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As a PPC advertiser, you may know by now that in September, Google announced that it planned to further expand the broadening of exact match keywords to make them, well, not so exact.
As its name once suggested, Google exact match keywords triggered ads that matched the exact keyword search. The function essentially hindered or prevented an ad from being served altogether if it didn’t perfectly match the keywords in the specified order of your choosing. While stringent, and perhaps even limiting, it also gave advertisers complete control over the terms for which their ads appeared.
Google’s recent announcement upends those previous parameters. Powered by machine learning, Google's update may also trigger ads for searches with close variations -- ones that match the keyword intent or that otherwise have the same meaning as the specific keyword, including the same keywords in any order.
"This means your exact match keywords can show ads on searches that include implied words, paraphrases, and other terms with the same meaning," Google said in its help docs.
Granted, “exact match’ might now be a bit of a misnomer. But think of it this way: If you’re marketing for a hospitality industry business and using the exact match keywords “San Diego luxury beach hotels,” your ads might show on terms such as “luxury beach hotels in San Diego” or “San Diego luxury hotels near beaches.” The list goes on, but you get the idea. Even if it isn’t an exact match, the new Google update now takes into consideration a multitude of new words that fall under the umbrella of “implied words, paraphrases, and other terms with the same meaning.” Subsequently, your ads would appear because all of the search terms contain the same basic intent as the original keyword. What wouldn’t necessarily trigger ads are terms like “best San Diego hotel” or “four-star San Diego hotels,” simply because the intent is slightly different.
Google says that the impetus for its latest development is largely attributed to the constantly changing ways that people search, noting that new searches comprised “roughly 15%” of the total they see every day. And that’s a lot.
Google’s latest keyword expansion follows a 2014 update to its platform that included plurals and misspellings as ‘close variants’ to phrase and exact match keywords. But the biggest difference between the two is that plurals and misspellings are generally easy to determine and course correct. Intent, on the other hand, can incorporate broad definitions that are often open to interpretation, indicating that advertisers should closely monitor how this will impact their campaigns, both in the short and long term.
Of course, the same “intent” might not translate to the same value for your campaigns. What’s more, even slight variations between keywords can result in significant disparities in conversions, which in turn could have a dramatic impact on your PPC strategy over time.
That said, thus far there doesn’t appear to be major performance fluctuations at a macro level, but the industry is seeing changes at the keyword level, as those with more history, higher click volume, and quality score are receiving more impressions. For example, one ad group is now seeing the exact match of “flu treatment” triggering ads more often than the exact match of “treatment for the flu.” While the overall performance from cases like these hasn't changed much, CPCs have increased slightly in some.
Also, one potential drawback as a result of the change is that some advertisers are splitting one campaign into three or four different campaigns in order to target specific match types. That, in turn, causes complications for bid automation if those campaigns don’t generate enough conversions to use automated bidding.
It also might mean some extra legwork on your part to beef up negative keyword lists. While there are an exponentially greater number of relevant keyword combination possibilities, there are perhaps just as many, if not more, keywords and keyword combinations that wouldn’t be a fit or that wouldn’t target the right audiences. For advertisers, that will inevitably require valuable time, resources, and personnel that could otherwise be spent elsewhere. On the other hand, it might eliminate the need for you to separate exact and phrase match keywords (allowing you to recoup some of the time you lost adding to the negative keywords list).
But for digital advertisers, results from the expanded Google exact match keyword update are thus far positive. For one, it provides a wider array of close variants to what would have been pure exact match terms, of which 99 percent have been relevant. That means that you have more keyword possibilities, along with a slew of new opportunities available to you that you otherwise would have missed because a phrase wasn’t ‘just so.’ Also, with the exponential number of new queries and search terms that are continuously emerging and being used, it’s likely that consumers are looking for your products with terms you haven’t even considered.
Ultimately, time will determine whether Google’s latest experiment will have a significant impact on digital advertisers. But opening new keyword possibilities has a strong potential to open new doors that lead to new audiences, higher ROI, and yet untapped revenue that will ensure that your campaigns remain on an upward, and profitable, trajectory.
The advertising industry has made huge strides in attempting to understand the mind of the consumer and potential buyer. But it hasn't been able to predict the future - that is, until now. With the emergence and proliferation of predictive advertising technologies that predict consumer behavior before it actually occurs, that future may well be here.
It's well established that predictive analytics has dramatically changed the digital marketing landscape in recent years, and it’s only continuing to grow and evolve. According to a recent report, the global predictive analytics market is set to reach $10.95 billion by 2022. Predictive analytics has a variety of applications in marketing. But for digital marketers, the most valuable application will be predictive advertising.
As a subset of predictive analytics, predictive advertising is leveraged by businesses to analyze data from consumer behavior, which then uses these insights to predict future trends and optimize marketing and sales strategies.
Perhaps most importantly, predictive advertising can help you identify members of your audience that are likely to convert while automatically prioritizing leads, made possible by leveraging advanced statistical modeling and machine learning. Specifically, machine learning looks at historical data patterns and derives insights from these patterns in order to make informed changes to advertising strategies. And there are a number of benefits to using machine learning, including:
What’s more, machine learning makes it possible to achieve these goals with more speed and accuracy than an entire team of data scientists.
Artificial intelligence is a powerful technology that makes predictive advertising possible. But another key element is the wealth of consumer data available today. The growth of Internet of Things (IoT) devices is presenting a myriad of opportunities for data collection and analysis. And it’s no secret that the average consumer today leaves a massive digital footprint, which is only continuing to grow. Thus, predictive advertising strategically leverages this data to drive a plethora of consumer insights, including:
Without a doubt, the wealth of data available today enables marketers to better understand the intentions, preferences, and buying patterns of individual members of their audiences, while also making it possible to better track the nuances of the market they’re advertising in. That said, this data is only valuable if advertisers find ways to successfully unlock it. Conversely, the abundance of data can easily overwhelm marketing teams with too many relevant touchpoints to analyze, creating significant gaps and a host of missed opportunities.
Now enter predictive advertising, which can use your internal audience data as well as third-party behavioral data to identify new potential customers to target and enable you to broaden your audience base further than you would if you simply relied on regular targeting tactics.
