Tag Archives: Search Marketing

15 PPC pro tips for writing text ads

Want to know how to write great paid search ads? Columnist Pauline Jakober shares some tips from her years of experience writing PPC ad copy.

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The technology behind AI in PPC

Artificial intelligence (AI) has been around for a long time, so why are we only just now exploring its applications for PPC? Columnist Frederick Vallaeys explains the technology, its evolution in recent years, and what’s next for AI in paid search.

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Understanding AdWords keyword match types for manufacturers

With much of AdWords’ help documentation geared towards retailers, it can be confusing for manufacturers to figure out how best to utilize the platform. This guide to match types for manufacturers from columnist Dianna Huff can help.

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High-level search marketing: How to keep your momentum from the holiday season going

Businesses tend to have a huge marketing push right before, and often during, the holidays, but often times these marketing campaigns fizzle out after the new year.

It’s easy to dial back your marketing efforts and budget after a busy season, but if you’re smart you’ll keep that momentum up well into the first months of the new year.

Here’s how you can keep up your push in marketing efforts in 2018.

Start email marketing campaigns early and target right

If you played smart during the holidays, your email leads should’ve increased significantly. The best practice is to act fast. Your new leads may have purchased their holiday gifts already, but that doesn’t mean they’re done shopping. Understand that your customers want to hear from you, so it’s best to act fast.

This starts with targeted email campaigns. Instead of doing the hard work yourself, use the help of marketing automation software to determine which content fits each audience. For example, automation software looks at the previous purchases of customers and prompts emails for similar products.

Keep in mind that you don’t want to overdo it with the emails. This will turn your customers away quicker than they came. Offer valuable content in your emails early on and you’ll keep your customers coming back.

Some ways to add value to your email marketing campaign:

  • Reach out to customers who purchased their products as a gift. Use similar product suggestions for future gift purchases
  • Contact customers who left an abandoned cart. Customers often use their shopping carts as a “wish list” of sorts. Reach out to those customers to see if they plan to complete their purchase
  • Offer a discount to entice customers to purchase. Free shipping adds tons of value. Make your discount exclusive to email subscribers to further add value.

Continue to use paid ads

You already have your paid ad campaign underway from the holidays. Don’t let those ads go stagnant as you start the new year.

Leading up to (and during) the holidays, ads from all over are competing. That energy slows down as the holidays end. Take advantage of both lower competition and less expensive ads during the aftermath of the holidays.

This is a new year, which means it’s the right time to switch up your strategy. You’re no longer in holiday mode, but laying out the foundation for the rest of the year.

Do you normally bid second position keywords throughout the year? Change your strategy and look for keywords that are first position. The holiday campaign may have busted your budget, but that doesn’t mean you should pull back on your paid ads. You’ll actually spend more money in the long run, and completely kill your momentum from the holidays.

Keep your paid ads running throughout the year, so you’re not halting traffic and trying to build it back up after you run your ads again.

Take advantage of keywords around new year’s resolutions

“New year, new me” is the mantra for most people after the holidays are finished. A new year means a fresh start, and regardless of your market, customers focus on improving their health and well-being. Use these trends to benefit your business. This means creating impactful content that’s valuable to customers and their goals for the new year.

Use your content to promote your products and services in a way that appear useful to your customers. How can you portray your products as a tool for achieving customer goals? This tactic is possible to spin no matter what industry you’re in.

For example, let’s say you’re a company that specializes in green cleaning products. Cater your content towards improving health and keeping chemicals out of the home.

You know keyword choice is imperative when working on your search marketing campaign. Take advantage of new year resolutions by choosing keywords that match. For instance, words like “get healthy” and “get organized” are keyword phrases that tend to pop up as the new year approaches.

Look at last year’s organic keywords. Which were the best performing, and which could you stand to ditch?

Take a peek at your competitors’ keywords, too, to see what they’re ranking highly for. Incorporate these keywords into your blog posts and social posts to drive traffic to your company’s website.

