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Archives for May 2014

Panda 4.0 Analysis | Nuclear Option Rewarded, Phantom Victims Recover, and Industry Experts Rise

May 23, 2014 By Glenn Gabe 37 Comments

Panda 4.0 Rolls Out

On May 20th, 2014 Google’s Matt Cutts announced that Panda 4.0 was rolling out.  Leading up to that tweet, there was a lot of chatter across the industry about an algorithm update rolling out (based on reports of rankings volatility and traffic gains/losses).  I was also seeing lots of movement across clients that had been impacted by previous algorithm updates, while also having new companies contact me about massive changes in rankings and traffic.  I knew something serious was happening, but didn’t know exactly what it was.  I thought for a while that it could be the pre-rollout and testing of Penguin, but it ended up being a new Panda update instead.

Matt Cutts Announces Panda 4.0

When Panda 4.0 was officially announced, I had already been analyzing sites seeing an impact (starting on Saturday May 17th, 2014).  I was noticing major swings in rankings and traffic with companies I’ve been helping with previous algo trouble.  And like I said above, several companies started reaching out to me via email about new hits starting that weekend.

And I was glad to hear a confirmation from Matt Cutts about Panda 4.0 rolling out.  That enabled me to hone my analysis.  I’ve mentioned in the past how unconfirmed Panda updates can drive webmasters insane.  When you have confirmation, it’s important to analyze the impact through the lens of a specific algorithm update (when possible).  In other words, content quality for Panda, unnatural links for Penguin, ad ratio and placement for Top Heavy, etc.

And by the way, since Google named this update Panda 4.0, we must assume it’s a new algorithm.  That means new factors could have been added or other factors refined.  Needless to say, I was eager to dig into sites that had been impacted to see if I could glean any insights about our new bamboo-eating friend.

Digging into the Panda 4.0 Data (and the Power of Human Barometers)
I’ve written before about the power of having access to a lot of Panda data.  For example, working with many sites that had been previously impacted by Panda.  It’s often easier to see unconfirmed Panda updates when you can analyze many sites impacted previously by the algorithm update.  I’ve helped a lot of companies with Panda hits since February of 2011 when Panda first rolled out.  Therefore, I can often see Panda fluctuations, even when those updates aren’t confirmed.  That’s because I can analyze the Panda data set I have access to in addition to new companies that reach out to me after getting hit by those Panda updates.  The fresh hits enable me to line up dates with Panda recoveries to better understand when Google rolls out unconfirmed updates.   I’ve documented several of the unconfirmed updates here on my blog (in case you wanted to go back and check the dates against your own data).

So, when Google announced Panda 4.0, I was able to quickly start checking all the clients I have helped with Panda recovery (in addition to the ones I was already seeing jump in the rankings).  And it didn’t take long to see the impact.  A number of sites were clearly being positively impacted by P4.0.

Panda 4.0 Recovery

Then, I analyzed new sites that were negatively impacted, based on those companies reaching out to me after getting hit (starting on 5/17/14).  Together, I have been able to analyze a boatload of Panda 4.0 data.  And it’s been fascinating to analyze.

I have now analyzed 27 websites impacted by Panda 4.0.  The sites I analyzed ranged from large sites receiving a lot of Google Organic traffic (1M+ visits per month) to medium-sized ecommerce retailers and publishers (receiving tens of thousands of visits per month) to niche blogs focused on very specific topics (seeing 5K to 10K visits per month).  It was awesome to be able to see how Panda 4.0 affected sites across industries, categories, volume of traffic, etc.  And as usual, I was able to travel from one Panda 4.0 rabbit hole to another as I uncovered more sites impacted per category.

 

What This Post Covers – Key Findings Based on Heavily Analyzing Websites That Were Impacted by Panda 4.0
I can write ten different posts about Panda 4.0 based on my analysis over the past few days, but that’s the not the point of this initial post.  Instead, I want to provide some core findings based on helping companies with previous Panda or Phantom hits that recovered during Panda 4.0.  Yes, I said Phantom recoveries. More on that soon.

