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How to Avoid Duplicate Conversions and Recreating the Conversion Funnel for GA4

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20 Google Analytics Alternatives - Moz

The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

As you’re probably all too aware at this point, GA4 is coming. Old versions of Google Analytics will be switched off for pretty much everyone come June 2023.

While GA4 is improving all the time, there are quite a few things that people are used to seeing in old versions of Analytics which, at the very least, take a bit of creativity in the new world.

One example is how conversions are handled. In the old versions of Google Analytics, a conversion could only fire once per session. In GA4 conversions are just another kind of event, so it’s possible for a conversion to fire multiple times in one session.

Problem is, you might be very interested if someone signs up via your contact-us form once. But that person might reload the thank-you page, or sign up for something else via a different form on the site. That doesn’t mean you necessarily want to track two conversions.

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Speaking of signing up via different forms, on some websites, users may wind up on the same thank-you page having taken very different routes to get there. If we don’t have that much control, and we’re having to rely on thank-you page views to track conversions, it can be hard for us to separate out different kinds of conversions.

In old versions of GA you could use funnels with a “required” step. You might have one goal with a funnel requiring your event page, another goal with a funnel requiring a different page, and rely on them to give you different conversions. There also isn’t an obvious way to do this in GA4.

In this post, I’m going to take you through how to:

  • Avoid double counting in GA4.

  • Automatically ignore suspicious conversions (like people landing direct on the conversion page).

  • Recreate the kind of funnels we expected in Universal Analytics (in fact we’ll make them better).

I’ll take you through a few bits in GA4 and others using Google Tag Manager. The GA4 approach is more straightforward, but the Tag Manager is more robust and can help you make sure that all of your conversion pixels are showing roughly the same information (because we’re long past the point where GA is the only place we’re recording conversions).

Managing conversions in GA4

This section is about changes we can make purely through the GA4 interface. As long as you’re sending your page views conversion events to GA4 you should be able to use these tactics without any code changes.

However: There are some limitations of doing things through GA4, for example it can mean that your GA data doesn’t line up with conversions recorded via other platforms.

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Avoiding double-counting

Julius Fedorovicius (of Analytics Mania fame) has produced a fantastic guide to making sure that conversions are only recorded once per session.

You should have a read but broadly:

  • You create a custom audience based on a sequence that begins with “session_start”

  • You fire an event when someone enters that audience

  • You use that event as your conversion.

No surprise that Julius has come up with a really smart way to handle the problem of double-counting:

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If you’ve created Segments in Universal Analytics Audience sequences in GA4 look very like the sequences we used to create for Segments. However, the old Segments were just a way of visualizing data, whereas Audiences in GA4 are a way of grouping data. We can use Audiences to create something new.

That distinction is important because we can do cool things like fire custom events when someone enters an audience (which Julius makes use of in this solution).

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Universal Analytics Segment sequence creator

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GA4 Audience sequence creator

The limitations of using Google Analytics audiences

This isn’t really a limitation as far as GA goes but it’s a consideration nonetheless. Julius’ solution is great for making sure we’re not double-counting conversions in GA, but GA probably isn’t the only way we’re recording conversions.

The average site probably has a bunch of separate conversion tracking pixels and those could end up double-counting conversions.

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For example: Facebook and Google both describe how they avoid double-counting conversions, but their solutions largely rely on exactly matching transaction IDs, and even if they’re handling it okay, there’s a bunch of smaller fish out there that are also offering conversion tracking and can need a bit more hand-holding.

If we want to make sure that we’re only recording one conversion per session, it’s useful to make sure all of our conversion tracking is working in a similar way. Tag Manager is a great solution for that (I describe a solution in the Tag Manager section below).

You can also run into problems if, for example, your confirmation page is somehow indexed or bookmarked by users — people landing directly on it can lead to weird unexpected conversions. We can also use Tag Manager to guard against that a little bit.

Recreating the conversion funnel

Sticking with the GA4 interface for now, we can also adapt the AnalyticsMania approach to create our funnel-based conversions too by adding additional steps to the sequence.

For what it’s worth, conversion funnels are not the ideal way to categorize conversions. If you can use anything more direct (like the id of the form they’ve filled out, a separate thank-you page) then that’s a much more reliable way to categorize conversions. That said, we don’t live in a perfect world, and sometimes there isn’t the option to completely rebuild your conversion process.

In Fedorovicius’ example we just have two steps in our audience sequence:

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  1. Session_start
    Indirectly followed by

  2. Conversion

Which basically means “someone lands on the site and then at any point during their session, they convert”.

To recreate the goal funnels you might be using in Universal Analytics – we can just add another step to the sequence. For instance:

  1. Session_start
    Indirectly followed by

  2. Visiting our event_page
    Indirectly followed by

  3. Landing on our thank you page/converting

That should mean we can create one conversion which is: Users who went through our event page and then converted.

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And another conversion which is: Users who went through our sponsorship page and then converted.

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There are some limitations here though, for example, what if someone:

  1. Landed on the site

  2. Visited our event page

  3. Then visited our sponsorship page

  4. Converted using the form on either.

They would fulfill the criteria for our event conversion and the criteria for our sponsorship conversion. We’d record a conversion for each and we’d end up double-counting after all.

This is also a limitation of the old Universal Analytics funnels: Just because a step in the funnel was required doesn’t mean the user can’t wander off around the site between that step and their final conversion. So, if it’s any consolation, this isn’t any worse than old Universal Analytics funnels (but we can still do better).

The problem with using “directly followed by”

You might say “well that’s easily solved — at the moment the sequence says is indirectly followed by and we can just change that to is directly followed by”.