Predictive advertising can draw correlations between demographic and behavioral factors that regular marketing analytics simply wouldn’t be able to make. Leveraged in tools like Google’s Lookalike Audience and Facebook Similar Audiences these technologies provide the ability to draw correlations between different demographic and behavioral data to identify new relevant audiences to target. For example, say predictive analysis helps you discover that members of your current customer base are likely to read a certain online publication. From there, you could then start targeting other people who also read that publication.
Most marketers today who use data to drive targeting insights rely on their own first-party behavioral data: metrics like site pages visited, lead magnets downloaded, and abandoned carts. But first-party data only tells you so much about your audience’s needs and intent to purchase. When you add in behavioral touchpoints from other sites, you get a much richer picture of a lead’s intent, which in turn makes it possible to reach leads with relevant marketing messages deep in the sales funnel, as well as improve retargeting capabilities for display ad campaigns.
The better businesses understand their audiences, the easier it is for them to create relevant, targeted ad copy that converts. Combining first and third-party audience data allows you to build more robust buyer personas to inform your marketing collateral. But can these creative changes be automated and implemented at scale? The answer is yes, but with the help of machine learning. Machine learning can drive predictive insights and in turn help you make smart choices to improve advertising copy and ad design. While machines aren’t replacing real creatives, they can help optimize marketing collateral to become more effective and relevant to target audiences.
Predictive advertising already allows you to automate ad personalization based on a variety of behavioral, demographic, and situational factors such as device ID, domain, location, purchase history, or interests, and trigger that data to reach relevant audience members. Predictive advertising insights can also inform the right kind of copy to include in dynamic PPC ads. And we’re only just beginning to realize the possibilities for its potential to unlock new, unique and valuable customer demographic insights.
According to data from Nielsen Digital Ad Ratings service, billions of online marketing dollars are being wasted in advertising -- largely because ads are reaching the wrong audiences, reaching the right audiences at the wrong time, or businesses are simply spending more than necessary to achieve their marketing goals.
On the other hand, businesses that focus on minimizing wasted ad spend get the double benefit of being able to channel their saved budget into other marketing initiatives. Predictive advertising can help with this by executing nuanced targeting and bid adjustments in real-time to drive more ROI. A good example is Google’s automated bidding platform, which allows advertisers to choose a goal (site visits, visibility, conversions, etc.) and then leverages audience data from its advertising network as well as competitor performance data to automatically adjust bids in real time.
But targeting capabilities become even more nuanced and effective when using third-party predictive advertising technologies. Because now you’re free to use any kind of relevant third-party data you want, so you can rely on site visits, social media engagements, your PPC campaign data and other variables to drive even deeper insights. And instead of relying on the one-dimensional goal options of Google’s automated bidding, you can customize the key performance indicators (KPIs) you want to target.
Thanks to smartphones and on-demand information, it’s become increasingly difficult for advertisers to target audiences at some of the most critical and relevant times. For many purchase decisions, it’s possible for people to show intent and convert into a buyer mere minutes later. By the time they see advertisements for the product they’re looking for, it’s already too late.
Google calls these micro-moments: An intent-rich moment when a person turns to a device to act on a need — to know, go, do, or buy. There are four key micro-moments that advertisers can target to help their audiences convert:
Not surprisingly, targeting ads to consumer micro-moments is incredibly valuable for businesses because consumers are determined to find what they’re looking for, and will be interested in brands that help them achieve that goal.
But successfully targeting ads to micro-moments is essentially impossible without using some kind of automation. While PPC advertisers can use Google’s in-market audiences to determine who is searching for certain categories of products and automatically target them with relevant advertising, predictive advertising can take this goal to the next level by helping you anticipate customer needs before they start showing strong signs of purchase intent. Using historical data of consumer online behavior and demographic information, predictive advertising can anticipate what kind of people could be interested in your products and services before they start the buying journey. In essence, it’s possible to start targeting these micro-moments before they even occur.
Of course, there are some kinds of micro-moments advertisers can’t anticipate in advance. Someone’s car breaks down on the side of the road and now they’re looking for auto repair services. Or someone’s relative passed away and now they need funeral home services. How can advertisers target these new “interests” when they come up so suddenly?
Predictive advertising technologies can handle the challenge because they analyze massive amounts of data in real time. Machine learning can infer intent from search queries, location, and other factors, then automatically serve relevant ads. What’s more, this is all done in the background, giving marketing managers the freedom to pursue other media-buying opportunities.
Predictive advertising is a relatively new application of predictive analytics. For most marketers, it might sound like a luxury only the most competitive enterprise businesses can afford to fully utilize. And that likely won’t change as long as adoption of the technology remains low. In the future, however, it will likely be essential for a wide range of businesses. Consider:
The competition
Over time more businesses will adopt automation and predictive advertising to optimize their campaigns. Taking advantage of the same technologies to improve campaign performance will become the only way to keep up with the competition, let alone stay ahead.
The savings
Arguing that predictive advertising is “too expensive” to fit budgets will be difficult as the technology continues to demonstrate value for businesses. Predictive advertising can identify minute bidding inefficiencies that can add up to a significant reduction in unnecessary ad spend. Not taking advantage of the technology can end up costing you money instead of saving it.
Budget reallocation opportunities
Predictive advertising helps advertisers ensure they only spend the minimum amount necessary to reach their marketing goals. That means more of your advertising budget can be redistributed to other initiatives that maximize ROAS. This is particularly important considering that for every $1 spent on Google Ads, businesses can earn $2 of revenue. Predictive advertising helps make sure each dollar of your budget is well spent.
Efficiency
Predictive advertising can automate a wide range of campaign optimization tasks that would otherwise need to be done by advertising managers and their teams. Rather than replacing their jobs, AI and machine learning can help free team members to focus on other marketing initiatives, such as discovering new media buying opportunities to drive growth.
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Google Ads and other major advertising options are already making big changes to incorporate AI and machine learning into their platforms. And a wide variety of external tools, with more advanced targeting, data analysis, and optimization features, are also available. Given the enormous benefits, value and competitive edge predictive advertising brings, it’s simply a matter of time before all advertising becomes predictive. And tools like machine learning paired with advanced statistical analytics can help businesses of every size improve the relevancy, efficiency and ROI of their advertising campaigns.
The future is being able to predict the future. And with predictive advertising, we’re one step closer to that reality.
