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Adwords bidding strategies have changed a lot in recent years. PPC advertising has always been keyword-focused, but audience targeting features are now more advanced when it comes to improving campaign performance. Google themselves are even taking the focus away from keyword targeting, rebranding from Google Adwords to Google Ads in 2018. This shift towards audience targeting is great news for advertisers looking to optimize and grow their efforts, especially if they utilize Google’s audience bid adjustments. Here’s everything you need to know about the role audience bid modifiers play in Adwords bidding strategies.
Bid adjustments are a Google Ads feature that can help you optimize performance by displaying ads more or less frequently based on where, when, and how people search. Through performance analytics and audience insights, you may discover that clicks are more profitable when they come from a certain device, location, audience, or at a certain time of day. Bid adjustments let you take advantage of these insights to target the most valuable clicks for your business.
Types of Google Audience Bid Adjustments
Bid adjustments (also known as bid modifiers) make it possible to increase or decrease your bids based on certain circumstances you choose. With Google Search Ads, there are several types of bid adjustments you can use:
Device - Show your ad more or less frequently for searches on computers, tablets, or mobile devices.
Location - Show your ad more or less frequently to customers in certain countries, cities, or other geographic areas.
Ad scheduling - Increase or decrease your bids for campaigns that show only on certain days or during certain hours.
Remarketing lists for search ads (RLSA) - Set bid adjustments to show ads to people on your RLSA lists. (Example: Increase your bid by 25% for people who viewed your website in the last 30 days.)
Interactions - Increase your bid for mobile devices to show call interaction ads more frequently for mobile phone users.
Demographics - Adjust your bid to target potential customers based on gender and/or in certain ranges of age and income.
How Bid Adjustments Work
Bid adjustments are set by percentages. Say you set a max CPC bid of $1 for a campaign, but you discover your ads perform better on desktop than mobile devices. You can increase your bid by 20% for searches on desktop, resulting in a final bid amount of $1.20.
Bid adjustments can be set at the campaign or ad group level. If you set more than one bid adjustment in a single campaign, they are usually multiplied together to calculate an overall bid increase or decrease. Combined bid adjustments can’t exceed a 900% bid increase.
To target audiences within your search campaigns, Google allows you to use several major audience types:
In-Market
In-Market audiences include people who are actively researching products or services similar to yours. These audiences are great to target if your main focus is to drive conversions. Google has a long list of relevant in-market categories to choose from, examples of which include:
Remarketing
Remarketing audiences include people who have engaged with your company in the past by visiting your website, downloading your mobile app, or watching your videos, etc. You can build remarketing lists using snippets of code on your website or app. You can also set rules for which site visitors should be added to the list, and how long they should stay on it.
Affinity
Affinity audiences are built for businesses running TV ads who also want to expand campaign reach online. Affinity audience targeting is a good choice if you want to build brand awareness in the digital space. Google provides a list of curated Affinity categories for advertisers to choose from. Some ideas:
Custom Affinity
Custom affinity audiences are audience categories that are tailored to your brand. Custom affinity audiences are created using a number of factors, including:
Custom affinity audiences are much more specific and relevant than general TV audiences. To illustrate, a running shoe company could target Sports Fans as an affinity audience, or they could target Avid Marathon Runners as a custom affinity audience.
All bid adjustments are valuable to advertisers to improve targeting, performance, and ROI from Google Ads. Audience bid modifiers, though, have arguably the greatest potential when talking about improved performance, especially when used in combination with other bid modifiers such as location and ad scheduling.
Here are some of the main performance opportunities:
They help you target very specific groups of people
Google’s audience targeting options allow you to show ads to very specific groups of people. You can target based on interests, online behavior, what they’re actively researching, where they are located, how they’ve interacted with your business in the past, and more. Targeting audiences with the right combination of characteristics makes it easier to reach the right customers with your advertising message.
They’re highly customizable
There are a number of ways to define target audiences based on specific behaviors and characteristics of your target market. You can use audience targeting to create, exclude or combine different lists in a way that’s infinitely customizable. The only requirement is that the number of people in a list reaches 1000 for 30 days.
They help you prioritize different buyer personas
Most businesses today have several target audiences who would be interested in their products and services. But some audiences are more likely to convert and drive revenue than others. Audience bid modifiers can help you target multiple audiences simultaneously, while also prioritizing the more valuable ones.
For example, say a software company offers a product that is relevant to both freelance sole proprietors and start-up businesses. Their analytics show that when a startup CEO clicks on their ad, they’re more likely to purchase the premium product version. The company can increase bids for this audience to drive more conversions and revenue, while still targeting all relevant audiences overall.
They help you promote niche products at scale
If your ad groups reflect your product categories, then it’s possible to use audience bid modifiers to effectively promote niche products at scale. For example, say a video game company wants to promote a series of sports video games. They want to target gamers as well as sports enthusiasts. It’s possible to use bid modifiers to prioritize promoting these products to gamers who also like sports.
Advertisers who take full advantage of these performance opportunities will find that audience bid modifiers can:
There are many ways to benefit from audience bid adjustments to improve campaign performance, but doing so manually comes with some issues. Most advertisers begin by adding certain audiences to their campaigns at a 0% bid modifier, then monitoring performance. If the audience is more responsive to their ads, then they start increasing audience bids to improve targeting. This strategy is problematic for several reasons:
Improved Performance ≠ Maximum Performance
Say you identify an in-market audience that is more likely to click and convert. You increase bids for that audience by 15%, and drive more revenue as a result. You might think that your optimization work is done, but you really don’t know if that bid adjustment was the most efficient and effective strategy to improve performance. Maybe a 10% bid adjustment was all you needed to drive the same results. Or maybe 20% would drive exponential growth. The only way to find out is to change and test your bids adjustments to discover the perfect strategy.
Markets Change
Audience bid modifiers aren’t something you can research, set, and then forget about. Audiences, competition, and the overall market landscape are constantly changing. It’s possible for an effective bid modifier to start performing poorly over time. Like with most optimization initiatives, you have to systematically monitor the performance of bid adjustments and make necessary changes.
Challenging to Scale
The challenges mentioned above are enough to hinder even the most modest advertising programs from using audience bid modifiers at scale. Now imagine if you’re running a huge account with hundreds or thousands of campaigns. Applying and optimizing audience bid modifiers across campaigns becomes impossible to scale.
Like with most optimization strategies today, the only way to fully benefit from audience bid modifiers is through automation. Right now there are a few different options to automate audience bid adjustments:
Google Smart Bidding
Google’s Smart Bidding is a subset of automated bid strategies that use machine learning to optimize for a set marketing goal. Smart Bidding strategies include Target CPA, Target ROAS, Maximize Conversions, and Enhanced CPC.
