Dynamic Remarketing: Building The Best Lists


Dynamic Remarketing gives advertisers the unique ability to remarket with banner ads that showcase the exact products the potential customer viewed. The caveat, as with all remarketing, is of course that the potential customer had to visit your site in the first place. The potential for this new type of remarketing is huge, and we encourage you to test a Dynamic Remarketing campaign against your existing Remarketing campaigns to see what works best for you or your clients.

Dynamic Remarketing Examples
Source: ThinkWithGoogle.com

As we started setting these campaigns up for our clients (and followed Google’s setup guide here), we ran into a few snags with the automatically generated lists created by Google. Upon further review, and a phone call or two to our Google reps, we now create our own lists through Google Analytics and do not rely on the accuracy of Google’s pre-populated lists for a couple of reasons:

  1. They didn’t work.
  2. When they did work, we tested their lists vs. ones that we created, and the list sizes were wildly different (and much smaller when created by Google).

How To Build Your Initial Lists

For each of these remarketing lists you build in Analytics, make sure to check the radio button “Create my own remarketing type using Segments.”

1. Pageview>1; Did Not Checkout

Our first list is essentially an “All Site Visitors” list but a little more targeted. First of all, we want to make sure they didn’t bounce right away, and second, we want to make sure they didn’t check out. To ensure they didn’t bounce, we set the Pageview to >1, and to ensure they didn’t checkout, set your Transactions to equal 0.

Custom Remarketing List in Google Analytics

 2. Abandoned Cart

Hopefully you already have an Abandoned Cart list you can use from your general Remarketing campaign. If not, setup this list in the same way we started #1. Under the Conditions section, you’ll want to add 2 Filters.

  1. Page contains [enter the portion of the URL that is specific to your cart]. Example: Page contains /cart.php
  2. Transactions per user are = to 0.

Essentially, the user added something to their cart but did not check out.

3. Product Page View

This list gets a little complicated. If you’re lucky enough to have a site that’s URL structure contains /product/ on every product page, you’re in for an easy list build! Just set Page contains /product/ and Transactions = 0.

If you are like some of our clients, you’ll need to get a little creative. For example, we picked specific silos of the site that were the most profitable and combined them in one list, so if a user hits any of those silos or pages and products but did not check out, they’ll be included in this list.

 While these three ideas are not an exhaustive list of all the things you could test and build using Google Analytics and Dynamic Remarketing, this is generally where we like to start. Once you begin getting enough data, you can start optimizing and create new tests.

Have a great list idea that isn’t mentioned above? Please share it in the comments.

 

How Long Should I Run My Experiment in AdWords?


“How long should I run my experiment?” asks a ridiculously high number of online marketing managers. Typically, the answer to this question is more complicated than most want to hear. It may be a buzz phrase by now, but the goal with any experiment is to reach statistical significance–not simply to run an experiment for a pre-determined period of time. When measuring some AdWords metrics for a “winner,” it can be difficult to determine when statistical significance has been reached, especially with the limitations of the AdWords Experiments feature.

For any AdWords managers who are very hands-on with their accounts and want to verify statistically significant results, Delegator has provided the AdWords Statistical Significance Calculator. Whether you’re testing ad copy, different landing pages, or any assortment of variables that can be separated into “Group A” and “Group B,” this calculator allows you to work on actionable data alone.

Example: I am testing two separate landing pages with the exact same ad copy to see which page leads to the most conversions. I’ve been running my experiment for one week, and I have gathered this data so far:

Landing Page 1

  • Clicks: 958
  • Goal Completions: 33

Landing Page 2

  • Clicks: 1,014
  • Goal Completions: 45
The data is not significant.
Using the calculator, the results for my experiment are not significant, so I must either run my test longer or try a different test that may be more conclusive.

With any test, Delegator encourages running for at least one entire week since shopping and browsing patterns can vary by day of the week. After one full week, the calculator will let you know whether your data is conclusive enough for you to act on it.

