We’ve gathered 6 reasons to monitor mentions and prepared actionable tips that will help you to manage your reputation based on what people are saying online. Bonus: awesome infographics inside.
We’ve gathered 6 reasons to monitor mentions and prepared actionable tips that will help you to manage your reputation based on what people are saying online. Bonus: awesome infographics inside.
Google Analytics 360 customers that use DoubleClick Campaign Manager (DCM) can take advantage of a native integration and link the two products together, bringing DCM data directly into your Google Analytics reports. Access your View-Through and Click-Through metrics within your Acquisition reporting and gain better insight into how your DCM traffic compares with other traffic channels. Excited yet? Keep reading!
DCM stands for DoubleClick Campaign Manager and is the central hub for advertisers to serve display ads and manage campaigns (publishers, check out the DFP integration). DCM is where you can perform media planning, manage creatives, target ads and run reporting (though it is not where you buy inventory).
DCM was formerly called DoubleClick for Advertisers (DFA) which was replaced with this new, robust platform. You can think of DCM as the super-charged option compared to running display ads through AdWords and the Google Display Network (GDN, another acronym!) since trafficking can involve non-Google networks and ads can be placed directly on specific sites. Beyond the popular leaderboards and rectangles, it includes cross-device, video, rich media and YouTube ViewThru formats in addition to the typical static display and creative sizes.
DCM is optimized for enterprise-level organizations like large Ecommerce sites, travel sites and banks as just a few examples. Small to mid-size businesses will likely use AdWords to run display campaigns.
If this sounds like your organization or corporation, chances are you are already on the enterprise/premium Google Analytics 360 as well. This is great news! With 360, you have the ability to integrate the two platforms and let DoubleClick Campaign Manager share data with Google Analytics. This is a great benefit because it unlocks a subset of reports under Acquisition that are specific to DCM. But before we get to those…
If you have both DCM and Google Analytics 360, there’s no reason not to integrate. Once the decision is made, contact your Google Partner to start the process since it involves e-mailing permissions and Google engineers enabling the link on their end.
The information you will need to provide is the following:
Media cost data does not have to be included with the integration, so make sure to ask your DCM manager if they would like those metrics to be shared with Google Analytics. Typically different teams are viewing each platform, so it’s a good idea to check.
*Watch out! This can be confusing if you are using a shared DCM account. If that is the case, use the parent Advertiser ID.
You’ll work with your Google Partner to help get the link established between DCM and GA.
As you’re setting up this integration, make sure that the Google Analytics or Google Tag Manager settings are ready to go as well.
In Google Analytics, navigate to Admin >> Property >> Tracking Info >> Data Collection. The toggle for Advertising Reporting Features needs to be turned on after reviewing Google’s related policy as well as your organization’s own privacy policies.
If you are tracking through Google Tag Manager, you can find this setting in your Pageview tag under More Settings >> Advertising.
Once the link is active, you’ll be able to see it under Admin >> Property >> DoubleClick Digital Marketing >> DoubleClick Campaign Manager Linking.
This is also where you will have to choose which views you would like to see the data in. If no views are checked, the reports will be blank so don’t skip this step.
Before we get into the reports, it’s time to address the first thing that you or your teammates will notice right away…
When I mention mismatched metrics like sessions, transactions and conversions, I’m not just referring to the discrepancies between the DCM platform and Google Analytics. I’m referring to comparing the Source/Medium report to the DoubleClick Campaign Manager report in Google Analytics under the same property. This doesn’t mean that the integration is broken or that you are doing anything wrong with DCM or Google Analytics.
It’s important to know that these are two different tracking programs and they work and behave using two different models. The DCM model lives in its own bubble and really only cares about itself – all traffic that isn’t DCM will be ignored. So in Google Analytics, this model is used only in the DoubleClick Campaign Manager reports section. The usual GA attribution can be expected in the regular reports, which is why the numbers will be so different.
Let’s take an example – if a user ever saw or clicked a DCM ad at any point then visited your site, it will be counted in the DCM model. So if I see and click an ad somewhere, then eventually search for something and click on your site’s organic link, then in my DCM reports, it will count as a DCM session and another Click-through.
This model makes sense here because the integration metrics come directly from DoubleClick Campaign manager. DCM is all about how many eyeballs saw your ad so the model will be about impressions and clicks regardless of other traffic sources in other sessions. This is similar to how AdWords reports don’t exactly match your GA reports.