In addition, I want to provide findings based on analyzing sites that were negatively impacted by Panda 4.0.  The findings in this post strike a nice balance between recovery and negative impact.  As many of you know, there’s a lot you can learn about the signature of an algorithm update from fresh hits.

Before I provide my findings, I wanted to emphasize that this is simply my first post about Panda 4.0.  I plan to write several additional posts focused on specific findings and scenarios.  There were several websites that were fascinating to analyze and deserve their own dedicated posts.  If you are interested in learning about those cases, the definitely subscribe to my feed (and make sure you check my Search Engine Watch column).  There’s a lot to cover for sure.  But for now, let’s jump into some Panda 4.0 findings.

 

Panda 4.0 Key Findings

The Nuclear Option – The Power of Making Hard Decisions and Executing
When new companies contact me about Panda, they often want to know their chances of recovery.  My answer sometimes shocks them.  I explain that once the initial audit has been completed, there will be hard decisions to make.  I’m talking about really hard decisions that can impact a business.

Beyond the hard decisions, they will need to thoroughly execute those changes at a rapid pace (which is critically important).  I explain that if they listen to me, make those hard decisions, and execute fully, then there is an excellent chance of recovery.  But not all companies make hard decisions and execute thoroughly.  Unfortunately, those companies often sit in the grey area of Panda, never knowing how close they are to recovery.

Well, Panda 4.0 reinforced my philosophy (although there were some anomalies which I’ll cover later).  During P4.0, I had several clients recover that implemented HUGE changes over a multi-month period.  And when I say huge changes, I’m talking significant amounts of work.  One of my Panda audits yielded close to 20 pages of recommendations in Word.  When something like that is presented, I can tell how deflated some clients feel.  I get it, but it’s at that critical juncture that you can tell which clients will win.  They either take those recommendations and run, or they don’t.

To give you a feel for what I’m talking about, I’ve provided some of the challenges that those clients had to overcome below:

  • Nuking low-quality content.
  • Greatly improving technical SEO.
  • Gutting over-optimization.
  • Removing doorway pages.
  • Addressing serious canonicalization problems.
  • Writing great content. Read that again. :)
  • Revamping internal linking structure and navigation.
  • Hunting down duplicate content and properly handling it.
  • Hunting down thin content and noindexing or nuking it.
  • Removing manual actions (yep, I’ve included this here).
  • Stop scraping content and remove the content that has been scraped.
  • Creating mobile friendly pages or go responsive.
  • Dealing with risky affiliate marketing setups.
  • Greatly increasing page speed (and handling bloated pages, file size-wise).
  • Hunting down rogue risky pages and subdomains and properly dealing with that content.
  • And in extreme cases, completely redesigning the site. And several of my clients did just that. That’s the nuclear option by the way.  More about that soon.
  • And even more changes.

Now, when I recommend a boatload of changes, there are various levels of client execution. Some clients implement 75% of the changes, while some can only implement 25%.  As you can guess, the ones that execute more have a greater chance at a quicker recovery.

But then there are those rare cases where clients implement 100% of the changes I recommend.  And that’s freaking awesome from my standpoint.  But with massive effort comes massive expectations.  If you are going to make big changes, you want big results.  And unfortunately, that can take time.

Important Note: This is an incredibly important point for anyone dealing with a massive Panda or Penguin problem.  If you’ve been spamming Google for a long time (years), providing low-quality content, that’s over-optimized, using doorway pages to gain Google traffic, etc., then you might have to wait a while after changes have been implemented.  John Mueller is on record saying you can expect to wait 6 months or longer to see recovery.  I don’t think his recommendation is far off.  Sure, I’ve seen some quicker recoveries, but in extreme spamming cases, it can take time to see recovery.

