… and more?<\/p>\n
When you have the ability to track your ROI on every launch, every funnel, every email, and ad campaign \u2014 you can cut the fat and double down on what’s working.\u00a0![\""You](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox1.png\")
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This transforms your business from one that spends time, money, and resources on strategies that just seem<\/em> like they’ll work well, to a business that makes smart, data-driven decisions and knows<\/em> what strategies will work well.<\/p>\n To do just that, you need Google Analytics campaign tracking.<\/p>\n (RELATED:<\/strong> Applying Website Analytics to Your Digital Marketing<\/a>)<\/p>\n Today, we’re sharing the complete guide to Google Analytics campaign tracking, including…<\/p>\n Ready to dive in?<\/p>\n Let’s start with\u00a0tracking how visitors are getting to your site. We\u2019re going to do this with UTM parameters…\u00a0<\/strong>\u00a0<\/strong><\/p>\n Do you know what UTM stands for?<\/p>\n If so, you\u2019re officially one of the cool kids in digital marketing. \ud83d\ude42 UTM is short for…<\/p>\n Urchin Tracking Module<\/strong><\/em>, a system that allows users to tag hyperlinks in order to trace where visitors originated.<\/p><\/blockquote>\n If you\u2019re a Google Analytics<\/a> user (which you should be<\/a>), you can use these to figure out how people are getting to your site (and what they\u2019re doing when they get there).<\/p>\n By adding additional text on the end of every hyperlink you share, you can tag people who click those links (and hit your site) with relevant information about…<\/p>\n Let\u2019s give a quick overview of the different UTM parameters that matter:<\/p>\n Generally speaking, source describes where your visitors came from.<\/p>\n It tells you the specific place where the referring link lives:<\/p>\n Common sources include:<\/p>\n Medium tells you how the visitors got to your site.<\/p>\n This is the highest-level way to sort data with UTMs and consequently includes the broadest categories.\u00a0Some of the most common mediums include:<\/p>\n This describes the specific ad, banner, or email used to share the link.<\/p>\n It is used to determine what creative is working best at promoting an offer or distributing content. This will vary wildly by platform, content type, and offer. And there\u2019s no standard for nomenclature.<\/p>\n My advice?<\/p>\n Be descriptive<\/strong> so you can easily remember what email or ad<\/strong> you\u2019re talking about.<\/p>\n Campaign is similar to content in that it\u2019s a pretty open-ended field.<\/p>\n Its basic purpose is to highlight promotional offers or content distribution strategies so you can easily compare performance across time and platform.<\/p>\n Campaign links should be consistent across all different sources and media <\/strong>for any given promotion to ensure the campaign as a whole can easily be analyzed.<\/p>\n Here\u2019s an example that shows exactly what one of these links might look like for a flash sale of the Content Engine<\/a> (one of DigitalMarketer\u2019s Execution Plans):<\/p>\n Creating properly attributed hyperlinks will take some time to get used to, but the data it provides will be worth its weight in gold.<\/p>\n To make consistency easy, I recommend creating a unified document where you track all the hyperlinks you use, making it easy to refer back to when you\u2019re analyzing later.<\/p>\n This is what mine would look like….<\/p>\n Luckily for you, Google makes actually building these links super easy! They have a free UTM builder <\/a>where you can just plug in your information and automatically generate a hyperlink.<\/p>\n Now we’re going to see what people do when they arrive on your site. Slightly more complex, A LOT more exciting.<\/p>\n Goals<\/strong> are a way to track the actions people take on your site by tallying specific behaviors. <\/em><\/p><\/blockquote>\n What makes goals really useful is not just the ability to say how many times an action was taken, but to look at who took the action. Thanks to the UTM parameters, you can actually do this!<\/p>\n But\u00a0let’s not put the\u00a0cart before the horse \u2014 let\u2019s go over how to set up the most basic goal: opting in<\/strong> for a Lead Magnet<\/a>.<\/p>\n Let\u2019s build one to track our Perfect Blog Post Template<\/a>.<\/p>\n For our goal, we want to know when someone hits our Thank You page \u2014 after they\u2019ve visited the opt-in page. Here\u2019s how to make this happen:<\/p>\n Google offers a variety of goal templates, which should fit your specific needs (though you can create custom ones as well). Since we want to track opt-ins, “Sign Up<\/strong>”\u00a0should be perfect for us.<\/p>\n For Destination<\/strong>, change your rule to “Begins with<\/strong>”\u00a0and add your Thank You page \u2014 that\u2019s where people who opt-in end up.<\/p>\n Using “Begins with<\/strong>”\u00a0helps ensure all opt-ins are properly credited.