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Surely that would mean that someone is on the sponsorship page and goes directly from the sponsorship page to the thank you page, right?

Unfortunately that’s usually not what “directly followed by” means because there’s all kinds of things that can get recorded in analytics which aren’t page views.

For example if someone lands on the sponsorship page, and then scrolls down and lands on the thank you page, the thank you page view doesn’t directly follow the sponsorship page view. It goes:

  • Page view: sponsorship

  • Scroll

  • Page view: thank you

So “directly followed by” isn’t an easy solution.

How about “within x minutes”?

GA4 has a really cool feature in the sequence builder where we can set a timer in-between steps. Even outside of tracking conversions within a session we can use it to keep track of cool things like people who came to our site, didn’t convert that time, but came back and converted within the next couple days.

Jill Quick has been talking a bunch about how powerful these options are.

We could use this to say something like: person landed on our event page and then landed on our thank you page within 10 minutes.

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But as I’m sure you’ve guessed, that ends up being a kind of arbitrary cut off, maybe someone spends some time thinking about how to fill out our form, or maybe someone really quickly goes to one of our other pages and converts there. This could be better than the basic funnel, but we could also end up ignoring completely legitimate conversions.

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So what do we do?

Using GA4 sequences for this is kind of fine, as I say above it’s certainly not worse than Universal Analytics, but we could do better with Google Tag Manager.

Managing conversions in Google Tag Manager

These approaches require you to run all your tracking via Tag Manager. Though even aside

from this, if you’re not already using Tag Manager, I’d advise you to look into it!

Since we need to keep track of what’s happened to a user across multiple pages, these solutions are also going to make use of cookies. In case that fills you with dread, don’t worry:

  • I’m going to walk you through how to create and delete these cookies (it takes a little Javascript but it’s copy-paste and easier than you think!)

  • These aren’t the kinds of cookies designed to give away people’s information to other services.

To reiterate what I say above: While this approach takes a bit more effort than just doing things through Google Analytics it allows us to do two things:

  1. Make sure all of our various tracking tags are firing in the same way

  2. Have more fine grained control, particularly if we’re trying to categorise different paths to conversion.

Avoiding double-counting

To recap what we want to do here, we want to make sure that if someone visits our site and converts we fire a conversion. However, if they revisit a thank you page, or go through a different conversion, we don’t fire a second conversion that session.

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To do that, we’re going to:

  • Set a cookie when a user converts.

  • Make sure that the cookie automatically disappears after 30 minutes of inactivity (this is the default timeout for GA4 sessions but if you think that’s too short you can set it to whatever you want).

  • Every time we go to fire a conversion, check if that cookie is present and, if it is, don’t fire the conversion.

That should mean that if someone comes to our site and converts, we’ll set the cookie, and that will stop us from firing any more conversions (GA4 or otherwise) until the user has taken a little time away from the site.

Setting a cookie in JavaScript

The first thing you need to know is that we can use Tag Manager to run any JavaScript we want. The second thing to know is that we can use JavaScript to set cookies.

So first: Go to Google Tag Manager, create a new Tag and select the Custom HTML type

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Give the tag the name “[Tag] setCookieConverted” and in the html content paste:

<script>

// Get time 30 minutes from now (this is because the default GA session time out

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// is half an hour and we want our cookie timeout to match)

var minutesToAdd = 30

var currentTime = new Date(); // Get current time

var newDateObj = new Date(currentTime.getTime() + minutesToAdd*60000); // Add our minutes on

// Set the domain your’re working on, this is because we want our cookies to be

// accessible in subdomains (like test.example.com) if needed

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var yourDomain = “example.com”

// Set a cookie called ‘converted’ with the value being ‘true’ which expires in 30 minutes

document.cookie = “converted=true; path=/; domain=”+yourDomain+”; expires=”+newDateObj+”;”

</script>

It should look like this:

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The custom HTML tag will add the content there to the page, and as soon as the page detects a new script (the one we’ve written) it’ll run that script.

What our script does is:

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  • It finds the current time, and what time it’ll be in half an hour.

  • It uses that, and your domain, to set a cookie called “converted” which can be read by any page on your website.

When you go to save your tag it’ll probably say “No Triggers Selected”.

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For now we’re going to click “Add trigger” and choose the “All Pages” trigger.

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This is purely so that while we’re putting this together we can easily test it..

Reading our cookie value

Tag Manager has a built-in way to read cookie values using variables. So go to the variables section, create a new variable called “convertedCookie” and set the Cookie Name as “converted”.

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Now, if you click the “Preview” button and open up your site we can start to look at what value the convertedCookie variable pulls through for you.

Click into the “Variables” tab and you should see convertedCookie somewhere in the list. Here’s an example with other cookies blocked out so you know what to look for.

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So now we can use the value of that variable in Tag Manager as part of our logic.

Using conversion cookie in our conversion logic

Everyone’s conversion setup will be the different so this might not match what you’re doing exactly but if you’re considering using GTM I’m assuming you are firing conversions something like this:

  1. You have a trigger based on some condition (probably either a custom event or a pageview)

  2. You have a tag (or multiple tags) that send your conversion information whenever that trigger is activated.

What we’re going to do is tweak your trigger to add another condition.

Imagine that your trigger was previously firing on every thank-you page visit:

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What we’re going to do is add a second condition to the trigger:

convertedCookie does not contain true

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While this example uses the thank you page path, it doesn’t have to, it can be anything.