Smart Bidding considers audience signals when optimizing campaign performance. It’s possible to add audiences to a campaign or ad group that uses Smart Bidding. This indicates the audience is important for reaching campaign goals.
Here’s how to set up automated bid strategies with remarketing lists:
Google’s Smart Bidding is a great way to apply audience bid modifiers to your campaigns at scale. But the downside is you don’t have any control over how Google uses your audiences to automate audience bid adjustments.
Google Ads Scripts
Another more customizable option to automate audience bid adjustments is Google Ads Scripts. Using simple JavaScript, scripts are a way to programmatically control Google Ads data. There are many scripts available out there, and some can help you automate audience bidding.
Just keep in mind that if you want to make changes to your audience bidding strategy, you’ll have to edit the script.
Automated Bidding Technology
With automated bidding technology, it’s possible to create bid adjustments for all audience types: Remarketing, Custom Affinity, Affinity, and In-Market. The system uses all your relevant business data, statistical models, and machine learning to dynamically adjust bids and maintain optimum performance in real-time. These granular performance improvements maximize the value of all bid adjustments to drive business goals and revenue.
Automating audience bid adjustments is just one step in a complex series of calculations all aimed at minimizing necessary ad spend and maximizing performance:
Automated bidding technology solves problems PPC managers face with precision, adjusting to market changes, and effectively scaling their programs with the help of audience bid modifiers.
Most PPC managers today understand the value of audience targeting as part of Adwords bidding strategies. But if you want to maximize the value of audiences to improve campaign performance, you need to use Google audience bid adjustments to prioritize the most valuable audiences.
Manually optimizing audience bid modifiers can drive performance, but is limited in scalability. Selecting a strategy to automate audience bid adjustments maximizes the benefits while freeing up more budget and manpower to pursue new growth initiatives.
Most e-commerce advertisers failed to pay attention to Bing Shopping in the past, but things are quickly changing. Bing has made major alterations to their features and user interface to make it more appealing and worthwhile to businesses. Rather than trying to be different from Google Ads, Bing now embraces similarities. They make it easy for advertisers to import their campaigns from one platform to the other.
As an e-commerce business, you have a prime opportunity to reach new audiences with Bing Shopping. If you’re ready to expand your digital marketing strategy, here are nine tips for success with Bing Shopping ad optimization.
Product attributes are an important factor in Bing Shopping. There are a number of them that must be included for your ad to qualify for the Bing Network:
There are also many optional attributes you can include. Some of these optional attributes have a direct impact on how Bing categorizes and displays your products. It’s good practice to optimize your Bing Shopping campaigns by including as many product attributes as possible. You should also consider including:
Implementing all the relevant product attributes can be time-consuming, but it’s advantageous to do so to give Bing the most pertinent information to categorize your products. For example, a shoe retailer that includes optional size and gender attributes - “women’s size 7 US boots” - can make their products much more relevant for queries.
E-commerce advertisers promote a variety of products that drive revenue for their business. Marketers prioritize promoting high-margin products, and this should be reflected in Bing Shopping campaigns as well. Bing offers an opportunity to do this by allowing you to set priority levels for each campaign:
These settings override campaign bid settings. Utilize them the right way, and you can promote all of your products while still prioritizing those that are most valuable. Setting campaign priorities can also help you achieve other goals, such as clearing out excess stock. To maximize the benefits for your business, be sure to set campaign priorities strategically.
Bing makes it easy to set up new shopping campaigns by importing your existing Google Shopping campaigns onto the platform. E-commerce advertisers spend a lot of time optimizing their target keywords in Google Ads while failing to realize that Bing Shopping is a completely separate landscape. You can import your campaigns, but then you must adjust targeting and negative keyword lists to optimize for a different audience.
As a best practice, you should regularly review your search terms in Bing. It can help you to identify important growth areas such as:
Creating your keyword lists and ad groups are not simply tasks for the initial campaign setup. Engage in a constant process of auditing your search terms reports on Google and Bing to reveal opportunities to optimize in the long run.
Generally speaking, you want your ad groups to only include closely related products. Product groups allow you to select products from your Bing Merchant Center catalog to include in specific ad groups. You can organize products into groups using attributes from your catalog feed, namely:
You can also assign multiple attributes to narrow down your group even further:
For example, a children’s toy retailer could create a product group based on brand (Tailspin toys) and the custom label of age (1-5). Using product groups makes it possible to quickly create ad groups and optimize bids for products with certain characteristics.
Your product images are arguably the most important aspect of Bing shopping optimization. Quality images of your product can help your Shopping ads stand out from the competition, improving clicks and conversions.
In April of last year, Bing made it possible for advertisers to add additional images to their product offer feeds. Instead of choosing one key image for your product, you can add up to 11 total images. Take advantage of this feature by showing your product from different angles or with different staging elements. Select one to serve as the featured image for the product and the rest will appear as thumbnails. Images must be bmp, gif, exif, jpg, png or tiff; the recommended minimum size is 220 pixels by 220 pixels.
The Automatic Item Updates feature ensures the availability and price information on your Bing Shopping campaigns always reflects your website. Online e-commerce stores can quickly run out of stock on an item, but still end up serving ads for it. This results in wasted clicks and ad spend.
Automatic Item Updates sync your website’s price and availability microdata with your Bing Merchant Center feed. This way, it automatically updates your inventory data throughout a business day without requiring action from your advertising manager. Employing an automation feature like this can improve the efficiency and effectiveness of your advertising campaigns. Bing will never show ads for a product that is out of stock, and listed prices will always reflect real demand. Based on your needs and goals, you can set Automatic Item Updates to update price only, availability only, or both metrics.
One of the most underused and valuable assets for Bing Shopping ad optimization is custom labels. Labels are attributes that let you organize campaigns, ad groups, ads, and keywords into groups that are important to you.
Custom labels have no effect on how Bing categorizes your products, which is why many advertisers ignore them. Custom labels, though, can help you gain insights and improve targeting in many ways:
Using Bing’s shared labels library, it’s possible to create a single label and add it to different keywords, ads, ad groups, or campaigns. This allows you to create groups that are significant to you across assets, and easily access them using Advanced Search. For example, you could create a shared label called “Holiday promotion” and add it to campaigns relevant to seasonal promotions. Then, to increase the budget for all holiday promotion campaigns, you can filter products based on the label and make the changes.
