product functions for Earth Networks, a technology-driven solution that helps mitigate weather-related financial, operational and human risks for numerous industries, including airports, broadcast companies and energy and utility organizations.

According to Agrawal, the prospect experience is about making a great impression from the very first touch point — and for him, martech plays a crucial role in that experience. He uses an example of a brick-and-mortar retail store greeter to emphasize his case.

“It’s like walking into a department store and being greeted by someone who is waiting for their shift to end or someone who sincerely wants to help you solve your need. That is when a first impression is born,” explains Agrawal. “From a marketer’s perspective, that can be the first place someone sees your brand. The language and messaging you use in the first email the prospect receives, or the customer focus your sales team has during the first sales call.”

The way Agrawal sees it, martech fits into that journey by giving brands insight into market needs — allowing them to get into their prospect’s head and empathize with whatever their business struggle may be.

“Whether through surveys, intent information [or] other behavioral queues, you can craft your messaging dynamically for each prospect’s unique pain point.”

Agrawal will be joining the CEO and founder of IntelliPhi, Anand Thaker, to discuss how companies are using marketing technology throughout the customer-to-prospect journey at this year’s MarTech Conference in Boston.

Where does marketing technology play the most significant role when determining the lifetime value (LTV) of a prospect-turned-customer relationship?

Agrawal: You can break down LTV into two basic components: pricing and renewal rates. Customers like to do business with people they like.

The first impression I spoke about earlier sets the stage for a potentially long relationship if you can take that first impression and snowball its effect by demonstrating the value you can bring to the table. You can tailor the actions you take to get them through the funnel early in the process by capturing information on your prospect through their journey via behavioral tracking tools, their interaction with your content and one-on-one conversations.

Once they are ready to buy, having technology to help test and optimize pricing can then have significant impact over the LTV of that customer over time. Using A/B testing and price optimization tools can help optimize here.

After they become a customer, your focus on renewals will be largely dependent on your ability to successfully onboard the customer so they begin getting value out of the product as soon as possible with the least amount of friction and provide first-class support via that customer’s preferred channels of engagement.

Some will prefer self-service support, others will want to chat within the product, and others may like the old-fashioned phone number to ring. Enabling the preferred support models for each customer in a personalized way makes for a happy customer.

What about customer acquisition costs (CAC)? How do martech tools impact the cost of acquiring customers?

Agrawal: Similar to LTV, CAC can be broken down into two primary components: cost per lead and conversion rates.

If you break these components down, you look for tools that help you lower your cost per lead. The lower your cost per lead and higher your conversion rates through the funnel, the lower your overall CAC will be.

Optimizing your cost per lead is really a function of strong segmentation, so you spend your marketing dollars in targets and with people who will appreciate your value proposition. You’ll also need to understand which marketing channels to use to reach those specific segments in the most efficient and cost-effective way.

Your marketing automation will likely house most of your segmentation intelligence. You may have access to channel intelligence you’ll want to look at directly from those sources — social media, AdWords, display ad platforms, content syndication and others you may be using.

For conversion rate optimization, you’ll need to find the tools to help you understand attribution of each action and channel, and its impact on conversion. Your automation platform may have basic tools to help, but you may want to leverage more full-featured analytics platforms to get granular.

In your opinion, how important is creating a ‘personalized’ prospect experience for B2B marketing organizations?

Agrawal: In today’s world, everyone wants personalization. Even traditional segmentation based on firmographics is not effective anymore.

Your buyers are individuals and have different motivations that you can’t tell from knowing how many employees they have, or what their annual revenue is. With new intent-identifying tools, you can find out what people are actively searching for.

In Salesforce’s recent State of Marketing report, 65 percent of business buyers said they would switch brands if a vendor doesn’t personalize communications to their company. I’d actually interpret that to mean they expect personalization to them personally more than their company.

At the end of the day, purchase decisions are made by individuals.

Do you think most anchor platforms — CRMs and CDPs — offer the basic necessities to start a successful relationship with a prospect, or do you think most companies need to go beyond these platforms?

Agrawal: Many marketers rely on marketing automation and CRM tools for all their activities. While these can form the foundation of your martech, there are several point solutions that should be leveraged to plug into these platforms for specific use cases.

Oftentimes, the marketing automation interfaces are good for some features, and not for others. For features that are not user-friendly, you may need to look at other point solutions that are easier to leverage and interpret. You may be reluctant to spend money on another tool for a feature you theoretically already have, but if the feature can make meaningful impact to your marketing processes, then the investment is worth it.