Once you make this change, you can go and test your conversion. Because you have another tag adding the converted cookie on each page view, your conversion shouldn’t fire when it normally would.

Now we just need to change our converted cookie so that it only appears after someone has converted.

At the moment we’re setting the “converted” cookie on every page view, so we’ll never get any conversions.

We need to update that so:

  • We set a cookie when someone converts.

  • Every time we load a page, if the person is marked as “converted” we reset the cookie (I‘ll explain).

Setting a cookie only when someone has converted

First: we need to remove the trigger from [Tag] setCookieConverted so it doesn’t fire at all.

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Then we go to whatever tag we’re using to send our conversion, open up “Advanced Settings”, click “Tag Sequencing” and select “Fire a tag after”.

Then we select our setCookieConverted tag and check “Don’t fire if conversion tag fails”.

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This should mean that whenever we send our conversion, we’ll automatically then activate our cookie tag and mark the user as converted.

So now our logic is:

  • If someone converts, we check if there is a cookie saying they recently converted already.

  • If they don’t have that cookie we send a conversion.

  • Then we automatically set that cookie.

To test this, you can either clear the cookie or wait for it to expire. Here are instructions for how to clear cookies in Google Chrome (which you’re probably using if you’re working with tag manager).

Now, if you got into GTM preview and click around you should be able to look at your variables and see that convertedCookie is back to being ‘undefined’.

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If you convert, you should see that both tags fire — your conversion tag and your setCookieConverted tag.

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But if you convert again (reload the page, re-fill the form, whatever you’ve got to do) you should see that neither tag fires.

Congratulations! You’re filtering your conversions to avoid recording a conversion more than once for someone in a 30 minute window.

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We just want to make one last tweak now.

Refreshing the cookie if it has been set

Our cookie has a 30 minute expiration. That means it’ll stick around for 30 minutes and then automatically be deleted from the browser. But what if someone hangs around on our website for more than half an hour, reading a blog post or something, and converts again?

To help deal with that, we’re going to add another trigger which checks if the user has recently converted, and if they have, refreshes the cookie with each new page load.

Head back to [Tag] setCookieConverted

At this point it should have no firing triggers. We’re going to add one back in.

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Click the blue plus sign in this screen, and again in the next screen that comes up, we’re going to create a new trigger.

In the new trigger, we set it to fire only on page views where convertedCookie contains true.

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So this gets a little bit circular, but basically:

  • When someone converts we set a “converted” cookie for the next half hour.

  • Every time someone loads a page, if they have a “converted” cookie we reset that cookie for another 30 minutes.

  • If at any point the user doesn’t load a new page for 30 minutes, the cookie will expire, which means our refresh won’t be triggered.

You can test this by clicking around your site with the GTM preview. Once you’ve converted, the [Tag] setCookieConverted should fire on every new page load.

Wrapping up

All you need to do now is make sure that all of your conversion tags use that same trigger (the one that has the condition that convertedCookie isn’t “true”). Once that’s set up, they should all behave the same — only recording one conversion per session unless someone clears their cookies or just hangs around on one page for a very long time.

What if we find we’re getting weird conversions where users haven’t visited any other pages on the site?

I have worked with sites in the past where:

  • There’s useful information on the thank-you page and users have been keeping it open/coming back to it.

  • Confirmation pages have been indexed in Google or people are finding their way to the conversion page some other way.

That can lead to weird tracked conversions that don’t correspond to actual conversions. While these problems should be solved at source, we can also clear up our analytics using the steps in “Creating a conversion funnel” below.

Creating a conversion funnel

This builds on the cookie meddling we’ve done in the last section, so if you haven’t read that bit, it’s worth taking a look!

If you’re here not because you want a specific funnel but because you want to deal with weird conversions where users just land straight on the conversion page – don’t worry you follow these instructions exactly the same, you just set the trigger for every page except your conversion page (I’ll take you through that).

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Setting a “path” cookie

Just like the “converted” cookie before, we’re going to create a new cookie that records the location of the current page.

Create a new Tag called [Tag] setCookiePath, choose “Custom HTML” and add the following JavaScript

<script>

// Get time 30 minutes from now (this is because the default GA session time out

// is half an hour and we want our cookie timeout to match)

var minutesToAdd = 30

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var currentTime = new Date(); // Get current time

var newDateObj = new Date(currentTime.getTime() + minutesToAdd*60000); // Add our minutes on

// Set the domain your’re working on, this is because we want our cookies to be

// accessible in subdomains (like test.example.com) if needed

var yourDomain = “therobinlord.com”

var pagePathName = window.location.pathname // Get location of current page

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// Set a cookie called ‘converted’ with the value being ‘true’ which expires in 30 minutes

document.cookie = “conversionPath=”+location+”; path=/; domain=”+yourDomain+”; expires=”+newDateObj+”;”

</script>

It should look like this:

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This will save a cookie that records the location of the page. The first time it’s loaded it will create a new cookie with that information, every time after it’ll replace the value.

We’ll use this to make sure that whichever funnel page our user interacted with last is the one we record.

Triggering on your funnel pages

In creating our “funnel” we’re assuming that there are certain pages a user passes through in order to convert. So we’re going to set this to trigger only when one of those funnel pages is involved.

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In your [Tag] setCookiePath tag – click to add a new trigger and create a new trigger.

We’re going to configure our tag to activate on every user click. This means that if a user is hopping between different funnel pages, each one will overwrite the cookie as they click around but only the one they interacted with last will be the one that sticks around in the cookie value.

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Getting our funnelCookie

As in the double-counting instructions, create a new variable. But this time, call it funnelCookie and set the “Cookie Name” to conversionPath.