Fast forward to Panda 4.0.  It was AWESOME to see clients that made massive changes see substantial recovery during P4.0.  And several of those clients chose the nuclear option of completely redesigning their websites.  One client is up 130% since 5/17, while another that chose the nuclear option is up 86%.  Here’s a quick screenshot of the bump starting on 5/17:

A Second Panda 4.0 Recovery

 

Side Note: The Nuclear Option is a Smart One When Needed
For some of the companies I was helping, there were so many items to fix that a complete redesign was a smart option.  And no, that doesn’t come cheap.  There’s time, effort, resources, and budget involved versus just making changes to specific areas.  It’s a big deal, but can pay huge dividends down the line.

One client made almost all of the changes I recommended, including going responsive.  The site is so much better usability-wise, content-wise, and mobile-wise.  And with Panda 4.0, they are up 110% since 5/18 (when they first started seeing improvement).

I’ve mentioned before that for Panda recovery, SEO band-aids won’t work.  Well, the clients that fully redesigned their sites and are seeing big improvements underscore the point that the nuclear option may be your best solution (if you have massive changes to make).  Keep that in mind if you are dealing with a massive Panda problem.

 

Phantom Victims Recover
On May 8th, 2013, I picked up a significant algorithm update.  After analyzing a number of websites hit by the update, I decided to call it “Phantom”.  It simply had a mysterious, yet powerful signature, so Phantom made sense to me.  Hey, it stuck. :)

Phantom was a tough algorithm update.  Some companies lost 60% of their traffic overnight.  And after auditing a number of sites hit by Phantom, my recommendations were often tough to hear (for business owners).  Phantom targeted low-quality content, similar to Panda.  But I often found scraped content being an issue, over-optimized content, doorway pages, cross-linking of company-owned domains, etc.  I’ve helped a number of Phantom victims recover, but there were still many out there that never saw a big recovery.

The interesting part about Panda 4.0 was that I saw six Phantom victims recover (out of the 27 sites I analyzed with previous content quality problems).  It’s hard to say exactly what P4.0 took into account that led to those Phantom recoveries, but those victims clearly had a good day.  It’s worth noting that 5 out of the 6 sites impacted by Phantom actively made changes to rectify their content problems.

One of the sites did nothing to fix the problems and ended up recovering anyway.  This could be due to the softening of Panda, which is definitely possible.  There were definitely some sites I analyzed that showed increases after Panda 4.0 that didn’t necessarily tackle many problems they were facing.  But in this situation, the site was a forum, which I cover next.  Note, you can read my post about the softening of Panda and what I saw during the March 24, 2014 Panda update to learn more about the situation.

Phantom Victim Recovers During Panda 4.0
Forums Rebound During Panda 4.0
My next finding was interesting, since I’ve helped a number of forums deal with previous Panda and/or Phantom hits.  I came across four different forums that recovered during Panda 4.0.  Three were relatively large forums, while one was a smaller niche forum run by an category expert.

One of the larger forums (1M+ visits per month) made a boatload of changes to address thin content, spammy user-generated content, etc.   They were able to gut low-quality pages, noindex thinner ones, and hunt down user-generated spam.  They greatly increased the quality of the forum overall (from an SEO perspective).  And they are up 24% since Panda 4.0 rolled out.

Noindexing Low Quality Content on a Forum

A second forum (1.5M visits per month) tackled some of the problems I picked up during an audit, but wasn’t able to tackle a number of items (based on a lack of resources).  And it’s important to know that they are a leader in their niche and have some outstanding content and advice.  During my audit I found they had some serious technical issues causing duplicate and thin content, but I’m not sure they ever deserved to get hammered like they did.  But after Panda 4.0, they are up 54%.

And the expert-run forum that experienced both Panda and Phantom hits rebounded nicely after Panda 4.0.  The site has some outstanding content, advice, conversations, etc.  Again, it’s run by an expert that knows her stuff.  Sure, some of the content is shorter in nature, but it’s a forum that will naturally have some quick answers.  It’s important to note that the website owner did nothing to address the previous Panda and Phantom problems.  And that site experienced a huge uptick based on Panda 4.0.  Again, that could be due to the softening of Panda or a fix to Panda that cut down on collateral damage.  It’s hard to say for sure.  Anyway, the site is up 119% since May 17th.

