When someone is brand new to remarketing, they typically start with an “all visitor” audience. This is not a surprise since “all visitor” audiences are a default audience in Google AdWords. Then as we get more experienced, we realize we can create audiences based off of other pages, YouTube actions, mobile app actions and more. But as Google’s technology evolved, so did the remarketing capabilities within AdWords and Google Analytics. What’s my favorite tool to help build better remarketing audiences? It’s an easy answer. It’s Google Tag Manager.
Not only does Tag Manager save time by allowing me to add all of my tracking codes in one location, but I can easily set up a variety of events to track in Google Analytics. Any event recorded in Google Analytics can be used to create an audience for you to use in RLSA or display remarketing campaigns. This glorious arsenal of user data -will give you a better understanding of user intent on your website and allow you to create remarketing ads that speak to the exact action the user took.
If you’re not familiar where to create remarketing audiences in Google Analytics, here are the steps.
When we remarket to page visits, we’re also remarketing to the visitor who was only on that page for 5 seconds and never came back. When we remarket to actions or engagements valuable to my business, I can try and guide that user to the next step of the funnel. Let’s see a few examples of tags we can create (with the help of some smart people) to help set up intent-based remarketing campaigns.
LunaMetrics has helped me out on this one. They have a very easy guide on form engagement tracking in Google Tag Manager. In just four, easy steps you will be able to see how many people started to fill out your forms, but never completed the task.
In the image above, we can see this form had over 2,000 people start to fill it out but never completed it. Those people are defined under the Event Action of “skipped.” We can then head over to Google Analytics and create an audience for those unique users.
Now you might be thinking, “Why don’t you just create a remarketing audience for users who visited the contact us page?” Fair question. Here is why I’d choose this approach. Who do you think is a more valuable lead? The person who visited the page or the person who started filling out a form? I’ll choose the latter any day. And because the user started the process of reaching out to the business, I’m comfortable choosing a more aggressive ad message since the user is further down the funnel than a first-time visitor.
After Hours Mobile Click-to-Call
Take a look at this mobile click button…
We can clearly see the hours called out by the phone number. When we look at the analytics, however, we can see many people still call during off-hours. Yes the company has an answering service so people can leave a message, but I want them to convert ASAP.
Using Google Tag Manager, I created an event to track every click on this phone number from a mobile device.
I then went to Google Analytics to start creating the first of two remarketing audiences. You’ll see why we need two audiences in one moment. After the Event Label information is entered, I added an extra filter for “Hour.” (As of the date of this post, Hour is the only time filter we can use in Google Analytics so I won’t be able to filter out Sundays completely.) First, I added the Hours in between 0 (midnight) and 7 (which will end at 7:59 a.m.) for the first set of off hours.
After the morning off-hours audience is saved, I created an off-hours audience for the evening with the Hours changed to be in between 18 (6:00 p.m. military time) and 23 (which will end at 11:59 p.m.)
After my two off-hours audiences are implemented in my campaigns, I can then show those specific users ads similar to the following…
What’s the biggest fear for someone who’s snowblower is broken? It’s going to snow again. I’m using some scare tactics here to get the user’s attention. And since I know the user already tried to get a hold of me, I’m letting them know if they contact us, they’ll get a quicker response in hopes it steers them in the proper direction.
Time to play devil’s advocate again. You might be thinking, “If you have good customer service, won’t you call the user back?” Great question, but here are a few reasons why you’d want to keep pursuing those users.
People Who’ve Watched Videos Embedded on Your Site
AdWords already offers remarketing capabilities from YouTube videos. Here is a list of the current options we have.
While this video targeting is great, you can only use it if you have your YouTube channel linked with your AdWords account. I want to take my video remarketing lists one step further. Maybe you have other people’s videos embedded on your website. Or maybe you just want to remarket to users who engaged with the videos on your landing page. With the new YouTube video trigger released in the fall of 2017, we can now capture those interactions. Let’s take a look at just one example of how you can set up video trigger.
Are you geeking out like I am? Of course you are. We can now capture when a user plays the video, when a user pauses the video, when the video buffers, and how long they watched the video (in either percentages or seconds). We can also choose to capture actions on all embedded videos.
