As Google has scaled up its Shopping products in recent years, there has been a growing consensus in the retail search marketing space that Shopping ads are one of the most effective ways to win valuable consumer clicks.
This is especially true of the non-branded, broader search terms that are typical of the early stages of the customer journey.
During this phase, Google Shopping ads – commonly referred to as Product Listing Ads, or PLAs – are considered to be a key means of engaging consumers early, and boosting new customer acquisition.
If the trends that we are currently seeing continue, 2018 will be a year of increased investment in Google Shopping ad formats across product-based search.
While text ads are still the most popular advertising format in many categories, retail-specific categories tell a very different story, with spend on Google Shopping ads far outstripping text ads in retail categories.
A new study by AI-powered search intelligence platform Adthena, analyzing 40 million search ads from more than 260,000 retailers, has shed light on the extent to which Google Shopping ads have come to dominate retail search marketing.
In this piece, we will look at some of the key findings from the report, explore the causes of Google Shopping’s phenomenal expansion, and consider what retailers can do to “future-proof” their search marketing strategy against upcoming shifts in the market.
Content produced in collaboration with Adthena.
The growth of Google Shopping
The Google Shopping ad unit has evolved considerably over the past few years, with increased attention and prominence afforded to Shopping ads in the search results page. This has resulted in a rise in clicks and impressions that has fueled the growth of Google Shopping ads in retail categories.
As of Q1 2018, Google Shopping ads are driving 76.4% of retail search ad spend in the US, and 82% of retail search ad spend in the UK – an overwhelming majority in both instances.
Adthena’s research found that in the US, this 76.4% of search spend was responsible for 85.3% of all clicks on AdWords or Google Shopping ads between January and February 2018. In the UK, the 82% of retail search ad spend invested in Google Shopping ads was responsible for 87.9% of clicks.
These figures confirm that Google Shopping ads are still offering good value to retailers in terms of spend/click ratio, and suggest that the value of Google Shopping ads has not (yet) reached saturation point, with room for growth in some key areas.
Mobile is one of these: according to Adthena’s research, although shopping ads on desktop generate a slightly greater share of clicks, Google Shopping ad spend on mobile now matches that of desktop, supporting evidence that mobile search is serving as a crucial touchpoint for product purchasing decisions.
Presently, Google Shopping ads on mobile are driving 79% of device ad spend in the US, and win 87.9% of clicks. With Google shifting more and more emphasis onto mobile search, this is likely to become an increasingly important area for retailers to invest in, and we may yet see these numbers grow further.
However, how much longer can Google Shopping continue its rise before the market eventually becomes saturated? To answer that, we need to understand what has fuelled Google Shopping’s dominance of the retail search market in the first place.
What is fueling Google Shopping’s retail dominance?
Ashley Fletcher, VP of Marketing at Adthena, believes that prominence and reach are the two key factors that have driven the rise of Google Shopping ads in retail search marketing.
Google’s introduction of a carousel for desktop Shopping ads in October 2016 was the first major change which gave increased prominence to Google Shopping ads. Since then, the ad unit has only developed further, with even more different formats for advertisers to benefit from.
“The unit has evolved both in terms of prominence on the page and in terms of ad features,” says Fletcher. “It’s also very rich in content – particularly on mobile – with multiple variants of the unit available to advertisers.”
In the US and the UK, the number of ads in the desktop carousel has even doubled as of February 2018 to surface 30 paid listings. This may go some way to explaining the particular dominance of Google Shopping ads in the US and UK – as we saw from the statistics in the previous section.
Then there’s reach: as Fletcher explains, in the past year, Google Shopping Ads have begun influencing users higher up the purchase funnel through far broader terms, appearing for much more generic product searches than before.
“In the last year, Shopping ads have started to trigger on a lot of the upper-funnel, generic terms – like “red dress”, or “black dress”. This is really driving users into a brand experience around those generics: it encourages the user to start drilling into those terms, and conduct longer-tail keyword searches off the back of that.
“These are very high-volume terms, keywords with a lot of traffic – so mastering that could be a challenge for search marketers, but you now need to be present at the top of that funnel, as well.”