Forums Recover During Panda 4.0
Industry Experts Rise
During my research, I saw several examples of individual bloggers that focus heavily on niche areas see nice bumps in Google Organic traffic after Panda 4.0 rolled out.  Now, Matt Cutts explained Google was looking to boost the rankings of experts in their respective industries.  I have no idea if what I was seeing during my research was that “expert lift”, but it sure looked like it.

Here’s an example of a marketing professional that saw a 38% lift after Panda 4.0:
Bloggers Recover During Panda 4.0

And here’s a sports medicine expert that has shown a 46% lift:
Niche Expert Recovers During Panda 4.0

It was great to see these bloggers rise in the rankings, since their content is outstanding, and they deserved to rank higher!  They just didn’t have the power that some of the other blogs and sites in their industries had.  But it seems Google surfaced them during Panda 4.0.  I need to analyze more sites like this to better understand what’s going, but it’s worth noting.

Update: I reached out to Matt Cutts via Twitter to see if Panda 4.0 incorporated the “authority” algo update I mentioned earlier.  Matt replied this afternoon and explained that they are working on that independently.  So, it doesn’t seem like the bloggers I analyzed benefited from the “authority” algo, but instead, benefited from overall quality signals.  It was great to get a response from Matt.  See screenshot below.

Matt Cutts Tweet About Subject Matter Expert Algorithm

 

An Indexation Reality Check – It’s Not The Quantity, But the Quality That Matters
After conducting a laser-focused Panda audit, it’s not uncommon for me to recommend nuking or noindexing a substantial amount of content.  That is usually an uncomfortable decision for clients to make.  It’s hard to nuke content that you created, that ranked well at one point, etc.  But nuking low-quality content is a strong way to proceed when you have a Panda problem.

So, it was awesome to see clients that removed large amounts of content recover during Panda 4.0. As an extreme example, one client removed 83% of their content from Google’s index.  Yes, you read that correctly.  And guess what, they are getting more traffic from Google than when they had all of that low-quality and risky content indexed.  It’s a great example about quality versus quantity when it comes to Panda.

Indexation Impact and Panda 4.0

On the other hand, I analyzed a fresh Panda 4.0 hit, where the site has 40M+ pages indexed.  And you guessed it, it has serious content quality problems.  They got hammered by Panda 4.0, losing about 40% of their Google organic traffic overnight.

If you have been impacted by Panda, and you have a lot of risky content indexed by Google, then have a content audit completed now.  I’m not kidding.  Hunt down thin pages, duplicate pages, low-quality pages, etc. and nuke them or noindex them.  Make sure Google has the right content indexed.

 

Engagement and Usability Matter
While analyzing the fresh hits, it was hard to overlook the serious engagement issues I was coming across.  For example, stimulus overload on the pages that were receiving a lot of Google organic traffic prior to the hit.  There were ads that expanded into or over the content, double-serving of video ads, stacked “recommended articles” on the page, lack of white space, a long and confusing navigation, etc.  All of this led to me wanting to bounce off the page faster than a superball on concrete.  And again, high bounce rates and low dwell times can get you killed by Panda.  Avoid that like the plague.

Check out the bounce rates and pages per session for a site crushed by Panda 4.0:

Low Engagement Invites Panda


Side Note: To hunt down low-quality content, you can run this Panda report in Google Analytics.  My post walks you through exporting data from GA and then using Excel to isolate problematic landing pages from Google Organic.

Downstream Matters
While analyzing fresh Panda 4.0 hits, it was also hard to overlook links and ads that drove me to strange and risky sites that were auto-downloading software, files, etc.  You know, those sites where it feels like your browser is being taken over by hackers.  This can lead to users clicking the back button twice and returning to Google’s search results.  And if they do, that can send bad signals to Google about your site and content.  In addition, risky downstream activity can lead to some people reporting your site to Google or to other organizations like Web of Trust (WOT).