Review your data and strategize for the upcoming year

No doubt about it, the months of January and February are slow months for everyone, no matter your industry. The best way to push forward is to take a look at what worked and didn’t work during the holiday season.

It’s also a great time to learn more about your new customers. This gives you great leverage to start working on your campaigns throughout the new year.

Look at things like your timing and segments. Who responded well to specific emails? Which groups brought you the most ROI? How was the timing of your campaign? When looking at your new customers, figure out which of these groups fit well for your business.

As far as your website goes, A/B testing will tell you which pages of your website responded well with your customers. Test your non-holiday specific landing pages and compare them to your holiday pages.

Notice the shift between the two and apply those shifts to your new year campaign. Take this information and tweak the things that didn’t work and apply those changes to your upcoming campaigns.

The takeaway

After the surge of the holidays, most SEOs and marketers feel they’ve exhausted their resources and budget. This doesn’t have to be the case. The success of a holiday campaign should continue well into the new year. Keep these things in mind during your slow months and you’ll keep the momentum up to prepare you for spring and busier selling seasons.

How do you keep your momentum going into the new year? Let us know what has worked for you in the comment section below.

Amanda DiSilvestro is a writer for No Risk SEO, an all-in-one reporting platform for agencies. You can connect with Amanda on Twitter and LinkedIn, or check out her content services at amandadisilvestro.com.

The 2018 guide to B2B Sales, Part 1: Demand gen and demand capture

If you’ve ever made the switch from B2C or ecommerce to B2B marketing, you know there’s a world of difference.

B2B offerings are generally much more expensive, with a very long lead-to-close time, and marketing needs to be addressed in a different and strategic manner.

In B2B marketing, you must reach users at every point of the funnel – and keep educating them in stages along the way.

Through a series of blogs, I will discuss strategies for how to generate demand, drive qualified leads, master content delivery, and essentially close the sales loop via paid media. In part 1 of this series, we’ll talk about how to generate new demand and capitalize on the intent that already exists.

Let’s jump in.

Use both search and social to get in front of the right audiences

You’ve got more than a few powerful levers to pull to get in front of qualified buyers. I recommend you start with your two biggest: paid social and paid search.

Paid social allows you to get in front of relevant audiences and let them know you and your product/service exist. This is a demand generation play – reach highly targeted audiences who would likely purchase your product/service, educate them on your brand/product/service, and ideally drive them to your site to push them into the funnel.

Paid search capitalizes on the intent that already exists. People are searching for what you have to offer, so leverage paid search to ensure you are capturing that interest.

Paid social strategy

For paid social, I would recommend the following channels and strategies:

Facebook

  • Make use of lookalike targeting! Take your customer list and, rather than uploading the entire list, segment your top (highest-LTV) customers and create lookalikes based on that group.
  • Use Facebook’s native targeting capabilities to segment and address audiences based on different titles, companies they are employed with, etc.
  • Use 3rd-party data companies (e.g. Axciom and Datalogix), which allow you to target businesses of different sizes, specific roles, decision makers, etc.

LinkedIn

With LinkedIn, you are able to truly hone in on your target audience by leveraging a mix of the right industries, functions within those industries, seniority type, and company size. LinkedIn’s CPCs are considerably higher than those of other channels, so you must be willing to pay a premium price for the first click to bring the user onto your site – this way you can introduce them to your brand and educate them on your offerings.

After the leads are in your funnel, you can market to them through other channels, significantly cheaper channels to push them through the funnel (which we’ll address in another post).

Twitter

Twitter is another great social platform to find relevant audiences. Although volume is not as large as that of the other platforms, you can still leverage some of their targeting capabilities to get in front of the right eyes.