While these developments have spurred a huge surge of growth in Google Shopping ads over the past two years, Fletcher believes this expansion won’t continue for long.
“In 2018, we’ll get closer to saturation point,” he says. “I don’t think there’s much room for further growth.
“Then I think we’ll get into the space we were in with text ads, where advertisers will be limited on spots, margins are going to be squeezed – meaning CPCs are going to increase – and it will come down to marginal gains: how can you optimize performance, as growth slows down?”
What can retailers do to get the most out of their ad spend in that environment?
“First and foremost, being able to manage at scale is a must-have,” says Fletcher.
“Secondly, master your categories. If you are a retailer, then knowing that you’re winning in – for example – men’s board shorts, and getting down to that level of knowledge with your categories, is essential.
“If you don’t do that, then you’ll have a very blinkered view of what’s going on.
“If you’re a department store retailer, for example, and your products reach more than 200 different categories, there is a dependency on knowing how well you’re performing in each of these categories. You’re going to have different competitors in each one: the challenge is knowing that, and making sure you are still winning there.”
Adapting for the future of search marketing
The rapid uptake of Google Shopping ads as the most significant part of retail ad spend budgets reveals how quickly search marketers adapt to new formats and opportunities.
As search advertising practices continue to change and new formats are introduced, advertisers will need to maintain this agility in order to keep ahead of the game.
“Google Shopping can be quite daunting for some advertisers when they take their first steps into it,” says Fletcher. “But if you do that with enough research, and enough context about what’s going on in each of your retail categories, you’ll have a far better chance of surviving.
“If you don’t follow the trends, adopt early, and understand these channels, you will get left behind.”
Amazon Shopping, for example, is a growing force in the retail search landscape which Fletcher believes will only play a bigger role in years to come, threatening to erode the dominance that Google Shopping currently enjoys.
Even as they take steps to future-proof their search marketing campaigns in the realm of Google Shopping, search marketers should investigate the opportunities presented by Amazon, in order to ensure the longevity of their search marketing strategy going forward.
The power behind search-based marketing has always been intent. Search engines like Google gave us the ability to put our ads in front of people at the exact moment they were searching a specific keyword. Because people were searching, we could safely assume they were ready to buy and it has worked beautifully for years.
However, over time a couple of problems started to crop up. First, with the success of pay-per-click (PPC) advertising we began to see lots and lots of competitors. Anyone could bid on a keyword and the auction-based nature of the platforms meant that average cost-per-click (CPC) continued to rise. Secondly, as Google became its own verb, people began searching for lots and lots of things. They wanted to find out the answer to trivia questions, learn details about upcoming events, get pictures of celebrities, etc. This watered down the intent. Someone searching for “King James” might want to learn about Lebron James or buy a Bible.
Get Past Keywords Keywords
Most new PPC advertisers focus heavily on keyword research and selection. They believe that if you pick the right keywords you’ll get clicks that you can turn in to sales. While I agree that you must choose the correct keywords, the attitude above forgets that each search has a unique intent. It further ignores the fact that search engine results pages offer numerous options to click.
With increased cost and competition, the key to success is less on what keywords you choose and more about what message you’re presenting, aka your ad copy. Ad copy influences who you get to click, how well qualified they are and how well prepared they are to respond to your product/service. So how do you write more compelling ad copy?
While economics assumes that all people behave rationally, marketers realize that people are complex mixtures of emotion and logic. Virtually every company I have worked with could explain logically why someone should use their product/service. These appeals usually center around cost, time savings and ease of use and can be quite effective. However, consider these alternatives:
- Lowest prices on product X
- Don’t overpay for product X, buy from us
Our first option is matter-of-fact and gets the message across, but the second option evokes fear. People don’t want to overpay (very negative emotional association) and you offer them relief from that fear. That’s how you get the click.