When you create custom labels based on attributes it’s easy to derive performance insights from them. Say you labeled two different holiday campaigns “Holiday 2017” and “Holiday 2018”. You can run a report to compare the performance of the different campaigns or ad groups/ads associated with them. You can also use labels to tag your keywords as brand name vs generic, or other attributes, then run similar performance reports.
It’s also possible to create automated rules based on your custom labels. If, for instance, you discover generic keywords perform better than brand name keywords from your analytics report, you can create an automated rule to change bids on keywords labeled “generic.” When used the right way, custom labels are a valuable tool to improve targeting and optimize your Bing Shopping campaigns.
Optimizing ads on Bing is an art, especially when it comes to bidding. There are a number of minor changes you can make to your budget allocation that have a big impact on campaign performance. You can use bid adjustments to target specific audiences with your ads and prioritize certain keywords or demographics. Your options for bid adjustments include:
Based on performance insights, you should experiment with different bidding strategies and see which help you reach your audience with relevant Shopping ads at the optimal time.
If you’re advertising in the United States, then you can also take advantage of Merchant Promotions to create more effective Bing Shopping ads. Merchant Promotions are a way for advertisers to highlight special offers in their product ads. These ads have a “Special Offer” extension that display a promotional code.
Merchant Promotions can significantly improve your Bing Shopping optimization by creating a sense of urgency for people to act on the promotion. Special offers help your ads stand out from the competition.
E-commerce advertisers today have a big opportunity with Bing Shopping. If you create and optimize Bing Shopping ad campaigns, it’s possible to reach wealthy shoppers in a marketplace that is much less crowded. Optimizing ads on Bing can be a challenge, though, if you don't approach it strategically. Take full advantage of the strategies and technologies mentioned in this post to get the most out of your Bing campaigns.
A short time after the advent of the Internet, early search engines set the stage for search engine marketing, commonly known today as simply SEM. OpenText Corporation debuted the first pay-per-click ads paving the way for an early form of SEM, but it wasn’t called that yet. In fact, it didn’t even have a name. It wasn’t until technologist and entrepreneur, Danny Sullivan coined the term search engine marketing in a 2001 article on Search Engine Land that the field became recognized in its own right.
A few years after the first PPC ads were launched, GoTo.com began an auction-based system that operates in a similar fashion to how the search engines of today run their paid advertising business. As more devices capable of browsing the Internet came into our pockets and into our homes, people began spending more time on the web, guided to the content they wanted by search engines. These cultural developments allowed SEM to explode in popularity.
But how did we get here? There were many steps along the way. In this article we dive into the history of SEM; how it came into existence and how it has developed into the billion-dollar industry it is today.
To better understand the history of SEM, it’s important to first understand what it means. Over time, the definition has changed: where once SEM was an umbrella term that incorporated search engine optimization (SEO) and paid search, it now stands alone. The term today is used solely in reference to paid search and includes marketing areas like display, shopping, and pay per click (PPC). SEO contrarily is all organic and is based on making changes to websites, specifically content and architecture, on the backend to help ensure web pages rank higher on the search engines.
Upon the invention of computers, the first question was how to connect them. The Advanced Research Projects Agency Network (ARPANET) began working on what we now know as the Internet in the late 1960s. According to History.com, on January 1, 1983, researchers began to assemble the “network of networks” that became the modern Internet.
A need quickly arose of how to search through all the information available. The first well-documented search engine was originally named Archives, later shortened to Archie, debuting in 1990. Created by Alan Emtage, a McGill University student, Archie was used as a way to index FTP archives and it worked by curating a database of webfile names that it would match with queries.
Archie was soon followed by new search engines created at other schools in the United States, namely Veronica which focused on plain text files and a Jughead which worked similarly. These two got their names from characters in a widely popular comic book, Archie Comics. Later in 1990, computer scientist Tim Berners-Lee invented the World Wide Web, and throughout the years that followed websites increased in number and became more prevalent in everyday life.
With the Internet growing by content and reach, more and more information was readily available and people wanted better ways to search and access it. Early search engine companies were working to monetize their businesses and this fueled OpenText, a search engine based in Canada, to run the first pay-per-click ads in 1996. The ads sold showed up on the search results page and were called preferred listings.
Fast forward two years to 1998 - a big year for search - and enter Larry Page and Sergey Brin, two graduate students studying at Stanford and the founding fathers of Google. GoTo hosted a TED presentation about the first auction-based PPC program, discussing their move to auction their results to the highest bidder of a word or phrase. Those paying the most would top the search rankings while lower bidders would be displayed further down the page. GoTo changed its name to Overture in 2001 before eventually selling to Yahoo! in 2003.
In little over a year, Google was processing 500,000 queries per day and at the turn of the Millennium growth skyrocketed when Google became the client search engine for Yahoo! Google Ads were on Google search results beginning in 2000, at first selling as a monthly service to advertisers. In 2004 Yahoo! ended the engagement with Google at a time when it was being searched 200 million times per day.
Google’s advertising system, Google Adwords was launched in 2000 with 350 customers. In 2018 Google rebranded this offering to Google Ads to better encompass the types of ads they work with, and it is today the leading publisher in the search space.
In 2005 Google, Yahoo!, and Bing Ads supported manual bidding which increased SEM’s popularity. According to an old article published by The New York Times, SEM was growing faster than traditional advertising as early as 2006. With new personal computing devices added to our lives and the introduction of the iPhone in 2007 and iPad in 2012, the web became more accessible to an increasing number of people. SEM was no longer tied to the desktop but open to people on the go via mobile or tablet.
SEM began changing as the way people were searching evolved, allowing segmentation between devices and geo-targeting. To assist advertisers, bid automation platforms like Google Smart Bidding were launched and this was later followed by bid optimization platforms. The next trend was incorporating big data in bid adjustments in 2015.
Today, at $40.6 billion, paid search holds the largest share of digital ad spend in the United States and it’s showing no signs of slowing down any time soon. Google’s market dominance in the search space is still maintained today, with more than 70% of worldwide online search requests being handled by Google, making it a significant part of how many people find content on the Internet.
Search advertising has become so pervasive it was even apart of crafting this article. As I write, I have been fact-checking and confirming information by using Google. It was written across three different devices and you can bet I encountered search ads along the way.
An increase in digital advertising spend is projected for 2019 with projections rising from $45.81 billion to $48.49 billion. If recent trends continue, spend will continue rising. While we don’t know exactly what is next for SEM there are some pioneering new techniques in the field such as applying predictive engagement, machine learning, and data science methodologies including natural language processing and bid-landscape data to the bidding process.
One thing is for sure, our devices are here to stay and, with them, SEM. SEM will continue to grow and evolve as our technology does.