Yes, this calculator is designed specifically for AdWords account managers, but the functionality can work on any data you collect about your website through any channel. For additional testing ideas or help managing your account, give us a shout.

Start Calculating Now!

How Do I Measure Remarketing Performance?


How do you know if you’re remarketing well? This is a tricky campaign to measure, especially since it’s more likely to play a big part in assisted conversions compared to any other campaign. For ecommerce clients, the “Time to Purchase” report might help give you some insight into how remarketing compares to the typical conversion cycle for last-click conversions.

The “Time to Purchase” report (categorized under the Ecommerce Conversion reports) has two views: “Days to Transactions” and “Visits to Transactions.” These two reports together give you a sense of just how engaged remarketed users are within the conversion cycle.

  
Photo: Company A remarketing results showing low engagement.

In the above report to the left, 18.18% of remarketing transactions have occurred 7-13 days after the initial visit. However, we see to the right that most remarketing transactions occurred in less than 4 visits to the site. What we’re seeing here is that, potentially, one to two weeks can go by with few visits back to the site before a remarketed customer will convert. This company may be interested in trying to close that time gap with a more robust remarketing strategy.

Alternately in the example below, most remarketing transactions occurred less than 4 days after the initial remarketed visit, yet a significant portion of visitors come back to the site 7-25 times until they convert. These visitors are highly engaged for fewer days. The company below had remarketing results much like what’s shown above until we put an expansive remarketing strategy into place. Now remarketing brings in a significant portion of last-click conversions and assists in almost every AdWords conversion.

  
Photo: Company B remarketing results showing high engagement.

Take a look at your “Time to Purchase” reports. If it looks like you’re not getting much engagement through remarketing, it might be time to rework or start up a new strategy. If you’re not sure where to get started, let us know so that we can help.

The 4 Most Overlooked Items During Google Analytics Setup


Google Analytics offers incredible insights on your site visitors, and the data it provides helps you make the most optimal business decisions. That being said, there are countless items in Analytics that usually end up overlooked when a new site is launched. If you want the cleanest, most relevant data possible from your Google Analytics, here are four key items to pay attention to during your setup.

1. Site Search

An easily overlooked Analytics option, site search can provide invaluable data on how your users are utilizing your internal search. Setting this up is a very simple process. First, perform a search on your site and then look in the resulting URL for the term you searched for. The string between the “?” and and “=” is the query parameter. In the case of Delegator.com, the query parameter is “s”, as seen below.
Site Search Query Parameter
Now that you know your query parameter, head over to the Admin panel in Google Analytics and click “View Settings” at the Profile level. Towards the bottom, you will see what’s in the screenshot below. Just check the box for “Do track Site Search”, enter your query parameter, click Apply, and you’re good to go!
Google Analytics Site Search Setting

2. IP Filters

Decisions are best made when backed by accurate, meaningful data. There’s no quicker way to muddle your Google Analytics data than to ignore its awesome filter options, specifically IP filters. A common best practice is to exclude the IP addresses of anyone on your team who is regularly on your site, so you’re not skewing your data.

To find out your IP address, just visit WhatIsMyIP.com and record the IP address it returns. Next, head over to the Admin panel in Google Analytics and click on “Filters” at the Profile level, then click on “New Filter”. Enter in a name for the filter and follow the layout in the screenshot below, inserting the IP address you recorded earlier. Then, just click save and you’re done! Repeat this process as needed for more employees or internal computers.

IP Filter - Google Analytics

3. Linking AdWords & Webmaster Tools

As simple as these two items are, I’ve seen them overlooked time and time again in Analytics audits. If you don’t link your AdWords account to Analytics, you are flying blind on your AdWords spend with respect to on-site metrics and ecommerce data. Don’t be that guy – it’s foolish to ignore such juicy, free data. Google walks you through the process in very clear detail here.

While you’re at it, linking your Webmaster Tools is a very simple process as well, outlined here. This lets you view Webmaster tool data within the Analytics interface, which is a lot more streamlined and easier to navigate.