After all, if you have a capability that is hard to use, you just won’t end up using it. In fact, only 3 percent of marketers cite getting full value out of their martech tools (Sands Walker State of Marketing 2017).

Where do you think most marketers are missing the boat when it comes to using martech in their prospecting efforts?

Agrawal: The biggest gap I see and have been hearing about is with how you tie all this martech together to get a full view of the prospect journey and how all the touch points can be viewed collectively to identify deeper insights.

Most tools have analytics embedded within them, so it’s easy to see on a relative basis how one tactic within the same tool performed over another tactic. But getting cross-platform insights is where many teams still struggle.

These insights would provide better intelligence to know what messaging, channels and content may resonate with various personas or target markets — leading to better relationships and a more efficient funnel conversion.

For marketers who want to fine-tune their martech stack to better align with the prospect experience, what technology do you think they should be considering?

Agrawal: With the frantic pace of change in martech, it’s important for marketers to invest time understanding the landscape of available technologies. The demands on today’s marketer are increasing, and using technology to optimize your marketing operations and execution can have a significant ROI.

An evaluation of a tool can take several months to fully understand its value and relevance to your organization. When you can, leverage peers to shorten the list of tools to evaluate. Be sure to form a strong relationship with your account managers representing your existing martech so you know what’s on their roadmap.

With more than 5,000 vendors, the martech landscape is crowded, and differentiation is highly sought after. Vendors are going to be innovating and encroaching into adjacent areas of martech. Before you decide to purchase a new tool, do your diligence to see if you may be getting a variety of that tool in the near future within an existing product.

Also, social media players are increasingly becoming competitors in the martech space. Facebook Live is becoming an integrated content creation and distribution tool. LinkedIn is growing its popularity as a publishing platform.

Remember when Facebook went public and their revenue strategy was uncertain? Their stock ascent since then is a clear indication — with their growing and engaged audiences — of their ability to create content. Facebook’s ability to target on highly specific criteria will make them a continued force in martech.

Keep your pulse on what the social media leaders are doing.

If you’re headed to the MarTech Boston Conference, be sure to attend Anuj Agrawal’s session on Tuesday, October 3. As part of the conference’s marketing track, “From Prospect to Reference Customer: Maximize Lifetime Value with Martech,” Agrawal will be discussing the role of martech throughout the customer journey with IntelliPhi CEO and Founder Anand Thaker.



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Google Shopping gets top spot impression share & product diagnostics reporting

Each year, Google rolls out several new features ahead of the holidays for retail advertisers. This year’s updates have started coming out.

The company introduced a new metric and new reporting for Shopping campaign advertisers — only in the new AdWords interface.

The new metric, called absolute top impression share, reports how often Shopping ads and Local Inventory ads appear in the first spot on mobile and desktop. Google says that during Q4 last year, the first Shopping ad on mobile saw up to three times more engagement than the other spots.

On the Products page, a new diagnostics report lets advertisers dig deeper into product status issues in AdWords.

 

These features can be added to the list of features exclusive to the new AdWords interface — what Google calls the new AdWords experience — that’s rolling out to advertisers through this year.



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Evaluating PPC talent, part 2: The test

Previously, we discussed how to find good PPC candidates for your particular company, but now it’s time to evaluate those candidates.

It comes down to this: You’ve held dozens of interviews with candidates almost impossible to tell apart. They all have similar credentials. They’ve worked in the right industry or environment, have used similar tools to what your paid media team uses and didn’t hesitate to answer your questions. But what’s next?

The technical assessment of your PPC hire may be the thing you’ve most overlooked, and it can often lead to a complete disaster.

How do we evaluate PPC talent?

You cannot properly assess how someone will fit into your team and impact your business simply by reviewing resumes and asking them a few questions to make sure they speak the language.

Unfortunately, there is also no one-size-fits-all assessment your team can find online and use. You have to start by taking an honest look at your work environment and understanding the person who will be required for the job. What tasks would this person be expected to complete daily, weekly or monthly?

If you’re a SaaS (software as a service) startup in need of speed and growth, you simply cannot afford to hire someone who hasn’t been through that; bringing on PPC manager from a local digital agency won’t get the job done. Your hire will need to understand how to deliver a plan of upcoming experiments at scale and execute on them quickly. There can’t be a learning curve.

