Read this playbook from DialogTech and learn how to:
Visit Digital Marketing Depot to download “The Click-to-Call Playbook for Display Advertising.”
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Below is what happened in search today, as reported on Search Engine Land and from other places across the web.
In the market for a new job? Google appears to be testing a new search feature just for you.
Google has been busy with 1,653 launches, 9,800 live traffic experiments, 18,015 side-by-side experiments and 130,336 search quality tests.
Here’s a look at what’s happening with Shopping ads, expanded text ads, device bidding and more.
Check out the cheesy Google logo on their home page today.
Columnist Brian Smith discusses some of the recent developments and technology that will impact local search, both in the short term and the long term.
In this week’s Search In Pictures, here are the latest images culled from the web, showing what people eat at the search engine companies, how they play, who they meet, where they speak, what toys they have and more. Google meeting room that looks like an airplane: Source: Instagram Bing body painting: Source: Twitter Google […]
Industry
Local & Maps
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Searching
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SEM / Paid Search
Search Marketing
The post SearchCap: Google job search, metrics on search update & cheese doodle appeared first on Search Engine Land.
Google seems to be testing a new search feature. This one is designed to help searchers find new job openings. John Doherty spotted this test for queries on Google that include [jobs online], [data entry jobs online], [newbury street jobs] and so on. Google shows job listings and takes you into what appears to be their very own job search portal to drill down deeper.
Here are some screen shots of the job search results in the core web results:
After you click on “more jobs,” it takes you into this jobs-specific search results interface that gives you additional filters for job categories, titles, dates, types, state, city, company type and employer. The interface looks a little bit like the local results interface, with the listings down the left-hand side and results in the middle.
This story is developing, and we will update it as we have more information from Google. As we wrote earlier today, Google performed 9,800 live traffic experiments last year; this is just one of the many new ones.
The post Is Google testing its own jobs search engine? appeared first on Search Engine Land.
With over 90 million customers watching a combined 125 million hours of television and movies everyday, there’s no doubt that Netflix has changed the way we watch our favorite shows. It has also become a prime force in our daily lives — integrating into everything from mobile devices to our language and culture.
And with a relatively low 9% churn rate (lower than any other subscription streaming service), one has to wonder — how does a service like this continue to keep their customers engaged in both the short and long term? How do they succeed when others fall short? Let’s take a closer look and discover how they do it.
As a subscription service, each new month gives every Netflix users a chance to cancel the service.
Like all subscription companies, the best step Netflix can take to reduce churn is to create a great product that people are willing to pay for. They do this by having a large library of original and licensed content. As long as people keep watching, they’ll keep paying.
Let’s look at how Netflix achieves relatively low churn rates, when compared to their peers.
With more than a third of U.S. households subscribed to Netflix, it’s no secret they’re far ahead of their competitors (namely Amazon Prime and Hulu Plus) in the video streaming subscription race. Recent research by Parks Associates showed that only 4% of U.S. broadband households cancelled their Netflix service — representing almost 9% of Netflix’s subscriber base.
By comparison, 7% of users cancelled their Hulu Plus subscription within a year — but that figure represents approximately half of Hulu Plus’ current subscriber base.
What this tells us, is that not only are most households electing to keep their Netflix subscription and “test the waters” with other streaming services, but those same users keep coming back. But what is it that draws them back?
Perhaps some of what makes Netflix so irresistible among its user base are its original shows. With fan favorites like House of Cards and Orange is the New Black, Netflix has its finger on the pulse of what users are watching. And they’re not just skimming the surface, either. They look at things like:
And that’s not all. They’re also gathering data on:
Netflix knows when the credits roll – but it’s also speculated that they’re monitoring things like the volume, movie/show setting, colors and so on. All of this information is not just collected, but also acted upon.
Some might even say that Netflix took a huge gamble ($100 million to be exact) in purchasing the exclusive rights to House of Cards but they did so with a concrete hypothesis — that a large portion of its customers streamed “The Social Network”, directed by David Fincher from beginning to end. House of Cards is also directed by David Fincher. What’s more, they also noticed that films with Kevin Spacey tended to do well, as well as the original British version of House of Cards.
But Netflix didn’t just settle on one trailer to introduce users to House of Cards. Spacey fans saw trailers that exclusively featured him. Women who watched Thelma and Louise saw trailers featuring the female protagonists of House of Cards and big time film buffs saw trailers that reflected Mr. Fincher’s finest directing moments.
All of these points intersected in a way that practically lit up a path to customer engagement and retention. And all of them were made possible thanks to insights delivered by big data.
But this method only attracts users who happen to be watching other movies. What about when they’re not watching? Netflix has that covered, too.