  • Lookalikes: very similar to the strategy used on Facebook
  • Targeting by followers:
    • Build out conquesting campaigns to target users following your competitors
    • Target followers of industry thought leaders and publications

Paid search strategy

Paid search is expensive – but extremely effective. Users looking for your brand, product, or service are already exhibiting intent that positions them closer to sale, so these are users you must target.

Our paid search strategy at 3Q has two main components. The first is to implement the Alpha Beta campaign structure, based on single-keyword ad groups and a mixture of negative, exact, and broad match that allows you to capture and control your top keywords while testing new keywords. If you need a refresher on how the Alpha Beta campaign structure works, a quick Google search should help fill you in.

The second is to develop competitor conquesting campaigns that capitalize on the intent that our competitors have built. Note: if your competitors are bidding effectively on their own brand terms, you’ll likely pay a pretty penny to compete, but it can be a very effective shortcut.

Use landing pages strategically

For both paid search and paid social, it is crucial to segment the audiences and keywords appropriately to be able to send these different audiences and appropriate keywords to the most relevant landing page/piece of content.

For prospecting campaigns, you need to get a sense of what each audience is looking for and serve them content that not only gives them an overview of what your business is at a high level, but also offers them value and true insight into your business – this may be a whitepaper, a demo, etc.

Think about the keyword or the type of audience you are targeting. For example, if you’re targeting audiences from specific industries (e.g. finance, retail, food and restaurant, etc.), send them to landing pages specific to that industry if available.

If you’re targeting more senior-level executives, think about the right content to deliver to them, something more high-level discussing key impacts to the business, value props, etc., that your service or offering would bring. If you’re targeting those whose job this would directly impact, highlight the more technical specifics.

The goal is to truly cater content towards the individuals you are targeting; this will make the clicks you’re driving much more effective.

Stay tuned for part 2 of this series, in which I’ll discuss building audiences, smart segmentation, and leveraging the right content for mid-funnel remarketing and your overall nurture.

Artificial intelligence and machine learning: What are the opportunities for search marketers?

Did you know that by 2020 the digital universe will consist of 44 zettabytes of data (source: IDC), but that the human brain can only process the equivalent of 1 million gigabytes of memory?

The explosion of big data has meant that humans simply have too much data to understand and handle daily.

For search, content and digital marketers to make the most out the valuable insights that data can provide, it is essential to utilize artificial intelligence (AI) applications, machine learning algorithms and deep learning to move the needle of marketing performance in 2018.

In this article, I will explain the advancements and differences between artificial intelligence (AI), machine learning and deep learning while sharing some tips on how SEO, content and digital marketers can make the most of the insights – especially from deep learning – that these technologies bring to the search marketing table.

I studied artificial intelligence in college and after graduating took a job in the field. It was an exciting time, but our programming capabilities, when looking back now, were rudimentary. More than intelligence, it was algorithms and rules that did their best to mimic how intelligence solves problems with best-guess recommendations.

Fast forward to today and things have evolved significantly.

The Big Bang: The big data explosion and the birth of AI

Since 1956, AI pioneers have been dreaming of a world where complex machines possess the same characteristics as human intelligence.

In 1996, the industry reached a major milestone when the IBM’s Deep Blue computer defeated a chess grandmaster by considering 200,000,000 chessboard patterns a second to make optimal moves.

Between 2000 and 2017, there were many developments that enabled great leaps forward. Most important were the geometric increases in the amount data collected, stored, and made retrievable. That mountain of data, which came to be known as big data, ushered in the advent of AI.

And it keeps growing exponentially: in 2016 IBM estimated that 90% of the world’s data had been generated over the last few years.

When thinking about AI, machine learning and deep learning, I find it helps to simplify and visualize how the 3 categories work and relate to each other –  this framework also works from a chronological, sub-set development and size perspective.

Artificial intelligence is the science of making machines do things requiring human intelligence. It is human intelligence in machine format where computer programs develop data-based decisions and perform tasks normally performed by  humans.

Machine learning takes artificial intelligence a step further in the sense that algorithms are programmed to learn and improve without the need for human data input and reprogramming.

