All You Need To Know About First Click, Last Click and Attribution Modelling

attribution modelling -

Readers note: This article was originally published in 2018 and was last updated on April 23rd 2020.

When it comes to attribution modelling, there is not a one-size-fits-all solution. The attribution model you choose will depend on the channels and campaigns you are analysing. In this article, we take a look at the most common attribution models so that you can evalute your performance and optimise for campaign success.

In an ideal world, we would want our visitors to click on one of our ads or blog posts and convert into a lead almost instantly.

How easy would it be to demonstrate the value of our marketing?

We could simply sign into Google Analytics and allocate credit solely using last-click attribution.

(Quicker than when Instagram rolled out the swipe-left feed update and switched back to its original design after the outbreak of complaints.)

The pressure of having to prove the quality of our marketing activities every Monday morning would simply disappear.

Although, sadly, life isn’t that simple.

Visitors don’t just land on your website and make a sale.

P.S. If you’re reading this article and thinking, “Katie, that’s not true, my customers always convert within one touch-point,” then please share your magic formula with me.

Coincidentally, as I update this article, I’m halfway through the book Top of Mind by John Hall.

Within the book, John claims that it takes individuals 7-13 touch-points before converting into a sale.

Although average touch-points are dependant on the value of the sale and industry type, whatever service or product you’re selling, it’s extremely likely that your customers generated several touch-points before converting into revenue.

So, on that note, we’re going to explore attribution modelling in more detail.

Taking a look at how each attribution model works and how to choose the best one to measure your marketing.

Editors Note: If you’re here because you’re struggling to attribute sales revenue across multiple channels then I suggest that you check out our eBook on Closed-Loop Marketing Attribution. Or, if you’d prefer, you can request a demo of our attribution software to learn how to match marketing activity with revenue over multiple touchpoints.

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What Can You Expect To Learn

I’ll be focusing on first-click and last-click, in particular, as they’re the most popular attribution models used by marketers.

If you’ve spent time in your career running paid campaigns, the terms “first click and last click”, should sound extremely familiar.

After, I’ll make my way through other attribution models:

  • Last Non-Direct Touch Attribution
  • Time Decay
  • Linear Attribution
  • U-Shaped Attribution
  • W-shaped Attribution

Understanding attribution models are critical to analysing campaign performance.

With the right attribution model, you can find out exactly what impact your marketing is having on your bottom-line figure.

So, let’s get started.


What’s an Attribution Model?

In its most basic form, an attribution model is a rule, or set of rules, that determines how your analytics tool applies credit for clicks, form completions, and conversions.

Despite being around for some time now, marketers still find the process of attribution modelling a challenge. And as more attribution models are created, it becomes more difficult to pick the right one for your business.

In fact, there’s no such thing as the perfect attribution model”.

Each one comes with its own advantages and disadvantages.

Although, without an attribution model, it would be near impossible to prove the value of your marketing activity.

The key is to understand which attribution model is the best fit for your business – and you can start by asking yourself the following questions:

1. What is the exact end goal of my marketing activity?
2. Which attribution model will help me measure these objectives the best?

After learning more about each attribution model, hopefully, you’ll be a step closer to choosing the best one when it comes to measuring your marketing.


Types of Marketing Attribution Models

To explain the most common marketing attribution models, it helps to refer to a sample of a buyer’s journey.

I will be using the following journey to illustrate how each attribution model works:

Visitor journey -

1. An anonymous visitor clicks on a Google ad and lands on your site.
2. They use a brand search in Google and visit a case study page where they sign up to your newsletter.
3. Two weeks later, they click through to a blog post via a newsletter.
4. After two months, they visit your pricing page via direct. From there, they convert by clicking a button to schedule a meeting with sales.


First Click Attribution

In the first click attribution model, all of the revenue generated from the sale is attributed to the very first campaign the customer interacted with.

first click attribution -

In the visitor journey above, first click would attribute all of the revenue from the sale to the ad the customer first clicked on.

First click attribution is good at showing you which of your campaigns is best at generating awareness and traffic.

The screenshot below is how you would assign first click revenue automatically if you were using marketing attribution analytics such as Ruler:

first click attribution -

However, first click attribution doesn’t take into account all of the other touchpoints a customer interacted with along their journey.

It certainly wasn’t just the ad that drove the sale.

The blog and email marketing campaign also played a part.


Last Click Attribution

In the last click attribution model, all of the revenue is attributed to the very last channel the customer interacted with before making the purchase.

Last Click Attribution -

In the example buying journey above, last click attribution would assign all of the revenue from the sale to your direct visit.

Last click attribution can show you what the final point is in your buying journey and what channels are most effective at turning anonymous visitors into leads.

In the screenshot below, we’ve used the same account and date range that appeared in the first-click example, but assigned it to last-click:

last click attribution -

Like first click attribution, this model neglects all of the other marketing campaigns that played a part in influencing the sale.

Last click attribution doesn’t account for any of the other campaigns or channels the customer interacted with.


Last Non-Direct Click Attribution

Last Non-Direct Click Attribution is essentially the same as above, but with a small exception.

Any direct traffic is ignored, and 100% of the credit is assigned to the last channel that the visitor clicked through before converting into a customer.

last non direct click attribution -

So, if we were to use our sample journey, then 100% of the credit would be assigned to the email campaign that inspired a click to the blog.

This model is best if you want to fully understand the effectiveness of your final marketing activities without direct traffic getting in the way of your analysis.

Although the same applies as above, this model doesn’t account for any of the other campaigns or channels the customer interacted with.