Your YouTube remarketing audience is complete! If you have the ability to create or showcase a lot of great video content on your site, then you’ll have no problem creating relevant remarketing audiences. Different ad groups for each video remarketing list will allow you to change your ad text to include a relationship with the video those users watched to have a better connection with your audience. If you want to set up video audiences like the one I mentioned, check out Simo Ahava’s post on the YouTube Video Trigger.
If you love remarketing, and we know you do, make Google Tag Manager your new best friend. You’ll find a treasure chest of new ways you can segment your remarketing audiences to test out new user behavior. I only showed you three, easy audiences you can create from event tracking. Let me know @MilwaukeePPC if you’ve had success with event remarketing audiences or have any questions on the set up.
I read a quote once about fearlessness that said, “F-E-A-R has two meanings: ‘Forget Everything and Run’ or ‘Face Everything and Rise.’ The choice is yours.” Since leaving Marketing Nation Summit, where we were given all the building blocks we need to be Fearless Marketers, it has been our mission to remember what we learned and take it to heart as the year marches on.
When we announced the Fearless 50 program, we tasked ourselves with searching the world for marketers who exemplified what it means to be bold, brave, and fearless. Who would have thought when this idea was hatched that the nominations would flood in the way they have? We were humbled to read every incredible story that the Marketing Nation submitted to us and narrowing it down to select just 50 members was almost an impossible challenge.
After poring over countless inspirational nominations and long deliberations, it is our pleasure to announce the second half of the inaugural class of the Fearless 50:
Personal and professional acts of fearlessness should not only be recognized but celebrated as shining examples of what we all should aspire to be. One of our Fearless 50 members, Maria Pergolino, CMO of Anaplan, shared her excitement, “I’m honored to be a part of Marketo’s inaugural Fearless 50. Being recognized amongst such amazing marketing professionals inspires me to continue to be fearless in Anaplan’s marketing efforts, developing new methods, and driving results.”
While the inaugural class of the Fearless 50 has come together, there is more work to do. We look forward to sharing the stories of these 50 incredible marketers and continuing to inspire the Marketing Nation to approach each day with fearlessness and bravado.
Fearlessness isn’t a personality trait, it’s a state of mind. We can choose to follow in the footsteps of these 50 bold marketers whose names will go down in Marketing Nation history, and, if we do, we will never view fear as “Forget Everything and Run,” but as “Face Everything and Rise.”
Marketo is proud to welcome the inaugural class of the Fearless 50—please be sure to check out our blog post that announced the first 25 members as well! And we thank our Fearless 50 program sponsor, PFL, for joining us on our quest to find the world’s most fearless marketers.
The post The Final 25 Members of Our Fearless 50 Are Here! appeared first on Marketo Marketing Blog - Best Practices and Thought Leadership.
While I’m hardly an Iron Chef, I do enjoy cooking. And one thing I love cooking is Mexican cuisine. Living just south of Oklahoma City, Oklahoma in Norman, there’s plenty of inspiration for these wonderful dishes. So recently, when I was scanning the Williams Sonoma website looking for Amazon FBA product ideas, I came across this listing for Mexican Cooking Essentials: Mexican Cooking Essentials | Williams Sonoma. And as usual, when I see cool products the first thing I always think to myself is… “Hey! These would make some great Amazon FBA product ideas!” 5 Amazon FBA Product Ideas for Mexican Cooking Remember: While I do my best to arm you with the data you need to make good product decisions, there’s always the potential that the product may not work out. This material is meant for educational and entertainment purposes. Always do your own research. 1 – Tortilla Warmer (Opportunity 6) What I learned with the Jungle Scout Chrome Extension Pro: 126 average units in sales per month. Not the highest sales in the world, but it’s nice to see a decent average among the non-outliers. 24 average reviews for non-outliers. So it doesn’t take a lot to combat the preexisting ... Read More
As the amount of data available online continues to grow, so do advanced marketing strategies that businesses can adopt to harness and use all that valuable information. You may be wondering where to start or how to enhance your data-driven marketing efforts.
Here are five trends and how to take advantage of them to move to the front of the pack:
1. Personalized User Experiences
Have you ever logged into your Amazon account and found customized product recommendations based on your shopping and browsing activity? Or found your homepage experience personalized in real time to reflect your online behavior? These are examples of how marketers are using data to understand their customers better and create individualized user experiences.
To adopt this strategy:
2. Predictive Analytics
“Predictive analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data,” according to SAS’ definition. “The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.”