Here is a handy cheat sheet of emotion-loaded words that you can incorporate into your ad copy:
I recently attended a presentation about the use of pronouns in ad copy. Mark Irvine, of Wordstream, shared the 3 most effective pronouns to use in ad copy:
#3 – “We” sells a solution
#2 – “You” speaks directly to your audience
#1 – “Him/Her” connects with a relationship
Notice that all of these pronouns shift the focus away from you as the product/service provider. People stop thinking about cost or features and start thinking about how it benefits them or how it will benefit their significant other. See the results from Mark’s analysis. Spoiler alert: They dramatically increased CTR.
Always Be Testing
Over the years I’ve had a lot of really good ad copy ideas fail. I’m not too proud to admit it. Sometimes that bone-dry descriptive ad copy is exactly what your customers want. But many times I’ve seen significant improvement in performance by testing a “crazy” idea. What will work best for your customers?
I don’t know. Your marketing people might not know either. But the only way you’re going to find out if your current ad copy can be better is if you get out there and test it. Put 2-3 ads in all your AdWords ad groups and change the campaign setting to “Optimize indefinitely” (that forces Google to give all copies a fair chance, though it won’t guarantee equality of impressions). Let your customers tell you what they prefer and what they don’t prefer with their clicks and conversions.
Source: How To Write Compelling Ad Copy
Maybe you’ve heard of blockchain, but why should you care? Contributor Tony Edward describes the dramatic impact the technology could have on digital marketing and advertising.
If you’ve heard of Bitcoin then you most likely have heard of blockchain, the technology that enables Bitcoin and other cryptocurrencies to exist and function. The technology is forecast to disrupt many industries as it allows users to conduct transactions without a middleman in a secure and transparent format.
Some of the industries that can potentially be disrupted are car sales, voting, ridesharing, real estate, insurance, sports management, loyalty cards and gun tracking. While the search marketing industry is not as mainstream as the aforementioned industries, it can also be potentially disrupted by blockchain.
Now, before we go any further, this article is not about Bitcoin or other cryptocurrencies. However, if Bitcoin is adopted by large companies such as Amazon or Walmart, it will certainly have an impact on the future of payments between search marketing agencies, website owners, advertisers and others. Contract agreements will also be impacted, as the blockchain could be leveraged for more transparency and accuracy.
What is blockchain
Here is a great definition of blockchain offered by Don and Alex Tapscott, authors of a 2016 book called “Blockchain Revolution”:
The blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value.
Image courtesy of weforum.org
In layman’s terms, it’s like a Google Doc spreadsheet that is shared with the public which displays transactions and is tamperproof. Many are considering blockchain to be as impactful as the internet was in the ’90s.
Impact on search engine marketing (SEM)
In the digital marketing world, many central authorities, such as Google and Facebook, connect advertisers with website owners. For example, Google is a central authority in programmatic ads, where it helps advertisers run ads on websites via the Google Display Network. Google essentially is the middleman that helps advertisers and website owners trust each other. If they already trusted each other, they would not need Google as an intermediary taking a cut of the profits.
Enter blockchain, which can verify that every user is genuine with 100 percent accuracy and that the website owner is only charging the advertiser for genuine clicks through to their site. Then the website owner and the advertiser don’t need a middleman to arbitrate their agreement, which would save them both money. Blockchain presents a big threat to Google’s display network revenue.
Blockchain being the unhackable distributed ledger is going to also help reduce online fraud. It will provide transparency for persons involved in a transaction without giving away their personal details, essentially proving they are a real person. Ad fraud is a big problem: It cost advertisers over $7 billion in 2016. A number of players — including Microsoft, the Interactive Advertising Bureau (IAB) and DMA (in partnership with MetaX) — are already working on blockchain-based digital identification systems.
Impact on search engine optimization (SEO)
As companies start to adopt blockchain, they will need to integrate it within their websites. This involves the web developers as well as the SEOs, if they are trying to gain organic search benefits as well as display the information from the blockchain transactions.
This will present both technical issues and opportunities in which SEOs will have to work alongside developers to resolve compatibility issues with different content management systems and website platforms. I have noticed that the Schema community has already started to work on Schema Markup for blockchain certificates and user ID profiles. Both items are a work in progress and have not yet been published on Schema.org.
Here is a glimpse of what the codes for both items looks like.