As a marketer, you have access to a popular search platform with desirable and high quality target demographics, accelerating growth rate and profitable long-tail search opportunities. No, we’re not talking about Google — we’re talking about Bing. It may be surprising, but Bing is a hugely overlooked opportunity for search engine marketers today. While Google has always held the lion’s share of the search market, Bing PPC opportunities continue to grow every year. The Bing platform processes more than 15 billion searches monthly, and boasted 142 million unique searchers in 2017.
So for advertisers who only focus on Google, failing to create a Bing PPC strategy represents a lot of missed opportunities.
Meanwhile, the demographic makeup of Bing users is also unique, providing a slew of compelling reasons for advertisers to place their PPC ad money there. Consider:
In short, Bing is a great platform to target bottom-of-the-funnel online shoppers who are willing to spend more than the average searcher.
Another major benefit of using Bing for SEM is lower competition. Fewer advertisers have Bing PPC strategies, making it easier to gain access to higher ad positions at a more affordable rate than with Google Ads.
So, if you’re ready to start incorporating Bing PPC into your search engine marketing mix, here are seven important secrets for success.
Back when Bing was in its infancy, Microsoft wanted to build a search and advertising experience that was vastly different than Google’s. Over time they came to the conclusion that making the platform dramatically different from Google's wasn’t the right way to compete with the search giant, so they changed their strategy. Now Bing and Google advertising are so similar, it’s possible to easily transfer your Google ad accounts to Bing using account syncing.
While importing is quite simple, there are a few key differences between Bing and Google advertising to keep in mind. Once you transfer accounts, you may want to make some changes to your campaigns to optimize on Bing’s platform.
Some of the key differences include:
Bing treats negative keywords differently
Both Bing and Google Ads allow you to include negative keywords at both the ad group and campaign levels. However, unlike Google Ads, Bing will not negate any keywords that are included as one of your target keywords. With Bing, you can still show ads for negative keywords that appear in a target keyword phrase. Google Ads, on the other hand, automatically blocks searches related to that negative keyword even if they’re relevant to your campaign. What’s more, if you have broad match negatives in your Google Ads account, Bing considers them phrase match when you transfer over.
Automated rules do not transfer
If your Google Ads campaigns include automated rules, you’ll need to recreate them after transferring your accounts to Bing as they won’t automatically transfer.
Create a Bing Merchant Center store for shopping campaigns
If you have Shopping campaigns, you’ll need to create a Bing Merchant Center store before importing from Google Ads to Bing Ads. The system will prompt you to link the campaign to your store before you can import it.
Bing’s language and location targeting differ
If you’re targeting more than one language with your Google Ads campaigns, it’s important to know that Bing doesn’t support as many languages as Google. If you import an account targeting languages that Bing doesn’t support, it will default to the parent language.
With Google Ads, it’s also possible to target more than one language within a campaign; Bing only allows you to target one language. So when you import multi-language-targeted accounts, Bing will select the highest ranked supported language and you’ll need to create new campaigns to target secondary languages. It’s also important to know that you cannot change your language or location targeting once you save a campaign.
Just because Bing makes it easy to sync with Google on its platform doesn’t mean they should always mirror each other. Optimizations you make to improve your Google Ads campaigns might not be relevant to your Bing audience. Or there might be a better way to optimize those campaigns. Bing has a unique audience — in fact, 27% of Bing clicks come from searches that are exclusive to the Bing Network.
So use account syncing initially to copy over your Google Ads campaigns. Then utilize Bing’s internal tools, analytics, and insights to drive unique optimization decisions. Using Bing’s analytics features or even its third-party bid management tools can help you discover optimization opportunities unique to the Bing PPC network and its audience.
Doing another set of analyses for a second search network is time-consuming, which makes it difficult to scale. But there are plenty of available automation technologies that can help you optimize both your Google and Bing PPC strategies by using unique datasets that require no extra time or effort for advertisers.
In mid November, Bing Ads fully rolled out the Competition Tab — a new analytics feature offering important insights and recommendations — that includes two sections: Audience Insights and Recommendations. Audience Insights allows you to see how your impression share is performing against the competition, incorporating important metrics like overlap rate, average position, position above rate, top of page rate, and outranking share.
Search advertisers can use these insights to understand what changes they can make to improve their ad performance against competitors. The Recommendations section can also help do this for you, using machine learning to suggest changes to improve performance, such as optimizing campaign device targets, location targets, and expanded keyword targeting among others.
About a year ago, Bing launched its own dynamic search ads similar to Google’s. In case you aren’t familiar with the technology, dynamic search ads automatically target relevant search queries based on your web content. Instead of creating your own ads one-by-one, Bing creates targeted and relevant ads for you by scanning your site content. Dynamic search ads are a great opportunity for businesses whose site content changes frequently due to the fact that there’s no need to create new and customized ad titles every time you have a new sale or special offer.
Bing’s dynamic search ads also save time, as you don’t need to maintain keyword lists or manage your own bids. And by streamlining your processes, dynamic search ads can also help you discover opportunities you might have overlooked to drive conversions.
Bing's search ads have some unique offerings that allow you to make better-targeted ads. Google Ads enables you to target a specific keyword, while Bing Ads sets extra parameters for reaching audiences by providing more specific information related to their search query.
Like Google Ads, Bing recently developed automated bidding strategies. By utilizing search patterns analysis, clicks, and conversions, Bing can automatically optimize your bids while simultaneously respecting your budget limit.
There are four main ways Bing can manage your bids for you:
1. Enhanced CPC
Enhanced CPC (cost per click) is the default bid strategy for all campaigns. It adjusts bids in real-time, increasing them on searches that are more likely to convert and decreasing them on searches that are less likely to convert. Enhanced CPC can increase your total number of conversions while reducing cost and staying within your budget limitations.
2. Maximize Clicks
Maximize clicks is available for search ad and Dynamic Search Ad campaigns. The goal of this strategy is to get as many clicks as possible within your budget. If you want to have greater control of your budgets, you can also set a maximum CPC to ensure Bing never pays more than a certain amount per click.
3. Maximize Conversions
Maximize Conversions is available for search ad campaigns and sets your bids in real-time to get as many conversions as possible. With this strategy, you don’t need to set your own ad group or keyword bids. Like with Maximize Clicks, you can also set a maximum CPC for more control of budget spend. In order to use Maximize Conversions, you need to set up conversion tracking and have at least 15 conversions in the last 30 days.