You can apply this approach to advance account-based marketing (ABM), which promotes sales-and-marketing alignment by focusing only on key target accounts that match your company’s ideal customer profile. The goal: better understand which companies are most likely to do business with you. In the B2C world, predictive analytics can help you focus your ad spend on the right people, helping you achieve a higher ROI.
Predictive analytics can strengthen your marketing results by helping you identify:
3. Data Onboarding for Targeted 1:1 Ad Campaigns
Data onboarding is a strategy that’s catching on rapidly. A report by the Winterberry Group, cited in Ad Age, predicts the data onboarding market will reach $1 billion in 2020.
Lotame, a data management platform, defines data onboarding as “the process of transferring offline data to an online environment for marketing needs.” Lotame adds, “Data onboarding is mainly used to connect offline customer records with online users by matching Personally Identifiable Information (PII) gathered from offline datasets to find the same customers online.”
You can use such a platform, along with identity resolution (described below) and omnichannel marketing, to reach the same audience on multiple devices with personalized messaging.
4. Identity Resolution for a 360-Degree Customer View
To offer the best omnichannel experience, you need to recognize and tie together your customers’ identities across all the channels and devices they use. Identity resolution helps you do that, enabling you to expand your view of a customer to their apps and interests.
Identity resolution makes possible more precise targeting, omnichannel tracking and measurement, and personalization at scale.
You can use a toolset such as StiristaLINK, which connects B2B and B2C identities for a 360-degree view of your prospects. This lets you develop integrated communications to reach the same person, for example, via Facebook, Twitter, other social channels, and personal and business email.
5. Artificial Intelligence and Machine Learning
Top data-driven marketing companies like Google, Facebook, Amazon, Twitter, and LinkedIn are already actively using artificial intelligence (AI), machine learning, big data and predictive analytics to improve their products.
For example, LinkedIn uses machine learning (the ability of machines to teach themselves from data they collect) to power its smart replies recommendation engine.
Google uses artificial intelligence and predictive analytics to power its autocomplete search prediction engine. Once you begin typing in the search box, an algorithm utilizes all user data acquired to show what you might be interested in before you finish typing. These predictions are based on information gathered on the interests of other people with similar search queries.
Google’s latest product release, RankBrain, uses predictive analytics and AI to decide which pages to rank in search results, in real time. It understands searchers’ queries (keywords), measures how people interact with the results (user satisfaction) and then ranks the pages that best answer users’ questions.
Facebook also uses machine learning to power its Website Conversion engine. For example, the tool can calculate your cost per purchase and estimated conversions after 50 conversions. The “machine” requires a certain number of conversions to learn and predict which type of audience will better respond to your offer in the future.
So, there you have it: Five crucial data-driven marketing trends to adopt or start using more extensively. Now more than ever, businesses must assemble and integrate customer data to gain insights that will help you create a great, seamless customer experience spanning multiple channels. Leveraging these trends will move you along that path toward better results.
Which other trends should be added to this list? Tell me about it in the comments.
Bing Ads recently released a new intent based audience targeting for search campaigns called in-market audiences. These new in-market audiences are designed to allow advertisers to target users that Bing determines are ready to make a purchase. Bing Ads’ in-market audiences are now available for search campaigns in the U.S. market.
What are they?
Bing Ads’ in-market audiences utilize artificial intelligence (AI) to curate audience lists of users who have shown purchase intent signals in one of various categories currently available. The purchase intent signals used to generate the audience lists include searches, clicks, page views, or other interactions on Bing or Microsoft services. Once the lists are applied to search campaigns, advertisers can either target only the users on the list (target and bid) or make bid adjustments for users on the list (bid only).
There are currently 208 in-market audiences to choose from with categories ranging from in-market for car batteries to in-market for air travel. There are currently 21 broad categories such as Auto & Vehicles or Travel with sub-categories available in all. Bing Ads has increased the number of available in-market audiences since they launched, and we should expect the in-market audience categories to continue expanding. Bing Ads in-market audiences are available in all campaign types including shopping and search.
The introduction of in-market audiences demonstrates that Bing and Microsoft are now taking major steps to leverage user data from across their network to provide value for advertisers. Prior to the introduction of Bing Ads’ in-market audiences, Google was the only platform that provided AI driven audience insights using data across a large and diverse audience network.