The following sample markup (from our company) is in JSON-LD format. Full details can be viewed on GitHub.
Blockchain user ID profiles
As new blockchains are developed and it is more widely adopted, it will certainly disrupt the search marketing industry in many other ways. For now, search marketers should pay close attention to blockchain as it grows.
For local businesses, having a strong presence in the local search results is fundamental to those all-important conversions.
Just to be clear, a “local business” refers to any business that has either a physical location that offers face-to-face contact with the customer, such as a showroom or shop, or one that offers a face-to-face service within a certain area.
When it comes to local search, it’s simple: if searchers can’t find you on the web, then frankly, you don’t exist. It’s the way of the modern world.
It’s all very well dominating the SERPs for your more general target keywords, but if you fail to rank highly for location-specific terms then you are missing an almighty opportunity.
When users are searching for a local term, they are far more likely to be looking for a service or product. Hence why the conversions on local search tend to be higher, and why you need to ensure that your local search engine marketing is up to scratch.
Those fundamentals will set you up for ranking well for local search terms, but there are extra steps you must take to differentiate yourself from the competition and really bolster your local SEM strategy.
Local business listings
The first place to start is with local business listings. Ensure that your business is included in all the major directories (Yell, Yelp, Thomson Local, etc.), as well as any industry specific ones. Some listings may already exist, and it may just be a case of claiming your business so that you can take ownership of the listing.
We recommend keeping track of all your business listings in one comprehensive spreadsheet to save you repeating or forgetting any entries. It also enables you to be consistent (more on this in the next point) in your information across all listings.
Remove all duplicated entries, as multiple listings for one business or location can become confusing, both to potential customers but also to Google. And we certainly don’t want to be confusing the Big G.
Be thorough but don’t be reckless. Avoid spammy directories as these could have a detrimental effect on your SEO. Deploy a spot of common sense to identify the spammy directories but if you are really unsure then it’s worth checking the spam score via Moz’s Open Site Explorer or via other similar tools.
So this technically falls under business listings, but it’s so important we’ve given Google My Business it’s own subheading. Arguably the most important business listing because, well, it’s Google. Remember to implement the following:
- Claim your business via a verification process
- Include accurate information: contact details, location and opening hours
- Carefully select a small number of highly relevant categories to represent your business
- Ensure up-to-date branding, such as in any images of logos or premises
- Use high quality images to represent the business
Be comprehensive and accurate in the information you provide in order to strengthen your Google My Business profile and improve your chances of being featured in Google’s three-pack.
NAP consistency sounds a like a fancy term but the concept is very simple. NAP stands for Name, Address and Phone number, although it is sometimes expanded to NAP+W to include website address too. As mentioned above, it is crucial that your business information appears consistently across the web.
This is particularly important to consider if your business has changed address, contact details or even rebranded. Any mentions of your business will need to be checked and updated to ensure accuracy.
Simply google your business name (do the same with your previous business name if you have undergone a name change) and work your way through the listings. Maintain a spreadsheet of your progress so you can keep track.
Reviews can bring both utter joy and absolute misery to any business owner. Unfortunately you cannot simply ignore them, as reviews are indeed used as ranking signals in the eyes of the search engine. This is especially true for your Google My Business reviews.
Not only are reviews important in terms of local rankings, they are also key in terms of click-through rates. According to a recent study by BrightLocal, 74 per cent of consumers say that positive reviews make them trust a local business more.
Apart from providing the most incredible customer service you can muster, how else can you seize some control over your reviews? No, this isn’t about getting your mum, brother and great-nan to write a review for your business. It’s about a bit of gentle encouragement and managing a bad customer experience before it reaches the review stage.
It is also important to check the rules and regulations of each review platform, as they all have very different policies on asking customers for reviews and responding to them.
We’ve had several clients who have received a negative one-off, anonymous review that is either quite clearly spam, or in some cases, a bitter competitor or personal enemy. These situations can get a bit sticky, but sadly there isn’t an awful lot you can do.
Generally people won’t be deterred by one bad review, and the best course of action is to encourage other happy customers to get reviewing. This will push the bad review down and push the average star rating back up.