4. Missing/Inaccurate Ecommerce Tracking

There are few things more frustrating in Google Analytics than having no ecommerce data for an ecommerce website. Setting up ecommerce tracking is a tricky piece that will most certainly require a developer to help implement, but it is absolutely invaluable to your long-term success. If you don’t have crystal clear transparency on how much revenue your various traffic sources are driving to your site then you are making suboptimal decisions, plain and simple.

Ecommerce Tracking Fail

These four items only represent a small portion of what often gets overlooked with your average Google Analytics setup. There are countless things you can do with remarketing lists and custom metrics. Same can be said for custom dashboards, reports, and advanced segments. The moral of the story? Don’t be content with “Vanilla Analytics”. Get out there and make your GA data more accurate and relevant!

The Science of Digital Landscapes


Calm down, reader. We’re not telling you to go out and buy goggles and an Erlenmeyer flask (but you can if that makes you feel fancy). The science of digital landscapes is grounded in one simple method: testing. As elusive as website testing may seem, it’s a method with important foundational principles.

A/B Testing

Maybe you’ve known for years that your company should be testing its webpages, but you don’t know where to start. Some testing tools that are marketed as easy-to-use quickly turn complicated, and sometimes they don’t allow the full spectrum of testing that you’re looking for. In our experience as a digital marketing agency, platforms for testing are ever-evolving, but throughout our years of testing we’ve established some staple principles and approaches that anyone looking to improve their digital presence should follow.

1. Annotate Everything

Even if you don’t know what to do with Google Analytics data, annotations are a crucial piece to both effective testing and keeping track of your website history. If you ever think, “Should I annotate this?” the answer is usually, “Yes.” We often dig into old data looking for trends and would never be able to identify what kicked traffic up or down without a stream of relevant annotations.
Screen Shot 2013-08-13 at 6.40.38 PM

2. Measure Results

With annotations in place, all you really have left is interpreting the data between and through these annotations. Figuring out what’s really going on with your site and attributing that to a cause will continue the beautiful cycle of testing. Maybe you changed the color of a button, and suddenly navigation to the page referred from the button click drops off. This information is just enough to start back at square one and try a different approach.

3. Form Realistic Hypotheses

Sometimes it’s hard to know what to test. As much as possible, let the data dictate what you test. Look for data drop-offs and low-engagement page elements. Rework huge eyesores, like walls of text and jarring readability roadblocks. Once you’re in the regular practice of measuring results, you’ll find yourself quickly collecting a pool of what to test and how to test it.

As a general rule, avoid forming hypotheses with “best practices.” Your site users are your own, and they don’t belong to A-list marketer/blogger Joe Schmo who wrote that post about always including purple unicorns in the footer. Nothing can inform what’s best for your site like your data does.

4. Use only SIGNIFICANT DATA

“How long should we test this?” I dub this the question of the year, every year. My response: “Until the data is statistically significant enough to draw a conclusion.”

Not everyone is a statistician. That’s okay. Just make sure you’ve got one on hand to check your conclusions. Interpreting data is not necessarily easy, so it’s best to leave any complicated analysis to the ones who can measure statistical significance.

5. Accept When You’re Wrong

Hypotheses are going to be wrong. Many tests will show you that you didn’t have it all figured out after all. Don’t let this make you feel like a failure, or like you don’t know your market well enough. There are too many factors outside of your control for you to always have a handle on how things should pan out. Being wrong in your assumption will ultimately land you on what does work. Let testing teach you about your audience. Relationships are hard!

We at Delegator know as well, if not better, than anyone else how difficult the entire testing process can be. We try our best to stick closely to these core principles and attitudes that we know will carry us through the frustrations, and, consequently, we land on many victories. Go ahead and make some adjustments. Approaching website improvements scientifically should alleviate some fears and uncertainty, and it’s best to remember that your website can ALWAYS be improved, no matter how great you may think it is. Just ask the data.