Having these reports available lets you tie ad trafficking activity to your web behavior and thus your users’ experience.
You will see a new menu option when you go to the reporting tab in the Google Analytics 360 interface under Acquisition >> DoubleClick Campaign Manager.
In addition to these specialized reports, DCM traffic will also show up in Google Analytics reports that you may already be familiar with.
This section refers to the main All Traffic reports under Acquisition in Google Analytics. DCM traffic will show up as dfa/cpm which is a throwback to the DoubleClick for Advertisers days. It uses the usual Google Analytics model rather than the DCM model for sessions, conversions and transactions.
If your data looks different and you do not see ‘dfa’, check out this information on UTM overrides.
Use this report when you want to see sessions that are directly from your DCM ads and when you want to see conversions where DCM was the most recent session. TIP: Switch to the ‘Floodlight’ tab in the Explorer to see the DCM Conversions and DCM Revenue metrics with Source/Medium.
The dfa source and cpm medium will be grouped into the ‘Display’ channel by default, so you can see that data in the Channels and Treemaps reports as well.
To analyze DCM as it relates to multi-session journeys, check out the Conversions >> Multi-Channel Funnel Reports and the Attribution >> Model Comparison Tool reports. Above the reports you can switch from All to DCM to see DCM paths by advertiser, site, campaign and placement. Now we’re getting even more value by combining DoubleClick Campaign Manager data with Data-Driven Attribution!
DCM and DCM with the Google Analytics Model are available to use as secondary dimensions in the standard reports as well as in custom reports. These dimensions are around advertiser, site, placement, Floodlight IDs and activities, as well as creatives and ads.
I’ll note that the DCM (still referred to as DFA) metrics are not included in the Google Analytics BigQuery tables, unlike DFP. They are also not funneled into the Data Studio Google Analytics data source, however a new DCM data connector was recently released.
The DoubleClick Campaign Manager and Google Analytics 360 integration provides the opportunity to analyze DCM campaign performance alongside your Google Analytics data. The integration does not cost extra above the cost of Google Analytics 360, so existing customers can get started by contacting their Google Analytics Certified Partner. Enterprise organizations using the free version of Google Analytics will not be able to use these reports inside of Google Analytics without upgrading to the Google Analytics 360.
Being able to see richer display data allows you to analyze engagement, weight attribution and have insight into how it relates to the micro-conversions you may have set-up as Google Analytics goals. It also provides an opportunity for collaboration and transparency if your organization works with a media team using DCM separate from your web and analytics team using Google Analytics.
Providing SEO services even to this day is still a very lucrative venture. The SEO industry is estimated to be worth $79 billion by 2020, according to SEL’s report last year. Whether you choose to be a solo consultant or to start and operate your own agency – there is money in it. I can […]
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As Google Analytics (GA) Analysts and Enthusiasts, we love strategy. We love to look forward. But it seems at times our industry, and ourselves included, can easily become fixated on the new:
But maintenance is important. It allows us to head off problems before they catch fire.
Regularly checking in also allows us the ability to be proactive about trends. This way, we are no longer reactively building our implementation and applying band-aid fixes.
Let’s avoid frustration and develop a solid approach so this doesn’t happen:
The important thing is stay on a schedule. You’ve heard the adage “Practice Makes Perfect” or the adjusted “Perfect Practice Makes Perfect.” It’s important to be consistently checking in to Google Analytics and checking that things are tracking properly, that your numbers are going in the right direction, and that you’re collecting the right data to make decisions. Not sure where to begin? We’ve helped to create a schedule to stay on track.
While not necessarily exhaustive, it identifies several key recurring milestones to help us keep our implementation in peak running order. It also has built-in a method for routine reporting and trends analysis. We have broken out the Calendar into Weekly, Monthly, Quarterly, Semi-Yearly and Yearly Tasks. The tasks within the calendar are spread throughout the year so new day/month is overly front-loaded when those yearly tasks roll around. You can configure it to send an email reminder the day before the task is due.
Below is a breakdown and summary of each one. They also include links to sample reports from the Google Merchandise Store Analytics Demo Account. You can gain access to their GA data here.
Check conversions for any noticeable movement week over week.
Look over the default reports for any anomalous activity.