Many review platforms allow you to reply to reviews. This can be a good opportunity to set the record straight but you have to be careful about it. For this reason, sometimes it is best to get someone who is not as emotionally invested in the business to either write the response or edit it before it gets published. Be professional, remain calm, and kill them with kindness.
If you don’t already have location pages on your website, then you could be missing a valuable opportunity to target all the relevant locations. For each key location that your business operates within, create a page dedicated to that location on your website. This is easier if you have a unique physical address in each location, as it is important to include as much location-specific information as possible.
Where there is a physical location, be sure to include an interactive map and images to further enhance the page. If you do not have separate physical addresses, try including testimonials and case studies relevant to each location.
This will help you to avoid duplicating content across your location pages; it’s a fine art to differentiate the copy, but do it right and it can have seriously good effects on your local SEM strategy.
Once you have your location pages set up, the cherry on the cake is schema markup. The whole concept of structured data can sound very daunting to markup newbies, but it’s easier than it sounds. Schema markup simply helps search engines to understand what your website is about.
This is particularly important for local information, as it will help those spiders crawl your location pages and you’ll benefit as a result.
According to a study by Searchmetrics, pages with schema markup rank an average of four positions higher in search results. Now that’s a pretty good incentive. Get your head around schema markup and you’ll have that crucial advantage over your competitors in the local search results.
Ensuring your local search marketing strategy is up to scratch needn’t be difficult or convoluted. Follow the above steps and obey the usual SEO rules. With some hard work and perseverance, you’ll start dominating those coveted top spots and see your conversions skyrocket in no time.
Learn how machine learning and automation are empowering search marketers today and how it can tackle digital marketing’s data problems.
Advertising has changed a lot over the years.
There was a time when machine learning, automation, and software-based marketing tech stacks weren’t a “thing.”
But now we’re past the days of just radio, outdoor, print, and a handful of channels on TV.
There are hundreds of channels across physical and print media and online at present, including social, mobile, and video. Even TV has diversified into hundreds of cable channels on your remote control. And yet, digital ad revenue has gone on to surpass that of TV.
The dominance of digital is nothing new. Paid search marketing is becoming more data-focused than ever before.
In fact, if you check the folders on your computer, I’m guessing some of you will find a few million-row spreadsheets full of cost-per-click bids, conversion rates, and return-on-ad-spend figures – along with countless other metrics for however many thousands, or millions, of keywords you manage.
So, What Do You Do with Big Data?
Because paid search is so reliant on big data – really big data, the kind that causes Excel spreadsheets to eventually crash for having too many rows – it’s my belief that the future of digital is inextricably tied to machine learning.
Is it because machine learning, automation, and software will completely replace savvy digital professionals and their creative ideas?
No. Far from it.
I believe that the future of digital will be a combination of smart marketers – like yourself – empowered by smart automation based on machine learning. As it happens, in a survey we recently ran on the subject, 97 percent of top digital marketing influencers (including speakers from AWeber, Oracle, and VentureBeat) agreed.
What Is Machine Learning & Why Is It Important?
Machine learning is the smart automation that can parse those million-row spreadsheets and pull valuable insights out of those mountains of data.
(To clarify, processing data to pull insights is something machine learning can help with… but actually taking those insights and doing things that are creative and smart with them? That’s still very much the domain of brilliant marketers like yourself, and why the ingenuity you bring to the table will continue to be so important when facing tomorrow’s digital challenges.)
As for why machine learning is important? For starters, digital advertising has a data problem. In addition, the face of marketing is changing due to the way your customers are becoming aware of, considering and purchasing your goods and services.
Digital’s Data Problem in Three Parts
Data is a challenge in modern marketing. There’s significantly more of it than there used to be, and as marketing technology matures, it becomes capable of collecting even more on top of that.
Data overload is a known problem. There’s too much of it – an overwhelming abundance of it already.
Yet Oracle points out that digital data growth is expected to increase globally by 4,300 percent by 2020. This problem isn’t going away anytime soon.