AlgoSleuth Updated for Panda 25


It’s been a little over a month now since the launch of our free SEO tool, AlgoSleuth. AlgoSleuth utilizes the power of the Google Analytics API to provide a powerful analysis of your site’s organic traffic and highlights all major Google Algorithm updates that may have affected you over the past several years.

AlgoSleuth was recently updated so that it now includes traffic data spanning Google’s most recent Panda 25 algorithm update. We will continue to update it well into the future as new algorithm updates are pushed out by Google. The next planned update will also include some new features we’ve been working on. If you haven’t tried out AlgoSleuth yet, just click below to grab a copy and test it on your site!

 

AlgoSleuth -  Now Updated for Panda 25

3 Advanced Segments You’ve Probably Never Used


So, it’s been a while since we last talked about Advanced Segments in Google Analytics. Over the past 18 months, Google has added even more value and depth to their Analytics offering, enough to easily overwhelm your average user. Advanced Segments allow you to quickly compare certain groups of visitors against one another, and these segments can also be combined with custom reports and filtering for even greater in-depth analysis. Here are three segments we highly recommend that you can quickly add (and tweak) to get even more out of Analytics.

1. Visitors who Abandoned a Goal

Conversion rates are the bread and butter of what keeps an e-commerce business ticking. Though it heavily depends on the industry, the average conversion rate for e-commerce sites is around 2-3%, at best. Having said that, wouldn’t you love to have better insight on your site visitors who DON’T convert? Having an advanced segment for visitors who start but do NOT finish a goal is invaluable. As illustrated below, this segment will allow you to track these visitors and try to narrow down the reason(s) why they dropped out of the funnel. Download it here. (Must Be Logged Into Google Account)

Advanced Segment - Abandoned A Goal

2. Separate Segments for AdWords Text Ads, PLAs, Remarketing & Display

With the recent addition of enhanced campaigns, it’s clear that Google is varying the ways it allows advertisers to reach their target audience. That being said, if you have a large account that uses more than just basic text ads it’s crucial to be able to see how they contrast with one another. If your account has PLAs, Display ads and Remarketing ads, why not have an Advanced Segment for each? This way, you can divide that traffic out and see how each is performing across ALL of the reports in Google Analytics. If your naming conventions are in proper order, this can be easily done by using our Advanced Segment (download it here – Note:Must Be Logged Into Google Account) and modifying it by using a simple “Include Campaign Containing” for “Remarketing”, “Display”, and “PLAs”. Create one advanced segment for each of those. Then, for the text ads, you simply set a filter to “Exclude Campaigns Containing” those same three, separated by “AND” statements. If your AdWords account doesn’t have each of these broken out into their own campaigns then you should definitely knock that out first.

Advanced Segment - AdWords Breakdown

3. Using the Service Provider Report for B2B Lead Gen

My last advanced segment comes straight from the LunaMetrics blog. I feel that this report has the potential to deliver a lot of value for B2B lead generation, as well as marketing agencies. With this advanced segment a large majority of the “legitimate” Internet Service Providers are filtered out so that when you go to the Network report under Audience > Technology > Network, you then should be able to scroll through this list and pick out companies that are large enough to show as their own “service provider”. Just to show the proof of concept, our Chattanooga neighbor Smart Furniture shows up on our list. Feel free to tinker around with this segment to try and see what more it might offer. Download it here(Must Be Logged Into Google Account)

Advanced Segment - B2B Lead Generation

Reporting TRUE AdWords Assisted Conversion Values


Great, Multi-Channel Expectations

When Google Analytics Multi-Channel funnels first came out, we were AWED and AMAZED. The metrics I latched onto first were the assisted transaction and revenue attributions. At last! Now those lower-converting AdWords campaigns could show their value. I knew they had to be doing something, but I didn’t have the tools to prove it before.