Check the monthly Bounce Rate compared to the prior month.
Review Change History for any undocumented/unknown activity. (You’ll need edit permissions at the account level to view).
If found, confirm changes with stakeholders and place any necessary annotations.
Check Monthly Conversions Compared to the same month the prior year. This is a big one. Allow yourself some time to complete.
Check and record your property hit volume from the past 30 days.
Check the hostnames sending data to your property from the prior 90 days.
Monitor Spam Traffic on your site in the past month.
Check the Channels Report compared to the same quarter last year.
Doublecheck the other Google products that are linked with your GA property, like Google AdWords, etc.
Assess your Default Channel Groupings Configuration.
Check Six-Month Conversions compared to the same period the prior year. This is a big one. Allow yourself some time to complete.
These tasks are broken out throughout the year bi-monthly.
Check your site(s) for missing GA/GTM code.
Check your Google Analytics Configuration for PII
Check Google Analytics Goals and Filters setup.
Check Google Analytics Custom Dimensions & Metrics setup.
Are there any new dimensions/metrics that need to be added.
Check Google Analytics Goals and Filters setup.
Check Google Analytics User Access Settings across all levels (Account, Property & View).
Opposed to daily calendar tasks, we’d recommend establishing custom alerts to notify you should any major tracking event occur. Custom Alerts such as:
This holistic approach will help you keep tabs on and stay pro-active with your Google Analytics Properties. Let’s keep things nice and tidy!
Content Marketing offers a tremendous opportunity for businesses to boost their results — it allows you to improve your online reputation, build a community and grow advocates of your brand. Check this guide to learn how to develop a great Content Marketing strategy for your company in 2019, step by step.
If you read our blog regularly, you’ve heard about Google Data Studio, a great new product from Google that’s designed for data visualization and reporting collaboration/sharing. If you haven’t already created a few reports, make sure to check out Jon’s excellent overview of the tool and its features before you get started.
Similar to other reporting tools like Tableau, you can connect multiple data sources to Data Studio and create customized visualizations. You can even get granular with stylization. But, while it’s nice to be able to make reports look pretty, it’s equally important to focus on the data. Remember why we’re creating reports in the first place – to visualize data in ways that make it valuable and actionable for its audiences. Like any reporting or implementation efforts, it can help to have a strategy for Data Studio before you dive in.
The first step, if you haven’t done this already, is to identify the goals for your website – this is a must! Determine what data you’ll use to measure goal achievement; different users or teams may have their own goals and metrics that they use for measurement and analysis. If you don’t have an idea of what you hope to accomplish with your website, it will be difficult to visualize success.
In addition to pinning down your objectives, you’ll want to make sure you have systems in place to collect the right data, whether through Google Analytics or another source. By establishing key metrics early on, you’ll have direction when building reports later.
Will Data Studio be used as the final data visualization, or do reports still need to be shared in a different format? Identify who will be using the data and in what applications. There are often many people using datasets to measure their achievements and contribution to reaching goals.
Data Studio works well for situations like the following:
Data Studio can be a great option for some, but not meet the needs of others. Keep in mind that Google Data Studio is still in beta, and they are constantly making updates, fixes, and adding new features! Don’t believe me? Check out the release notes, they’ve been updating Data Studio about every week or so. So while some features may not be perfect just yet, remember that Google Data Studio will just continue to get better!
One of the best features of Data Studio is the ability to dynamically interact with the report, changing the date range, filtering elements, etc. Understandably, however, many will see Data Studio as a replacement or upgrade for existing report visualizations within the Google products they’re currently using, like Google Analytics and Google AdWords. This leads to one of the biggest gripes that we’ve heard so far, which is the limited ability to download or email static reports easily from Data Studio.
Currently, there’s no easy to do this from within the interface. Your browser may support printing the report to a PDF, but you may need to manually stitch multiple pages together. Remember that if you do use a method to save your report as a PDF, you lose the elements of interactivity and shareability that make Data Studio special.
Although our love for Data Studio runs deep, it does have limitations in some cases. In these situations, other reporting solutions may still be a better fit, from basic (Google Analytics Dashboards, Excel) to complex (R, APIs). For example:
How will you get the data into your reports? Will it come from several different sources? This is where you can plan out what Data Studio connectors you’ll need to use to get the right information into your reports. Data Studio currently provides several types of connectors that allow you to bring in data from Google products (including ad platforms), databases and external files.