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Once you’ve done that you should be able to test by using preview, going to any old page of your site (as long as it’s not one of your funnel pages) and checking funnelCookie in the Variables (it should be undefined).

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Then go to one of your funnel pages, you should be able to see the cookie change.

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As you visit other pages on the site, funnelCookie should stay the same, unless you visit another funnel page.

Changing our conversions based on the funnelCookie

Now, there are smart things you could do here with extracting the value of funnelCookie and putting that into a variable in your conversion tag but the setup for every tag will be different and I want to give you an option for if you’re not able to do that.

This will create a little bit more mess in your Tag Manager account because you’ll be duplicating some of your trigger and conversion tags.

First, let’s go back to the conversion trigger we were working on before. It looked like this when we left it:

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We’re going to add in another condition:

funnelCookie contains event-page

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This means now that this conversion will only fire if the last funnel page our user passed through was the event-page.

After this we can duplicate this trigger, our conversion tags, and, for our other set of conversions, change the funnelCookie value for the trigger.

Maybe instead we make it:

funnelCookiecontains form-page

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Now you have two sets of conversions, each of which will fire based on which funnel page the user passed through. From there you can edit the values sent.

A couple caveats

Instead of duplicating our conversion tags it would be much better to pull in the value of the funnelCookie variable and use that to just dynamically change some of the values we’re sending as part of the conversion.

With this approach, you also run the risk of not recording any conversions at all if a user hasn’t passed through one of your funnel pages. That might be what you want, but it’s worth bearing that risk in mind in case you think people might take legitimate-but-unusual routes to conversion.

While I can’t take you through the process of updating all of your conversion tags, one option to make this information more ready for filling out conversion tags (and to optionally set a fallback in case you want to avoid losing conversions) is to use a lookup table like this, where you take the funnelCookie value and categorise the values.

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Then instead of adding the funnelCookie value in your trigger, you keep the trigger the same and pull in the lookup table value.

Triggering on any page except your conversion page

If you’re not concerned about constructing page funnels but you want to make sure that users have visited at least one page before converting. There are a couple changes:

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  • You don’t bother creating different conversion flows, you just have one flow, but you still add a funnelCookie requirement which says that your funnelCookie has to be some page rather than undefined

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Conclusion

Hopefully this has helped you get an idea of how to get more control of the conversions being recorded on your site, whether that’s entirely through GA4 or using the power of Tag Manager.

Happy tracking!

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MARKETING

Unlocking Hidden Revenue: The Inbox Retargeting Methodology

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Unlocking Hidden Revenue: The Inbox Retargeting Methodology

Page conversion rates have ALWAYS been a problem. The simple fact is most people don’t convert even on the most optimized pages. 

What’s why traditional retargeting on ad networks has been so dang powerful. While retargeted leads come cheap, they still aren’t free. Worse, you’re back competing against your competition in the ol’ ad auction system.

For the last 6 years, I’ve been using a tactic called Inbox Retargeting to identify who lands on my key pages and directly reach out to them in their inbox.

No more ads. No more auctions. Just a targeted contact that showed they were interested, but didn’t quite take the leap yet.

Before I dive into the “What’s” and “How’s”, this tactic can only be used in the good ol’ US of A. If you aren’t in the states or don’t have clients in the states, you’re out of luck. Sorry!

How It Works

Inbox retargeting doesn’t take a lot of heavy lifting. I’ll share the strategy next but I wanted to start with some of the logistics.

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DISCLAIMER: I am not a lawyer or coder, so keep that in mind if technical or legal questions pop up.

If you have a website, you have tracking scripts, e.g.,  GA4, the Facebook Pixel, Heatmap software, etc…

To get started with Inbox retargeting, you just need to be able to copy and paste two scripts on your site:

  • A collection script: This fires and tries to identify the visitor

A suppression script: You’d fire this on your conversion confirmation pages, you don’t want people who converted to land in your Inbox Retargeting campaigns.

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The tech works off of a database of contacts in the United States that are eligible for emails, so it’s completely above board with your ESP. However, you’ll want to do a few things before you start treating them like a regular member of your email list.

We initially tested this on one of our paid media campaigns. We already had a really strong campaign that we wanted to squeeze more leads out of…and boy did we.

We were driving traffic from Meta (Facebook for the OGs) to this landing page:

1710795438 272 Unlocking Hidden Revenue The Inbox Retargeting Methodology

This page converts at 58%. Yeah, that’s a humble brag…deal with it.

Even with a 58% conversion rate, we’re still missing out on 42% of the traffic we’ve already paid for. That’s kind of a bummer.

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After we added the collection script to the page, they were able to capture a lot more leads. The conversion rate jumped from 58% to a very sweet 87% – that’s a 50% increase!

That was the impact on a single page, that’s when we knew it was time to go bigger.

The Strategy

Most of the tools out there, whether it’s Retention.com or Customers.ai, are going to charge based on the number of contacts. So it can get pretty easy to burn through contact credits if you run the script on every page you manage, your site and your clients’ sites included.

That’s why you’ll want to make sure to select pages that capture intent versus targeting all of your traffic.

ID Key Pages

Here are some of the pages you should consider adding the collection script:

  1. Campaign Landing Pages – If you’re paying to send someone to a page, the referring source piqued their interest. If they didn’t convert, you’d definitely want to follow up.
  2. Product Pages – If someone is viewing this page they’re evaluating a particular product they were interested in.
  3. High Intent/Value Content Pages – This could be your pillar content on your blog pages, podcast pages, or your top level service pages.
  4. Registration Pages – This is a subset of a landing page, but if someone got all the way to a registration or sigh up page, they’re a prime candidate for outreach.
  5. Cart Pages – People abandon carts all the time. If you weren’t able to catch their details during checkout, this is an ideal opportunity.