<\/p>\n The other way to ensure that we\u2019re tracking actual opt-ins and not just accidental Thank You page visitors is to create a funnel.<\/p>\n This involves adding the URL string of the opt-in page as well (check out the graphic below). You’ll turn Funnel to “ON<\/strong>” and add a step with the page field including the URL that precedes your destination page.<\/p>\n Set this step to “Required<\/strong>” and you’ve added this rule!<\/p>\n For your URL strings, always use the text after your domain name, not the entire URL \u2014 Google already knows the root domain!<\/p>\n Once you\u2019re done, verify your goal to make sure you set it up correctly. Then click “Save<\/strong>” and you\u2019ve built your first goal in Google Analytics!<\/p>\n Since we just set this goal up, we\u2019re not going to have any information to look at. So, let\u2019s review an older funnel already tracked with goals and see how we can use these goals with UTM parameters to get insight into our customers.<\/p>\n To take a peek at these insights, you\u2019ll want to visit Conversions > Goals > Overview<\/strong> under the reporting section of Google Analytics.<\/p>\n We’ll select a goal from the drop-down at the top, and then, near the bottom, we\u2019ll change the details from “Goal Completion<\/strong> Location” to “Source \/ Medium<\/strong>.”<\/p>\n Here\u2019s what we see:<\/p>\n You can see that Facebook ads are one of our biggest sources of traffic. Interestingly, it looks like our automated follow-up emails are the next biggest source of conversions.<\/p>\n Goals are a great way to gain insight into what channels are driving the most visits.<\/p>\n With a little bit of know-how and a lot of proper attribution tagging, Google Analytics campaign tracking can give you some great insights!<\/p>\n (RELATED:<\/strong>\u00a0The Beginner\u2019s Guide to Google Tag Manager: Parts, Setup, and Creation<\/a>)<\/p>\n Now that we\u00a0know the bare bones needed to properly track success and what channels are driving that success\u00a0\u2014<\/em> how do we put this to work?<\/p>\n Like I said earlier…\u00a0 When you have the ability to track your ROI on every launch, every funnel, every email, and ad campaign \u2014 you can cut the fat and double down on what\u2019s working.<\/em><\/p>\n In the next section, I\u2019m going to show you exactly how DigitalMarketer cuts the fat and doubles down on what’s working\u00a0through unique strategies that combine proper attribution with audience insights.<\/p>\n This powerful information gives\u00a0us the ability to break our audience up into segments based on…<\/p>\n In the context of analytics:<\/p>\n Segments<\/strong> represent groups of visitors grouped by shared characteristics or behaviors.<\/em><\/p><\/blockquote>\n For the example we\u2019re looking at today, conversions will represent Lead Magnet downloads<\/strong>.<\/p>\n Let’s take a look at…<\/p>\n We launched the 10-Minute Social Media Audit<\/a> as a Lead Magnet\u00a0in January 2016.<\/p>\n The paid traffic campaign drives traffic to this landing page…<\/p>\n The campaign has produced 14,764 leads so far, giving us plenty of data to get a sense of exactly who is interested in this offer and what\u00a0channels are working best.<\/p>\n If 15k leads sounds impossible, don\u2019t worry \u2014 you won\u2019t need this many leads to start getting actionable data.<\/p>\n We are going to cover how to create useful segments<\/strong>, and how to drill down into these segments<\/strong> to better understand the people taking the actions we\u2019re looking for.\u00a0 There are two main goals in this analysis:<\/p>\n Sounds pretty simple, but this is one of the best ways to make the most of your budget, or know where you should spend your time and energy driving new customers.<\/p>\n Let me introduce you to your new best friend:<\/p>\n You\u2019ve probably seen this when you\u2019ve logged into Google Analytics<\/a>…<\/p>\n But I bet you haven\u2019t spent too much time looking at this information.\u00a0And even if you have, I can promise you that it hasn\u2019t been actionable<\/strong>.<\/p>\n That\u2019s because the default is to aggregate all site visitors into a single audience, which leaves you with a mush of different groups all mixed together into an unusable mess.<\/p>\n Our strategy will show you how to focus on the most valuable, highest-converting audiences, and figure out what makes them tick<\/strong>.<\/p>\n Before we dive into exactly what information you should be looking at, and how to pull it, let\u2019s talk about how to create the segments you\u2019ll use to dig into your audience information.<\/p>\n There are two key strategies you can use to build these, the first of which relies on the campaign tracking we presented above.<\/p>\n Luckily, if you\u2019re still feeling a little confused about campaign tracking, we\u2019ve got a workaround you can use to get some of the same information\u00a0\u2014<\/em> as long as your attribution is correctly done.<\/p>\n Creating segments is fast and easy.