According to Bing, in-market audience targeting had a major positive impact on conversion rate and click-through-rates, with conversion rates increasing 48% and click-through-rates increasing 28% for advertisers participating in the pilot.
The success or failure of Bing Ads in-market audiences will likely depend heavily on how much data the Bing and Microsoft network has on users in the audience you want to target. Advertisers who have had previous success with Bing users will likely experience the biggest positive impacts of the in-market audiences. The degree to which an advertiser’s customers aligns with available in-market audience categories will also play a major role in the success for each advertiser.
The availability of low funnel in-market audiences combined with the ease of setup make testing in-market audiences a no-brainer for most advertisers. Bing Ads’ in-market audiences represent a valuable example of successfully pairing large data and AI to provide value for advertisers. As digital advertisers, it’s time to accept that soulless AI tools are now beginning to add significant value to advertising campaigns.
Marketing and sales team are active players in the blame game. While the sales team thinks the marketing team shared only contacts (read, unqualified leads), the marketing team blames the sales team for not being able to convert all the excellent qualified leads they hand off.
According to MarketingSherpa, 61% of B2B marketers send all of their leads to sales even though only 27% are actually qualified. Not only this, sales reps ignore 50% of the marketing leads according to a study by the TAS Group.
Wondering why the percentages are so high?
Because there is a lack of shared understanding of what a qualified lead is. Each team works on their own definitions which not only creates confusion but results in frustration and lost revenue.
In this blog, I’ll cover what makes a lead sales qualified, how these leads fit into the buyer’s journey, how to score your leads, and more.
Customer Qualification Cycle: MQL vs. SQL
Not understanding the difference is one of the main reasons marketers end up spending time on unqualified leads who don’t want to be sold.
MQLs show repeated interest in your website content (not necessarily your product or services) and are likely to become your customer. Simply put, they have become the hand-raisers from your potential customer pool. However, remember that MQLs are not ready to buy, but they will respond to strategic nurturing.
SQLs, on the other hand, are further along in their buyer journey and are sales-ready. They fit perfectly into your buyer persona profiles and are likely to talk with a sales rep.
One of the defining differences amongst these two is the readiness to buy. An MQL is most likely NOT ready to buy your product today, but an SQL is a qualified lead which can be approached by your sales team immediately.
If we had to sum this up in one line, we would say:
The primary difference between MQL and SQL is that an MQL is a visitor who is aware of their problem while an SQL is a lead who knows that your product may be the solution to their problem.
Moving from MQL to SQL is time-sensitive, and as a marketer, you do not want to miss that window. By having a good understanding of the buyer’s journey and qualification cycle, you can determine where leads are at and pass it on to the sales team accordingly
How Does it Fit Into Your Buyer’s Journey
The buyer’s journey is typically made up of 3 stages: awareness, consideration, and decision.
Each of this stage also represents qualification of leads.
At the awareness stage, you are dealing with a lead. When the lead starts considering your product, your potential buyers have transitioned to MQLs. Finally, when the leads start looking at your product/service as a solution to their pain points, they have become a sales qualified lead and are ready to be approached by your sales team.
So, what is your first step towards knowing when to tell your salesperson if the lead is sales qualified?
Align Sales and Marketing Teams
To analyze conversion from MQL to SQL correctly, you need a strong relationship between the two teams. Knowledge about target markets, customer profiles, and behavior shared between sales and marketing will help you in pinpointing which leads are still to be nurtured and which are ready to go through your sales process.
You are looking out for answers to:
This logically brings us to the next question: how do you combine this knowledge to skyrocket conversion rates to ensure you maximize resources?
Lead Scoring Metrics
Let’s get one thing straight. Not every lead is sales-ready. But, leads can be nurtured.
If your marketing team starts sending every inquiry to the sales team, you will only waste your sales team’s time which makes for a not-so-great customer experience. Sometimes, those leads are just students who want to read your ebook for an assignment or to study for a test. Sometimes they can be job seekers who are frantically looking to gather as much information as they can.
Hence, it is essential to analyze the intent of each lead carefully. And, to interpret this intent, you need to have an effective behavioral yardstick—you need detailed lead scoring metrics.