4. Target CPA
Target CPA (cost per acquisition) is available for search ad campaigns and you don’t need to set ad groups or keyword bids. Instead, you set your 30-day average CPA goal as well as your budget, and Bing PPC features will automatically align your bids to this average. How much you spend on individual conversions varies, but Bing PPC offerings ensure it’s in line with your average cost per conversion. For this strategy, you'll also need conversion tracking and have at least 15 conversions in the last 30 days.
Automated bidding is a great strategy for marketers who are new to PPC advertising and might not have the skills or resources to conduct optimizations on their own. More advanced marketers can use third-party bid management tools to scale their strategy and drive insights from a wider dataset of audience behavior, which provide additional features that more accurately reflect the unique, multifaceted SEM goals of individual organizations.
In addition, Bing’s advertiser training resources offer a useful chart to help you determine if you need conversion tracking and if it’s possible to use a third-party bid management tool based on your bid strategy.
Another unique new feature of Bing ads is LinkedIn Profile Targeting. Released as a beta feature in October 2018, it offers a powerful new targeting feature, especially for B2B marketers.
LinkedIn Profile Targeting, which is available for text ads, shopping campaigns, and dynamic search ads, allows you to target more than 575 million global LinkedIn members spanning 145 industries, 80,000 companies, and 26 job functions when you use its data for search campaigns.
Advertisers can apply LinkedIn Profile Targeting at the campaign or ad group level. You can set bid modifiers to better reach certain profile targets. For example, a 15% increase for profiles in the graphic design industry or information technology job function.
Bing’s in-market audiences are an advanced targeting feature that allow you to target people who have shown purchase intent in a relevant category, such as searches, clicks on Bing, and page views on Microsoft services. If someone searches for vintage car accessories on Bing, for example, they could end up in the “Auto Parts & Accessories” audience category.
Currently, there are 208 in-market audiences, including apparel, entertainment, business services, computers, and children’s products, among others.
In-market audiences are simple to set up and can drive conversions by reaching likely to convert audiences. You can associate in-market audience lists to ad groups and target and modify bids for these audiences. Advertisers can also set bid modifications for specific audiences, such as setting a 20 percent bid boost for in-market audiences.
When Bing piloted in-market audiences last year, they found it can improve conversion rates by 48% and click-through rates by 28%. This makes it a great way to target audiences that are ready to convert and even easier to target people at the bottom of the sales funnel.
Bing also makes it easy to monitor the impact of in-market audience targeting on overall campaign performance. Bing enables you to view reports using audience segmentation from the Accounts Summary page or the Campaigns, Ad Groups, Ads, Keywords, and Ad Extensions tabs.
They say never put all your eggs in one basket. That especially applies to your long-term PPC advertising strategy. Google may be the king of search and search engine marketing, but diversifying is always a smart option for advertisers. What’s more, by exploring options outside of Google, you have access to Bing’s unique audience, a wide array of advertising options, and targeting features — all of which have the potential to complement your Google strategy and drive even more conversions.
While Bing might still be an unknown, its growth, quality demographics, and PPC opportunities are all on a trajectory going up and to the right. But like anything else, you won’t truly realize its full potential for your PPC strategy until you start opening its doors and exploring your options.
Read even more Bing ad secrets here: 13 More Bing Ads Secrets to Broaden Your SEM Coverage
You might often hear marketers tell you to take the time to carefully execute PPC campaign management for optimal performance, then you can simply "set it and forget it." While it may be a popular philosophy, it’s also a common misconception among amateur advertisers.
Without a doubt, setting up well-targeted campaigns lays a strong foundation that gets you off to a great start. But experienced marketing managers know that PPC campaign management and optimization aren’t static disciplines. Both competitors and the market rapidly change, and thus, so do the needs of your audience and their search queries. And if you don’t keep up and make necessary changes, your competition will soon outperform you by doing so first.
As with a well-tended garden, in order to get your campaigns to grow and thrive, you need to continuously keep them managed and maintained. Reviewing how your audience reacts to and interacts with your PPC ads can also provide you with new insights that make your campaigns even more effective.
Smart advertisers conduct routine PPC campaign management tasks regularly -- sometimes even daily -- to implement important changes like:
If you choose, you can let your PPC campaigns run themselves in the background. But if you want to maximize ROI from your ad spend, ongoing PPC campaign management and maintenance is a must. Here are eight strategies you can leverage to maximize ROI from your PPC campaign management efforts.
PPC advertising can help drive numerous marketing and business goals. But targeted, successful campaigns don’t attempt to achieve everything at once. Subsequently, an important part of PPC campaign management is defining a clear goal and appropriate metrics that can be measured against key performance indicators (KPIs).
Before starting a campaign, you should be able to answer questions such as:
Define your goals before you start because it will ultimately impact what bidding strategy you choose, what keywords you target, and what kind of ads you serve.
Carefully structuring your account from the beginning is an important part of PPC campaign management, making your campaigns easier to manage, and reducing the chances of making big targeting mistakes, such as:
When you’re starting out with just one or two campaigns, account setup might seem easy. But if you plan to expand in the long term, it’s important to consider multiple factors when initially laying a foundation for your account structure.
Setting up your account the smart way means:
When setting up your campaigns and ad groups, consider what kind of PPC campaign management tasks you’ll be performing down the road, and make choices that will simplify this for you. For example, don’t put too many ads in an ad group, and use detailed names to describe your campaigns and ad groups. Don’t create multiple campaigns for the same product category, or target multiple products/services with a single ad group.
When you first create your keyword lists, you’re often taking a guess at what keywords are relevant to your audience without any hard data. But as your campaigns get underway and evolve, you can then start to gain some perspective regarding which queries perform better than others.
A great strategy advertisers can apply when setting up new campaigns is to start using modified broad match keywords, which provide a list of search queries that trigger one of your ads. You can then duplicate your campaign and add these same keywords as phrase match keywords. Search terms that actually generate clicks on your ads can then be added as exact match keywords. Known as segmenting keywords by relevance, this strategy enables you to bid more on high converting queries. Also focusing on more relevant keywords will improve your Quality Score, making ad relevance an important factor.
It’s equally essential to remove keywords that are causing problems with your campaigns. Take the time to review the information under the “Search terms” tab and remove keywords that:
Removing problem keywords from your campaigns will help free up your budget so you can focus on high-quality keywords, and thus, channel your efforts around achieving the highest ROI.