The list of connectors has grown since Data Studio first launched, and will likely continue to grow. While it doesn’t include many third-party connectors, it does give you the ability to bring in data from your own databases, an uploaded file, or our personal favorite, Google Sheets. If you can get the data into Google Sheets, via APIS, Add-Ons, or any other method, you can visualize it in Google Data Studio.
For more information about connectors, check out Sam’s post on data connectors and data sources.
Once you’ve decided that Data Studio is the way to go, start planning your reports, or check out a few templates first. (We have a content template and an ecommerce template!) This is a step that many people skip, but can actually be more efficient. By envisioning the way you want to present data in your reports, you may not end up needing to spend as much time configuring or manipulating the data within the Data Studio interface.
Whether you use a wireframe tool, whiteboard, a sketchpad or MS Paint (no judgement), make this a quick exercise. Based on the goals for your website, what metrics or data show that these goals are being achieved or provide insight into key interactions throughout the site? Whether from Google Analytics or another data source, it’s important to know what pieces of information you want to include in order to make the report useful.
You may have different ways of visualizing data depending on the department or team, and this step helps you make sure your final Data Studio reports are relevant and useful.
Finally! This is the moment you’ve been waiting for. Now that you know what data you want to include and an idea of how it should be presented, set up your data sources and add it to your report. There are several built-in options for charts and graphs, so you can choose the ones that best visualize your data. Then, get creative by adding brand logos and images, customizing colors and fonts, etc. You can even easily add notes and analysis anywhere within the report, which isn’t possible with Google Analytics Custom Reports or Dashboards.
Hopefully, because you’ve developed a strategy and framework ahead of time, you won’t end up spending most of your time formatting. Instead, you’ll be able to dedicate more time to using the reports for the exciting stuff that really matters, like analysis and measurement!
If you are a publisher, using Google Analytics, but only relying on Pageviews and Sessions metrics, with all due respect, you are doing it wrong. Or rather, you’re not getting the full benefit of your investment in analytics.
This post is developed to inspire you to dig in your data, slice and dice it in a structured way, and look for opportunities where you can advance your KPIs and grow your business. Regardless of what KPIs you are focused on, whether it is increasing ad revenue, increasing engagement, creating awareness, bringing in new subscribers, etc, you should be always using the data you collected in GA to enhance your understanding of your audience, produce the most valuable content, and share it with your users at the right time (and potentially at the right place).
Some of the following questions would help you make quick decisions about content, users, events, and sources. There will also be some advanced questions that could be better addressed outside the GA interface, through a “data science project” via BigQuery. Hopefully we spark some advanced reporting ideas, inspire you about adopting more personalized content recommendation techniques, and discuss the importance and relevance of a few new analytics tools, namely Google BigQuery, Data Studio, and Optimize.
Also, before you begin answering the questions in this post, think about what your reaction would be to the findings; ask yourself how the results could benefit different teams in your organization – whether it be technical aspects, creative insights, or content/authorship related subjects.
Publishers have a trove of information outside of Google Analytics that when married with online performance and behavioral data can help enhance their reporting and understanding of how the content or the audience performs. We can use two different features in GA to bring in this external information: Custom Dimensions and Content Groupings. Hopefully you’re familiar with these features, or else we have a great post about the differences between the two.
At the very minimum, I would recommend having the following dimensions defined in your Google Analytics account:
Content related dimensions:
User related dimensions:
Be creative and come up with dozens of other content/user oriented dimensions. This is especially relevant if you are a Google Analytics 360 customer and you have the ability to allocate 200 different dimensions.
To populate values in these custom dimensions you can use Google Tag Manager or use the Data Import feature of Google Analytics. Through GTM, You can pull what you need off the page from the
Meta tags, or get them from the values in the
dataLayer. You can then set these values as custom dimensions or content groupings.
Let’s start by looking at some reports around the content you are producing.
Here are some high-level ideas for reporting on content – the idea is to figure out if the content is engaging enough, and where we could improve. To answer these you can create custom reports and segments or analyze the data in Google BigQuery. BigQuery is the best tool for analyzing the customer journey.
1. Which categories drive the most traffic? To answer this, create a report to show the number of sessions by the Category custom dimension or Content Groups.