<\/p>\n You create a set of rules that include or exclude certain people. This allows you to narrow down your audience to look at a specific subset, like people who opted in for a Lead Magnet, rather than all site visitors.<\/p>\n Once you\u2019ve created your segment, you can analyze how this subset of visitors behaved or, in our case, who is in the subset.<\/p>\n Let\u2019s walk through exactly how you can create your own segments.<\/p>\n First, click \u201c+ Add Segment\u201d which you can find under the Audience, Acquisition, Behavior, and Conversion sections.<\/p>\n Once you open up the segment menu, we\u2019re going to create a\u00a0new segment.<\/p>\n We have two options for how to create our segment…<\/p>\n The most accurate is to combine Goal Completions<\/strong> with traffic source<\/strong>, which gives you a breakdown of site visitors who took the action you want to analyze\u00a0\u2014\u00a0<\/em>in this case, opting in for the 10-Minute Social Media Audit\u00a0\u2014<\/em> that came from a specific channel.<\/p>\n If you haven\u2019t been using goals, you can alternatively look at site visitors who reached the Thank You page for the opt-in.<\/p>\n This is typically less accurate and does not work if you direct traffic to the Thank You page from any other source, so the best choice is to use goals.<\/p>\n Let\u2019s walk through how to actually set this up.<\/p>\n First, we\u2019re going to go to Conditions. This is where we\u2019ll select goal completions, or page visits, as one of our audience creation rules.<\/p>\n If you\u2019re using Goals as your inclusion rule, create a condition that includes Users who have completed the Goal more than 0 times.<\/strong><\/p>\n …Yes, Google Analytics terminology sure sounds weird sometimes.<\/p>\n If,\u00a0instead, you\u2019re using page visitors, you\u2019ll set users to include page that contains the slug of the URL<\/strong>.<\/p>\n Now that you\u2019ve got your condition set, you\u2019ll go to Traffic Sources and include the channel you want to focus on.<\/p>\n For us, it\u2019s going to be Facebook as the source and PPC as the medium, so we can specifically see how our Facebook PPC ads performed.<\/p>\n Now that we\u2019ve created the segment, we can see just how big it is:<\/p>\n So, we have 6,202 users in this segment\u00a0\u2014<\/em> that\u2019s 6,202 people who opted in for our 10-Minute Social Media Audit they found through a Facebook PPC ad.<\/p>\n That\u2019s more than enough<\/strong>\u00a0users to make this work.<\/p>\n As a general rule,\u00a0aim for a minimum of 3,000 people in your audience<\/strong>\u00a0\u2014<\/em> that ensures you\u2019ll have reasonable enough subgroups to put some faith in your age demographic groupings.<\/p>\n You can experiment with fewer, but the more conversions you\u2019ve got in a category, the more trustworthy your data will be.<\/p>\n Now that you\u2019ve got your segmented audiences, let\u2019s dive into the meat of this post…<\/p>\n Now we’re going to figure out exactly who is opting in (and who\u2019s not), so you can do more of what\u2019s working.<\/p>\n There are two main types of data we\u2019re going to be looking for:<\/p>\n Demographic<\/strong> data describes what people are<\/strong> like.<\/p>\n Generally, it\u2019s statistical details like age and gender, but we\u2019ll be lumping device type and location into this category as well.<\/p>\n This information helps you understand exactly who you are speaking tor and will guide the targeting you use in your campaigns.<\/p>\n Psychographic<\/strong> data instead describes what people like.<\/p>\n It\u2019s all about interests, hobbies, and likes. This speaks more to the personality of the audience. Psychographic data is most powerful when it\u2019s used to shape your messaging.<\/p>\n We\u2019ll be looking at a few different ways Google Analytics defines interests, including affinity categories and in-market segments. We also are going to include an estimate of the audience\u2019s general wealth.<\/p>\n Normally, household income is demographic. But because we\u2019re only going to be able to say whether or not the audience is in the market for luxury goods, it\u2019s less hard data and more of a way to feel out what they are looking for.<\/p>\n Here\u2019s a quick breakdown of the data types:<\/p>\n Let\u2019s start with the demographic data\u00a0\u2014<\/em> it\u2019s pretty cut and dry (though yields very interesting insights).<\/p>\n We\u2019re going to actually create custom reports, rather than use the actual insights tab. That\u2019s because we need to make sure we look at Users, not sessions<\/strong>.<\/p>\n However, we\u2019ll be tracking all the data points you normally look at in the audience insights tab.<\/p>\n For our demographic reports, we want to look at…<\/p>\n To get started, go to Customization and select “+ New Custom Report.”<\/p>\n We\u2019re going to build one report to look at demographic data and one to look at psychographic data. That will make it easy to run these reports for all kinds of audience segments.<\/p>\n Create four Report tabs, one for Age, Gender, Location, and Device Type.