Even if you do a great job establishing your negative keyword lists in the beginning, you can’t possibly know every potential irrelevant keyword associated with your ads -- this can only be determined by monitoring campaign performance.
Some experts will actually tell you that maintaining your negative keyword lists is even more important than managing your normal keyword lists, simply because there’s a significant negative impact every time your ad shows for one of these irrelevant keywords. As previously mentioned, relevance is an important factor in determining your Quality Score for a search query. Low relevance means low Quality Scores, worse ad position, and poor performance.
Making regular changes to negative keyword lists is especially important for advertisers in niches related to news or pop culture topics. Beyond mining your search terms report, you can also set up Google Alerts for important brand keywords, which will allow you to discover new and trending news topics that could cause irrelevant search queries to trigger your ads.
Some advertisers put so much energy into keyword targeting and bid strategies that they forget about their advertising collateral altogether. But the actual advertisements you display and their associated landing pages are of equal importance for PPC campaign management.
Delivering ads for the most relevant search queries doesn’t matter if your ad copy and call-to-action aren’t optimized and attract prospective targets. By the same token, you won’t also be able to drive on-site conversions from your efforts if your landing pages offer poor user experience.
So if you’re experiencing unexpectedly low Quality Scores within your campaigns, your advertising collateral could be the culprit. Consequently, you’ll need to monitor performance and take the necessary steps to continually improve it.
Test your ad copy
Often, even the smallest changes to your ad copy can significantly impact PPC performance. A more relevant headline or call-to-action, for example, can mean the difference between a person ignoring your ad or clicking through and converting. Similarly, including relevant ad extensions can also have a big impact -- an auto repair business, for example, could significantly improve ad performance by including call extensions with their ads.
In short, smart advertisers simply don’t guess at the ad copy that is most relevant to their audience -- they set up different ad versions and test performance. One way to do this is by leveraging advanced settings in Google Ads to rotate different versions of your ads indefinitely. You can also rotate and automatically optimize to display the best performing ad over a set amount of time.
Improve landing page user experience
Equally important to monitoring how audiences interact with your ads is how they interact with your website content once they click through. A slow loading page will naturally result in a higher bounce rate. Meanwhile, other landing page elements could lead to user experience issues that frustrate visitors.
It’s important to also ensure the content on your landing page matches the content of the associated ad. A specific, targeted ad that leads users back to a generalized landing page will most definitely cause confusion or make visitors wonder if they accidentally clicked on the wrong ad. Consequently, you’ll need to be sure to use language that helps reassure visitors that they’ve landed in the right place.
Google wants to help its advertisers succeed in their PPC efforts. And PPC campaign management is a huge part of this, so they have a big incentive to help with that as well. One of the ways Google does this is by sending email alerts with important information to help you improve your accounts and campaigns.
Google can send you email notifications for:
Smart advertisers can and should take full advantage of these notification services so they can react quickly to the problems and opportunities Google identifies. That said, you’re not automatically signed up to receive all of these alerts -- some require an opt-in. To ensure you’re receiving the most important alerts you need for campaign maintenance, check your email notification settings under “Setup” then “Preferences” from your Google Ads account.
Set up Google’s email alerts the way you want them. With Reports, for example, you can choose to receive all available reports as an email alert, or select the most critical reports that you customize yourself. This way Google can bring your attention back to your PPC accounts whenever they need critical maintenance.
Automated rules are another important tool Google offers to help you manage your PPC campaigns, allowing Google to make changes to your account for you based on rules you create. And by taking full advantage of these automated rules, you’ll save time and improve the performance of your campaigns without needing to make laborious manual changes.
Here are some of the many ways you can leverage automated rules for PPC campaign management:
To leverage these tools to their full potential, consider the kind of regular campaign management tasks you perform manually and see if they can be automated via Google. From there, you can then start creating your own custom rules to help you save time and improve campaign performance.
It’s no secret that in recent years, Google Ads has rolled out a variety of important campaign management features. For example, by using machine learning technology, the platform provides recommendations that can help you improve campaign performance and the strength of your accounts.
When you’re first starting out, it’s highly valuable to take advantage of these features because effective campaign management isn’t something you can do all on your own. The market, competition, and your audience are constantly changing. As a result, comprehensive PPC campaign management is a full-time job for even small business marketers. For larger businesses or those with aggressive growth strategies, keeping up with campaign maintenance manually is practically impossible.
And while Google’s internal automation features are a great place to start, they offer limited use of powerful technology. Machine learning and artificial intelligence can not only help you discover new insights and opportunities, it can act on them for you.
However, while the data that Google leverages comes solely from your PPC ad performance and that of your competitors, no business solely exists within the bubble of Google PPC advertising. There’s a wealth of data beyond Google that can drive even more relevant insights such as audience data from your CRM platform and third-party intent data from other sites around the web -- none of which Google’s AI platform even considers.
So if you want to get the most relevant help to improve PPC campaign performance, you’ll need to use a technology that draws on all these data sources to gain a full picture of your audience and market. By using the same powerful machine learning and AI technologies as Google, you can make significant changes to your bid strategy, keyword targeting, and other campaign factors aimed to dramatically boost conversion rates, lift ROI and improve the overall performance for even your most underperforming campaigns.
Creating and executing successful PPC campaign management is a critical building block for an effective SEM strategy and imperative for maximizing your return on ad spend (ROAS). That said, it’s no secret that the myriad of maintenance tasks associated with a high bar of success are an expense that can quickly add up to take you over budget. In short, you have to spend a lot of time, personnel and resources to consistently and continuously maintain your accounts while making the necessary changes needed in order to keep them optimized. And while necessary for PPC growth, it’s a precarious balance to maintain.
That’s where artificial intelligence and automation come in, which, among other things, make it possible to better optimize your campaigns while simultaneously reducing the amount of hands-on work needed from marketing managers.
Any marketer worth his or her salt knows that there is no recipe for instant campaign success. A successful PPC campaign needs to be well-tended, carefully monitored, and constantly updated to accommodate the ever-changing market tides. Like anything worthwhile, it requires patience, care, and a little TLC. But maintenance and management can also be time-consuming, laborious, and eat into profits when it becomes too big for your organization to handle or exceeds your resources. Finding the right tools that leverage automation to establish accounts, refine keywords, define and uphold campaign goals and enforce automated rules can go a long way to ensure that crucial functions are done swiftly and accurately. And by keeping the busy work off of your plate, you’ll be able to focus on what matters most -- designing even better, stronger, and more creative campaigns that take ROI -- and resulting profits -- to new levels.