With the vast content library available, it would be overwhelming to not recommend shows to users. So Netflix doesn’t just collect data about the shows you watch — it acts on that data too, sending you emails when a show is added that you may like based on your existing viewing habits.
The email itself is simple and straightforward, and, this is the important part — you can play the episode right from within your mobile device, or add it to your watch list. So it’s not just notifying you that you might enjoy this show, but rather giving you an action to take that lets them better tweak suggestions according to your viewing habits.
Many people find push notifications bothersome and frustrating — but it all depends on where they come from. Things that affect users directly – like utilities (your water or electricity is scheduled to be off for a time) or transportation (there’s a car wreck near you that may slow your commute) are definitely wanted.
Movie or series suggestions don’t seem like they’d be high up on users’ priority lists, but Netflix has done a fine job of customizing and fine tuning what gets shown to each user. For example, if you followed season 1 of House of Cards, Netflix lets you know that Season 2 is now available:
What it doesn’t do is inundate you with notifications when every new season or every new movie is listed. Each push notification is carefully crafted again, based on the data from your viewing habits. This way, it’s not intrusive, but rather engaging.
Netflix is also famous for its recommendations. It knows it has just 90 seconds or less to convince you that there’s something worth watching that’s catered to your tastes, it looks at things such as the genre you watch and your ratings, but also what you don’t watch. There’s a very real problem of overwhelming the user — with so many choices, Netflix doesn’t want to get too personal.
And it doesn’t care so much about what you watch, but rather that you watch. When given the choice between calling a friend, reading a book or watching Netflix, they obviously want you to keep coming back.
And although Netflix does push its own original series up on its recommendation pages, it plays a flat fee to content providers, so there’s no reason for its recommendation algorithm to favor one series over another. Everything it recommends to you, it does not just because of your viewing habits today, but also historically.
All of these options filter in to create a uniquely personalized — but not too personal — list of recommendations specifically tailored to each user. An engaged user is a happy user, and Netflix is pulling out all the stops to keep them watching.
Interestingly enough, the personalization algorithm resets every 24 hours, making it more likely that users will keep discovering current titles of interest from Netflix’s ever-growing catalog.
Not surprisingly, Netflix also does a great deal of split testing — a couple hundred tests each year to be exact. It randomly selects around 300,000 users from around the world and tests everything from images to font size.
Whenever major changes are made, such as a homepage redesign, users are understandably upset and backlash is imminent – it’s in our nature to tend to resist change. However, Netflix does a good job of easing them into the new design by explaining what has changed and why. According to Netflix’s vice president of product innovation, Chris Jaffe, however, less than half of their tests have a positive impact on metrics.
Even still, with so many options to keep users informed across nearly every type of device, Netflix is continuing to test, innovate and refine its algorithms to prevent churn and keep users watching — and those users are at its core in a quest for never-ending user experience growth.
What are your thoughts on Netflix’s methods to keep you hooked? Have you discovered new shows as a result of their recommendations? Share your thoughts with us in the comments below!
About the Author: Sherice Jacob helps business owners improve website design and increase conversion rates through compelling copywriting, user-friendly design and smart analytics analysis. Learn more at iElectrify.com and download your free web copy tune-up and conversion checklist today!
Merkle’s Digital Marketing Report for Q1 points to strong growth from Google and the continued strength of PLAs (Google Product Listing Ads). Expanded text ads have yet to yield promises of CTR gold. Bing and Yahoo’s lack of mobile market share is hampering growth. Here’s a look at some of the key trends from the report. (Keep in mind the data reflects spending from Merkle’s own client base, which skews large retailer.)
Spending on Google AdWords increased 21 percent year over year in Q1 2017, up from 19 percent in Q4 2016. Click volume increased 20 percent over the previous year. CPCs ticked up 1 percent.
Merkle credits the addition of a fourth mobile text ad, PLAs in image search, Google Maps ads and the return of separate device bids as key contributors to growth over the past year.
Tablet bids have steadily declined relative to desktop since Google enabled advertisers to bid separately on the two devices last summer. Merkle says decoupling tablets from desktop helped drive growth, with advertisers able to adjust bids separately for higher-value desktop clicks.
Google AdWords phone and desktop spend increased 51 percent and 12 percent, respectively, while tablet spend fell 23 percent.
Phone CPCs continued to gain ground on desktop in Q1. For non-brand queries, phone CPCs were 43 percent lower than desktop CPCs in Q1, compared to being 51 percent lower in Q4. Tablet CPCs were 25 percent lower than desktop in Q1, down from near-parity in early 2016, when the devices were combined in bidding.