<\/p>\n You\u2019ll set the Metric to “Users”<\/strong> for all four of these reports\u00a0\u2014<\/em> that\u2019s the constant between them.<\/p>\n For Age, the dimension drill down will be Age, for Gender, it will be Gender, and for Device, it will be the Device Category.<\/p>\n Location is the only oddball; instead of doing a normal explorer view, you\u2019ll use map overlay (which replaces the need for a dimension).<\/p>\n Save the report when you\u2019re done and you\u2019ve got a ready-made demographics report to use time and time again!<\/p>\n Still with me? Now let\u2019s look at the data.<\/p>\n We\u2019ve still got the segment we created applied, so we can dig in and see exactly who is responding to our 10-Minute Social Audit.<\/p>\n Here\u2019s a quick overview of the age and gender:<\/p>\n At first glance, we can see that this campaign is working well with both the 25-34 range, then the 35-44 range.<\/p>\n It\u2019s particularly interesting because a lot of these ads were aimed at supervisors, which would most likely skew the age average upwards.<\/p>\n But the fact that the 25-34 age range dominated with over 30% of the opt-ins suggests that either the ad appealed more to non-bosses OR the average age of bosses that care trends younger.<\/p>\n Either way, it\u2019s likely that the ad copy needs to be re-evaluated through the lens of a younger audience because while 35-44 was the second most prevalent age group, it ate up a larger percent of the overall campaign budget.<\/p>\n Retooling the campaign so that it speaks to a younger audience could do a lot to increase opt-ins and drop cost per click (CPC).<\/p>\n As for gender, women represented nearly 2\/3 of the opt-ins for this campaign, which is a significant enough percent that the ads should be optimized for a female audience.<\/p>\n Since these ads weren\u2019t weighted to allocate more budget to either gender initially, creating a second version of the campaign that solely targets women is a great way to boost clicks and ad relevance, and drop CPC.<\/p>\n Location isn\u2019t particularly interesting for this campaign because we only targeted the US, UK, Canada, and Australia with our Facebook ads. If you were looking at a different channel, this would definitely be a data set worth exploring.<\/p>\n You may realize that spending your traffic budget in a country you didn\u2019t consider and could really take advantage of regional interests.<\/p>\n One of the most important things for DigitalMarketer to note is the Device split:<\/p>\n This is so critical because it\u2019s radically different<\/strong> than what we see across the entirety of our site and audience segments generally speaking.<\/p>\n On average, about 33% of traffic that comes to our sites is from mobile.<\/p>\n However, for the people interested in the Lead Magnet, there is a 70% lift in mobile traffic percentage. It is critical for these campaigns that we design our conversion funnel with mobile users in mind if we want to turn Lead Magnet downloaders into purchasers.<\/p>\n So that\u2019s how to dig into the cold hard facts about the audience, and we\u2019ll use that information to shape the targeting of the campaign during our optimization phase.<\/p>\n But what about the messaging?<\/p>\n What about our follow up strategy?<\/p>\n To figure out our best tactics here, we\u2019ll turn to psychographic data.<\/p>\n We\u2019re going to create another custom report, this time looking at Affinity Categories and In-Market Segments.<\/p>\n This will follow the exact same process as before except that our Dimension Drilldowns will be Affinity Category and In-Market Segment, respectively.<\/p>\n So we\u2019ve got our report, now let\u2019s look at the actual data.<\/p>\n When looking at these categories, a comparison to averages is what I like best because it highlights interests better than raw numbers.<\/p>\n I\u2019ve pulled some of the favorite and least favorite likes of this audience, and the results are interesting.<\/p>\n The broad categories like \u201cMovies\u201d tend to ride towards the top, while categories that drill down tend to float towards the bottom.<\/p>\n But, you can see that Entertainment & Celebrity News Junkies made it into the top two interest segments, which is huge.<\/p>\n When you\u2019re trying to think of messaging, focus on more niched-down categories than the broad high-level ones.<\/p>\n Sure, this audience likes movies, but they clearly HATE horror films. So, if you went in blind and tried a scary movie theme with your next ad campaign, there\u2019s a good chance you\u2019d have a flop on your hands.<\/p>\n (RELATED:<\/strong> Google Custom Affinity Audience: Scale Your Campaigns and Reach Converting Customers in 3 Steps<\/a>)<\/p>\n While Affinity Categories look more at likes, In-Market Segments give us some indication as to what this audience is in the market to purchase (or may have just purchased).<\/p>\n I like to alphabetize In-Market Segments to look at interest clusters across category subsets. So here we can see that Education is interesting to the people who opted into our Lead Magnet, particularly childhood education and college and graduate studies.