Machine learning can be applied to many different problems and data sets. Google’s RankBrain algorithm is a great example of machine learning that evaluates the intent and context of each search query, rather than just delivering results based on programmed rules about keyword matching and other factors.

Deep learning is a more detailed algorithmic approach, taken from machine learning, that uses techniques based on logic and exposing data to neural networks (think human brain) so that the technology trains itself to perform tasks such as speech and image recognition.

Massive data sets are combined with pattern recognition capabilities to automatically make decisions, find patterns, emulate previous decisions, etc. Self-learning comes from here as the machine gets better from the more data that it is supplied.

Driverless cars, Netflix movie recommendations and IBMs Watson are all great examples of deep learning applications that break down tasks to make machine actions and assists possible.

Organic search, content and digital performance: Challenge and opportunity

Organic search (SEO) drives 51% of all website traffic and hence in this section it is only natural to explain the key benefits that deep-learning brings to SEO and digital marketers.

Organic search is a data-intensive business. Companies value and want their content to be visible on thousands or even millions of keywords in one to dozens of languages. Search best practices involve about 20 elements of on-page and off-page tactics. The SERPs themselves now come in more than 15 layout varieties.

Organic search is your market-wide voice of the customer, telling you what customers want at scale. However, marketers are faced with the challenge of making sense of so much data, having limited resources to mine insights and then actually act on the right and relevant insight for their business.

To succeed in highly demanding markets against your competitors’ many brands now requires the expertise of an experienced data analyst, and this is where machine learning and deep learning layers help recommend optimizations to content.

Connecting the dots with deep learning: Data and machine learning

The size of the organic data and the number of potential patterns that exist on that data make it a perfect candidate for deep learning applications. Unlike simple machine learning, deep-learning works better when it can analyse a massive amount of relevant data over long periods of time.

Deep learning and its ability to identify or prioritize material changes in interests and consumption behavior allows organic search marketers to gain a competitive advantage, be at the forefront of their industry, and produce the material that people need before their competitors, boosting their reputation.

In this way, marketers can begin to understand the strategies put forth by their competitors. They will see how well they perform compared to others in their industry and can then adjust their strategies to address the strengths or weaknesses that they find.

  • The insights derived from deep learning technologies blend the best of search marketing and content marketing practices to power the development, activation, and automated optimization of smart content, content that is self-aware and self-adjusting, improving content discovery and engagement across all digital marketing channels.
  • Intent data offers in-the-moment context on where customers want to go and what they want to know, do, or buy. Organic search data is the critical raw material that helps you discover consumer patterns, new market opportunities, and competitive threats.
  • Deep learning is particularly important in search, where data is copious and incredibly dynamic. Identifying patterns in data in real-time makes deep learning your best first defense in understanding customer, competitor, or market changes – so that you can immediately turn these insights into a plan to win.

To propel content and organic search success in 2018 marketers should let the machines does more of the leg work to provide the insights and recommendations that allow marketers to focus on the creation of smart content.

Below are a just a few examples of the benefits for the organic search marketer:

Site analysis

Pinpoint and fix critical site errors that drive the greatest benefits to a brand’s bottom line. Deep learning technology can be used to incorporate website data, detect anomalies tying site errors to estimated marketing impact so that marketers can prioritize fixes for maximum results.

Without a deep learning application to help you, you might be staring at a long list of potential fixes which typically get postponed to later.

Competitive strategy

Identifying patterns in real-time makes deep learning a brands’ best first defense in understanding customer, competitor, or market changes– so that marketers can immediately turn these insights into a plan to win.

Content discovery

Surface high-value topics that target different content strategies, such as stopping competitive threats or capitalizing on local demand.

Deep learning technology can be used to assess the ROI of new content items and prioritize their development by unveiling insights such as topic opportunity, consumer intent, characteristics of top competing content, and recommendations for improving content performance.