Source: Merkle
With 52 percent click share, PLAs accounted for more than half of retail search ad clicks in Q1, up from 48 percent in Q4. For non-brand queries, PLAs drove a whopping 75 percent of all clicks for retailers.
Spending on Google Shopping rose by 32 percent year over year in Q1, compared to 12 percent for text ads. Growing impression volume on mobile is helping to increase PLA click share, and growth was largely driven by non-brand queries.
Source: Merkle
Search partners, which includes Google image search, accounted for 11 percent of PLA clicks for the quarter, similar to Q4’s share.
In Q1, Local Inventory Ads (LIA) accounted for 19 percent of all Google Shopping clicks on phones. CTRs on LIAs are 19 percent higher than PLAs on phone and desktop. Not surprisingly, online conversion rates for LIAs, which are designed to direct store traffic, are lower than PLAs.
Merkle has consistently reported seeing mixed results since ETAs first came on the scene last year. The Q1 results for ETAs show a CTR lift compared to standard text ads only on desktop ads shown at the bottom of the page.
After accounting for device, keyword type, and ad location, there is still no clear evidence that Expanded Text Ads are producing consistently higher click-through rates than the legacy Google text ad format.
Source: Merkle; high-traffic ad groups with both formats active in Q1
Overall, text ad spending on Google increased by 12 percent. However, non-brand text ad spending rose 16 percent year over year. Merkle says the fourth mobile ad unit and the addition of ads in Google Maps has done more to buoy text ad growth than format changes.
Across Bing Ads and Yahoo Gemini, spend fell by 14 percent compared to the previous year, marking the fifth consecutive quarter of spend declines.
With Google as the default search option on Android and iOS devices, mobile weakness continues to be a considerable handicap for Bing and Yahoo. Google accounted for 97 percent of mobile phone traffic in Q1. Bing and Yahoo clicks made up 19 percent of desktop clicks for the quarter.
There is much more detail in the report, including on organic, social and Amazon. It’s available for download here.
The post 6 key paid search trends from Merkle’s Q1 2017 report appeared first on Search Engine Land.
Google revamped its How Search Works site, the site they launched in 2013 to describe the efforts Google makes in search. Google added some new metrics around the various Google search launches they made last year, how many tests they tried out and the various numbers around their diverse set of search experiments.
Google mentioned the update to this site when they also announced Project Owl earlier this week.
The site shares that Google launched 1,653 new search changes last year, based on 9,800 live traffic experiments, 18,015 side-by-side experiments and 130,336 search quality tests.
As you can see, only a small percentage of what Google tries actually goes live, but to launch over 1,600 new changes in search in a single year is massive. In fact, we don’t know exactly how many of the 1,600 changes are user interface changes versus new feature changes versus algorithmic or ranking changes. I doubt Google would share those details.
What we do know is that only one percent of searchers were part of the 9,800 live traffic experiments and that while we likely covered many of them, I am sure we missed the majority of those experiments.
Here is an animated GIF of the page that documents these numbers:
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Today’s special Google doodle honors the inventor of the Camembert cheese. Marie Harel was born 256 years ago today in Crouttes, France. She invented the Camembert cheese back in 1791, at the age of 30.
The Google doodle shows the steps it takes to make Camembert cheese in nine different Google logo slides. Google said that the “Doodle celebrates Harel’s 256th birthday with a slideshow that illustrates how Camembert is made, step by step.” “It’s drawn in a charming, nostalgic style reminiscent of early 20th-century French poster artists, such as Hervé Morvan and Raymond Savignac,” they added.
Her work earned her a statue in Vimoutiers in France.
Marie Harel lived to the age of 83 and died on November 9, 1844.
The post Google doodle celebrates Marie Harel, the inventor of Camembert cheese appeared first on Search Engine Land.
We’ve entered an exciting time for local marketing. Big Data, digital assistants, augmented reality and beacons will fundamentally change the way users discover locations. As Bob Dylan so aptly pointed out, “The times they are a-changin’.”
As such, local marketers and advertisers need to start thinking about how they’re going to change along with the times. Here’s what you need to know about the future of local discovery.
Proximity is the primary ranking factor in local searches. That’s not likely to change. After all, what’s nearby is the fundamental aspect of local discovery.
What is changing, however, is the filter that sorts out, ranks and presents those nearby locations. What filter, you ask?
It’s you.
Going forward, local discovery will function as proximity filtered by your individual preferences. The person searching will inform what locations are shown.
In truth, this is nothing new. Google, Bing, Safari and Yahoo have been personalizing search results for some time through tracking your browsing history. What is new is the sophistication of artificial intelligence and Big Data analytics.