<\/p>\n Dating services clearly stands out and is something that this target audience is highly interested in.<\/p>\n So ads that used the language of education or dating are set up for success.<\/p>\n Lastly, we can use our sleuth powers to get a sense of whether or not this target market is interested in luxury goods and therefore get a sense of whether or not they fall on the high end of the spectrum of income.<\/p>\n To do this, we\u2019ll see if they have high concentrations of interest in categories that indicate wealth \u2014 namely luxury items.<\/p>\n Here are some general categories to use for this analysis:<\/p>\n Only about 3% of our audience for this campaign showed up with any of these segments, indicating that the people opting in for this Lead Magnet are not notably wealthy.<\/p>\n So, following up with a campaign for a particularly pricey item will likely be less successful than one with more moderate, Tripwire-style offers.<\/p>\n Let\u2019s combine all the different data points we have on our audience and figure out what the profile is of our ideal candidate\u00a0for the 10-Minute Social Media Audit:<\/p>\n Gender<\/strong>: Woman<\/p>\n Age<\/strong>: Late 20s, early 30s<\/p>\n Preferred Device<\/strong>: Smartphone<\/p>\n Estimated Average Income<\/strong>: Under $100k Annually<\/p>\n Role at Work<\/strong>: Non-Supervisor<\/p>\n Likes & Interests<\/strong>: Movies, Celebrity & Entertainment News, Pop Music, Education, Career Consulting, Dating Services, Home D\u00e9cor & Gardening Services<\/p>\n Dislikes<\/strong>: Sports, Horror Films, Boardgames, Video Games, Automobile Accessories<\/p>\n We\u2019ve now constructed an ideal candidate profile for Facebook ads we run to our 10-Minute Social Media Audit based on what has worked so far.<\/p>\n With this information, we can attack the campaign from a new angle and speak more directly to our target audience.<\/p>\n Imagine what your paid traffic team could do with this level of detail about whom they are targeting.<\/p>\n Don\u2019t forget that this can be applied not just to people who opt-in but to purchasers or, with careful targeting, membership site users. In addition, you can use this strategy for any<\/strong> platform that drives sufficient traffic volume.<\/p>\n Now let’s explore how to use segments to evaluate the historical performance of a campaign…<\/p>\n In this guide, we\u2019ve talked about three of the most powerful ways to use Google Analytics:<\/p>\n Mastering these will give you an edge over most other marketers<\/strong> because you\u2019ll know how to see what\u2019s working on your site, figure out where your visitors are coming from, and understand your audience composition.<\/p>\n There\u2019s just one problem.\u00a0 UTM parameters and goals can only work for you if you do your due diligence and set them up in advance.<\/p>\n Marketing is a busy, frenetic game and it\u2019s a near-certainty that we all will launch at least one campaign without getting our goals properly set up.<\/p>\n I made this mistake recently.<\/p>\n DigitalMarketer rolled out a campaign promoting a new Lead Magnet, the 15-Point Landing Page Audit<\/a>, and I didn\u2019t set up a goal in Google Analytics to track it.<\/p>\n So, now we\u2019ll never know how that campaign performed, right? \ud83d\ude41<\/p>\n Well\u2026<\/p>\n \u2026this not the end of the post, so you might have guessed that there\u2019s actually something I can (and did) do to figure out what happened!<\/p>\n By using segments, one of the tools we\u2019ve already discussed in this post, we can evaluate historical performance<\/strong>.<\/p>\n I\u2019m going to show you why segments are one of the most powerful things you can do in Google Analytics<\/strong> (we\u2019ve only scratched the surface so far) and walk through how to set them up to review historical data.<\/p>\n And we\u2019re going to use our 15-Point Landing Page Campaign as an example \u2014 so you\u2019re going to get a peek behind the curtain at exactly how we do this at DigitalMarketer.<\/p>\n To solve the challenge of analyzing a sales funnel from the past, we\u2019re going to return to the segment builder and explore a new section of this tool: sequences.<\/p>\n As a quick refresher, segments in Google Analytics are groups of site visitors that have shared characteristics or behaviors<\/strong>.<\/p>\n These interactions are known as dimensions and metrics. They include information like:<\/p>\n Inside of Google Analytics, you can get started with segments by clicking \u201c+ Add Segment\u201d under the Audience, Acquisition, Behavior, and Conversion sections.<\/p>\n Once you\u2019ve got the segment menu pulled up, click the red \u201c+ New Segment\u201d button to go to your custom segment builder (where we\u2019ll be hanging out in this article).<\/p>\n There are all kinds of ways to filter your visitors in segments, but, with what we\u2019re trying to accomplish, we\u2019re going to be focusing on the bottom section.