Effectively it’s any page where you’re pushing a specific action. While the above pages are the pages to choose from, a homepage is acceptable but will require a little more finesse when you follow up.

Map to Email Campaigns

Now that you’ve identified where you’re going to identify leads, you’ll need to map it to your automation tool.

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Unlocking Hidden Revenue The Inbox Retargeting MethodologyUnlocking Hidden Revenue The Inbox Retargeting Methodology

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Most tools have a direct integration with your email service provider, but worst case scenario you may have to pass the data through a no code integration tool like Zapier.

Once you’ve worked out the digital plumbing, you’ll want to follow up based on the page the contact was collected on. Here’s how you should approach follow up:

  1. For Campaign Landing Pages – Give them the specific asset. They were interested in it, you’ve got their contact information, just hand over the goods. This builds good will at the start of the relationship.
  2. Product Pages – Send over the details of the product or product category they were viewing. This could be as simple as a reminder or you could build goodwill with a special offer or coupon.
  3. High Intent/Value Content Pages – Send over some of your best content or freebies that move people to the next phase of the Customer Value Journey.
  4. Registration Pages – Treat these like an “abandoned cart” type of email and get them to take that next step.
  5. Cart Pages – Same as “Registration Pages” but it’s, you know, an actual abandoned cart reminder. Similar to the product pages you could entice them to come back with a deal or coupon.
  6. Homepages – If you do run these on the homepage, you’ll need to do more of a reintroduction then transition to showcasing your best stuff.

Email Structure

The initial message you send needs to have a very specific flow. There are four critical things that need to happen when they open up your Inbox Retargeting message.

First, remind them about who you are and how they know you. This can be as simple as a, “Hey, thanks for stopping by…” message. Have some fun with it.

Next, you need to provide highly specific value based on their browsing intent. If you get this wrong, they’re just going to file your message under SPAM.

After that, you’ve got to set expectations with what they’re getting and now you’ll be communicating with them moving forward.

And Finally, you need to give them an EASY OUT. These campaigns have our highest unsubscribe rate, but that’s because we outright ask people to unsubscribe if they don’t want any additional contact.

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Once you’e gone through this, you treat them like one of your regular subscribers with all your fancy ascension automations, content emails, and promotional emails.

Here are the email stats from one of our PPC Campaigns:

1710795439 568 Unlocking Hidden Revenue The Inbox Retargeting Methodology

With an average open rate of 53.87%, we know there’s a base line interest in the deliverable. The click rate is DANG good for messaging visitors who didn’t convert.

Sure the unsubscribe rate is a little high for this campaign, but that is intentional. We push them to opt-out in the first email so we don’t get dinged later with complaints.

The Payoff: An Additional 109k Last Year

I mean, who doesn’t want another cool 100 grand for adding a script to your website and writing a couple of emails? Here’s how the numbers work out:

Last year, we identified 3,714 leads using this method. IMPORTANT: When I was pulling these numbers, I realized we installed the code wrong on some pages and missed out on about another 2k leads…oops!

Our average lead cost was ~$7, so the leads themself were a $26,000 additional value. This alone would be a reason to use the tech.

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BUT JUSTIN, did they convert?!

Yes!

We closed $36,000 in IPPC business from this lead source. For what we spent on those leads we’re looking at a 750% ROAS. Not too shabby.

The rest of the money we made was by selling this service to our clients. Since we run paid ads for clients, this method is a complete no brainer. We ran a pilot program and only offered this to a handful of clients last year, we averaged about 4k/month in sales.

We sold clients the leads at ~$2/lead for some of the niches we work in, that’s a steal. 

If you decide to sell this you need to make sure the client knows these are lower intent leads and will require longer term nurtures. If you follow the email strategy I shared above, you’ll be good to go!

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Protip: Charge for building the follow up sequence! 

So that’s it! If you’re running your own business or are an agency owner, you’ve got to consider Inbox Retargeting. Though, I do have some bad news…

Not to be “Chicken Little” but this is starting to get way more attention, there are services popping out of the woodwork so this will become a table stakes method. So get ahead of this today.

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MARKETING

What’s Media Mix Modeling? [Marketer’s Guide with Examples]

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What’s Media Mix Modeling? [Marketer’s Guide with Examples]

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By Emily Sullivan

Have you ever felt in the dark when it comes to understanding the real impact your marketing dollars are having across multiple channels? 

Determining where and how conversions are occurring is crucial in optimizing your budget to drive the most impact with your marketing budget. Media mix modeling (MMM) is an analytical approach used to gauge the effectiveness of various marketing channels in driving sales and conversions. This method allows us to decipher the true influence of advertising spend across diverse platforms by accounting for a myriad of factors, both within their control (like media channel spend, promotional strategies) and outside their control (such as economic conditions, competitor actions, and seasonal influences).

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One of the key strengths of media mix modeling is its ability to incorporate long-term brand building effects alongside immediate sales impacts, offering a comprehensive view of marketing effectiveness. It helps in identifying which channels are most efficient, how different channels influence each other, and how external factors affect marketing performance.

Media mix modeling is a powerful tool for marketers seeking to optimize their marketing investments. By providing a holistic view of how various factors contribute to sales and conversions, MMM enables data-driven decisions that enhance marketing efficiency and business growth.