With the burgeoning Internet of Things, the amount of customer and behavioral data is growing by the day. Even if Congress hadn’t cleared the way for internet services providers (ISPs) to sell your data, what marketers and advertisers know about customers was only going to increase thanks to the growing data fiefdoms of Google, Facebook, Apple, Amazon and Microsoft.
For good or ill, the ability to use that information to target the right customer with the right message at the right time is maturing. In fact, even back in 2012 ,Target had the capability to use data mining to predict the pregnancy of a teenager before her father could deduce the news himself. Big Data has come a long way since then.
In the case of local discovery, Big Data will help search engines personalize local results based on a user’s preference. The more the search engines know about you, the more relevant search results and maps will be.
For example, a search for nearby restaurants might include ranking factors such as your favorite dishes, food allergies, price point, time of day and how long it was since your last visit. Meanwhile, a search for a nearby product such as shoes might be filtered by your favorite brand, shoe color, size and any ongoing sales.
However, knowing your customer and targeting your customer are two different things. There needs to be a means of surfacing local information in a unified way, and that need will undoubtedly be addressed by digital assistants.
Digital assistants will serve as the connection between customer profiles and the preferred locations and products around them.
Digital assistants will be everywhere. On your phone, in your car, your house, your office — everywhere and inside everything connected to the internet.
The ultimate goal of Google Assistant, Amazon Alexa, Microsoft’s Cortana and Apple’s Siri is to become that universal connection between the physical and digital worlds.
In the context of local discovery, think of a digital assistant as your very own personal Rick Steves, providing you with everything you’d ever care to know about a location — and then some.
This omnipresent assistant, part tour guide, part planner, part shopping liaison, will provide users with the most relevant and personalized local recommendations for anything you can imagine.
And thanks to voice search, digital assistants are always listening.
Google Home and Amazon Alexa operate in this mode by default, and Apple’s latest iPhone update is pushing users to set up voice activation for Siri.
In addition to enabling ambient listening, voice activation establishes voice biometrics, which will allow digital assistants to become device-agnostic.
Whether it’s smart cars, smart homes or smart offices, the ability to distinguish between users is critical to translating your personal preferences regardless of location or device. This will provide a consistent user experience without a disruption to conversational context.
In fact, Google Home recently made progress on this front by being able to recognize up to six different voices from one device. It’s not hard to extrapolate this trend to the point that digital assistants will be able to recognize who you are regardless of where or what device you’re using.
Soon you’ll be able to make dinner reservations by talking to the digital assistant embedded in your hotel room, order an Uber from the digital assistant on your phone as you walk to the lobby and check your flight from the digital assistant inside your autonomous Uber — all without breaking the conversational context with your digital assistant.
With the rise of voice search, it’s also necessary to replace the traditional screen on your phone and monitor. A picture is worth a thousand words, so it’s unlikely that even a sweet-talking digital assistant will replace our need to visualize what’s in front of us.
As I outlined in a previous article, the solution to traditional screens is to replace them with augmented reality — your smartphone transforming into smart glasses. Based on Facebook’s recent plans for augmented reality, this indeed seems to be the direction we’re heading.
In my mind, augmented reality is likely to be one of the more exciting and less privacy-invasive developments of local discovery. You’ll be able to scout out a local restaurant, visualize the precise location of a product on a shelf or interact with custom location-based content triggered with beacons. Which brings me to the final trend you should be keeping an eye on.
Proximity targeting will flourish with the rise of augmented reality and digital assistants.
Beacons are perfect for surfacing content in a user’s immediate proximity. The challenge right now is alerting users to beacons. However, if everyone has a digital assistant embedded in their augmented reality glasses, it will be easy for users to discover beacon content and have that content personalized based on personal preferences.
Whether it’s triggering a coupon for a customer’s most likely purchase as he walks by a store entrance or promoting a fast food restaurant as a vehicle exits the interstate off-ramp, the potential for beacons is tremendous.
Many of these developments might seem too far out in the future. However, technology is evolving at an exponential rate. The time to start preparing and laying the groundwork for these marketing developments is now.
The post The future of local discovery appeared first on Search Engine Land.
In this week’s Search In Pictures, here are the latest images culled from the web, showing what people eat at the search engine companies, how they play, who they meet, where they speak, what toys they have and more.
Google meeting room that looks like an airplane:
Source: Instagram
Bing body painting:
Source: Twitter
Google indoor hallway race track:
Source: Instagram
Google fred fish mug:
Source: Twitter
Google android rusty helmet:
Source: Instagram
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Below is what happened in search today, as reported on Search Engine Land and from other places across the web.
Cortana was second for questions answered, Alexa second-best for accuracy.
Every advertiser measures success based on key performance indicators (KPIs) that they deem relevant. Columnist Andy Taylor asks, What do your chosen KPIs say about your priorities?