As discussed before, MQLs are the hand-raisers amongst the leads. Meaning, they are more engaged but not ready to buy or talk to a salesperson yet. Hence, you should be careful in choosing the basis, and only high-interest activities should trigger a transition from lead to MQLs. For example: revisiting product/services spec page, the pricing page, reading most of your emails, leaving items in the cart, etc.
While most of your time will be spent creating accurate metrics around MQLs, the transition from MQL to SQL is simpler to identify. It might look like signing up for free trials or setting up a discovery call with the sales personnel, or a similar activity.
You need to sit down with both the teams and draw the lead scoring metrics to eliminate all the “guesswork” from the cycle. You can make use of your marketing automation software to set up a lead scoring system which assigns a value to each action. These actions might involve website activity, the number of downloads, email activity, or social media interactions.
Take a look at the SnapApp’s example of a lead scoring system:
Once a lead reaches a decided threshold, they should be automatically assigned to the sales team.
While deciding a threshold seems so obvious, 46% of B2B marketers have NOT set up a lead scoring threshold that will automatically alert or route leads to sales. Strange, right?
While your lead scoring system generally will consist of adding up scores, you will benefit immensely if you include negative scoring for specific actions (refer to the graphic above). For example, if a qualified lead has suddenly stopped interacting with your product after signing up for a trial and does not respond to any emails.
When qualifying leads, here are the things to think about at each level:
Organization level: At this level, you are asking fundamental questions like whether or not the lead fits into the buyer personas you have set up.
Opportunity level: This is a critical level to qualify leads accurately.
At this stage, you are asking:
Stakeholder level: At this level, you are asking BANT (budget, authority, need, and time) related questions.
If your lead:
There you go!
By now, you know when to tell your salesperson if the lead is sales qualified.
When the leads are qualified properly, and strategically, everyone is happy. Customers feel you understand them, marketing teams feel appreciated that their qualified leads were approached correctly and the sales team is happy with lead quality because they sealed the deal.
Lastly, it keeps you away from selling to people who don’t want to buy.
When do you tell your salesperson that the lead is sales qualified? Which is one of the most important lead metrics? Let’s talk about it in the comments section.
When you think about automated bidding, or any machine-learning algorithm, it’s useful to envision a physical machine with lots of gears and belts in need of plenty of oil to stay running smoothly. Not to mention, useful human stewards to keep it all functioning. Even though the machines we’re working with in the digital marketing sphere are less tangible, there’s a lot we can do to proverbially “grease the wheels.” In this post, I’m going to lay out specific numbers that will be useful in determining which automated bidding strategy aligns with your goals and the necessary data needed to get that strategy off the ground.
Did you know that Google’s machine learning algorithms can process 70 million signals within 100 milliseconds? That’s insane, right? These data rich signals are informed by Google’s access to 7 different properties, each with a 1+ billion users. These include Google, Gmail, YouTube, analytics, android, Google Maps, and Chrome. All this to say, the machine is fed by an incomprehensible amount of data being processed in microseconds and to get it to work optimally, we need to steer it in the right direction.
Here is a break-out of automated bidding strategies, the business solutions they provide, and data needed to get them to perform seamlessly:
Use if your goal is to drive a high volume of site traffic at low cost while still optimizing for conversions.
Use if your goal is to scale campaigns at your current CPA goal or maintain consistent CPA.
Use if your goal is to get the most conversions from your existing budget.
Use if your goal is to grow conversion value. It considers both the likelihood to convert in an auction as well as the conversion value associated. This one takes a bit more “greasing.”
Target Outranking Share
Use if your goal is to outrank ads from a competitor.
Target Search Page Location
Use if your goal is to appear on the first page of search results or in the top positions.
When selecting a bidding strategy, keep these numbers in your back pocket. They may also help diagnose why a new strategy is not working. Knowing when to deploy a new strategy can be difficult, but you can always run an AdWords Experiment for many of the bidding strategies so you can get an idea of what performance will be like before you fully commit.
We have come to an advanced leg in our internet science journey. We can no longer think of the internet as a glorified encyclopedia. Enter the virtual assistant with its interpersonal secretary skills. Now, we have a machine that functions with human intent. In light of this, our search engine optimization (SEO) must reflect far more than keywords. The internet has become a dimension unto itself. One requiring taxation, government, policing, and commerce. With this complexity comes the need for far-advanced SEO.