And as I’ve said several times in this post, Panda is tied to engagement.  Engagement is tied to users.  Don’t anger users.  It will come back to bite you (literally).

 

Summary – Panda 4.0 Brings Hope
As I said earlier, it was fascinating to analyze the impact of Panda 4.0.  And again, this is just my first post on the subject.  I plan to write several more about specific situations I’ve analyzed.  Based on what I’ve seen so far, it seems Panda 4.0 definitely rewarded sites that took the time to make the necessary changes to improve content quality, engagement, usability, etc.  And that’s awesome to see.

But on the flip side, there were sites that got hammered by P4.0.  All I can say to them is pull yourself up by your bootstraps and get to work.  It takes time, but Panda recovery is definitely possible.  You just need to make hard decisions and then execute.  :)

GG

 

Filed Under: algorithm-updates, google, seo

How To Remarket 70+ Ways Using Segments and Conditions in Google Analytics

May 12, 2014 By Glenn Gabe 5 Comments

Remarketing in Google Analytics Using Conditions and Segments

I know what you’re thinking. Can you really remarket more than 70 different ways using segments in Google Analytics?  Yes, you can!  Actually, when you combine the methods I’ll cover today, there are many more types of Remarketing lists you can build!  So the total number is much greater than 70.

My post today is meant to introduce you to segments in Google Analytics (GA), explain how you can use them to remarket to people who already visited your site, and provide important Remarketing tips along the way.  I hope once you read this post, you’re ready to kick off some Remarketing campaigns to drive more sales, leads, phone calls, etc.

What Are Segments in Google Analytics?
Many digital marketers know about Remarketing already.  That’s where you can reach people that already visited your website via advertising as they browse the web.  For example, if John visited Roku’s website, browsed various products, and left, then Roku could use Remarketing to advertise to John as he browses the Google Display Network (GDN).  The Google Display Network is a massive network of sites that run Google advertising, and includes Google-owned properties like YouTube, Google Maps, Gmail, etc.  According to Google, the GDN reaches 90% of internet users worldwide.

Remarketing via The Google Display Network (GDN)

By the way, if you’ve ever visited a website and then saw ads from that website as you browsed the web, then you’ve been remarketed to.  As you can guess, this can be an incredibly powerful way to drive more sales, leads, etc.  It can also be extremely frustrating and/or shocking to users.  So be careful when crafting your Remarketing strategy!

When Remarketing first rolled out, you could only set up Remarketing lists in the AdWords interface.  That was ok, but didn’t provide a massive amount of flexibility.  That’s when Google enabled marketers to set up Remarketing lists via Google Analytics.  That opened up an incredible amount of opportunity to slice and dice visitors to create advanced-level Remarketing lists.  For example, you could create Remarketing lists based on users who visited a certain section of your website, or lists based on users completing a certain conversion goal, etc.  Needless to say, tying Google Analytics to Remarketing was an awesome addition.

Now, I started using Google Analytics Remarketing functionality immediately to help clients build advanced Remarketing lists, but I had a feeling that Google was going to make it even more powerful.  And they did.

Along Came Segments… Remarketing Options Galore
You might already be familiar with segments in Google Analytics, which was originally named “Advanced Segmentation”.  In July of 2013, Google released a new version in Google Analytics and simply called it “Segments”.  But don’t get fooled by the simpler name.  Segments enable marketers to slice and dice their users and traffic to view reporting at a granular level.  For example, I often set up a number of segments for clients, based on their specific goals. Doing so enables me to quickly view granular reporting by removing a lot of the noise residing in standard reports.

Using Segments to Create Remarketing Lists in Google Analytics

But starting in January of 2014, Google rolled out an update that enabled marketers to use those segments to create Remarketing lists.  Yes, now marketers had an incredible number of options available when creating Remarketing lists.  In addition, you could easily import segments you are already using! This means you could leverage the hard work you’ve already put in when creating segments in Google Analytics.