The program, coming out of pilot, spotlights offers in Bing product ads.
Spending declined on the desktop but grew by nearly $6 billion overall because of mobile.
The settlement stems from a case that dates back to 2008 about Google ads showing on error pages and parked domains.
Columnist Jacob Baadsgaard explains how assigning paid search keywords into different tiers based on performance allows search marketers to quickly make adjustments that can have a huge impact on their business.
Marketers and advertisers understand the importance of reaching consumers wherever they are— sometimes even before consumers get there themselves. Preemptive planning, tracking preferences and behavior, targeting, SEO, modern-day campaigns have tried it all in an effort to be seen and heard by their ideal consumer. For success in today’s digital marketing world, you need a […]
Industry
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Link Building
Searching
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In January, Stone Temple Consulting released a virtual assistant consumer survey showing the majority of respondents wanted the assistants to provide “answers” rather than conventional search results. Today, the firm published a follow-up study that measured the relative accuracy of the four major assistants.
It compared results of “5,000 different questions about everyday factual knowledge” on Google Home, Alexa, Siri and Cortana, using traditional Google search results as a baseline for accuracy. The following table shows the study’s top-line results.
As one might have anticipated, the Google Assistant answered more questions and was correct more often than its rivals. Cortana came in second, followed by Siri and Alexa. Of the questions it could answer, Amazon’s Alexa was the second most accurate assistant. Siri had the highest percentage of wrong answers of the four competitors. (Apple is reportedly “finalizing” its Amazon Echo competitor.)
Here’s Stone Temple Consulting’s summary of the outcome:
Google still has the clear lead in terms of overall smarts with both Google search and the Google Assistant on Google Home. Cortana is pressing quite hard to close the gap, and has made great strides in the last three years. Alexa and Siri both face the limitation of not being able to leverage a full crawl of the web to supplement their knowledge bases. It will be interesting to see how they both address that challenge.
One of the interesting observations in the report is about featured snippets. Cortana had more featured snippets integrated than any of the others, even Google Home, although Google search had more. Siri and Alexa lagged far behind in the category, although they want to use third parties to deliver “answers” and transactional capabilities.
There’s a good deal more discussion of both the results and the study’s methodology on the Stone Temple blog.
The post Report: Google Assistant bests rivals for questions answered and overall accuracy appeared first on Search Engine Land.
There are plenty of options for particular metrics to drive paid search programs toward, but not every KPI is created equal. Here, we’ll dive into what your preferred KPI says about you and provide recommendations to help you assess whether your KPI reflects the goals you care about.
All insights are at least slightly hyperbolic and assume you have a one-track mind for your KPI of choice. I bet some of you out there can keep two, three, maybe even more KPIs in mind when managing accounts, as you should. You’ll just have to meld the descriptions to uncover those deep insights into your psyche that you’re reading this to find.
You waaaaaaant them to want you.
You neeeeeeed them to need you.
Some brands care a lot about how likely a user is to click on an ad, and for good reason. Click-through rate (CTR) is a key component of Quality Score, which Google uses to determine both how well an ad ranks and what price an advertiser must pay for clicks. Higher CTR means better rank and lower cost per click (CPC).
Thus, brands should make their ads as appealing as possible to searchers. However, chasing CTR above all else can lead to some poor choices.
Could I probably make a few friends at a college activity fair with this sign? Sure.
Will they still be my friends if I don’t actually have the goods? Probably not.
Similarly, advertisers might be able to draw more clicks with some versions of ad copy but end up hurting conversion rate or brand sentiment in the process. As such, it’s important to avoid pitfalls like overpromising or misleading searchers in the pursuit of higher CTR.
You love to be seen, and ensuring your ads are present for a minimum share of relevant searches makes you feel good about your competitive position in search. Consistently getting in front of users searching for queries related to your business offerings is important, and that visibility can sometimes come at the cost of less flashy metrics like return on ad spend.
Advertisers can access estimates for the share of relevant impressions their ads are showing on the SERP by using Google Auction Insights reports. These reports also feature information on how often specific competitors are showing ads, as well as other metrics such as average position and top-of-page rate.
Shooting for impression share in search as your primary KPI isn’t that dissimilar from a television ad buy focused on reaching a specific segment of the television-watching population. Maybe in search you’re focused on getting in front of 100 percent of people searching for “red running shoes,” while on television you want to reach ESPN viewers in the 7:00–8:00 p.m. time block on the East Coast, with different categories of keywords somewhat analogous to different television channels in terms of audience differences.
The difference is that the effects of online interactions with ads are, for the most part, much easier to track than the effects of television ads. Users can be cookied, and online orders and other interactions such as email signups properly attributed to ad clicks. Thus, shooting exclusively for impression share requires abandoning this information in pursuit of visibility.