Content development

Score the quality and relevance of each piece of content produced. Deep learning technology can help save time with automated tasks of content production, such as header tags, cross-linking, copy optimization, image editing, highly optimized CTAs that drive performance, and embedded performance tracking of website traffic and conversion.

Content activation

Deep learning technology can help ensure that each piece of content is optimized for organic performance and customer experience—such as schema for structure, AMP for better mobile experiences, and Open Graph for Facebook. Technology can help marketers can amplify their content in social networks for greater visibility.

Automation

Automation helps marketers do more with less and execute more quickly. It allows marketers to manage routine tasks with little effort, so that they can focus on high-impact activities and accomplish organic business goals at scale.

Note: To make the most of the insights and recommendations from deep learning marketers need to take action and make the relevant changes to web page content to keep website visitors engaged and ultimately converting.

Additionally, because the search landscape changes so frequently, deep learning fuels the development of smart content and can be used to automatically adjust to changes in content formats and standards.

Deep learning in action

An example of deep learning in organic search is DataMind. BrightEdge (disclosure, my employer) Data Mind is like a virtual team of data scientists built into the platform, that combines massive volumes of data with immediate, actionable insights to inform marketing decisions.

In this case the deep learning engine analyzes huge, complex, and dynamic data sets (from multiple sources that include 1st and 3rd party data) to determine patterns and derive the insights marketers need. Deep learning is used to detect anomalies in a site’s performance and interpret the reasons, such as industry trends, while making recommendations about how to proceed.

Conclusion

Think of deep learning applications as your own personal data scientist – here to help and assist and not to replace. The adoption of AI, machine learning and now deep learning technologies allows faster decisions, more accurate and smarter insights.

Brands compete in the content battleground to ensure their content is optimized and found, engages audiences and ultimately drives conversions and digital revenue. When armed with these insights from deep learning, marketers get a new competitive weapon and a massive competitive edge.

The vicious cycle of ROAS targets is killing your business

While many companies focus on return on ad spend (ROAS) as their primary KPI for search, columnist Andreas Reiffen believes that ROAS targets can often inhibit growth and new customer acquisition.

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Killer demand gen strategy, Part 3: Facebook advertising

If you’ve been keeping up with this series, you’ve got your audience defined and designed creative to match. You’ve constructed smart Google Display Network campaigns to get those users pouring into your funnel.

Now let’s talk some of the most powerful targeting capabilities of all.

In addition to advertising on the GDN, Facebook is a platform you must use to reach your target personas. Facebook’s audience targeting capabilities are among the most effective you can access.

You can target interests, behaviors and a variety of demographic information to get in front of your ideal audience.

Explore Facebook’s targeting options

Think about the personas you have created and begin choosing the audience targeting available within Facebook that will help engage those users. For example, let’s say you’re selling luxury home décor. One of your personas is female, between the ages of 30-40, likes home décor, and is affluent. You would then pick targeting as relevant as possible to get in front of these users.

One example would be:

Additionally, you can layer further information onto your personas – for example, some of them might like celebrity gossip. Leverage Facebook’s audience narrowing and layer it on to test how it impacts performance. See below:

Killer demand gen strategy, Part 3: Facebook advertising

In addition to leveraging Facebook’s native audience targeting capabilities, consider leveraging 3rd-party data audiences from companies like Axciom or Datalogix.

These companies can provide you with rich data that can be highly relevant to your personas – and help you develop new ones.

Take advantage of Lookalikes

Lookalike targeting is another great way to identify the right types of audiences and leverage Facebook’s thousands of data points to get in front of them.

First, look at your customer list and identify different ways you can segment those customers into groups of identifiable characteristics. For example, you can segment out your highest-LTV audiences, different categories (e.g. furniture categories, high-AOV purchasers, etc.).

Then upload these customer lists into Facebook, which will leverage its algorithm to serve your ads to audiences that mimic your seed lists in characteristics, behaviors, and traits.