A Sad Discovery

I quickly came to discover, however, that these Assisted attributions are not in addition to the Last-Interaction conversions but rather include any conversion that involves an AdWords click along the conversion path, even if the Last-Interaction conversion was through AdWords as well. This means that we were reporting overlapping attribution on our AdWords transactions and revenue values! Basically, we couldn’t get anywhere near accurate revenue values for Assisted and Last-Interaction Conversions when combining their values together.

Data-Driven Redemption

That is, until we built a User-Defined Conversion Segment. We call our heroine “Exclude AdWords Last Interaction.” She looks a little something like this:

Exclude AdWords Last Interaction

Turn on this segment in the AdWords section of the Multi-Channel Funnels Assisted Conversions tab and it’ll set all of your Last-Interaction values to zero in addition to excluding any overlapping Last-Interaction revenue attributions from your Assisted conversion metrics. These are the REAL sidekicks — none posing as the breadwinner.

True Assisted Conversion Value

These reports now show overall revenue numbers that I can pass on to clients and not feel like they’re being quite so duped by the illusions of attribution as I once was.

If you need help setting up this segment or any similar to it, we’re here to help. Just let us know.

Set Up Analytics Alerts During Product Listing Ad Transition


Since Google Shopping completely falls under the umbrella of paid search as of October, some retailers are on edge about smoothly making this transition with little to no loss of product listing shoppers. This is especially important going into the holiday season when shoppers are clicking the mess out of those pretty pictures on their Google SERPs.

Now that these campaigns are becoming staples for positive PPC ROI, you’ll absolutely need to know whenever any anomalies occur. This is where custom alerts come in. Inside Google Analytics, you can set up a custom alert specifically for product listing ad campaigns and ad groups to monitor any online metrics on your site through these sources. To make sure your traffic isn’t dropping off, we recommend you set up an alert for any day when visitors from these sources significantly drop compared to the same day of the previous week. This way, you won’t have to lose days of revenue simply because you weren’t aware of a glitch that threw off or limited the eligibility of product ads.

Product Listing Ad Custom Alert

There are numerous other alerts you might want to set up for product ads, so think of what you’ll need to know in order to monitor this traffic and its conversions. For example, some product landing pages from these ads might have high bounce rates. You’ll be able to monitor these with alerts as well and begin looking into optimizing those particular pages. Take a few minutes to strategize and set up as many of these alerts preemptively as you can before you have to find out about an issue too late.

(Not Provided) Keyword Data to Rise


On May 7th, the Mozilla Privacy Blog announced that Google Secure Search has become the default standard in the Aurora build of Firefox.

Aurora is step 2 of 4 in the development cycle of the Firefox browser. This feature was announced weeks ago, but at the time was only in the Nightly development version of Firefox, a place where experimental changes are often tested and discarded. The move to the next development stage signals that Mozilla does intend to roll out this change in a future version of Firefox. You can read more about that, but the short version is, we can expect this to be the default search in the stable version of Firefox in 12-18 weeks

What does this mean for site owners and SEO’s? It will almost certainly mean a dramatic spike in (not provided) keyword data as Firefox is one of the most popular browsers in the world, with 35-38% of usage share in the US.

Many site owners are already seeing 15 or 20% of the search referral data as the dreaded (not provided) “keyword”. It is difficult to guess, but this number could be as high as 50-60% on some sites, when combining (not provided) data from logged in Google users as well as anyone using Firefox.

When the (not provided) referral data was introduced in October 2011 some site owners and SEO’s suggested that Google might be motivated purely by profits because all PPC keyword data can still be accessed anyone using Google Adwords. With the news that Google is paying the Mozilla Foundation $300 million a year to be the default search engine in Firefox, some people are questioning the Mozilla Foundation’s real motives with this move.

Feb. 14th, 2013 Update: Just as many analysts predicted, Google Chrome was not far behind in moving searches to SSL. iOS6 also jumped on the bandwagon now bringing the global averages for (not provided) keyword data to almost 30% of all organic traffic.