2. Article Views by Author: Who are the best performing authors? Which authors write the articles that get the least pageviews? Also, find out in which categories those authors are showing their best performance. To see this, pull a report for Pageviews by Author per Category/Content Groups. Furthermore, look at Acquisition per Author and measure the SEO effectiveness.
3. How many days does it take for a “hot” article to cool off?
4. What is the worst performing type of content on the site? What content is least engaging for your users? What can you do to help prevent them from leaving prematurely?
These reports would eventually help you with optimizing your Content Recommendation Engine based on the feedback you are receiving from GA. You want to make sure recommended contents are relevant to the user, based on what you know about them.
5. How much content do users view in one session, on average?
6. Do people who navigate through the recommended content tend to stay longer on the site, because they found the recommendations relevant and useful?
7. Which great articles are being dismissed when it comes to Organic search? Navigate to the All Page reports, apply the Organic Traffic Segment, and look for pages that have high pageviews but low entrances; these may be the pages that aren’t ranking well organically, but could be better optimized (SEO opportunity).
8. For bloggers, what is the best time of day to publish new content? Which day of the week is best? Are users more active on your site during certain times of the day vs others? Do these times differ based on what day of the week it is? For more guidance visit this blog on creating custom reports.
9. What is the impact of promoted content on overall user experience? What is the readership of the promoted content? Do users who consume the promoted content tend to interact with more content during the same session, or they find them irrelevant and exit the site? Is the promoted content a good representation of the quality of all contents? To answer these questions, you can create a segment of all users who interacted with the promoted content, and figure out how different their experience is, within a session, compared to all other users.
10. Context Switching: Do users navigate through different categories in a session e.g. going from tech news to sports to arts etc, or do they stay within one content group?
11. Which navigation features need to be developed or improved to help with finding new relevant content?
12. Do the length of the articles users are most engaged with have to do with the device type used to view them? Do users tend to read shorter articles on their phones? What about longer or more “analytical” pieces? Are those mostly read on desktops or tablets?
13. Comments: What content categories are the most promising when it comes to leaving personal/social comments? E.g. an editorial piece vs an analytical study vs a matter of fact report. How would you encourage discussions across the site? On average, how many comments does each article get? Also, analyze how users are interacting with each other; how many direct replies does a user receive after leaving a comment?
14. Cross Content Activity: In what percentage of sessions did users view different types of content? E.g. going from videos to articles to image galleries, etc.
Answering these questions will enable you to provide a more personalized experience to your audience and keep them more engaged on the site.
Now let’s discuss user engagement. Assuming you are tracking a variety of events through Google Tag Manager such as Navigation Menu clicks, Promotion clicks, Carousel (slider) clicks, Lazy Load events, clicks on Recommended Content, video interactions, scroll interactions, time spent engaging with the content (as opposed to the built-in Time on Page metric), etc, you should be able to pull detailed reports around user engagement. Google Analytics 360 would enable you slice and dice the event data to some extent, but using BigQuery for data analysis is highly recommended.
Here are some high-level questions to get the gears turning:
15. Which block of real estate is extremely valuable on the top level pages?
16. How does the position of a promoted/recommended content play a role in keeping the users engaged? Does promoting content on the side of the page work better than the bottom or the top?
Here are some high-level ideas for reporting on how video engagement looks throughout the site – must have Video Tracking in place:
17. What percentage of sessions included video interactions? What percentage of users watched videos? How many “video plays” were there vs. “videos watched to the end” (90% of the length or so)? What is the drop-off rate?
18. How does the engagement look across different devices?
19. Which user cohort (think locations, demographics, etc) is highly interested in videos? On average, how many more minutes do the “video consumers” spend watching videos compared to the other cohorts (e.g. “News Readers”)?
20. What percentage of users are highly engaged with videos, aka “video consumers”?
21. Which video category is the most engaging; e.g. sports vs tech or interviews vs reporting vs analytical pieces? What are the hottest video topics and stories? Also, break down the reports looking at different user groups.
If you are using our Scroll Tracking recipe, you should be able to create the following reports in the GA interface, Data Studio, or BigQuery.
22. How far down the page do people scroll? What does the breakdown look for different categories? You could also create a Custom Funnel in GA 360 to visualize the results, and have a separate tab for each category.