<\/p>\n \u201cConditions\u201d and \u201cSequences\u201d are unique when it comes to building a segment, which is why they are located under the \u201cAdvanced\u201d section. But don\u2019t worry, they aren\u2019t really more difficult to use.<\/p>\n While most grouping rules are binary \u2014 the visitor is from Facebook\u00a0or isn\u2019t, the visitor saw this page or didn\u2019t \u2014 these advanced filters give you much more granularity<\/strong>.<\/p>\n This granularity comes in the ability to group visitors according to multiple<\/strong> rules within a single dimension or metric.<\/p>\n For instance, you can set conditions to include\u2026<\/p>\n And sequences add another layer to this function because on top of having multiple rules, they require these rules to be done in a certain order.<\/p>\n Let\u2019s take a look at what the sequence section of the segment builder looks like.<\/p>\n At a glance, you can see sequences have a single step as the default filter.<\/p>\n However, by clicking the \u201cAdd Step\u201d button, we can harness this tool\u2019s full potential.<\/p>\n The reason that ordered steps are so important is because we\u2019re going to use the steps to represent the different parts of the buying process<\/strong>.<\/p>\n Adding steps to a sequence allows us to stack visitor interactions, each one representing a different stage of the customer\u2019s opt-in or purchase process.<\/p>\n Sequential segments are useful for almost every type of website. That\u2019s because whether you\u2019re collecting email addresses or selling product(s), there are always a series of pages between the beginning and end of whatever actions you want your visitors to take.<\/p>\n We can create sequential segments to represent each of these stages and figure out how many people did what we wanted!<\/p>\n Now let\u2019s look how to do just that using our real-life example\u2026<\/p>\n In order to dig into how well our audit did, we need to know two things:<\/p>\n For this funnel, there are five different pages:<\/p>\n We\u2019re going to use those URLs to create our segments, and we are going to filter our Google Analytics account to include the date range we ran this promotion.<\/p>\n In order to make this work, we need to build a segment to represent each stage of the buying journey.<\/p>\n This first one is the easiest because there\u2019s only one-page visitors could see at this point in the journey.<\/p>\n We know that 10,851 users started the journey.<\/p>\n There are two important choices that we\u2019ll continue to use as we go through this:<\/p>\n Sequence Start<\/strong> is set to \u201cAny user interaction\u201d rather than \u201cFirst user interaction\u201d because we want to include people who might have visited other pages on our site before starting in this sales funnel.<\/p>\n Grouping Type <\/strong>is set to \u201cUsers\u201d rather than \u201cSessions\u201d because we want to look at people, not individual web sessions for the buying journey. The main reason we do this is to include visitors who returned to the buying journey from a follow-up series. But you may prefer to look at individual sessions in your business.<\/p>\n Our next segment is when we start taking advantage of this tool.<\/p>\n You can see we added a second step in this new segment, which takes us to 6,839 users.<\/p>\n From just these two segments, we can deduce that 63% of users who saw the 15-Point Landing Page Audit opted in to get the download.<\/p>\n One new option when we add steps is the \u201cis followed by\u2026\u201d setting. There are two choices, \u201cis followed by\u2026\u201d and \u201cimmediately followed by\u2026\u201d<\/p>\n Immediately followed by disqualifies anyone who visits a different page in between your steps.<\/p>\n Because we want to include visitors who returned to the funnel, we are using the non-immediate option. But when you want narrower restrictions, the immediate option is usually correct.<\/p>\n Here\u2019s the last one we\u2019ll look at:<\/p>\n You can see only 483 of the users made it through the funnel to the order form, giving us a 7% conversion from sales page to order form. We can already tell that the sales page will be a good point for optimization of this funnel.<\/p>\n Now let\u2019s bring everything together.<\/p>\n In the same way we\u2019ve stacked interactions within a single segment, we can stack segments to build a sales funnel!<\/p>\n That\u2019s the real secret sauce that we\u2019re driving towards because we can look at multiple segments at once to illustrate what our sales funnel looks like<\/strong>, measuring the number of visitors at each step of the process.<\/p>\n To best view and understand our stacked segments, we\u2019ll go to Audience > Overview in Google Analytics<\/strong>.<\/p>\n You can only include four at a time, but this should give us exactly what we need to see how well our 15-Point Audit performed; we can look at two different sets of four segments to review performance.<\/p>\n To review multiple segments, click \u201c+ Add Segment\u201d and select everything you want to include.