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Interested in how Centro's automated technology can help you unlock improved PPC performance? Connect with our digital experts today.
‘Ask the Expert’ is a blog series that breaks down the complicated tools, tech, and trends you’ve been hearing about in the trade pubs and around the office. We reach out to our in-house experts to ask the tough questions and turn them into bite-sized Q&As for your reading pleasure.
This month’s topic? Machine learning. We brought in Centro’s VP of customer success, Steve Monti, to give us the breakdown.
In terms of advertising technology, what is machine learning?
Machine learning is a type of artificial intelligence (AI) where a computer system learns from data. In advertising technology, this is often used to improve the performance of ad serving systems, mostly in programmatic advertising, to show ads to individuals in order to achieve a result. The result could be a click or a variety of other types of actions that the advertiser wants. Different elements of machine learning can be present in many common systems used within the advertising tech space, such as demand-side platforms, ad exchanges, ad servers, and more.
How does it work within ad-buying systems?
Software with machine learning can optimize the performance of campaigns by gathering data to learn how key performance indicators (KPIs) were achieved in the past. The system then learns what element combinations are needed in a campaign to have the highest likelihood to generate the same result or KPI. The system will then structure a campaign to match those parameters to obtain the impressions that can lead to those same KPIs. Elements could include targeting data, device or location of a user, ad unit size, the content of the page, and more. Machine learning can build a model that will continue to hone as a campaign is running.
Is it related to algorithmic optimization?
Somewhat, of course! Machine learning uses algorithms, but not all algorithms lead to machine learning. Algorithms have the ability to make finite, black, and white decisions. Machine learning implies a logic of learning from those decisions over time.
Is machine learning strictly for optimizing to generate clicks?
Machine learning technology builds a model. In an ad-buying system, a model is made up of a mix of targeting combinations that calculate the probability of a result occurring. A click is a highly desired result, but a marketer can, theoretically, program their system to model towards other types of results as well.
Ok, I’m interested -- what does Centro offer in terms of machine learning within its platform?
Inside Centro’s platform, Basis, users can optimize campaigns with algorithmic optimization or machine learning. These features can also be turned ‘off’ or ‘on.’ When ‘on,’ the system continually learns based on more than 30 targeting parameters and will set bids based on the probability of success.
Learn more about the programmatic advertising opportunity with Centro, here.
The digital industry is constantly evolving, which can make keeping up with the latest trends and advances very challenging. Fear not! Centro is here for you. What are the emerging trends? What's still working? Where are we going next? In our latest infographic, we answer pertinent questions regarding digital platform investments, mobile, and the video landscape as they continue to move forward.
Click to read our take on the digital trends and predictions for 2019.
It might come as no surprise that today an increasing number of people are spending the majority of their waking hours staring at screens or swiping themselves into a frenzy on their tablets and smartphones. A recent study by market-research group Nielsen revealed that American adults now spend more than 11 hours per day watching, reading, or simply interacting with media online, up from nine hours and 32 minutes just four years ago. From a marketing and advertising perspective, that is a lot of face time you could be missing out on, and with it, brand awareness and revenue. Consequently, it’s more important than ever that you’re employing pay per click advertising, or PPC, to maximize value, profitability and ROI on your campaigns. So what is PPC?
We’ll break it down.
So, then, what is PPC? How does it work? And what are the benefits?
While the field has matured and grown increasingly complex in recent years, at its core, PPC is a model of internet marketing by which advertisers pay a fee each time a user clicks on one of their ads that appear online. It is, essentially, a measured method of buying visits to your website rather than deriving them through organic search with the idea that these ads will be of greater value to your advertising goals: more targeted and carrying a higher likelihood of conversion.
There are several types of PPC advertising, but the most popular remains paid search, commonly known as search engine marketing (SEM). This sophisticated, keyword-driven discipline allows industry professionals to place bids for ad placement on a search engine results page (SERP) real-estate when a consumer searches for a keyword that is related to their products or services. When implemented efficiently and funded smartly, PPC campaigns can be the most powerful weapon in a marketing armory and the return on investment (ROI) can be substantial.
Sounds easy, right?
Well, not quite. A lot of resources go into programming and maintaining the best campaigns. You need to consider first researching and selecting the most appropriate keywords, organizing those keywords into defined campaigns and ad groups, and then creating or adapting landing pages that are fully optimized for those all-important conversions. Throw into the mix that the SEM world is highly competitive, often forcing businesses to constantly alter their strategies, and you can see how it becomes difficult to anticipate and execute the best investments for your campaign strategy.
Here’s the good news, though. If you and Google are metaphorical “best friends,” it gets easier. Google became one of the largest companies on the planet because of advertising. In 2016, Google’s advertising revenue reached a massive $79.4 billion, accounting for more than 90% of its total revenue. This means that Google treats its SEM advertisers well, affording them prime space on results pages, which in turn, drives organic traffic further and further down the rankings.
If you want to start using PPC, it’s imperative that you know how to do it right or you risk wasting a significant amount of your budget. Google Ads (formerly Google Adwords) is Google’s very own advertising platform and the most popular system of its kind in the world today, allowing businesses to go to market on its search engine and its affiliate sites. This is where you set up your bids on the keywords you want to trigger an ad display.
Unfortunately, it’s not as easy as simply bidding large sums to ensure your ads show more prominently than your competitors. Instead, every time a search is initiated, Google will draw up a pool of ads that then become subject to an Ad Auction, an entirely automated process that determines who will claim the top spots on the SERPs. These “winners” are selected based upon an advertiser’s Ad Rank, a metric calculated by multiplying two key factors - the CPC bid (specifically, the highest amount an advertiser is willing to spend) and the Quality Score (a value out of 10) that summarizes the quality of your ad based on click-through rate (CTR), relevance, and landing page experience. The advertisers with a better Quality Score get access to more ads at lower costs.
So, how do you improve your Quality Score?
For one, establish an effective keyword list. This may be incredibly time-consuming but it’s the foundation of every SEM program. The most profitable advertisers on Google are the ones continuously engaged in a process of growing and refining their keyword portfolio, taking advantage not only of the most frequently searched terms close to the offerings they sell, but also the long-tail and other niche iterations that can often be hugely profitable due to their lower costs.