23. How long do people stay on different pages? The answer is pretty straight-forward if you are using our Engagement Timer recipe; you would need to breakdown the overall time per category; e.g. try to figure out if users are staying longer on the entertainment section.
24. Who are the most engaging authors or content producers? Create the Article Engagement by Author report, to look at the highest active time on page values (using the results of the Engagement Timer) in conjunction with scroll depth results.
25. Using the Engagement Timer, you can also create two Reader Cohorts, i.e. Skimmers and Readers, and analyze their behavior differently. Could you figure out which group is consuming the most content, and which group stays on the site longer?
We analyzed the audiences quite a bit so far within other reports. Now let’s examine the individuals more closely, with the hopes that it helps you personalizing the content and features.
26. How often do users return to your site? Look at Frequency & Recency reports. Also compare the trends between New Users and Returning Users.
27. What devices do your users use to visit your site, and are they working? Is your site optimized to support those devices? Is mobile traffic increasing? Are mobile visitors more or less engaged? You can apply the Mobile Segment in your Production View, or create a Mobile Only View to better analyze mobile traffic.
28. Ad-block Usage: What percentage of non-paying users are using ad-blocks? How much ad revenue are you loosing for those sessions? Do you need to start thinking about enforcing ad-block rules? Or are there better models for monetizing the site? You might want to focus on personalization and producing better content to encourage non-paying ad-blocking users to subscribe.
29. Geo: Are you segmenting the content based on its locality? Are you segmenting the users based on their location?
30. Are your users mostly relying on you to provide them with up-to-date local news? Or have you observed some other patterns?
31. Do visitors from rural areas show different browsing habits compared to the urban traffic?
32. Income: When segmenting users based on their income, or any other of the custom dimensions you added, do you see different trends in the type of content consumed, average time on site, video/scroll engagement, “Readers vs Skimmers”, etc?
33. Education and Professions: How does the education level impact all other dimensions described so far? What about different professions?
34. Top Commenters: Who are they and what do you know about them? What are they interested in?
35. If the intended demographics for particular content is provided by the author/content producer in the Meta data, you could take advantage of it to feed your recommendation engine with more granular data to come up with the most relevant content recommendations (personalization).
If you have implemented Login Tracking and are capturing User IDs in Google Analytics, you can benefit from using a “Logged-in” segment or a “User ID” view to analyze the behavioral patterns in segregation. Studying the subscribers pattern will help you come up with ideas for enhancing your “new subscribers” conversion funnel.
36a. Do subscribers visit the site more often? What about their content consumption patterns
36b. Do they read/watch fewer or more content?
36c. How engaged are the logged-in users?
36d. How many devices are used by logged-in users?
36e. How is Device Switching happening throughout the day? Do the users access the site on their desktops during the days and mobiles/tablets during the evenings? Would you prefer recommending longer or shorter content with regards to the device currently in use? Maybe offering different versions of the same article?
You can also plan on evaluating some of your hypotheses via A/B testing through Google Optimize.
Last but not least, let’s look at the Sources of traffic, how effective they are, and if they are impacting the browsing habits:
37. Authors: Measure how much new organic traffic each author is generating.
38. What is the Bounce Rates on the Landing Pages?
39. What is the number of articles read in a session per Source of the traffic? Try to figure out which Source is driving the most engaged users.
40. Social Trust: How often are “returning users” coming back through social channels?
41. Which categories drive the most “social traffic”? Which categories are best performing/highly engaging on social media? E.g. Compare the performance of different categories bringing in new traffic from Facebook vs LinkedIn vs Twitter.
42. Do you see spikes in metrics for timely content on heavy news days? If not, probably your users are getting their news elsewhere.
Publishers are putting in so much effort creating online content. Most publishers also invest heavily in their analytics infrastructure. But not all publishers are making data-driven decisions as to what to produce and how to create a more personalized experience for their users. I hope this blog inspired you to take another look at the piles of data you are collecting everyday in Google Analytics, understand what your visitors are there for, and come up with new hypotheses and tests to improve your online services to create the best experience possible.
By analyzing the content, events, audiences, and sources, you can provide quality content to the right consumers. By studying different user cohorts and analyzing the visitors’ past viewing habits and attributes, you could gain substantial insight into how to enhance your recommendation engine and how to dynamically change the experience for your users.