During the employee lifecycle there comes a point where it’s time to move on—whether that’s to a new challenge within your current role, a new role within (or out of) your current company, or a totally new career change—is completely up to you. Too often, those discovery conversations are external interviews, versus networking within a current company. How great would it be if you could take a leap or make a career change, without the added risk of starting with a new team or company that doesn’t know your added value?
When employees focus on self-improvement, companies succeed. Review a few tips to consider before changing companies, below.
Chances are, you will not enjoy 100% of what you do every day. It’s always going to be a give and take. However, there are important considerations to assess—are you learning? Do you enjoy the people you work with? We have found that many of the employees who leave Centro have an average tenure of 1.5 years at their next job, with many returning as “boomerang” employees after reflecting on the above questions. Before making moves to see if the ‘grass is greener’ elsewhere, explore your options within your current company first! Making a move within can sometimes be a step in the right direction towards long-term career goals, even if it’s a lateral move instead of a promotion.
We don’t know what we don’t know. Not sure what that next move looks like? If you’re unsure of a particular role and are thinking of switching careers, consider reaching out to other colleagues or team members who have done it, or are doing it currently. Search your company intranet or directory—look for titles that pique your interest and reach out to those people; set-up a time to connect via phone or over coffee. Ask them about their position and what it entails; what do they enjoy or find challenging? Discuss the day-to-day, so you can determine if it may be a fit for you.
Every role requires some kind of subject matter expertise. Find a subject you enjoy that pertains to the role and learn more about it! For example, if you decide you’re interested in HR—take an online course about employment law, read articles about employee engagement and retention, or attend an event that caters to that specific industry. Ask questions, learn from peers, and reflect on your new skillset. Did you find the subject matter engaging? Or did it make you want to take a snooze? Pay attention to those insights, as they could potentially lead you to something great.
Once you have reflected, networked and done your research—make a mental commitment. If you decide a career change is what you need, then raise your hand; talk to your manager or executive leadership to express your interest in another opportunity at the company. Stay engaged in your current role to ensure consistent performance, and work with leadership to see what options may (or may not) be available at your current company—make an informed decision.
If you’ve determined that you’d like to stay on your current career path but are feeling unfulfilled in your current role, identify what it is that is making you feel disengaged. Are you not learning at the speed you were hoping? Is your manager not accessible? Take change into your own hands—seek out the challenging work and collaborate with those that bring you positive energy. Talk to your manager to see how they can better support you in this journey.
There may come a time where you and your manager decide that your current company may not be able to bring you what you’re looking for. In this case, you can feel secure and confident in knowing you’ve assessed all options to determine the best path forward and move into the next endeavor with a clear mind and fresh slate.
Over the course of the last few years, marketing automation has become so sophisticated that it’s essential for success in today’s digital landscape. The benefits of automation are many: time savings, better audience targeting, better performance attribution, the elimination of wasted spend, driving increased revenue… the list goes on. The key to success in Google Adwords automation today is less about what you should automate, but how. In this article, we offer a complete overview of the best solutions for automating SEM in 2019.
Google AdWords (recently renamed Google Ads) is a frontrunner in developing solutions to automate and optimize advertising. They continue to roll out new tools that help marketers automate their PPC and display advertising efforts. While the key decisions are best made by PPC managers, the internal automation features of Google Ads can empower you to discover new targeting opportunities, improve ad performance, optimize bid strategies, and more. The growing list of Google Adwords automation features advertisers can take advantage of in 2019 include:
Responsive Search Ads
Responsive Search Ads, or RSAs, are a major new form of automation Google Ads rolled out in 2018. They’re still in beta and only available in a handful of countries. However, you can expect they’ll grow in use and importance in 2019.
RSAs can be likened to messaging optimization technology. For each ad you provide, multiple headlines and ad descriptions can be used in combination. Google automatically displays and tests different versions of your ad, using up to 15 headlines and four descriptions for each ad. This allows them to identify the content most closely matched to the search queries your target audience uses.
Smart Campaigns
Smart Campaigns are the new default campaign type when you sign-up for Google Ads. They’re designed to help small, location-based businesses optimize their advertising campaigns.
With this campaign type, you create your ad text and set a budget, then Google helps you with targeting. Smart ads appear when people in your target geographic area search for phrases related to your business on Google or Google Maps. They can also appear for people who search for terms related to your business and business location. Advertisers can forgo the default Smart Campaign option to choose which aspects of their strategy they want to handle manually or through automation.
At the time of writing, Smart Campaigns automate targeting and goal-based bidding. In the future they will also automate landing page generation based on Google My Business (GMB) data. This will be a valuable feature for businesses that don’t have landing pages on a native website.
Goal-Optimized Shopping Campaigns
The second major automated feature Google Ads launched in 2018 was goal-optimized Shopping Campaigns. This new campaign type automates ad creation and bidding, saving advertisers time on campaign management and optimization. All you have to do is set a specific marketing goal and Google will optimize your campaign to achieve it. Using automation and machine learning, Google can predict which search queries are the most relevant to your products. Google then presents your ad accordingly in search results, on the display network, YouTube, or Gmail.
Their algorithms take a number of signals into consideration simultaneously, including product characteristics, time of day, browser, geolocation, past search habits, and more. Realistically, goal-optimized Shopping Campaigns are able to make targeting decisions that would be impossible for a PPC manager.
AdWords Automated Bidding
Automated Bidding has been the most valuable AdWords automation feature for advertisers since its launch. Day-to-day practitioners don’t have time to manually adjust the max CPC for individual keywords to optimize their campaigns. Automated Bidding can take care of this task, optimizing max CPC based on specific goals. Google ads offers six major bid strategies based on different marketing goals:
Smart Bidding relies on machine learning and your chosen bid strategy to set the right bid for each auction. It also factors in important signals at auction-time, including location, time of day, device, remarketing list, and more.
Local Campaigns
Local Campaigns is another new automation feature that helps location-based businesses promote their stores and products in search, Maps, YouTube, and on the Display Network. Advertisers provide ad copy, a bid, and a few assets and the rest is automated. With the singular goal of driving in-store conversions, Google automatically optimizes ad placement, bids, and asset combinations. When people use Google Maps or local search to find businesses, your ads can appear based on your location and relevant queries. Local campaigns can even automatically display product discounts or other assets to maximize conversions.
Universal App Campaigns
Universal App Campaigns have been around for a while, and they’re one of the few fully automated advertising options on AdWords. With these campaigns you can choose between two goals: drive more app installs or more in-app conversions. App campaigns can automate:
Ad creation - It pulls information from your app store listing to create text ads. Google systems automatically create different ad versions and test to see which perform better.
