Category: Google Analytics

Above & Beyond: Last Click Attribution

Move beyond last click attribution in AdWords:

People often see many ads across different devices before making a purchase, booking a flight, or signing up for an account. Because of this, advertisers know that last click attribution may not always tell the full story. In 2014, we released the Attribution Modeling Tool in AdWords to share insights about how users interact with your ads. Later this month, you’ll be able to integrate the attribution model of your choice with your conversion data and bidding.

Attribution Model Dropdown - AdWords

For many years, we have jumped through hoops to report accurately based on client preferences on attribution model. This update is great step forward in that conversation. Unfortunately, this functionality acts more like a setting than a data filter. After making a change, future data is interpreted according to the new model. However, past data is unaltered. And if you ever wanted to switch back or compare two models, you can not easily view your data through the various lenses. You can only reset your preference and wait for data to collect – making the comparison of multiple models impossible.

 

Protect Against Duplicate Conversions Data in Analytics

via Google+:

Starting today, advertisers can insert Order IDs into AdWords conversion tags to automatically filter out duplicate conversions from the same device. By minimizing duplicate conversions and reviewing more accurate conversion data, you can make better budget and bidding decisions for your campaigns.

Until this update, advertisers added website code to make sure conversion tags didn’t fire again when people refreshed or returned to confirmation pages. For example, if you’re a hotel brand, you may notice customers returning to their booking confirmation pages, perhaps to find the reservation number or room check-in time the day before a trip. By including an Order ID into conversion tags, AdWords will not count these subsequent conversions with the same Order ID, so they won’t show up in your reporting.

Visit our Help Center to learn more and get started: https://goo.gl/XEzCEG

Although the negative impact has not been significant for most industries, it is nice to see Analytics taking steps to protect the accuracy of traffic data. At least now advertisers have a tool to protect against this sort of data bias.

The One Thing C-Suite Leaders Need To Know About PPC

Explaining The Value Of PPC To The C-Suite:

“There Isn’t Really A Traditional Funnel Anymore…It’s all about the micro moments.” – Jeff Allen

If there’s one drum beat I see our industry hammering this year, it’s that competition is just going to increase so getting creative and opening up your marketing scope will be the surest way to profitable campaigns. Each year there are more advertisers in the space, which drives up costs for the competition and then on top of that – the engines themselves change things fairly frequently (see: sidebar ad removal) and not always in a way that works out well for brands.

To complicate things further, as the search & digital landscapes continue to evolve, the consumers on the other side of the screen are maturing, as well. They know to research in more detail to make sure they’re getting the best deal and so on. The buying cycle is longer and starts earlier than it ever has before so the key is to solidify your position in every segment of the sales cycle, from consideration to purchase. This is a fact, and you can see it in the number of platforms, engines and technologies at the digital marketing industry’s fingertips. And they are all massively important to achieving continued and increasing profitability.

cross-channel conversion pathsDigital marketing has matured by leaps in bounds in the past few years. We now have a plethora of options – both in networks and targeting. However, the biggest shortcoming of our industry remains to be cross-channel tracking. That is folks who interact with ads on several different networks before making their buying decision. From each network’s reporting tools you can see only parts of the conversion path. But no reporting tool gives you the entire picture. Meanwhile, conversion paths are getting more and more complex. The temptation is to base advertising decisions based solely on what can be tracked (via Google Analytics or the like). But although the data doesn’t show the whole picture, we know these complex funnels are happening – both through buyer behavior studies and our own personal behaviors. We often see clients who want to limit their advertising to what is directly trackable, thereby neglecting the rest of the sales funnel and likely limiting their account’s true potential.

This is the biggest ‘miss’ in digital advertising today. And with most major search engines moving increasingly towards privacy (and rightfully so), it is unlikely that this type of tracking will be available anytime soon. In the meantime, smart marketers will need to rely a little more on intuition than raw data, if they want to fulfill their digital marketing potential.

Introducing Google’s New Analytics 360 Suite

The Google Analytics 360 Suite is a set of six integrated data and marketing analytics products, designed specifically for the needs of enterprise-class marketers. It all starts with understanding consumer behavior in the moment — getting the right insights, and then making your brand useful to consumers.

Google Analytics 360, formerly known as GA Premium, will roll out exciting new capabilities throughout the next couple of months as investments continue to grow. It will serve as the measurement centerpiece by analyzing customer data from all touch-points and integrating with our ad products to drive marketing effectiveness.

The new products — Audience Center 360, Optimize 360, Data Studio 360, and Tag Manager 360 — are available today in limited BETA. If you’re a Google Analytics Premium or Adometry customer, you will see the products renamed in the coming months, and we’ll let you know when you’re eligible to join the new betas.

via the Google Analytics Blog.

What Does It All Mean BasilWhat does this mean for most Google Analytics users? Not much, at least yet. This new suite of tools is marketed towards existing (and future) Google Analytics Premium users and offers some features that people have been craving for a long time. Google promises that Analytics 360 will allow users to “See customer behavior, channel performance, and much more in robust reports and dashboards. Connect online to offline as you understand user behavior across CRM, points of sale, call centers, devices, and the Internet of Things.”

With respect to just Google Analytics, the only primary change is that Google Analytics Premium is getting renamed Google Analytics 360. No new updates are being announced at this time, but several “exciting new capabilities” are on the horizon when the Analytics 360 Beta begins rolling out later in 2016, says Google. If you’re not a current Google Analytics Premium customer or don’t subscribe to the new Analytics 360 product, these new features will not be available to you.

Each of the six products in the Google Analytics 360 Suite will be available for purchase à la carte. Setup will be customized depending on the products a company chooses. Each product is also open, meaning all will integrate with non-Google, third-party products.

If you have any other concerns on how this change might affect you, let us know in the comments below!

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