SEO Is Distinction
SEO’s raw purpose is to give a brand digital distinction. It uses tech, yes. But these are only the mechanics of it. With so many MarTech options on demand, your challenge is finding the tech that fits well. It shouldn’t be as difficult as finding Cinderella after the ball to try on the glass slipper. Still, market saturation happens at unprecedented rates. There are thousands of feet, but only one can wear the slipper, right? Still, social media gets consumed in mainstream media hashtags. This weighs down the rudder that steers consumers to you. Even with good keywords, hashtags, and relevant shares you get lost in communication. Unless you take the proper steps to move forward with your strategy. You don’t wedge huge feet into dainty glass slippers. You find a metric to size the exact dimensions of the rightful user’s foot.
Tailoring your approach to your audience’s preferred method of communication is a timeless SEO skill. SEO is the fertilizer for page relevance continuity. Tools like Google’s PageSpeed Insights and Google Lighthouse are essentials.
Google PageSpeed Insights gives the real-world performance of the pages within your site for both mobile and desktop devices. Additionally, it provides suggestions on how to improve the page. Google Lighthouse is an automated open-source tool for improving the quality of web pages, both public and those which require authentication. It audits for performance, accessibility, progressive web apps, and more.
Mastering the speed of updates is like merging with traffic. Audits like Lighthouse are like crop checking in the agricultural world. Still, location overrides preparation. Plants don’t grow without the sun. Tailor the look of your website to match your message.
Even evolved, the internet will always have basic functions. Plugins aren’t going anywhere soon. If anything, they may be gaining momentum. New major content plugins, like those found on WordPress, are closing gaps in errors. 404 error alerts will become customizable. This means even your failed pages have room for your branding. These plugins will correct redirects and speed the de-indexing process.
Google as an Incentive
Google holds the championship belt in the search engine domination match. That doesn’t look like it will change soon. Acknowledging Google as a deciding force in SEO is standard. Take Google as an incentive to excel past the reach of well-established brands. Google News revolutionizes the way consumers see digital content.
Your customers want pure journalism told from the consumer’s viewpoint. They don’t want the trend race of the major publishers affecting the story. Your SEO puts your report in the Google News docket. The better compatible it is with Google’s new AI search assistants the more chances it has. Your consumers can cut through the hype and opinion mayhem. They can go straight to the pro source. Your source. Brand fame then becomes more than attainable. It is critiqued at all social levels. Responsible SEO is non-negotiable as the gap closes.
Security in SEO
The gap between the tangible and digital world closes further. Data crises have made heavy headlines. One wouldn’t think from an outsider’s view that SEO would hold the keys to this kingdom. Consider it. Becoming an information center for your industry that is also a brand has its own issues. Valuable information becomes exploitable information. Data is gold. Spend and store it with moderation.
Keep in mind that net neutrality is phasing out. Laws like GDPR pass on the same premise as global accounting principles. Data is business. Business requires ethics. SEO must apply to these rules or be a pointless waste of funds. Staying up-to-date on changing security policy is your civic duty. Your evolving content cannot take the transforming step otherwise.
Enter AI Guides
AI has empowered us in more ways than just automation. We have the ability to sift through thousands of pages, which makes these learning machines the university professors of the AI universe. Our dormant digital libraries now become instant downloads. These share to millions of communicating machine brains in an instant. Now, we have to leave lecture notes on each page. Our machines can take our information straight to class. Optimizations give them the ground to form a lecture on their own. SEO becomes more like the University of machines than a keyword list.
Distinguished SEO comes from a professional touch. Speed and performance in SEO now require more muscle behind the vehicle. Solutions exist to take a marketing scheme and add horsepower. Look for AI that empowers the marketer. AI like this has the power of the professor’s mind. It has the ability to find Cinderella on the moon and bring her slipper gift-wrapped. An amazing tool like this is your future saving grace. Invest in the bankable power of AI as a guide. Do so for the speed. Do so also because the traditional models of SEO will eventually fizzle to a low-burn. You will need more machine capacity than the internet’s non-machine learning era had available.