Targeting - Google automatically displays your ads on different networks for the right audience based on your goals. They match your ads to relevant search terms and ads can appear on Google Search, Google Play, YouTube, the Display Network, AdMob, and more.
Bidding - Google will optimize bidding based on your marketing objectives: more installs, driving in-app actions, or driving in-app action value.
Other Features
These are just a few examples of the many Adwords automation features that advertisers can employ this year and beyond. Others include:
Dynamic Search Ads - Create targeted ads using Google's index of your website.
Automated Rules - Make account changes automatically using conditional settings. Change your ad status, budget, bids, and more.
Google Ads scripts - Use JavaScript code to automate changes in your Google Ads account, such as adjusting bids, pausing ad groups, and adding keywords.
Recommendations - These suggestions to improve your campaigns automatically analyze performance and derive insights for you.
The list will continue to grow. The options your business should choose depend on your niche, strategy, and many other factors. Businesses that take full advantage of Google’s automation features are well-positioned to optimize performance in 2019.
Google is encouraging automation as a default setting across the platform. However, as more businesses employ these features, it will become more difficult to stay ahead of the competition. What many advertisers don’t realize is that there are various automation technologies beyond what Google Ads has to offer. These unique solutions make it possible to better optimize ad creation, targeting, bidding and a whole lot more.
Here are some of the many benefits of using third-party tools for AdWords Automation in 2019:
Comprehensive Data Analysis
Google AdWords automation utilizes all the relevant PPC data in their arsenal to automate insights and optimize campaigns for their advertisers. However, consumer digital footprints reach far beyond Google properties. There’s so much more data relating to market trends and audience behavior that advertisers can use to create and optimize their advertising campaigns. It doesn’t matter how great your automation algorithms are if you don’t have the deep, quality data to analyze.
There are a great deal of internal and external factors that can impact the value, relevance, and targeting of your PPC advertising campaigns. If you want to truly maximize campaign performance based on data insights, you must be able to analyze and automate decisions on a centralized platform. Third-party automation technologies can use unified data analysis to make smarter bidding decisions for your efforts on Google, Bing, and other advertising platforms. Powerful solutions can use third-party data, offline information, and other deep funnel metrics, such as:
Unified data analysis empowers you to get a clear picture of the whole customer journey, the state of your business, and other important market factors. You can use this information to accurately infer the likelihood a click will lead to a conversion, and the value of that conversion.
Nuanced Bid Automation
Google already has sophisticated bid automation capabilities, leading many advertisers to ignore the third-party solutions out there. Yet while Google does allow you to customize your automated bidding by choosing one of six strategies, third-party solutions go the extra mile and offer more nuanced options that you can customize to your complex business goals.
In the real marketing world, there’s no single key performance indicator (KPI) that fully illustrates your progress in achieving a marketing goal. Instead of choosing a single metric for bid automation, the best third-party solutions allow you to use a custom combination of KPIs such as conversions, profit, or revenue.
You can also choose exactly what data you want bidding algorithms to utilize to calculate adjustments. Use integrations with other business tools or database upload to incorporate any relevant data into the system, including all publisher data regarding costs, Campaigns, Ad Groups, Keyword Type, historical revenue, deep funnel or offline revenue data, and more internal metrics.
Real-Time Adjustments
Google stress the importance of targeting micro-moments with your marketing message. Micro-moments are, they say, “intent-driven moments of decision-making and preference-shaping that occur throughout the entire consumer journey.”
In order to deliver the right marketing message to the right audience at the right time, you need to be able to act quickly on your data insights as they come in. Advertising automation technologies with machine learning capabilities can understand the intentions behind audience behavioral data and make quick changes to take advantage of them.
Solutions that take one or two days to incorporate new data into your bid calculations are going to fall behind. If you want your advertising strategy to stay competitive, you need to use best-in-class technology that identifies and acts on data insights in real time. Making instant adjustments to your AdWords campaigns greatly improves the efficiency and precision of your efforts. You can gain more opportunities and make your ads more timely. These quick decisions also help reduce wasted ad spend because you never operate without the latest data insights on hand.
Historical Performance Insights
Maximizing AdWords performance isn’t just about acting on changes and opportunities in your recent market data. How your advertising campaigns have performed in the past can provide major insights to improve your current efforts. By aggregating audience and performance data in a centralized platform, you can identify patterns in market behavior and advertising strategy.
You’ll be able to answer questions like:
Historical performance data is particularly valuable for bid optimization. Using the data and context of your past performance, automated bidding platforms infer future performance and make changes to maximize business value.
There are many solutions that keep and utilize a limited amount of historical data that can inform strategies moving forward. To gain the most value, though, it’s important to store and fully utilize all the past performance data available. Using machine learning technology, automation can improve progressively when it comes to understanding future bid optimization opportunities and make necessary adjustments to take advantage of them.
This is called predictive analytics, and it’s nothing new. The finance industry has been using statistical models of past historical data to effectively predict market changes for decades. Applying it to the advertising industry allows you to effectively see around corners and make quick decisions to maximize performance and stay ahead of the curve.
Full Automation Capabilities
Most advanced AdWords advertisers understand that they cannot automate certain aspects of their optimization strategy. They pick and choose which aspects they want Google’s automation features to handle, then make manual changes when necessary. For example, they can make manual bid adjustments after considering historical performance data that Google’s automation technology doesn’t factor in.
But when you combine a complete, quality data set with a decision engine based on machine learning technology, it’s possible to fully automate a much larger number of processes. The volume of actionable data available today greatly exceeds what a marketing manager or a whole team of data scientists can humanly process. That is not to say that PPC managers are being rendered obsolete. It simply means they can spend more time identifying new opportunities for growth. This makes full automation capabilities even more essential for SEM success.
Google Ads continues to develop a wide range of new automation capabilities that smart marketers will take advantage of. But all the useful data insights you need to drive automation success can’t be found on Google properties. If you want to stand out from the competition (who are also adopting automation at an alarming rate), you need a technology that can maximize data insights for nuanced campaign optimization.
When it comes to improving quality of life and work, most think about reducing stress and increasing productivity. But how? Keeping a diverse exercise routine is a fantastic way to ‘kill two birds with one stone.’ Below are five exercise activities that can significantly improve your work/life blend.
Group classes are a great way to try something on to see how it feels and connect with your community while contributing to your health. Grab a friend and hop into a yoga, martial arts, or kickboxing class—all of these activities boost the immune system, foster positivity, build self-discipline, and clear the mind. Cycling, aerobics, and HIIT are some other great examples that will increase your heart rate.