For many brands, performance metrics such as return on ad spend (ROAS) are deemed more meaningful in allocating search spend as effectively as possible. However, there are some advertisers who would prefer to lock up a percentage of impressions related to particular categories of search, regardless of how ROAS turns out.
You care about profitability — unimpressed by all the impressions and clicks your ads are getting, you care about how much they cost and what your business gets out of them. Paid search is great for you, because it’s easy-peasy for most advertisers to track events such as orders and information inquiries to the clicks driving them.
The trickiness comes in how you measure that ROAS. Are you using last-click attribution? Accounting for offline interactions such as phone calls or store visits? Baking in the interactions that occur on a different device from the one searched on originally (cross-device)?
Not all ROAS measures are created equal, and the better an advertiser can get at attributing value to ads, the more effective optimization efforts will be. But since you care about performance so much, I bet you’ll put in the work to get attribution just right.
You’re all about growing your customer base, reaching those shoppers you’ve never been able to pull through other marketing channels. Maybe your business is such that paid search clicks from existing customers don’t carry much incremental value, or maybe you just really want to expand your market share.
There are a number of ways you can go about targeting those new customers. One is to shoot for cost per new customer acquisition as the primary KPI of search campaigns, while another strategy might involve trying to turn ads off to all existing customers via audience exclusions using Remarketing Lists for Search Ads (RLSA) and Customer Match audiences.
Choosing between these different methods of focusing on new customers should include evaluating what bringing back existing customers is worth. Is there literally no value to these interactions (very rare), or is it just that interactions with new customers should be valued more than those with existing customers (more common)?
Everyone likes new customers, but if you’re going to use new-to-file acquisition as a key measure of success, it’s best to make sure you’re not neglecting valuable existing clientele in search out of a desire for those shiny new shoppers.
I suppose what kind of person you are depends on what average position you want to be in. Want to stay in first? You’re a winner at heart who wants be number one. Really just hoping for position three? That’s a losing attitude right there.
Really though, shooting for average position in general is kind of a losing attitude. Sure, it might make sense to try to stay in position 1 for your own brand keywords, but shooting for a specific spot on the page with non-brand keywords regardless of cost and return on ad spend is pretty risky given the competitive nature of AdWords auctions. Get in a bidding war with a couple of competitors, and the ad spend can add up pretty quickly.
While there are some studies and individuals out there proclaiming that specific positions on the page magically perform better than others in metrics like conversion rate, most of the data and studies behind those conclusions can be politely characterized as pseudoscience. What’s more, even if those conclusions were true, they would change with every SERP update, such as the removal of text ads on the right rail and the addition of a fourth text ad above organic results rolled out in early 2016. As such, we recommend taking such declarations with a grain of salt.
The awesome part of paid search is that you can measure ALL of these metrics at the same time. The slight downside is that you have to choose what’s most important to your brand, which can be harder for some to pin down than others.
Paid search ads almost certainly have an impact on brand awareness and recall, though those effects can be hard to measure. Thus, it makes sense to take into account metrics like impression share to see how visible ads are for particular keywords.
At the same time, impressions don’t directly put money in the bank, and focusing on metrics like return on ad spend and cost per new customer acquisition can better ensure brands are getting enough out of their spend to justify the expense.
In the big scheme of things, brands should keep track of all of these metrics (as well as others, such as conversion rate, average order value and more) but optimize toward those that prove the real value of search.
The post What your paid search KPI says about you appeared first on Search Engine Land.
Bing is rolling Merchant Promotions out of pilot in the US, giving advertisers a way to highlight offers in their product ads.
When Merchant Promotions are active, ads can appear with a “Special Offer” extension. When users click on the notice, the offer pops up with a description, promotional code, expiration date and a link to shop the product.
Sellers need to fill out a form to apply for Merchant Promotions. Bing Ads says the approval process takes three to four business days.
Once approved, you’ll see a new Promotions tab in your Bing Ads Merchant Center account. You can set up promotions in the UI (shown below) or with a promotion feed.
To get reporting details on Merchant Promotions, select Click Type ID and Total Clicks on Ad Elements in the product partition and product dimension reports in Bing Ads.
For more details, see the blog post announcing the rollout.
The post Bing Ads rolls out Merchant Promotions for Shopping campaigns in US appeared first on Search Engine Land.
Paid search advertising accounted for roughly $35 billion in 2016, split almost evenly between the desktop and mobile. That’s according to the IAB’s 2016 revenue report, released yesterday.
On a percentage basis, desktop paid search declined by 10 points and was down by a little under $3 billion in real dollars. However, overall paid search revenues were up vs. a year ago by almost $6 billion.