There are two ways to succeed in content marketing: Be the first one to break a story. Or be the best one to tell it. The latter is where a 10x content happens. By providing content 10x better than what is currently out there for a certain topic. Apart from offering a great product/service, content is […]
Let’s take up an example of Iron Man to understand the entire buzz around Voice Search Optimization. Now, where does Iron Man come in an article about Voice recognition? The answer lies in the process of communication that happened between the super hero and his trusted lieutenant J.A.R.V.I.S.
Every question of Tony Stark was preceded with “Why” “How” “What” “Who” followed with a precise information query. The answer was prompt and to the point without any unwanted results or suggestions.
50% of the top million websites use Google Tag Manager, the incredibly powerful analytics/marketing tool that quickly deploys tagging across your website. Want to do Facebook remarketing? Subscribing to HubSpot, Pardot or another marketing automation service? Need to add an AdWords conversion tag?
So many actions marketers take require additional tracking code to be placed on website code and Google Tag Manager will handle that for us. Best of all, you don’t have to be an analytics nerd to implement this! Tag Manager empowers marketers to own and make changes without development or technical help. I’m not a coder at all, and I’ve launched GTM on a few dozen WordPress websites.
In the simplest configuration, Google Tag Manager fires and controls the Google Analytics tag on your website. See our post “What is Google Tag Manager? (And How Does It Work With Google Analytics?)” below for more gushing.
Navigate to the Tag Manager page and to sign up for free.
Create a new GTM account. Account name best practice: Use your company name (e.g. Alice’s Wonderland Resorts LLC).
Now name your container and choose what you want to track. Since we’re talking about WordPress websites here, select Web. Container name best practice: Use the domain name of your website (e.g. www.aliceswonderlandresorts.com).
Yes, I told you this wouldn’t be technical. It’s not! We just need to do a few copy / pastes. Once you click create, you’ll be presented with the following popup that contains the code that needs to be added to your site. This code snippet will have your Container ID, which is super important! Mine below is just an example. Don’t use it.
In WordPress, navigate to Appearance, then Editor. If you don’t see this option, then you do not have Admin access to your site.
Look on the right-hand side and you’ll see the files the make your WordPress template work. Look for Header.php and edit. This files controls all page templates in WordPress.
Paste the top portion of GTM code right after the opening <head> element (see screenshot). Use your browser search to locate the <head> if needed.
Paste the second portion of GTM code right after the opening <body> element.
Don’t monkey around with other stuff! Seriously.
When you’re done, click Update File.
Head over to our website and grab our basic recipe pack for GTM to do some Google Analytics tracking. This GTM pack will allow you to easily add ready-to-go tags to your new GTM container. If you have Google Analytics installed already, the recipe instructions will tell you how to add your tracking number to GTM.
Note: you don’t have to set up Google Analytics through Tag Manager, but it’s recommended. You can install Tag Manager and leave your existing Analytics in place. Learn about how Google Tag Manager and Google Analytics can work together.
Super Important Note: Google Analytics should only load on your page once. If you’re using a different WordPress plugin to load Google Analytics, then do not also load Google Analytics through Google Tag Manager.
Maybe you just need to install a Facebook remarketing snippet without a developer, use Tag Manager! But if you would like to migrate your Google Analytics tracking to Tag Manager, see our blog post that covers some other points about migrating your on-page Google Analytics to Google Tag Manager.
If you need to set up tracking for external service because you want to do some advanced marketing tracking or measure conversions from social or paid ad spends, it’s easy! Google Tag Manager comes pre-loaded with tons of external tags (view list) or you can use a special tag called a Custom HTML Tag to paste in other tags.
Here are GTM instructions for integrating popular marketing tags:
Remember to test your tags before publishing them. Google Tag Manager has built-in previewing and debugging. We also cover a few Chrome extensions for debugging that will come in handy!
Tag Assistant is a nifty freebie will look for the GTM container in your site source code and let you know that everything works. Add Google Tag Assistant to Chrome from the Chrome Store.
Now, re-load your website and open Tag Assistant. You should see a happy little face with your container ID:
Ding! My timer just rang. Did you make it? Remember, you don’t have to migrate Google Analytics right away if you just need to get one advertising tag on your site via GTM. You can do that step next (Spoiler: it takes longer than 4 minutes) and we’d love to help. Have you done a quick & dirty GTM launch like this in the past?