Although I thought I had a lot of flexibility in creating Remarketing lists leading up to that point, the ability to use segments opened the targeting flood gates.  I remember checking out the list of options when segments for Remarketing first launched, and I was blown away.

For example, using segments you could create Remarketing lists based on:

  • Demographics like age, gender, language, location, and more.
  • Technology options like operating system, browser, device category, mobile device model or branding, and more.
  • Behavior like the number of sessions per user, days since last session, transactions, and session duration.
  • “Date of First Session” where you could create lists based on the initial session date or a range (sessions that started between two dates).
  • Traffic Sources based on campaign, medium, source, or keyword.
  • Ecommerce options like transaction id, revenue, days to transaction, product purchased, or product category.
  • And you can combine any of these options to create even more advanced Remarketing lists.

 

Now, the options listed above are based on the major categories of segments in Google Analytics.  But you can also set Remarketing lists based on conditions.  Using conditions, you could leverage many of the dimensions or metrics available in Google Analytics to build advanced Remarketing lists.  Actually, there are so many options via “conditions” that I can’t even list them all here in this post.

For example, there are eight major categories of dimensions and metrics you could choose from, including Acquisition, Advertising, Behavior, Custom Variables, Ecommerce, Time, Users, and Other.  And each category has a number of dimensions or metrics you can select to help craft your Remarketing lists.

Using Conditions to Create Remarketing Lists in Google Analytics

Note, it can definitely be overwhelming to review the list of options when you first check this out.  Don’t worry, I provide some tips for getting started later in this post.  For now, just understand that you can use segments and conditions in Google Analytics to craft Remarketing lists based on a number of factors (or a combination of factors).  Basically, you have the power to remarket however you like.  And that’s awesome.

Examples of What You Can Do
Enough with the introduction.  Let’s get specific.  I’m sure you are wondering how segments in Google Analytics can be used in the real-world.  I’ll provide a few examples below of Remarketing lists you can build to get back in front of people who already visited your website.  Note, the lists you build should be based on your specific business and website.  I’m just covering a few options below so you can see the power of using segments to build Remarketing lists.

Example 1: Remarket to users who came from a specific referral path (page).
Imagine you knew that certain referring webpages drove a lot of high-quality traffic on a regular basis.  Based on the quality of traffic coming through those referring pages, you decide that you would love to remarket to those users as they browse the web (since you have a strong feel for the type of user they are based on the content at hand).

Using segments, you could create a Remarketing list based on the original referral path (i.e. the referring pages).  And once that list reaches 100 members, then you can start getting targeted ads in front of those users and driving them to your preferred landing page (whether that’s current content, campaign landing pages, etc.)

Using Referring Path to Create Remarketing Lists

And if you find several referring pages that target similar categories of content, then you could use Boolean operators to combine those pages from across different websites.  For example, {referring path A} AND {referring path B}.  For example, if three referring pages are all about Category A, then you could combine them to create a Remarketing list.  You can also use regular expressions to match certain criteria.  Yes, the sky’s the limit.

Using Boolean Operators to Create Advanced Remarketing Lists

Example 2: Reach a certain demographic that has visited your website.
Let’s say you just launched a new product targeting 18-25 year olds and wanted to remarket to users who already visited your website that fit into this category.  You know they showed some interest in your company and products already (since they already visited your site), so you want to reach them via display advertising as they browse the web.

Using segments, you could create a Remarketing list based on age using the Demographics category.  Simply click the checkbox next to the age category you want to target.

Creating Remarketing Lists Based on Demographics

Or to get even more targeted, you could combine age with gender to test various messaging or visuals in your ads.  Going even further, you could add location as another selection to target users based on age, gender, and geographic location (down to the city level if you wanted).

Combining Demographics to Create Advanced Remarketing Lists

Example 3: Target users of specific campaigns, ad groups, or keywords.
Let’s say you are already using AdWords to drive targeted users to your website.  Using segments in Google Analytics, you could build a Remarketing list based on specific campaigns, ad groups, or keywords.  For example, if you have an ad group targeting a specific category or product, then you could create a list containing the users that already searched Google and clicked through your ads related to that category.  It’s a great way to get back in front of a targeted audience.