A reminder: use tailored creative to these audiences. If you’re serving ads to lookalike audiences of your high-AOV purchasers, show creative with more high-end products to match their purchase behavior.

Another great way to get in front of relevant users is to leverage lookalikes as a base audience and then add in persona layers. For example, you may think about having an LAL of 5% and layering on celebrity gossip as a narrowing layer.

This makes your base audience similar in characteristics and traits to your customers, and it allows you to refine the audience to more closely match some of the personas you have built out.

Additionally, when creating your audiences, keep an eye on size. You will almost always want to leverage Facebook’s oCPM (Optimized CPM) tool, which requires an audience size of at least 400K to reach people, collect conversion data, and optimize towards users who are likely to convert.

As you know, a lead gen marketer’s work is only beginning when the leads are captured; there’s a long and winding road from lead to conversion, which will require a whole new series to address. But the above strategies should ensure that you’re working from a healthy foundation of leads.

Killer demand gen strategy, Part 3: Facebook advertising

If you’ve been keeping up with this series, you’ve got your audience defined and designed creative to match. You’ve constructed smart Google Display Network campaigns to get those users pouring into your funnel.

Now let’s talk some of the most powerful targeting capabilities of all.

In addition to advertising on the GDN, Facebook is a platform you must use to reach your target personas. Facebook’s audience targeting capabilities are among the most effective you can access.

You can target interests, behaviors and a variety of demographic information to get in front of your ideal audience.

Explore Facebook’s targeting options

Think about the personas you have created and begin choosing the audience targeting available within Facebook that will help engage those users. For example, let’s say you’re selling luxury home décor. One of your personas is female, between the ages of 30-40, likes home décor, and is affluent. You would then pick targeting as relevant as possible to get in front of these users.

One example would be:

Additionally, you can layer further information onto your personas – for example, some of them might like celebrity gossip. Leverage Facebook’s audience narrowing and layer it on to test how it impacts performance. See below:

Killer demand gen strategy, Part 3: Facebook advertising

In addition to leveraging Facebook’s native audience targeting capabilities, consider leveraging 3rd-party data audiences from companies like Axciom or Datalogix.

These companies can provide you with rich data that can be highly relevant to your personas – and help you develop new ones.

Take advantage of Lookalikes

Lookalike targeting is another great way to identify the right types of audiences and leverage Facebook’s thousands of data points to get in front of them.

First, look at your customer list and identify different ways you can segment those customers into groups of identifiable characteristics. For example, you can segment out your highest-LTV audiences, different categories (e.g. furniture categories, high-AOV purchasers, etc.).

Then upload these customer lists into Facebook, which will leverage its algorithm to serve your ads to audiences that mimic your seed lists in characteristics, behaviors, and traits.

A reminder: use tailored creative to these audiences. If you’re serving ads to lookalike audiences of your high-AOV purchasers, show creative with more high-end products to match their purchase behavior.

Another great way to get in front of relevant users is to leverage lookalikes as a base audience and then add in persona layers. For example, you may think about having an LAL of 5% and layering on celebrity gossip as a narrowing layer.

This makes your base audience similar in characteristics and traits to your customers, and it allows you to refine the audience to more closely match some of the personas you have built out.

Additionally, when creating your audiences, keep an eye on size. You will almost always want to leverage Facebook’s oCPM (Optimized CPM) tool, which requires an audience size of at least 400K to reach people, collect conversion data, and optimize towards users who are likely to convert.

As you know, a lead gen marketer’s work is only beginning when the leads are captured; there’s a long and winding road from lead to conversion, which will require a whole new series to address. But the above strategies should ensure that you’re working from a healthy foundation of leads.

Is holiday paid search more competitive in 2017 than 2016?

Columnist Andy Taylor explores year-over-year Auction Insights data from AdWords, revealing insights into this year’s holiday paid search landscape.

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