Secondly, ensure your landing pages are targeted. With an overabundance of information available on the internet, audiences quickly recognize whether they’re interested in a specific webpage or not. To grab their interest and keep it, creating optimized landing pages is a must, so consider everything from attention-getting headers, strong visual elements, clear calls to action (CTA) and focused copywriting.
The key to a robust, successful modern-day marketing strategy is learning to effectively utilize a diverse portfolio of channels that can help get your brand before the eyes of potential customers in different ways. Although PPC advertising looks simple on the surface, managing a successful campaign and navigating the intricacies of bidding are anything but. Savvy digital marketers are in a constant process of testing and experimenting with keywords, offers, landing page content, and a myriad of other variables, leveraging data from these campaigns to inform other strategies in their overarching marketing strategy. So think of it this way: email campaign A always promotes offer X, but testing across your PPC activities reveals that offer Y yields 50% more conversions. Ultimately, applying this scenario across all of your marketing efforts makes it clear that companies can uncover hidden opportunities for growth that would remain dormant if PPC wasn’t the secret weapon. Learning to wield it to its full potential makes this great marketing game much less intimidating, while empowering you to drive more profitable and effective results.
As a digital marketer, you know that in order to truly succeed in digital marketing, you need to understand the needs of your audience, target them at the precise moment of purchase intent, and deliver a relevant message that helps them convert -- easier said than done. Historically marketers have relied solely on traditional business intelligence to strike the right balance between this complex mix of elements in order to achieve their campaign and revenue goals -- a feat nearly impossible in today’s fast-paced digital world. But looking ahead, that's where smartphone AI will come in.
These days more than ever, consumers rely on their mobile devices as a tool to fulfill their shopping and product search needs. Thus, as technology has continued to evolve and adapt to consumers' changing needs and behaviors, smartphone AI has emerged as a viable tool for businesses, helping them drive insights to deliver the right marketing message to the right audience at the right time, while unlocking new potential targets, buyer intent and other relevant opportunities that promise a major win for ROI.
Safe to say, business Intelligence (BI) has grown exponentially in sophistication over recent years -- a development driven by increasing amounts of available consumer data. What’s more, today’s business intelligence capabilities are incredibly advanced, with the potential to drive more actionable insights than ever before.
The most common type of business intelligence marketers use today is descriptive analytics. Leveraging first party data directly from your business, descriptive analytics essentially summarizes the performance of a business in the digital market. Data sources include on-site behavior, your brand’s social media mentions, performance of your internal sales teams, advertising market share, which, when combined, can drive data insights to help make better business decisions.
The next step in business intelligence capabilities is predictive analytics. By strategically utilizing a combination of advanced statistical algorithms, first party data and external third party intent data, predictive analytics can project future performance of your marketing and business efforts.
As such, most marketers who adopt predictive analytics do so to forecast the trajectory of their campaigns and other marketing efforts based on their advertising investment and other strategic factors -- and its applications are numerous. For example, in addition to basic annual and quarterly forecasts, predictive analytics can perform sentiment analysis based on data from social media conversations and online forums. It can also make generalizations about how people feel about your brand by performing text analysis.
Yet even in light of these advanced capabilities provided by regular business intelligence, Artificial Intelligence (AI) can still, in many ways, surpass these insights. And when combined, both technologies complement each other to offer unique advantages and unprecedented lift to your PPC campaigns. And the businesses that take full advantage of it are primed to increase business growth and stay ahead of the competition.
Contrary to popular belief, AI doesn’t refer to one specific technology, but an array of potential digital capabilities that mimic cognitive human functions. Thus, any computer with the ability to adapt and learn from surrounding conditions and solve problems has artificial intelligence.
As you might already know, mobile devices today include internal AI engines that leverage a user’s personal data, as well as information from mobile device sensors, to analyze and make decisions on the device itself. Here are a few of the many applications of smartphone AI today:
Perhaps not surprisingly, smartphone AI not only offers a myriad of benefits for consumers, it’s changing the way they interact with their mobile devices. The combination of advanced natural language processing and intent prediction now makes it possible for mobile assistants to become intelligent chatbot interfaces that can both understand the relevant information that people need when they ask for it, and also infer intent through natural conversational language. In many ways, they have the potential to become as helpful as a knowledgeable friend -- with the added benefit of search engine access -- setting the stage for conversational commerce that holds the potential to be the next big game changer in app marketing.
Most importantly, AI is changing the mobile advertising market. As the majority of marketers know, mobile devices aren’t primarily used for making phone calls -- they’re the main purchasing tool for many eCommerce shoppers. And, thanks to AI, they can potentially be used by consumers for buying recommendations for an even greater, more personalized shopping experience.
Similar to keys or a wallet, mobile devices have become everyday tools for consumers, who regularly use their phones to communicate, navigate, research potential purchase decisions, and shop. As a result, mobile devices provide an extensive amount of relevant, actionable consumer data that organizations can use as part of their business intelligence efforts -- data that only increases in value as more people rely on their mobile devices to make everyday life decisions.
That said, the wealth of new available consumer data also presents a problem. Businesses simply can’t process it quickly enough for it to continually drive marketing insights and create additional value. That’s where AI comes in.
AI can help drive advertising strategies by:
It goes without saying that using AI technologies makes it possible and easier to analyze large amounts of consumer data. It can also help predict which kinds of consumers to target in order to reach your marketing goals. By making advertising campaigns more efficient and effective, AI can simultaneously reduce your necessary advertising budget while improving ad performance. It makes sense, then, that its capabilities be incorporated in the tools that consumers most use -- their mobile devices.
But while there are already a variety of tools and technologies on the market designed to help businesses improve mobile advertising with smartphone AI, adoption has only penetrated a small group of competitive marketers -- largely because the rate of AI adoption has been generally slow. Currently, most businesses are often too focused on gaining insights from their regular business intelligence capabilities -- which have significantly grown in value in the recent year -- to explore and consider more sophisticated options.
The truth is that business intelligence and smartphone AI aren’t mutually exclusive advertising growth strategies. While, AI can mimic the cognitive functions of real human decision-making, ultimately it’s your unique business and marketing priorities that drive the choices you need it to make.