<\/p>\n We\u2019ll start with the first four of our audiences:<\/p>\n By looking at the User section, we can derive our conversion percentages for each stage of the funnel:<\/p>\n We actually had no one reach the Thank You page \u2014 after digging into the problem, it was due to a tracking issue, not a funnel problem.<\/p>\n So, while segments are an extremely powerful way to retroactively review performance, they do require tracking to work<\/strong>.<\/p>\n From this quick analysis, we can already see that the Tripwire conversion rate is our best point of optimization.<\/p>\n We look for roughly 5% for these funnels, and we\u2019re sitting below 2.5%.<\/p>\n This gives us additional granularity into the performance between individual pages, where we can see that Sales Page to Cart is going to be the point of highest impact for our next test.<\/p>\n If we wanted to go more granular, we could add a traffic source (Facebook or email) to the segments.<\/p>\n These filters can be found underneath the \u201cTraffic Sources\u201d filter section of the segment builder.<\/p>\n We only drove email traffic to this offer, so there\u2019s no reason to worry about it.<\/p>\n But for your funnels, this would give you not just the offer conversion rate but also the performance from a specific traffic source.<\/p>\n This is a great resource when you\u2019re evaluating paid media spend or what offers work best for what kind of traffic.<\/p>\n So, we now know that segments can be very powerful and flexible tools for going back and reviewing previous performance for online lead and sale generation that you weren\u2019t thinking about as a \u201cfunnel.\u201d<\/p>\n But when we are thinking ahead, when should we use segments and when should we use goals?<\/p>\n You are only allowed 20 goals per view in Google Analytics, so those are better for funnels you\u2019ll be using for a long time.<\/p>\n Now, for custom segments, you can have up to 100 active at a time.\u00a0 However, you\u2019ll often want to use segments to dig deeper into different aspects of your account, so you need to have some number of them available at any time to analyze your data<\/strong>.<\/p>\n Additionally, segments are better for digging into individual stages of a funnel, while goals provide a more high-level view of performance.<\/p>\n As a general rule, segments<\/strong> are better for ad-hoc analyses and goals<\/strong> are better for tracking established, long-term sales and marketing funnels on your site.<\/p>\n While we have focused on sequential segments as a tool for looking at your funnels, that\u2019s not all they can do.<\/p>\n Because the great thing about segments is how flexible they are \u2014 here are just a few other ways you can put these to work:\u00a0 No matter how you decide to use sequential segments, you now understand the basic principles of one of the most powerful tools in the Google Analytics toolbox.<\/p>\n","protected":false},"excerpt":{"rendered":" From how to track your visitors to creating goals, use this complete guide to Google Analytics campaign tracking to help you make smart, data-driven decisions for your business.<\/p>\n","protected":false},"author":38,"featured_media":59458,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[194,34,202,93,174],"tags":[],"class_list":["post-120225","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics-data","category-blog","category-campaign-creation","category-content-marketing","category-engagement"],"acf":[],"yoast_head":"\n\n
<\/a>The ABCs (or UTMs) of Tracking the Origins of Site Visitors<\/h2>\n
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utm_source<\/h3>\n
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utm_medium<\/strong><\/h3>\n
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utm_content<\/strong><\/h3>\n
utm_campaign<\/strong><\/h3>\n
![\"An](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/utm-tracking-guide-img1.jpg\"){kind=tracking}
<\/p>\n![\"An](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/unspecified.png\")
<\/p>\n<\/a>Create Goals to See Who\u2019s Taking Action<\/h2>\n
Creating Goals in Google Analytics Step 1: Go the Admin Section of Google Analytics<\/h3>\n
![\"Go](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img13.jpg\"){kind=tracking}
<\/p>\nCreating Goals in Google Analytics\u00a0Step 2: Go to the Goals Section<\/h3>\n
![\"Go](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img14.jpg\"){kind=tracking}
<\/p>\nCreating Goals in Google Analytics\u00a0Step 3: Create a New Goal<\/h3>\n
![\"Click](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img15.jpg\"){kind=tracking}
<\/p>\nCreating Goals in Google Analytics\u00a0Step 4: Choose “Sign Up” Goal Type<\/h3>\n
![\"Choose](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/utm-tracking-guide-img5.jpg\"){kind=tracking}
<\/p>\nCreating Goals in Google Analytics\u00a0Step 5: Name Your Goal, then Select Destination for Goal Type<\/h3>\n
![\"Name](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/utm-tracking-guide-img6.jpg\"){kind=tracking}