Linear Attribution

In the linear attribution model, revenue from the sale is distributed evenly across all of the touchpoints in the buyer’s journey.

Linear attribution -

In the example customer journey above, the customer interacted with four different marketing touchpoints.

The linear attribution model would divide the revenue generated by four, attributing 25% of the sale to each of those campaigns.

Unlike first click and last click, linear attribution makes sure every campaign and channel that played a part in the journey gets equal credit for the conversion.

That said, marketers don’t often implement this model for one reason.

When all the channels receive equal credit, how can you possibly tell which channels are contributing the most value to the conversion path?

Remember, the whole point of using attribution modelling is to know what channel or campaigns provide the most significance.


Time Decay Attribution

In the time decay attribution model, revenue from the sale is distributed to all marketing touchpoints, but the most recent touchpoints receive a higher percentage of credit than the earlier ones.

Time decay attribution -

In the example above, the customer used four touchpoints.

The time decay attribution model would give credit to all four touchpoints, but the last two — your email campaign and direct search — would receive a higher percentage of credit than the first two touchpoints.

Time decay is good for showing you two things.

  1. Like Linear Attribution, it shows you all of the campaigns and channels that played a part in generating the conversion.
  2. It also shows you which of your campaigns/channels do the best job of getting leads to convert into a sale.

Which sounds great, but if your a business that primarily focuses on Top-of-the-Funnel (TOFU) campaigns, then this wouldn’t be the best attribution model for you.

Reason being, that Time Decay attribution doesn’t apply a fair amount of credit to any TOFU campaigns as it’s typically the farthest away from the conversion point.


Position-Based (U-Shaped Attribution)

Referred to as position-based by Google, U-shaped attribution is a multi-touch option that will prioritise the first anonymous touchpoint that initiated the visitor and the lead conversion touch-point.

The U-Shaped attribution model tracks every single touchpoint but will assign 40% to first and last-click.

The remaining 20% is then split evenly among the other touchpoints.

U shaped attribution -

So, in the example above, 40% would be assigned to the Google ad and direct.

Then, the remaining 20% would be split across the organic search and email.

The U-Shaped attribution model is great for telling you two things:

1. What channel is best for acquiring the most relevant audience.
2. What channel is most suitable for converting new sales.

It also assigns a portion of the credit to each touchpoint in the journey, whilst allowing you to optimise for the first and last-click attribution.

This is enough to make you believe that you’ve found your perfect attribution model and stop reading this article.

However, like every other attribution model mentioned, position-based comes with its own complications.

It treats all of the touchpoints in the middle as equal.

In reality, some could contribute to the journey more than others.

The visitor journey above is a good example of this.

The Google organic touch-point inspired a newsletter subscription.

Without this, the visitor would never have clicked through the email campaign to a blog on the website.

Although, both Google organic and email have been assigned the same credit.


W-Shaped Attribution

Following on from my previous point, the W-Shaped model is essentially the same as U-shaped but also assigns credit to the lead generation stage.

Each of the touch-points is assigned 30% credit.

Meaning, the last 10% is split among the other remaining touchpoints.

w shaped attribution -

So, if we revert back to our example above.

The Google ad, Google organic and direct would all receive 30% credit.

The remaining 10% would be assigned to email.

The W-shaped model is a popular hit with B2B marketers.

Especially those operating a sophisticated marketing funnel and have a huge focus on lead generation campaigns.

It allows them to identify how their audience found them, where they made their initial contact and how they converted into a prospective lead without spending too much focus on the points in between.


Why Understanding Attribution Is Important

Company executives expect marketing to be able to prove its ROI.

But if you’re not tracking your campaigns properly, you won’t be able to tell them the ROI of your different efforts.

So you spent £1,000 on Ads ads last month.

How much revenue did that investment generate?

If you’re a B2B marketer and your analytics program is using a last-click attribution model, you’ll probably never know.

Additionally, if you don’t understand how credit is applied to all of your campaigns, it’s impossible to use your analytics system to determine which campaigns are performing the best.

Don’t forget, the Closed-Loop Framework can reveal which of your marketing campaigns are generating the most revenue. You can download that here.

Clicks, traffic, and time-on-site are all good metrics to measure, but if your end goal is generating revenue, you need to know which campaigns do the best job of driving sales.


So, What Have We Learned Here?

When it comes to the attribution model, there is not a one-size-fits-all solution.

The attribution model you choose will depend on the channels and campaigns you are analysing.

As a marketer, you must educate yourself and choose a model that is connected with your specific goals.

There’s a chance that you might not get it right the first time around – but that’s ok.

Before co-founding Twitter, Evan Williams developed a podcasting platform called Odeo.

But that didn’t take off – no pun intended.

My point here is that, once you successfully connect the dots between your marketing attribution touch points you will add a whole new level of insight into your reporting in analytics.

You’ll be blown away by the variety of information you have.

Our analytics solution, Ruler Analytics, makes it easy for marketers to track marketing-generated revenue and attribute that revenue to the right campaigns whether it be first or last-click attribution.

Marketers have been using our product to switch between multiple different models, first-click, last-click, or linear, to see how their individual campaigns perform in different scenarios.

In addition to this, they have customer journey mapping to get a complete list of every single interaction that took place before the conversion.

It helps them figure out exactly how much revenue marketing is bringing in for the business.

You can learn more about that here.

If you would like me to explain any of these models in more detail, or think I’ve missed anything important, then be sure to let me know below.

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Written by

Marketing executive at Ruler Analytics with a background in SEO, analytics, content marketing and paid social. I help people (like me) close the loop between marketing-generated leads and revenue.