Get outside! If you live in a big city, you know just how refreshing it can feel to take a break—whether you take a long walk or play frolf (frisbee golf) in the park, or just step outside—whether that’s for a quick few minutes of fresh air or a week-long trip, it is always a good idea. Create a team or join a league—softball, kickball, flag football, you name it! Live in the Rocky Mountain area? A group trip into the hills, trees, snow, and sun on a board or ski can also provide peace of mind and a great workout.
Save time and money – by working out from the comfort of your own home! Whether you invest in P-90X, an online yoga video subscription, a set of free weights, or – go big – and spring for a Peloton, you can bail on that 40-minute round-trip commute. All too often, the hardest part of going to a gym is actually attempting to get out the door—working out at home takes out an additional layer of morning stress, and makes the whole process that much easier.
Is there anything more exciting than accomplishing a challenging feat? Ask anyone who has scaled a 14,000 ft mountain or run a marathon—devotion to a goal that pushes your limits further than you could’ve ever thought possible, is usually a goal worth pursuing. Joining a 5K for a cause or running a marathon in support of a friend or family member makes it all the more rewarding.
When it comes to workout form and spinal alignment, a personal trainer can be your new BFF. Target and activate different muscle groups and learn new methods or variations. Keep an open mind, and then bring that mindset into the workplace! Your self-discipline, clear mind and broad vision and will take you far in both lines of interest.
We understand that taking care of employees goes far beyond a paycheck. Centro’s ‘Buff to Get Buff’ Program reimburses employees for fitness-related expenses such as online/offline exercise programs, personal trainers, group classes, and race and team sports fees—ski passes are included too! What new types of fitness can you add to mix-up your routine? Learn more about Centro’s other benefits and current open positions here.
Employing Google Shopping has become a dominant advertising strategy for retail businesses in recent years. Early adoption was slow, but now Google Shopping ads make up 76.4% of retail search ad spend and receive 85.3% of clicks from Adwords or Google Shopping campaigns. There are many opportunities for retail businesses to gain visibility and drive sales of their products using Shopping feed optimization techniques. But it isn’t challenge-free.
Google Shopping has become so popular that the market is already saturated. Every retail marketer has a number of strong competitors they’re fighting against for rank and visibility in search results, and this competition is only set to become harder as more retailers enter the market.
In the past, the most expensive and competitive keywords were bottom of the funnel, suggesting shoppers had immediate purchase intent. Today, though, many advertisers target high-funnel search queries, driving up competition across the sales funnel. It’s no longer possible to save your advertising budget by targeting different points of the buyer journey. Everyone’s fighting for ad space, and it’s not going to get any easier.
Google has done an excellent job in recent years of catching up with Amazon in the retail search-advertising space, and they continue to roll out new features that make it possible to surpass them. A good example of this is Shopping Actions. Retailers who opt into this program can have their ads appear on Google Express, Google Search, and Google Assistant.
As more search advertisers start taking advantage of features like this, the landscape is going to become more competitive. Simply jumping on each new feature bandwagon Google introduces won’t be enough. The one thing that can relieve this issue is developing a feed optimization strategy that outperforms the rest.
The good news is that there is a long list of ways to optimize your Google Shopping Feed, and very few retail search advertisers are taking advantage of them all. The best way to stand out in a crowded marketplace and outperform the rest is prioritizing Shopping feed optimization. Here, we outline some essential techniques you need to be executing.
Your product images are one of the most important Shopping feed optimization techniques to focus on. They appear prominently in search results and can have a huge impact on click-through rate, or CTR. Including quality, relevant images alongside your products is just good e-commerce practice, whether it be on your website or in your Google Shopping Ads.
Here are some quick tips for your images:
You can also try out different kinds of images and test which ones perform better. For example, you can compare the performance of basic white-backdrop product images versus lifestyle shots.
Your product titles are another valuable element to consider. It’s important to include keywords as part of your product title, as this impacts what search queries your product will appear for. Your product title is also the most prominent aspect of Google Shopping results besides your image. Including relevant keywords in the title also helps search engine users feel like they’ve found what they’re looking for.
One thing you’ll want to do is ensure your product title includes a target keyword towards the beginning. But, there are other strategies you can use to optimize your product titles further. For example, you can include your brand name in titles to appear more relevant for branded keyword searches. Or you could include other details people might search for, such as size, color, material, etc.
You need to choose a single strategy here or risk creating long and unruly titles. Use insights from keyword research to determine what information is most important to include in your product titles.
A lot of advertisers don’t see the value in organizing their product types because they don’t have a direct impact on how Google categorizes and ranks products. But they are a powerful tool you can use to understand the performance of the different kinds of products you offer and make changes to your strategy accordingly.
First off, if you use your e-commerce tool (e.g. Shopify or Woocommerce) to generate product types for you, there are going to be some errors. Some products will be miscategorized, or you could end up with duplicate product types. Take the time to go through and fix these errors: it will be worth it for the insights they provide.
Divide your product types into clean, logical categories, then start using this as a factor when monitoring campaign performance. Error-free product categories can offer unique insights into performance improving opportunities that you may not discover otherwise.
Most ecommerce retailers today don’t take the time to create unique descriptions for their products. They stick with manufacturer default descriptions or use the same generalized description for a wide range of product variants.
Just like your product title, the description is another way Google can understand what your product is relevant for. They’ll also highlight keywords in your product description that match user search queries. Ensure that you include specific information here so you can outperform competitors that take the trouble. You should:
Using product categories as a data feed attribute is entirely optional, so most advertisers don’t use it or only select the most general category descriptions for groups of products. For example, a sporting goods retailer selling sports uniforms could categorize their products as:
Or as:
Most search marketers don’t go this granular because it’s a tedious task. But it’s worthwhile if you want to help Google fully understand what kind of queries your products are relevant for.
The good news is if you already did the hard work optimizing your product types, then it will make choosing your product categories much easier. You can download your feed to a spreadsheet, sort by product type, and then start adding in product categories in a new column.
GTIN is the acronym for Global Trade Identification Number. This identifying number shows Google that a product is unique. In some cases, Google requires a GTIN before approving a product for Merchant Center, but not in all cases. If you haven’t been using GTINs for your products up until this point, you might want to reconsider.
Using GTINs opens your products up to new opportunities to gain visibility in search results. If a number of retailers sell the same product, Google can categorize them together in the same auction based on the GTINs. This opens up the possibility for your ad to appear as the sole result for a Product Listing Ad for high funnel search queries. Google also often displays a banner of Google Shopping results for queries like “best of X” or “top X.” Your ads will only qualify for these results if you include GTINs.