Innovation is Natural Selection
Internet science is in the early civilization years. There will be exploration. Some colonization. Disputes of policy. Some will conquer. Some will take losses. Nothing is certain. Still, one thing we know. Innovation is the evolution of machines. The more life we give them the more they emulate life. Life has basic instincts. Evergreen SEO means optimizing to merge human information with machine intervention. When less is more, life will find its own way. Your job is to be vigilant. To water and sow the seed. As an event, natural growth will happen on its own volition. Allow the best odds for that selection and escape the brand burn-out complex.
As machine learning and AI become more prevalent, what future do you see for SEO? I’d love to hear your predictions in the comments.
The post SEO in the Age of AI: How to Get Ahead appeared first on Marketo Marketing Blog - Best Practices and Thought Leadership.
We all know that responsive search ads (RSAs) are the hot new ad type, but how will they fit into the grand scheme of digital advertising? What is the best course of action to implement them in your existing paid search strategies? We’ve observed some mixed reviews about the new ad type – have you found success with them?
We’ve seen both sides of the coin. There are definitely some upsides and some downsides to the new ad type. What have you seen? Do you feel passionately one way or the other?
Join Hanapin’s Matt Umbro and Directive Consulting’s Garrett Mehrguth as they engage in an honest discussion about responsive search ads, walking through all the pros and cons and advice around using the new ad type in your campaigns.
If you have not realized it yet, Facebook’s ad delivery system works on an auction system. This method Facebook has developed runs automatically to determine which ads will be seen in a user’s feed. A traditional auction system works on a “highest bid wins” system but let us make one thing abundantly clear, that is not how Facebook’s auction works. So how exactly does it work? Well if you are curious, continue reading and we’ll breakdown the components of the auction to get a better understanding.
When showing ads, Facebook aims to balance two things at all times. First is to create value for those advertising on Facebook. They want to help advertisers reach their target audience and get results from that target audience. Second is to keep the actual Facebook users in mind. Ads help Facebook pay the bills but they must deliver a positive and relevant experience to it’s users. The ads that are served to someone should be relevant to that person. To say this in another way with a quote from Facebook; “People see ads they’re more likely to find relevant, and advertisers reach the people who can help them meet their business goals.
Remember, the goal of Facebook is to achieve that balance by delivering the right ad to the right person at the right time. It achieves this through its automated auction. Like mentioned before this is not a traditional auction of highest bidder wins. So lets look at the three things that make up this auction to understand what Facebook calls an ad’s Total Value.
Bid is the traditional part of the auction. You can use Facebook’s two methods of bidding called lowest cost and target cost. Lowest cost is the more automated of the two and lets Facebook bid for you attempting to achieve your desire result at lowest cost. Target cost tells Facebook to achieve a result at a set goal and is more manual.
Estimated action rate is how likely Facebook’s algorithms think a person is going to take action on an ad. Facebook is looking for if your ad is generally relevant to someone or if it will actually get them to take whatever action you are optimizing for. These “estimates” are based on historical ad performance and previous actions of the person you are attempting to advertise to.
Ad quality and relevance. This one is a bit self explanatory. Facebook tries to find if your ad is going to be interesting and relevant to the person seeing it. They looks at things like positive feedback and negative feedback to help determine this. Meaning an ad with negative feedback can decrease overall value. Keep in mind that relevance score is NOT factored into this. Improving relevance score won’t necessarily impact your Total Value so it should not be your end goal.
Again, this is an auction so a users bid is a part of who will have their ad seen. Just don’t forget the other aspects! An advertiser who’s ad has a higher estimated action rate and/or ad quality and relevance can easily achieve a higher Total Value over a higher bidder.
Post Click Experience
One thing that is and is not included in Total Value is a user’s post click experience on your website. You might house this under estimated action rate but it could be its own criteria. What Facebook is looking for here is an advertisers website performance (load speed for example) and a user’s network connection. Facebook says “We will show ads to people when they are interested in the content and have a network connection that can quickly load the post click content.” This is their attempt to help users have positive ad experiences with advertisers. This system should also help to reduce a website’s bounce rate. If someone who clicks an ad can load a website quickly and engage with the content on the page, that is a positive things for both user and advertiser.
This was a quick insight into how Facebook’s ad auction works. Remember that Facebook tries to achieve a balance of good advertiser experience and good user experience. They do this through their ad auction which prioritizes Total Value over just highest bidder. This helps more relevant ads to be shown and enables people with smaller budget to compete in the auction competitively. Finally don’t forget about a user’s post click experience, invest in building a fast website with engaging content.