Creating Remarketing Lists Based on Previous Campaigns

And by combining the targeting listed above with ecommerce conditions like the number of transactions or amount of revenue generated, you could create advanced Remarketing lists targeting very specific types of users.

Creating Remarketing Lists Based on Revenue

Example 4: Pages or Page Titles
If you have been building a lot of new content and want to reach those visitors as they browse the web, then you could create a Remarketing list based Pages or Page Titles.  For example, let’s say you have 25 blog posts about a certain category of content.  They rank very well, have built up a nice amount of referral traffic, etc.  You could build a Remarketing list by select a grouping of pages via urls or via page titles. Then you could reach those users as they browse the web and drive them to a targeted landing pages, knowing they were interested in a certain post (or group of posts) about a certain subject.

Creating Remarketing Lists Based on Page Titles

And you can combine those pages with conversion goals to add users to a list that completed some type of important action on the site.  For example, users that signed up for your email newsletter, users that triggered an event, downloaded a study, etc.

Creating Remarketing Lists Based on Page Titles and Conversion

Remarketing Tips

Based on the examples listed above, I hope you see the power in using segments and conditions to craft Remarketing lists.  But as I said earlier, it can quickly become overwhelming (especially for marketers new to Remarketing).  Below, I’ve listed several important tips to keep in mind while crafting your campaigns.

  1. Remarketing Lists Require 100 Members
    A list requires at least 100 members before you can start showing ads to users.  Keep this in mind when building lists to ensure you can reach that number.  If not, you will never get back in front of those users.
  2. Start Simple, Then Increase in Complexity
    Based on the 100 member requirement, start with simpler Remarketing lists and increase your targeting as you get more comfortable with Remarketing.  Don’t start with the most granular targeting possible, only to have a list of 3 people.
  3. Refine Your Tracking Snippet
    Google requires that you refine your Google Analytics tracking code in order take advantage of Remarketing.  Review the documentation to ensure you have the proper technical setup.
  4. Craft a Strategy First, and Your Lists Should Support Your Strategy
    Don’t create lists for the sake of creating lists. Always start by mapping out a strong Remarketing strategy before jumping into list creation. Your strategy should dictate your Remarketing lists, and not the other way around.  Spend time up front mapping out who you want to target, and why.  And once you have a solid plan mapped out, you can easily build your lists via Google Analytics segments and conditions.
  5. Use Display Advertising In Addition to Text Ads
    Remarketing enables you to use both image ads and text ads.  Definitely use both when crafting your campaigns.  There are a number of sizes and formats you can use.  I recommend hiring a designer to build your ads unless you have in-house staff that is capable of designing high-quality ads.  Use image ads where possible to grab the user’s attention and provide text ads as a backup when a site doesn’t support image ads.  You don’t have to choose one or the other.
  6. Measure Your Results! Don’t “Set It and Forget It”.
    Remarketing is advertising.  And advertising campaigns should have a goal.  Don’t simply set up Remarketing without knowing the intended action you want users to take.  Instead, make sure you set up conversion goals to track how those users convert.  Do not set up the campaign and let it run without analyzing the results.  Understand the ROI of the campaign.  That’s the only way you’ll know if it worked, if the campaign should keep running, and if you should base other campaigns on the original.

 

Summary – New and Powerful Ways to Remarket
After reading this post, I hope you see the power in using segments and conditions for creating Remarketing lists.  In my opinion, too many marketers keep going after new eyeballs and easily forget about the eyeballs that already showed an interest in their company, products, or services.  I believe that’s a mistake.  Instead, marketers can craft advanced Remarketing lists to get back in front of a targeted audience.  Doing so provides another chance at converting them.

Remember, a warm lead is always more powerful than a cold call.  Good luck.

GG

 

Filed Under: adwords, google-analytics, sem, web-analytics

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