In this article, we explore how media mix modeling works, and how businesses can use analytics to drive smarter ad spend decisions.

What Is Media Mix Modeling?

Media mix modeling (MMM) is a type of analysis that measures the impact of media buys across multiple channels, showing the role various elements play in achieving a desired outcome—often a conversion or revenue KPI. With this information, marketing stakeholders are able to make specific adjustments to campaign spend to improve their progress toward reaching a given goal.

Media mix modeling can be used to address common brand marketing questions and pain points, including:

  • Which of our marketing efforts are having the biggest impact on reaching our goals—or, more simply—what’s working?
  • How big of an impact does seasonality have on our marketing performance?
  • How closely is our performance tied to promotional efforts? 
  • Are shifting consumer trends negatively or positively impacting outcomes?
  • Which specific mix of spend allocation drives the highest ROI?
  • How will these channels likely perform in the future based on their optimized spend allocation?

“Media mix modeling is a top-down , privacy resilient approach that evaluates how historical media activity, promotions, pricing, seasonality, and uncontrollable factors—such as economic activity—impact key business outcomes such as sales revenue. MMM is a scientific approach to attribution in the sense that it applies statistical methods to analyze and interpret marketing data, providing a systematic understanding of how different marketing channels contribute to overall business goals in the broader context of the market. The quality of insights derived from MMM heavily depends on the quality and granularity of the data used.”

— Annica Nesty, Group Director of Marketing Science at Tinuiti

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MMM leverages aggregate data, and can measure both online (digital) and offline (traditional) advertising channel performance, including (but not limited to): paid media channels such as social media channels, traditional print advertising, linear TV advertising, and other performance marketing efforts, organic media, operational factors like promotions, external factors like seasonality, economic conditions, outcome KPIs such as sales revenue, new customers, and conversions. 

How Does Media Mix Modeling Work?

The MMM framework is a type of statistical analysis that uses statistical methods and econometric models such as a regression analysis. This econometric model helps analysts determine the strength of relationships between a single dependent variable and an array of independent variables.

Media mix modeling analysis measures the impact of your media spend today, and is also helpful in predicting the future outcome of your marketing investments on a given variable.

Example:

Let’s assume a scenario where our target metric, or dependent variable, is revenue, a critical indicator of business success. We aim to dissect the influence of various marketing initiatives on this revenue. These initiatives, our independent variables, encompass a diverse array of digital advertising campaigns, including those run on TikTok, Instagram, Snapchat, as well as broader Display and Streaming platforms.

The number of independent variables under scrutiny does not dilute our core objective. The mission is to measure the relationship between the marketing endeavors and the revenue they generate. This involves not only identifying the direct contributions of each campaign to revenue but also understanding the nuanced interplay between them by observing how changing aspects of those independent variables impacts the chosen business outcome

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What can MMM Measure?

When using MMM to assess campaign success, marketers should leverage statistical methods and econometric models to get the most accurate picture possible. Data quality is essential in achieving an accurate media mix analysis, so take any needed time to clean your data before using it in your analysis. 

Key elements an MMM equation can measure include:

  • Base and incremental sales volume impact
  • Channel effectiveness and return on investment
  • Marketing spend saturation

Media Mix Modeling vs. Data-Driven Attribution Modeling

Like media mix modeling, attribution modeling also studies the efficiency of marketing strategies — but there are important differences.

Attribution modeling is a general term that refers to tracking engagement to better understand how specific tactics drive action at the user level. This modeling works well for analyzing specific customer touchpoints, focusing on elements like how a consumer converted, which creative on which channel led to that conversion, and what the expected ROI could be if more ad budget were shifted to that channel. 

Media mix modeling takes a higher-level, more comprehensive picture. This modeling isn’t designed to measure user-level engagement like impressions and clicks, rather its primary function is measuring the impact of an entire touchpoint on specific marketing objectives. 

Data-driven attribution modeling and MMM each have their own set of strengths. It’s not a matter of one being better than the other, rather one being better-suited to different types of marketing analysis. 

For example:

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  • The precision of the data-driven attribution: Let’s assume you want to invest more spend in a social ad campaign during the holiday season. While MMM is an option for determining where to allocate those dollars, data-driven attribution excels in dissecting the intricate customer journey, offering a microscopic view of user interactions. For instance, if you’re keen on understanding the exact value of a single click from your social media campaign, Data-Driven Attribution can illuminate the path. 
  • The holistic perspective of the media mix modeling:  Media mix modeling, can consider the impact of offline actions and initiatives. Unlike the more narrowly focused attribution models, which might overemphasize the first or last touchpoint, MMM assesses the collective impact of all channels over time. This makes it an indispensable tool for strategic planning and long-term investment decisions in your marketing portfolio.

“Attribution modeling is based on a bottom-up approach while media mix modeling takes a top-down approach. Media mix modeling provides a long-term view of the marketing ROI of media activity, while attribution modeling evaluates individual-level activity to provide a short term view of marketing ROI.” 

— Annica Nesty, Group Director of Marketing Science at Tinuiti

Why Does MMM Make Sense for a Post-cookie/Post-IDFA World?

In the post-cookie and post-IDFA landscape, where privacy concerns and regulatory changes limit access to individual user-level data, media mix modeling has become a pivotal analytical tool. MMM’s emphasis on overall marketing spend allocation and its proficiency in establishing cause-and-effect models, address the challenges posed by the diminishing availability of explicit conversion information, providing marketers with a privacy-respecting and insightful approach to navigate the evolving digital advertising ecosystem.

