All You Need To Know About First, Last Click, Linear and Decay in 1509 Words

attribution modelling - www.ruleranalytics.com

The marketing industry is crowded with so much technical jargon. It’s hard for us marketers to make sense of it all sometimes.

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

Although, for content and social media marketers who are used to measuring metrics such as traffic, time on page, and bounce rate, these terms may sound foreign.

Wherever your strengths lie in the marketing world if you don’t spend time educating yourself and finding the appropriate attribution model for your goals, eventually your campaigns will start to plateau.

They’re crucial to understanding how your campaigns are performing and how much revenue your efforts are generating for your business.

The first click, last click, linear, and decay are all attribution models. They’re a 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 marketing channels.

With that said, we decided to put together this simple, but an exact 1,509-word article on everything you need to know about the attribution models used in your analytics toolkit. We’ve kept it short and sweet so you can take away the important stuff and focus on applying it to your marketing efforts.

 

What’s an Attribution Model?

Imagine for a moment that you’re in charge of marketing for an e-commerce site. You run a series of AdWords ads for a big promotion, and over a 100 people click on your ad and make a purchase.

It’s pretty obvious in that scenario that the source of those sales was down to your ad campaign.

But in B2B marketing, it’s rarely so simple.

Most B2B buyers aren’t just following an ad and making the purchase there and then. Maybe they follow an ad the first time and check out your site. They may decide to read a few of your blog posts and sign up for your newsletter.

Over the next few months, they download case studies sent in your newsletter and follow your brand on social.

Ultimately they make a purchase. But what campaign do you attribute that revenue to?

Is it the original ad they clicked on, your blog, email campaigns, case studies, or all four?

If you don’t know what attribution model your analytics program is using, then your metrics may be deceiving. It’s possible that it’s attributing all of the revenue to ads, which masks the fact that your content, email, and social media marketing campaigns all played a part in the sale.

To really know which of your campaigns is performing the best and generating the most leads and revenue, you must understand the different types of attribution models, and make sure your analytics tool is using the one that makes the most sense for how you run your campaigns.

To break things down, we’re going to take a look at some of the most common types of marketing attribution models.

 

Types of Marketing Attribution Models

To explain the most common marketing attribution models, it helps to refer to a sample buyer’s journey. We’ll use the following journey to illustrate how each attribution model works:

  1. 1. Anonymous prospect clicks on an AdWords ad and lands on your site.
  2. 2. While there, they subscribe to your newsletter.
  3. 3. They receive a link to a case study in your newsletter and fill out a form to download it.
  4. 4. After reading your case study, they come back several times to read new blog posts.
  5. 5. After two months, they visit your pricing page. From there, they click a button to schedule a meeting with sales. During that call, they make a purchase.

 

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. In the example buying 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. However, it doesn’t take into account all of the other campaigns that the customer interacted with along his journey. It certainly wasn’t just the ad that drove the sale. Your content and email marketing campaigns also played a part.

 

Last Click Attribution

In the last click attribution model, all of the revenue is attributed to the very last campaign the customer interacted with before making the purchase. In the example buying journey above, last click would attribute all of the revenue from the sale to your pricing page.

Last click attribution can show you what the final point is in your buying journey and which campaigns are most effective at convincing customers to make a purchase. But like first click attribution, it neglects all of the other marketing campaigns that played a part in inspiring the sale. The model doesn’t account for any of the other campaigns the customer interacted with.

 

Linear Attribution

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

In the example journey above, the customer interacted with five different marketing campaigns: an AdWords ad, a marketing email, a case study, your blog, and a landing page. The linear attribution model would divide the revenue generated by five, attributing 20% 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 convincing the customer to buy gets equal credit for the conversion.

 

Time Decay Attribution

In the time decay attribution model, credit for the 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.

In the example journey above, the customer interacted with five different marketing campaigns: an AdWords ad, a marketing email, a case study, your blog, and a landing page. The time decay attribution model would give credit to all five campaign types, but the last two—your blog and the pricing page—would receive a higher percentage of credit than the first three touchpoints.

Time decay is good for showing you two things. Like linear attribution, it shows you all of the campaigns and channels that played a part in generating the conversion. And like last click, it shows you which of your campaigns/channels does the best job of getting customers to make the decision to buy.

 

A Quick Reference Attribution Type Chart

Use this chart to quickly reference how credit is applied for each of the four most common marketing attribution models:

 

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 AdWords 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. 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 isn’t a one-size fits all solution. The attribution model you choose will depend on the channels 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.

Switch between multiple different models, first-click, last-click, or linear, to see how your campaigns perform in different scenarios or use our customer journey mapping feature to get a complete list of every single interaction that took place before the conversion.

Ruler Analytics lets you build reports like a data scientist even if you’re not one. It helps you figure out exactly how much revenue marketing is bringing in for the business, and prove it to your clients and company leaders.

Written by

Liverpool born marketer. 3-years experience in content, outreach and SEO. I love to help individuals measure the true ROI of their marketing spend. I may occasionally use GIFs to express my point. I have an addiction to goal setting.