Mobile ad spending surpassed spending on the desktop for the first time, and represented 51 percent of digital ad spending in the US; in Q4 2016 it was 53 percent.
Total digital ad spending was $72.5 billion in 2016, up 22 percent from 2015. Mobile was responsible for growth across all digital formats: search, display, video, social and so on. Overall, mobile spending (across formats) came in just under $37 billion in 2016.
Growth of mobile ad spending in the US
Read a more complete breakdown of the IAB report on Marketing Land.
The post IAB: Paid search was 48 percent of total digital spend in 2016 appeared first on Search Engine Land.
Advertisers have begun receiving claim notice emails related to a $22.5 million settlement in a class action suit against Google.
The case, Google AdWords Litigation, Case No. 5:08-cv-03369-EJD, in the US District Court for the Northern District of California, stems from a 2008 claim that Google did not disclose that it placed ads on parked domains and error pages in violation of California’s unfair competition and false advertising laws.
The advertisers sought restitution for the difference between what they paid per click versus what they would have paid had they known their ads were appearing on low-quality pages that typically sent low-quality traffic. Google has consistently denied the allegations that it didn’t provide proper disclosure of where ads might show and maintains advertisers should have been aware.
The parties agreed to the settlement in February, ending the years-long dispute as the case wound through the courts.
This week, many advertisers — the class comprises about 2.3 million members, according to the settlement — received the email below, with instructions on how to file a claim. US-based advertisers that were charged for AdWords clicks on parked domains or error pages between July 11, 2004, and March 31, 2008, may qualify for a portion of the settlement. Potential payouts will depend on how much an advertiser spent and how many claims are filed.
In the fall of 2007, Google began testing a way for advertisers to opt out of having ads showing on parked domains and error pages. That option eventually rolled out globally in March 2008 and remains active today.
A Final Fairness Hearing is scheduled for July 27, 2017, at 9:00 a.m. PT in the Northern California District Court in San Jose.
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Ever feel like AdWords is one giant juggling act? You cut your cost per click, only to watch your conversion rate drop. You increase lead volume, but those leads don’t turn into sales. You finally boost sales, but now your cost per click is unprofitably high…
When does the madness stop?
With all of these apparently conflicting priorities, it can be easy to drop the ball a few times. Or, worse still, you might feel like AdWords isn’t worth the effort, throw your hands in the air and quit.
However, there is a way to juggle all of your marketing goals — a way to balance clicks, conversions, sales and return on investment (ROI).
The secret to this juggling act is… keyword tiering.
The idea behind “keyword tiering” (coining a new term here, I guess) is fairly simple: you categorize your AdWords keywords into different tiers based on the results they generate. Then, as your business needs change, all you have to do is turn tiers on and off to meet your goals.
So, if leads are more important than sales today, all you have to do is turn on a few more tiers. If profitability is more important than sales volume tomorrow, turn off a few tiers.
Once you have effective keyword tiers in place, you can instantly adapt to the needs of your company. It’s a straightforward way to match your AdWords advertising to your business goals. And the good news is, it’s fairly easy to implement:
As great as keyword tiering is, it does come with one caveat. In order to set up meaningful keyword tiers, you need to know which keywords are producing which results.
If you’re optimizing for leads, you need to be tracking leads. If you’re optimizing for sales, you need to be tracking sales. If you’re optimizing for ROI, you need to be tracking revenue. Depending on which metrics you’re tracking, that may mean you need to implement conversion tracking on your site or ensure that your CRM is tracking sales at the keyword level.
Unfortunately, only 29 percent of AdWords advertisers are even tracking conversions effectively enough to use keyword tiering. Far fewer are tracking sales and revenue at the keyword level.
If that describes your business, now is the time to fix things. A full description of how to track AdWords performance through to sales is beyond the scope of this article, but this article should help you get started.
Once you are tracking all of your relevant metrics and have keyword data for a couple of sales cycles, you can define your keyword tiers. How you define your tiers will depend on your specific business and marketing goals, but it’s often easiest to start with four basic tiers.
For example, if you are using AdWords to drive leads for your business, you might set up your tiers as follows:
Tier 1 keywords are your all-stars. They have a proven track record of producing profitable sales — in fact, there are very few reasons why you should ever turn these keywords off.
These keywords should always get budget priority and should never have their impressions limited by budget. If a Tier 1 keyword isn’t profitable above a certain average ad rank, it’s okay to lose impressions to ad rank, but never let these keywords lose impressions to budget limitations.
Remember, Tier 1 keywords are always profitable, so if you aren’t bidding on these keywords, you are losing money.