If you’re an agency, your hire might need to be a better public speaker and salesperson in addition to having technical PPC knowledge, and they will need be able to create (and explain) reports.

By understanding the specifics of the position and crafting a test around them, you are off to the right start. And while there is no one-size-fits-all, I can share three tests I highly recommend.

Test #1: The fake report

The fake report test might be my favorite, wherein you deliver an interviewee a fake dataset for analysis. Present a sample report and ask for recommendations based on the data. Hopefully, they will dig into topics like the following:

  • Suggestions on how to re-allocate budget for efficiency.
    • For search, this might mean indicating search impression share.
    • For social, this might mean indicating audience size and daily budget.
  • What channels should be tested, given the business goals?
    • Also, did they ask you about the primary KPIs for your ad campaigns? If not, it’s likely not the right fit.
  • Is there an appropriate mix of prospecting and retargeting?
  • Are campaigns organized in a way that makes sense? Should structural changes be made?

The suggestions above are not exhaustive, but the perfect candidate has these types of questions and thoughts from looking at your data. Let them show you how they think and make decisions.

If you use this test, consider throwing in something really strange. Give your potential hires something to question, and see what they come up with. I recommend something subtle, like duplicating click numbers several times, or having the total spend not add up — small details that would be important to capture if they were incorrect. After all, a few lines of data could seriously throw off your day, or even your month.

Here’s an example of a fake dataset you might present to your candidates for analysis, with inconsistencies highlighted in red. (Obviously, don’t highlight your inconsistencies for the candidates!)

Of course, not catching these inconsistencies shouldn’t keep you from hiring someone who is otherwise an absolutely perfect fit. But when each candidate seems to be almost identical, small details like this can be great differentiators. You want the person who digs most deeply into the data and sees inconsistencies. Incorrect data leads to incorrect analyses — and possibly incorrect actions. Incorrect data can mean pixels and tracking codes are firing improperly.

Test #2: A competitive analysis

There are several things that advertisers like to do, and checking out the competition is one of them. If you’re hiring for a position where they will have to touch Facebook Ads, the candidate who knows to follow competitor brands, engage with posts, or even go to their site and get into retargeting pool is the one to pursue.

One of the best weapons advertisers have in Facebook is to see how ads are being targeted. If a candidate is seeing prospecting ads from your competitors and has the foresight to check if it’s lookalike targeting or something more complex, hire them.

In AdWords, a hire should be able to not only have an understanding of keywords competitors might be using, but start to develop a feel for how each brand positions themselves in search. Ask candidates to evaluate the search landscape and come to you with estimated CPCs, top keywords, ad extensions and copy competitors are using, to begin building a complete picture of what your competitors are doing. With this information gathered, what opportunities do they see, and what recommendations can they make?

This test has several benefits: Candidates will have a better understanding of what first steps to make if hired, and you are provided with some much-needed outside perspective that can further inform your decision. Again, the key here is to find tests that would be applicable to the daily work your new hire will be doing, and checking out the competition will surely fall into that category.

Test #3: Next month’s budget

This test requires a willingness to share your current spend and results, but it will likely be worth it. Have the final candidates sign an NDA (non-disclosure agreement), then grant read-only Google Analytics access and share your most recent budget. Budget planning, especially for channel owners who will not have a direct supervisor managing this for them, is a 100 percent essential skill and cannot be overlooked.

Now, you won’t be able to judge from this exercise how well these candidates can stick to a budget, but a candidate who can identify areas where you are overspending or underspending — as well as new opportunities for test spend and a plan to execute — is one worth being excited about.

If you’re a high-growth organization that isn’t asking for someone to just conduct daily maintenance, but needs someone to optimize and then scale quickly, you need to evaluate more than just a potential hire’s PPC knowledge. General business skills, like budget allocation, are crucial to the position.

Customize your test for your business

Feel free to tweak any of the above tests to best fit your hiring needs. Again, I can’t stress enough that the most important step in creating a test for potential candidates is doing a thorough evaluation of what your new hire will be doing on a daily, weekly and monthly basis. Identify all the skills they will need, and start testing for relevant skills.

Hiring PPC talent isn’t easy. But when you’ve made sure your job listing accurately details your expectations and crafted tests to make sure candidates are the right fit, you’re going to make the process a lot simpler.

Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.



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