One of the most essential aspects of Shopping feed optimization today is automation. Every Google Shopping campaign draws information from your merchant feed, made up of structured data about what products you offer. Managing this information in a spreadsheet only works for the smallest businesses. It quickly becomes unruly when you have more than 20 products, let alone hundreds or thousands.
Google Ads developed automated feeds as a solution to this problem. Automated feeds essentially scrape your web pages to see what products you currently have on offer, then automatically generate relevant feed information based on this data. Automated feeds are extremely important for campaign optimization. For example, you can avoid wasting ad spend promoting a product that’s not currently in stock. Automated feeds can interpret stock information from your website and automatically update your campaigns to reflect this.
Automated feeds are the most beneficial when everything on your website is accurate. Otherwise data feeds can include broken links, improper product titles, and other issues. You can also end up including poorly performing products in your advertising campaign inadvertently.
At this point, you’re well aware that Shopping feed optimization techniques can be operationalized in different ways. There are different ways to optimize your product title, description, product categories, and more. If you really want to create the most optimized feed for Adwords, you should take the time to test different strategies.
Even if your Google Shopping feed is created automatically, it’s easy enough to create additional feeds to compare performance. “Supplemental Feeds” are a unique type of feed you can create to have standalone data on performance. You can’t add or remove products from them, but you can duplicate a primary feed then make changes to that existing data to test feed variations.
Supplemental Feeds are a powerful tool with which to experiment on performance data and understand what elements of your feed are most effective. You can also take advantage of custom labels within your Supplemental Feeds to drive even more insights. For example, you can use custom labels to group products in ways that are significant to your business, such as new versus old products, price categories, sale versus full price, etc. The performance insights you gain from Supplemental Feeds can inform mass changes you make to your primary feeds to improve campaign performance overall.
Put simply, automated bidding is essential for keeping up with the competition. Automated bidding allows you to bid more effectively and take advantage of micro-changes in the market. This simultaneously reduces neccessary ad spend and improves campaign performance.
Google offers automated bidding options for Shopping campaigns that you can set based on your campaign’s historical performance and future goals. Or you can rely on Smart Bidding to target overall performance for you.
Choose an automated bidding strategy that helps you beat out the competition in the areas that matter most for your business. And if Google’s preset automated bid strategies don’t match your current goals, third-party tools can.
Merchant Promotions is one of the Shopping feed optimization techniques with the most obvious performance benefits. Merchant Promotions is a feature that allows you to add special discounts, free shipping, or free gifts to your Shopping ads.
Once you submit a product feed to Google Merchant Center, you can start creating promotions. Create and optimize your Merchant Promotions so you can drive conversions, boost CTR, and attract more traffic.
There are always ways to improve your Google Shopping feed. Every time you add a new product to your ecommerce store, there’s a new opportunity for optimization. There’s no getting around the fact that ongoing feed management is essential if you want to stay competitive as a retail search advertiser.
Advertisers have two options when approaching their Google Shopping feeds: either take on the necessary leg work to create the most accurate and optimized data feed, or use automation technology to stay ahead of the game. Google Ads provides some internal solutions for automated Shopping feed management. But there are also a variety of third-party feed management tools that can provide advanced insights and optimizations. Invest in automation technology and use it to its full potential. This ensures the payoff outweighs the cost and drives business growth through retail search advertising.
It’s well established that landing page design impacts many facets of an SEM program's success. While we've previously discussed how to optimize overall design to secure more leads, ensuring your landing page is aesthetically pleasing and clearly articulates your message is only one piece of the puzzle. Before a user even clicks on your ad, various aspects of your landing page are factored into whether your ad is served, the amount of the required bid, ad placement, and, in some cases, ad quality. After clicking an ad, the user flow and prominence of conversion actions impact not only your bottom line but also the bidding insights and optimizations.
Let's dive into each of these.
First, before we dive into landing page relevance, we need to first discuss how Google ranks your ads. Each time one of your ads is eligible to compete in the auction, Google computes an ad rank for your ad and all others competing. The rank your ad receives determines whether it will be displayed, what position it will be displayed in, and the cost per click (CPC). While the exact formula is a closely guarded secret, the key inputs include your max CPC, the ad's Quality Score, search context (e.g. location, device, time, etc.), ad rank threshold (i.e. the minimum bid required for an ad to appear in X position), and the expected impact of ad formats and extensions.
While some of the other inputs are more straightforward, Quality Score is significantly affected by the quality of your landing page. Reported on a scale of 1-10 (with 10 being the most desirable), landing page relevance and experience are two of the components taken into consideration, along with ad and keyword relevance and quality. Thus, as Quality Score is factored in along with your bid and the other inputs to determine ad rank and CPC, you’ll also want to obtain a higher Quality Score for your ads to both improve their position and reduce CPC, all of which will lead to overall efficiency gains.
Now we can focus on landing page relevance. Imagine you are looking to buy a new collar for your dog. You then search for "skulls and crossbones dog collar" and click an ad. How likely would you be to stay on the site and buy something if you were taken to each of the following pages?
Most people would be more inclined to continue through the conversion funnel in experience A and maybe, B versus C or D. This difference in relevancy would then be reflected in the ad's Quality Score.
Outside of relevancy, page loading speed is also another major factor to consider. What if you ended up on landing page A but it took 15-20 seconds to load? Loading times of more than a few seconds are likely to see marked user drop off, even if all other best practices are followed, resulting in a much lower Quality Score.
While difficult to objectively measure, it is also worth considering how very general landing pages with multiple, branching funnels and calls to action can make insights and optimization more difficult. Take, for example, a company that sells enterprise software. They have determined through analyzing past sales performance that filling out a "Contact Us" form is most likely to lead to a follow-up conversation with a sales rep and ultimately a purchase. However, rather than investing in a streamlined landing page experience that has this call to action prominently displayed, all ads redirect users to the website's home page.
Given the clear benefit to the company for prospective customers to fill out the "Contact Us" form, it would make sense to optimize bidding toward that conversion action. However, all too often, the numerous potential paths for potential customers to get to “Contact Us,” and the competing calls to action on the homepage make that difficult, regardless of the bidding solution used. For example, a user located in Los Angeles searched for "keyword A" and upon arriving at the homepage, clicked through a few product pages and then left. Does that mean that users located in Los Angeles are less likely to convert and negative geo modifiers (i.e. decrease bids by 20% for searched from the Los Angeles metro area) should be added? Or is "keyword A" too broad of a term to lead to many conversions and should be bid down? Or are both actually good targets but the lack of a clear call to action (or too many calls to action) led the user down too many or a less-than-ideal path? By introducing the confounding variable of poor design, none of these questions can be answered with certainty, which in turn, can lead to suboptimal bidding decisions and lost potential efficiency gains.