An Example of Media Mix Modeling

With the right media mix model, a business can measure their past marketing performance to improve future ROI by optimizing the allocation of the media budget by channel and/or tactic, including: traditional and digital media channels, promotions, pricing, competitor spend, economic conditions, weather, and more.

Example:

An international ecommerce brand wanted to forecast their second-half of the year and create an optimal media mix to make their marketing dollars work smarter. A combination of client data, marketing data, and machine learning were required to create a powerful, custom media mix model. 

To build the model, the business used 2+ years of digital marketing and revenue data, analyzing it by market, tactic, and day. The data was then used to create model to assess future spend showing how changes in investment across channels could impact revenue and sales.

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media mix modeling

The full digital media mix model gave the ecommerce brand a detailed analysis of where to optimize their spend across all digital marketing channels. 

One recommendation was to shift dollars away from social—which historically had been at or near 30%—to paid search. This recommendation came with another layer of insight: The brand realized they were overinvesting in awareness campaigns, and needed to invest more heavily in capturing current demand during the 2nd half of the year.

Results: Working with a robust media mix model, the brand was able to break down how much media spend was needed by each channel in order to achieve the 30% YoY revenue goal they targeted. 

The Benefits & Challenges of Media Mix Modeling

MMM helps you accurately connect all the dots, leveraging (ideally) a wealth of provided data, to understand how disparate aspects of marketing campaigns work together in helping you reach your business goals. 

Benefits of Media Mix Modeling

The benefits of MMM are multifaceted, offering marketers a strategic edge in navigating the intricacies of their advertising efforts. Let’s dive into each benefit in detail… 

Omnichannel Campaigns: MMM excels in providing insights for omnichannel campaigns, allowing marketers to understand and optimize the impact of their initiatives across various channels. This capability is crucial in today’s interconnected digital landscape, where consumers engage with brands through diverse platforms.

Improved Oversight Over Media Spend Impact: MMM provides a comprehensive view of the impact of media spend, enabling marketers to assess the effectiveness of their investments. This improved oversight ensures a clearer understanding of how each component of the media mix contributes to overall campaign success.

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Media Spend Optimization: With MMM, marketers can optimize their media spend by identifying the most impactful channels and touchpoints. This data-driven approach allows for strategic adjustments in budget allocation, ensuring that resources are directed towards the avenues that yield the highest return on ad spend.

Effective Targeting of Audiences: MMM’s analysis helps in refining audience targeting strategies. By understanding which elements of the marketing mix resonate most with specific demographics, marketers can tailor their campaigns to effectively reach and engage their target audience segments.

Forecasting with Certainty: One of MMM’s strengths lies in its ability to forecast results with a high degree of certainty. This forecasting capability empowers marketers to make informed decisions based on predictive analytics, aiding in long-term planning and goal setting.

Reduced Reliance on Personally Identifiable Information (PII): MMM minimizes the reliance on personally identifiable information for analysis. This is especially crucial in an era where privacy concerns are more important than ever. 

Media mix modeling is a comprehensive and powerful tool, offering a range of benefits that contribute to a more effective, data-driven, and privacy-conscious approach to marketing strategy and decision-making. While there are many benefits to MMM, there are challenges as well. Let’s look into common challenges of MMM in our next section.

Challenges of Media Mix Modeling

MMM grows increasingly complex as the media landscape becomes more fragmented, and the customer journey more personalized. Whereas in the past, advertisers may have wanted to measure something as simple as the impact of a print ad in a Cleveland newspaper, today’s consumers are exposed to brands in a wide variety of locations and formats, from a subway transit poster to a Sponsored post on Instagram.

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Working with high-quality data is important in any measurement initiative, but for MMM to work effectively, it also needs a lot of data to build a reliable model. For example, if you wanted your model to consider the performance impact of seasonality, it would ideally need at least three full seasons (three years) of data to consider in its analysis.

This makes media mix modeling a ‘long game’ initiative with infrequent reporting by its nature. Brands and advertisers who are more accustomed to daily or weekly updates may struggle with ‘waiting out’ the analysis.

Because it’s not designed to make considerations based on user-level data, instead providing aggregate insights, media mix modeling offers limited insights on brand impact, personalized targeting, and customer experience. However, advanced models are available that can provide highly granular insights, but traditional MMM provides aggregate insights.

Common Misconceptions About Media Mix Modeling

Media mix modeling, like many other analytics solutions, has also become a marketing buzzword that has generated its fair share of misconceptions.

Here are a few of the most common misconceptions around media mix modeling.

Media Mix Models Are Not Transparent

With large datasets and statistical analysis involved in media mix modeling, the methods behind the technique have been critiqued for their obscurity. If there is no perceived transparency in the process, how does a brand know if its media mix model is really accurate?

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Any organization specializing in media mix modeling should provide a transparent approach, with deliverables such as outlines, milestones, and performance reports. Additionally, you may want to consider partnering with an agency that truly understands how media mix modeling aligns with your needs and expectations. Every business is unique and each media mix model is based on multiple factors.

Media Mix Models Do Not Provide Real-time Data

Today, results are often measured by the timeliness of their delivery, with the current digital marketplace allowing for almost instantaneous real-time data. Media mix models do actually provide compelling real-time marketing insights, perfect for evaluating new campaigns, new competitors, and assessing pricing actions or changes in promotional strategies. 

A powerful partner in media mix modeling will provide sophisticated tools and real-time approaches to satisfy your business performance assessments. Your partner should also be able to provide forecasting, simulation, or AI- and machine-learning-integrated models to suggest future movements. 