Despite the collection of data increasing exponentially, there’s a lack of centralized ownership with big data. You and your colleagues may be collecting CPC, CTR and CVR data in spreadsheets, but is everything centralized and standardized in a way that everyone in your organization can pull the data when they need?
Veritas reports that 52 percent of all business data is “dark” (of dubious or completely unknown value), and projects that mismanaged data will cost businesses $3.3 trillion by 2020.
There’s also a problem with siloing. Most businesses collect data in different buckets that aren’t necessarily integrated directly with each other, or indeed, with their own in-house marketing tech stack.
Accenture reports that while three-quarters of all digital skills gaps (the gap between a team member’s current level knowledge and the level of knowledge they need to successfully use new tech and tactics) come from lack of ownership, the remaining 25 percent of digital skills gaps come from a lack of integration.
And Then There’s the Changing Customer Journey
In addition to changes in the way data is collected and used in digital advertising, customer behavior is changing.
Advertising isn’t limited to a handful of channels. There are literally thousands of ways to reach customers, and pretty much all of them can be easily tuned out by an audience of increasingly demanding and disaffected customers who expect to have exactly what they’re looking for delivered to them instantly (and who will react poorly when it isn’t).
Research firm McKinsey breaks down the all-important consideration stage of the buying journey into four parts: “initial consideration; active evaluation, or the process of researching potential purchases; closure, when consumers buy brands; and postpurchase, when consumers experience them.”
The firm also finds that two-thirds of the touchpoints in the crucial evaluation stage are customer-driven, including browsing online reviews or soliciting word-of-mouth recommendations.
More to the point for those of us in digital, the use of ad blockers has increased 30 percent in the past year. And as you’ve surely heard, Google itself will be building in an “ad filter” in a 2018 version of Chrome to filter out “irrelevant” and “annoying” ads.
Effectively, as time passes, your ads are at greater risk of being filtered out by users who aren’t buying what you’re selling at this exact point in time.
How Does Machine Learning Solve These Problems?
Machine learning can be used to rein in the challenge of data, particularly when combined with disciplines such as probability-based Bayesian statistics, regression modeling, and data science. One of its greatest strengths here is the ability to take data-driven insights and build predictive models.
These predictive models can, in turn, be used to proactively address points of peak buying interest, attrition, or other key moments observed in the customer buying journey.
Examples of Machine Learning in Action
Let’s look at some examples of the way this technology is being used.
Chatbots & Voice Assistants
You may have noticed an increase in the use of conversational interfaces from major publishers such as Google, Amazon, Microsoft, Apple and Facebook in the form of chatbots and voice assistants (Alexa, Google Assistant, Siri and Cortana among others).
TOPBOTS notes that chatbots can have uses in unique, consumer-based contexts, such as event ticketing, health-related questions and the ever-important sports scores. These interfaces create a relevant and engaging user experience by supplying conversational responses based on historically-collected data – the most commonly-used or highly-searched terms.
Predicting & Preventing Customer Churn
A significantly deeper-funnel strategy at the post-purchase stage is to use machine learning to forecast common points of customer attrition.
Microsoft Azure and Urban Airship have both built predictive analytics models to determine the approximate timeframes and buying stages at which customers tend to most frequently churn. By projecting these important points in the future, these businesses are then able to proactively address common complaints before customers churn, driving higher retention and ultimately strengthening their businesses.
Natural Language Processing (NLP) and Semantic Distance Modeling
Another method of using machine learning specifically for digital advertising is to predict accurate bidding models for low-data keywords, such as long-tail keywords with high purchase intent but little to no empirical data.
In these cases, machine learning-based digital advertising solutions can assign new keyword groups based on semantically similar keyword groups and help advertisers ramp up long-tail keyword groups and all-new ad groups with a minimum of expensive testing time.
Machine learning isn’t necessarily a threat to marketers. On the contrary, it’s a powerful ally that’s making marketers’ lives easier while empowering them to predictively engage their customers in a highly relevant way.
Now, more than ever, it’s important to deliver the right message to the right customer at the right time – and with the power of machine learning, marketers are able to more accurately accomplish this goal by relying on actual data, rather than guesswork.