Conversely, imagine if the landing page for the software company mentioned earlier offered a more tailored experience with some basic product info that related to the ad clicked while clearly displaying the “Contact Us” form above the fold. Any insights related to the keywords, locations, or audiences that have a higher propensity to convert would be more reliable and more likely to lead to an overall increase in performance.
While landing page relevance and quality impacts overall PPC efficiency, there are some areas of PPC that have additional idiosyncrasies -- Dynamic Search Ads (DSAs) are a good example.
DSAs, ads which are automatically generated based on landing page content, are a great way to discover additional keyword opportunities and scale creation of highly-targeted ad copy. Rather than requiring you to create a preset keyword list, DSAs instead leverage Google's crawling technology to mine your website for relevant keywords and automatically use them for ad targeting and ad copy. However, as Google typically crawls sites every 2-3 days, frequently changing landing pages can lead to irrelevant traffic and inefficient spend for DSAs.
A common example of this problem, often cited by Google, are daily deals sites. For example, a particular URL that is crawled on Monday may offer a deal on a trip to Europe. However, when a user clicks on a DSA generated from this page on Tuesday, it has been replaced with a trip to Las Vegas. Given that the landing page experience is now unrelated to the ad the user clicked on, conversion is much less likely and often spend becomes inefficient.
While many components go into building a successful SEM program, landing page design is one area that is often overlooked. But as a critical pathway to your site and business, neglecting efficient landing page design will likely cost you leads, conversions and ultimately revenue. Rather than directing users to general areas of your website (like the homepage!), invest time in creating a more relevant, well-designed user experiences. For sites with a large inventory, newer tools like dynamic keyword insertion can be leveraged to make this process less time-consuming.
By making this investment upfront, you can improve your ad's Quality Score, obtain more reliable insights, make better optimization decisions, and understand if particular PPC functionality is appropriate for your use case. And you will also be giving your targets a clear path to entry -- all benefits that will help you to increase efficiency and have the most successful PPC program possible.
One of the oldest and most common ways of storing information is text. Humans have used text for thousands of years to record data long before the existence of Microsoft Excel or databases. Today, most information in an organization exists as text documents, such as emails, Google documents, or even post-its on the wall. That's where Natural Language Processing, or NLP, comes into play.
NLP is a branch of data science. Its main purpose is to turn text (and speech) into structured data to obtain actionable insights. The ‘natural’ in NLP is a contrast to ‘unnatural’ languages used by computers such as C++, javascript, python, etc.
NLP has several applications but can be grouped into two main categories:
Both of which are of incredible use for the largely text-based SEM industry. For SEM, you can use NLP for tasks such as search term reports and keyword expansion tools. Both tasks leverage NLP technology to analyze search queries, detect associated keywords and then suggest related keywords. Other, more complex uses of NLP involve generating audiences based on search term content or forming a baseline bid for long-tail keywords.
Phrase Segmentation
The first step involved in an NLP process is phrase segmentation. Specifically, NLP breaks the phrase down into sections, typically using full stops or commas.
Tokenization
After that comes tokenization, which is a fancy way of saying that we are going to “define the unit of the language”. In the case of English, that means a word that can be easily separated because it is contained between spaces. Then comes a first-grade refresher: deciding what type of word -- verbs, nouns or adjectives -- we are talking about. Tokenization does this easily for certain words such as car. However, it might need context when a word has multiple meanings such as bitter or fair.
Lemmatization
After that, we go to lemmatization, which means drilling down a word to its base form. Some words can vary from the root word, like geese and goose; lemmatization essentially tracks down the base word associated with all of those variations.
Remove Stop Words
From there, we remove stop words or filler words. These are stock words that don't really add any meaning to the phrase itself such as and, is, and, the. NLP removes these words to reduce the noise while interpreting the phrase.
Machine Learning
The following step is perhaps the most complex: using machine learning to understand how each component of the phrase relates to the others.
Noun Recognition
Once we have moved past the grammar portion of this process, the NLP funnel moves into noun recognition, which splits the phrases, but uses nouns as segments to extract information. It works like this: say our NLP system has detected nouns like “EU” “Trump” “California”. Our Named Entity Recognition algorithm (as it is technically called) recognizes that California and EU are geographical locations and that Trump is an American politician.
Coreference Resolution
The final step of the NLP funnel is coreference resolution, which aims to understand pronouns. While humans can determine through context to which noun the pronoun refers, it becomes trickier for a computer.
NLP is not without its challenges. Computer programming is based on understanding the literal meaning of structured languages. Transitioning structured languages to understand unstructured natural language with contextual reference, metaphors, spelling mistakes and all the idiosyncrasies contained in our written and oral communication is a huge leap.
Take, for example, the following headline from a major news publication: “Labor admits Brexit could lead UK to freefall.” A literal interpretation of this phrase is that the physical act of work (labor) has somehow gained consciousness and admits that were Brexit to occur, the entire physical United Kingdom would somehow be sucked into space and dropped off of earth's gravity. Of course, through context and social understanding, we immediately know the real meaning of the phrase. But we only acquire that understanding through years of practice interpreting and reading between the lines. Only context gives the phrase the meaning it really has: that a political party admitted to a potential economic impact were the UK to sever from the EU.
Here’s the problem: the computer not only has to understand the literal meaning of every word (even such terms as UK or Brexit which are acronyms, or terms not present in the English language), but it has to derive the potential contextual meaning from the combination of words in the phrase.
A whole spectrum of new developments are possible thanks to NLP. For example:
NLP also enables a new generation of search engines in which the user searches as they speak, eliminating keywords and topics (this is already present in Apple’s Siri and Amazon’s Alexa). The potential of NLP not only looks to the future but also to the past. Once NLP is sufficiently powerful, researchers can use it to analyze all the text data acquired from past activities, thus creating a sort of backfill for all the unstructured data that we have accumulated.
NLP is a branch of data science that uses a series of steps to segment and extract information from text and speech. It aims to solve limitations in software that understand only formal or structured data. Text or language is ‘unstructured,’ so converting into ‘structured’ allows us to convert a collection of information into actionable insights. And it’s becoming a valuable tool in SEM.
NLP tools are flooding the SEM industry for such functions as keyword expansion, search query analysis, predictive search, and voice search. And this is just the beginning of its many use cases. Going forward, we will leverage NLP in new, innovative ways, further bridging the gap between human language and computer data.