Your Tier 2 keywords aren’t quite as reliable as your Tier 1 keywords. They might deliver hit-and-miss leads or mildly profitable sales, but you can’t count on these keywords to always deliver.
There are a few different categories of keywords that can end up in Tier 2:
The good news is, you can often turn a Tier 2 keyword into a Tier 1 keyword with a little time and effort. But until that happens, keep your Tier 2 keywords in Tier 2 — no matter how much potential you see in them.
Tier 3 keywords are usually more bark than bite. These are the keywords that produce a lot of interesting results (like good lead volume or putting a product in a shopping cart), but that’s as far as things typically go.
As a result, these keywords have potential, but since you haven’t really figured out how to capitalize on that potential, they aren’t the first place you should be spending your advertising budget.
However, if your business is trying to grow and you’ve already maxed impressions for Tier 1 and Tier 2, Tier 3 can usually get you in front of a lot of potential customers. All you have to do is figure out how to turn that potential into actual revenue.
Sometimes, you simply need more clicks and conversions. Maybe you’ve got a sales team that is starting to lose momentum due to low lead volume. Maybe your business needs more sales to bring on potential investors — even if those sales aren’t particularly profitable.
Business is complex, and sometimes volume is more important than profitability.
Tier 4 keywords are a perfect fit for these sorts of situations. In general, Tier 4 keywords seem like a borderline lost cause (you’ve had lots of leads but no sales from these keywords). That doesn’t mean they can’t produce good results, but the odds aren’t in your favor.
In general, I prefer to leave Tier 4 keywords off most of the time, but it’s good to have them on hand for the occasional time when you really, really need to boost clicks and/or conversions.
Okay, so this isn’t technically a tier, but I wanted to point out that new keywords you are actively testing should not be grouped into your regular tiers. The whole point of your tests is to determine whether or not a new keyword is viable, so you can’t exactly assign new keywords into a tier until you’ve finished your test.
Of course, simply tiering your keywords in a spreadsheet somewhere doesn’t do your business a whole lot of good. To really use your tiers, you have to be able to sort your keywords in AdWords.
To do that, you need to label your keywords.
Hopefully, you’ve used labels before, but just in case this is new to you, let me show you how to label your keywords by tier. First, open your AdWords account and click on “Keywords.” Check all the boxes next to your Tier 1 keywords:
Then, click on “Labels” and check the box next to the tier you want to assign your keyword to.
If you haven’t created your tier labels yet, click “Create new” and do it now. Guess what? You just assigned all of your checked keywords to Tier 1!
Now all you have to do is repeat the same process for all of your other tiers (you can also label keywords using the AdWords editor if you want to speed things up a bit).
As a quick side note, to see which keyword is assigned to which tier, you’ll need to make sure you’ve added the “Labels” column to your Keywords report. To do that, click “Column,” click on the double arrow by “Labels,” and hit “Apply.”
Congratulations! You just set up keyword tiering! Not too bad, eh?
Now that you’ve set up your tiers, it’s time to take your AdWords juggling skills from this…
To this…
First, you’ll need to create and save a filter for each keyword tier. If you’re still on the Keywords tab, click “Filter” and “Create filter.”
Set the drop-down menus in the filter to “Labels” and “contains any.” Then, click on the last drop-down menu and choose Tier 1 (or whatever you named your tier).
Give your filter a name, make sure “Save filter” is checked, and click “Apply.”
You can now pull up all of your Tier 1 keywords simply by running your custom filter. Use this same process to create filters for your other tiers, and you should be good to go.
Now that you have your tiers set up, the next time your boss says, “We need to cut our AdWords budget by 50 percent this month,” all you have to do is run your Tier 3 and Tier 4 filters, check the box to select all, and click “Edit” and “Pause.”
In no time flat, you’ve cut ad spend to all of your poorly performing keywords. You might still have to make some adjustments to get to that 50 percent budget cut, but you know that you’re spending that limited budget where it matters most.
This tactic might seem fairly straightforward, but the ability to quickly maximize AdWords performance in any given situation can have a huge impact on your business.
Just to show you how this works in real life, here’s what happened when we set up keyword tiering for a lead gen client last year:
In just three months, their cost per conversion dropped by 62 percent. To make things even better, this benefit filtered through to their cost per sale and tripled the profitability of their AdWords account!
If you set it up right, keyword tiering can allow you to juggle priorities in your AdWords account with ease. As a result, your AdWords campaigns will perform better, and your life will be easier.
Talk about a double win!
So, if you’re sick of dropping the ball on AdWords, try setting up keyword tiering. You might not end up in Cirque du Soleil, but life will certainly be easier!
The post Keyword tiering: A systematic way to juggle your AdWords priorities appeared first on Search Engine Land.