<\/p>\nCreating Goals in Google Analytics\u00a0Step 6: Set Up the Specifics for Your Goal<\/h3>\n
![\"](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/utm-tracking-guide-img7.jpg\"){kind=tracking}
<\/p>\n![\"An](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/utm-tracking-guide-img8.jpg\"){kind=tracking}
<\/p>\n![\""Goals](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox7.png\")
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[Case Study]\u00a0Using Google Analytics to Generate\u00a0More Leads<\/h2>\n
![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/2016-04-29_13-50-27.jpg\")
<\/p>\n![\""Sounds](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox6.png\")
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![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img12.jpg\"){kind=tracking}
<\/p>\nHoning In on Your Audience<\/h2>\n
![\"click](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img2.jpg\")
<\/p>\n![\"Click](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img3.jpg\")
<\/p>\n![\"Create](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img4.jpg\")
<\/p>\n![\"Create](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img5.jpg\")
<\/p>\n![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img6.jpg\")
<\/p>\n<\/a>Understanding Audience Insights<\/h2>\n
![\""Understanding](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox9.png\")
Understanding your audience means driving down ad costs, or figuring out better strategies for monetizing the leads you\u2019re getting! So, if you\u2019re interested in spending less OR making more, you should probably read on.<\/p>\n\n
![\"A](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-graphic.png\")
<\/p>\nUnderstanding Your Audience: Demographic Data<\/h3>\n
\n
![\"go](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img7.jpg\")
<\/p>\n![\"Setting](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img8.jpg\")
<\/p>\n![\"Setting](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img9.jpg\")
<\/p>\nThe 10-Minute Social Audit Demographic Data<\/h4>\n
![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img10.jpg\")
<\/p>\n![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img11.jpg\")
<\/p>\n![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img12.jpg\")
<\/p>\nUnderstanding Your Audience: Psychographic Data<\/h3>\n
![\"Creating](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img13.jpg\")
<\/p>\nThe 10-Minute Social Audit Psychographic Data<\/h4>\n
![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img14.jpg\")
<\/p>\n![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img15.jpg\")
<\/p>\n![\""When](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox2.png\")
An ad that asks \u201cHow does your business\u2019 Social Media Score compare to Kim Kardashian\u2019s?\u201d would likely be a huge hit with this audience. On the other hand, sports-themed ads would most likely fall flat (spoiler alert \u2014 we ran some soccer themed ads and they did not perform well).<\/p>\n![\"In-Market](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/audience-insights-img16.jpg\")
<\/p>\n\n
Putting it All Together<\/h2>\n
<\/a>Historical Performance Tracking with Sequential Segments<\/h2>\n
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![\""Mastering](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox10.png\")
<\/p>\nExploring Segments\u2019 Most Sophisticated Filters<\/h2>\n
\n
![\"Get](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img1.jpg\"){kind=tracking}
<\/p>\n![\"Click](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img2.jpg\"){kind=tracking}
<\/p>\n![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img3.jpg\"){kind=tracking}
<\/p>\n\n
![\"What](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img4.jpg\"){kind=tracking}
<\/p>\n![\"Adding](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img5.jpg\"){kind=tracking}
<\/p>\nEvaluating the 15-Point Landing Page Audit<\/h2>\n
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![\"The](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img6.jpg\"){kind=tracking}
<\/p>\n![\"Adding](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img7.jpg\"){kind=tracking}
<\/p>\n![\"Adding](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img8.jpg\"){kind=tracking}
<\/p>\n![\""We](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox5.png\")
I set these up in the exact same way for the two remaining pages, giving us a total of five segments.<\/p>\n![\"To](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img9.jpg\"){kind=tracking}
<\/p>\n![\"Our](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img10.jpg\"){kind=tracking}
<\/p>\n\n
![\"These](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/google-analytics-campaign-tracking-img11.jpg\"){kind=tracking}
<\/p>\nWhen to Use Sequential Segments<\/h2>\n
![\"Segments](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox4.png\")
<\/p>\n![\""You](\"https:\/\/www.digitalmarketer.com\/wp-content\/uploads\/2021\/11\/GA_Quotebox3.png\")
<\/p>\n\n