Media Mix Modeling is Biased to Offline Channels

Though media mix strategies do integrate and consider offline channels in their approaches, media mix modeling also considers all digital channels — including display, email, paid search, social, and more. Remember—it’s considering your media mix. If that includes ten different channels and you provide enough high-quality data for each, they will all be considered in your marketing mix analysis. 

In fact, as customers have become more intertwined with digital channels, media marketing models have adapted to go even deeper into the analyses provided by those channels’ respective insights to support better budgeting choices and customer segmentation reports. 

Conclusion: MMM Closes the Loop on Marketing Performance

In an ever-evolving digital landscape, MMM’s adaptability to the post-cookie/post-IDFA world positions it as an essential tool for marketers. As businesses seek to connect the dots, leverage data, and make strategic decisions, MMM is a crucial ally in the dynamic realm of mixed media advertising.

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“At Tinuiti, we leverage measurement best practices such as MMM and incrementality to understand media effectiveness, predict future outcomes, create deeper insights, analyzing what-if scenarios to provide recommendations that optimize media performance. This helps brands understand what channels they should be investing in, how they should shift budgets (media mix), creating a high-level view of what channels are driving overall sales and ROI. Our goal here is to deliver growth for our clients by maximizing the return on investment through best in class measurement”

— Annica Nesty, Group Director of Marketing Science at Tinuiti

At Tinuiti, we know, embrace, and utilize MMM. Our Rapid Media Mix Modeling sets a new standard in the market with its exceptional speed, precision, and transparency. 

Our proprietary measurement technology, Bliss Point by Tinuiti, allows us to measure what marketers have previously struggled to measure – the optimal level of investment to maximize impact and efficiency.  But this measurement is not just to go back and validate that we’ve done the right things. This measurement is real-time informing what needs to happen next.

Curious about how we can tailor strategies to hit your unique marketing bliss point, including Rapid Media Mix Modeling? We’re eager to chat. Contact us today for details.

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Email Ready to Send? Make Sure to Tick These Things off First!

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Email Ready to Send? Make Sure to Tick These Things off First!

Designing and developing an email campaign is a complex mechanism; a few things will inevitably escape your attention during the process. So, before you hit that send button, you must draw up a foolproof checklist to ensure every single component in your campaign is in its rightful place. Wondering what an ideal pre-flight checklist looks like? We’ve carefully compiled everything necessary in this blog. Read on to find out!

Subject Line and Pre-header Text

A subject line can make or break your emails. It’s the first thing about your email that reaches the audience, and if it fails to hit the right notes, you’ll have a tough time convincing your subscribers to engage with your emails.

What makes a subject line tick, you ask? Let’s take a look!

  • Your subject line should prioritize an economy of words; this will help you on two accounts- firstly, a crisp and to-the-point subject line increases your probability of catching the reader’s attention. Secondly, longer subject lines run the risk of being clipped on mobile devices, thereby spoiling the subscriber’s user experience. By keeping your subject lines concise, you eliminate this possibility.
  • Ensure your subject line clearly explains what readers can expect upon opening the email. The more guesswork your subject line demands of readers, the less likely they are to open your email.
  • Steer clear of using words that might be considered spammy. With email filters becoming more and more sophisticated, usage of any sort of contentious term in your subject line will result in ISPs flagging your email as spam.
  • Personalize your subject line. In a climate of increasingly crowded email boxes, personalization is one technique you simply can’t afford to overlook.

Besides fine-tuning your subject line, you also need to pay attention to your pre-header text. Building upon the context provided by your subject line, pre-header texts give readers an additional nudge to open their emails. Two crucial things that you must keep in mind while curating your pre-header texts are:

  1. It must exist only as an extension of your subject line; it must not try to introduce any new ideas on its own.
  2. It must be mobile-optimized.

Broken Links

Given that the links embedded in your email eventually facilitate a conversion, it is imperative that you thoroughly evaluate their health prior to delivering your emails. Broken links aren’t just bad for business; they also spoil a subscriber’s user experience.

Here are a few things you must check after embedding a link in your email:

  • This might sound trivial, but do check if the link you have inserted is the one you intended to or not; the only thing perhaps worse than having a broken link is having an irrelevant one.
  • Check that the link is redirecting the user to the desirable destination.
  • If the download of a resource is supposed to be triggered by clicking the link, check if that’s functioning properly; you wouldn’t want subscribers clicking umpteen times on your link only for it to return nothing.

Accessibility

Apart from acing your content and design, you must also work towards making your email campaigns accessible; people making use of assistive technologies must be able to engage with and comprehend your emails in an absolutely hassle-free manner.

Given below are a few measures that will help you make your campaigns accessible to all:

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  • Organize your email content. Break down long paragraphs into small sections of 2-3 lines. Use bullets and subheadings wherever necessary. This will make it easy for assistive technologies such as screen readers to parse through your content.
  • Write descriptive alt texts for the images you’re including. Besides improving accessibility, alt texts also enable search engines to crawl your page more efficiently, thereby boosting your SEO.
  • Use semantic markup; this will help screen readers navigate your emails in a smooth fashion.
  • Try to stick to a single-column layout while designing your email template.

This email from AllTrails is an ideal example of an accessible template.

Inbox Preview

Different email clients render emails differently, even if only slightly. Hence, before sending out your emails, you must preview them across different environments and clients to check if they appear as desired. If you are designing your email for dark mode, too, it becomes that much more important to preview it before delivering.

Wrapping It Up

For your email campaigns to be able to drive maximum impact, they must be free of blemishes of all kinds. We hope the pre-flight checklist we shared above proves to be of help to you when you sit down to create your next campaign.

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