Business intelligence capabilities such as descriptive and predictive analytics can tell you a lot about current and future performance potential. And businesses that combine these BI capabilities with smartphone AI can often create sophisticated, efficient and effective advertising strategies that can often outpace competitors solely relying on just one of these technologies.
In 2016, mobile internet usage surpassed desktop for the first time, and the gap only continues to become ever wider.
Since the future of internet will be mobile, businesses are starting to make it a priority. Google itself has made several major algorithm changes to prioritize mobile-first indexing, as well as launching its Accelerated Mobile Pages (AMP) project to improve the speed at which sites load on mobile devices.
Mobile prioritization affects all areas of search engine marketing (SEM), including SEO and PPC advertising. The landing pages you create for your PPC ads need to offer a good mobile user experience, as this affects your Quality Score and other advertising outcomes. Users are also much more likely to bounce after clicking on your advertisement if they find landing pages difficult to navigate, further underscoring that mobile will need to be a priority for a successful, long-term SEM strategy.
Most businesses today build their buyer personas based on demographic factors and what they imagine are the needs and pain points of their target audience. But with smartphone AI, it’s possible to gain an even deeper understanding of what people really want and why by conducting intent-based marketing -- nearly impossible to do properly without using advanced data insights. Among other things, smartphone AI has the potential to process phone and chat conversations, as well as draw on location-based data to specifically understand what a person has the intention of doing or buying.
And businesses that use smartphone AI insights in combination with their own business intelligence tools can optimize their mobile sites to deliver the kind of content audiences really want -- because they have the power to really know. As more and more businesses adopt this advanced targeting strategy, it will becomes increasingly challenging for the competition to keep up.
Targeting your audience with the right message during these micro-moments is essential for business success. And Smartphone AI makes it possible to better understand a user’s intent so you can deliver a targeted ad or marketing message at the time and place they can benefit from it the most. Google calls these micro-moments, intent-driven moments of decision-making and preference-shaping that occur through the entire consumer journey. Of online consumers, 69% agree that the quality, timing, or relevance of a company's message influences their perception of a brand.
In addition, the user experience will also have to be prioritized as smartphone AI becomes more prominent. Marketers will need to create concise, targeted landing page copy that easily enables users to make quick purchase decisions with the click of a button. It will also become important to prioritize mobile ease-of-use, while also reassuring users on your page copy that they’re making the right decision.
When you make marketing decisions and advertising campaign adjustments based on business intelligence insights, it’s always a process of trial and error -- in order to stay optimized you need to constantly measure results, adjust for market fluctuations and retarget your strategy consistently.
Machine learning provides a solution to help simplify this process for advertisers. Among other things, machine learning can analyze consumer behavior, see how audiences interact with your ads and marketing message, then help you make necessary decisions to improve your targeting -- all of which boost smartphone AI's capabilities that provide deep insights into customer intent. Machine learning also has the ability to analyze large amounts of consumer data and recognize complex patterns that regular data scientists wouldn’t be able to discover.
Managing reams of business intelligence data is daunting enough as it is and ostensibly, adding smartphone AI into the mix could be perceived as yet another obstacle for your marketing teams to overcome. But in reality, with the increasing reliance on mobile devices as a tool for shopping and searching, leveraging smartphone AI is an investment that not only makes sense but promises sustainable ROI over the long term.
As a digital marketer, you know that the industry doesn’t stand still for a moment. Competitors have are always finding new and creative uses for business intelligence capabilities in an effort to gain an edge in the market.
That’s your opportunity to leverage a tool that your customers are already using. Marrying smartphone AI to your existing arsenal of business intelligence capabilities will only work in your favor -- whether it's unlocking buyer intent, applying new predictive behavior technologies, or creating a better shopping experience -- that will give you the leg up you need to leave your competitors behind.
Consumers are constantly inundated with video ads from a multitude of brands both large and small. Whether they're on a PC, tablet, or laptop, they're exposed to one ad after another—which makes it easy for them to ignore what doesn't connect or stand-out. This creates a unique challenge for brands/agencies alike, and poses the question: How do companies capture the short attention span of consumers in an entirely saturated market?
Here are five proven advertising techniques to help your brand break away from the pack.
In-your-face branding is a turn-off for today's consumers. They've become desensitized over the years, making consumer advertising with heavy-handed branding largely ineffective. Instead, consider a technique called brand pulsing. This technique strategically knits branding through an advertisement in an understated way. It ensures that your brand is seen, but in an effective, understated way.
Ad placement can impact the effectiveness of messaging and affect how consumers think about the brand. Ads must be relevant not only to the audience, but also the space in which they’re located. For example, if you own a company that manufactures dog toys and your ad appears on a website dedicated to maintaining saltwater fish tanks—it’s probably going to miss the mark. Utilize a demand-side platform to help discover ad space that is most relevant to your brand and vice versa.
Establishing a personal connection is crucial to effective advertising in a saturated market. One of the most valuable advertising tips for companies in any industry is to find a way to empathize with their target audience. This is less difficult than it seems. Think about it—most companies are created because they offer a product or service that solves a problem or satisfies a need. Show that you understand their challenges and frustrations and that your product or service is the solution.
Create highly shareable video content that’s appropriate for a wide range of audiences. Avoid segregating some markets to appeal to others. For example, the use of crude humor for shock value may increase your number of views but is likely to isolate certain segments of your audience.
Today's consumers value rich, interactive experiences on and offline. Avoid talking at them—instead, provide your audience with educational and actionable content. Deliver a full experience. Do that, and they will remember your brand. Content that’s extravagant for the sake of being extravagant is easily forgotten, while content that cultivates a positive learning experience is usually the most effective.
Maximize Brand Exposure
There is a myriad of advertising techniques and tactics that can be utilized to increase brand exposure, however, many of them fail to take into account that online channels are now very saturated with ads. What worked a few years ago, may not work now. Stay on top of the latest advertising tips to maximize exposure and make your ad dollars work harder for you.
Centro offers a performance-driven, demand-side platform designed to help you streamline media campaigns across a multitude of online channels. For more information about how programmatic can transform your consumer advertising, contact us today.
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Sources
https://www.acuityads.com/blog/2017/11/06/seizing-short-attention-spans-saturated-online-channels/
https://centro.net/
https://centro.net/services
https://centro.net/products/dsp-programmatic-advertising
https://centro.net/products/reinventing-digital-media-planning