Get ahead of the game: a complete overview of all Revenue Attribution Models

“Talent wins games, but teamwork and intelligence win championships.” —Michael Jordan

The age of data has given marketers more options than ever. Too many, actually! Marketers find themselves overwhelmed with data, trying to figure out what content and campaigns actually work, and which marketing channels should get the credit. 

Did your Facebook ad land the deal? Was it your blogpost? Or that last phone call to your prospect?

Just like scoring a point in a basketball game involves several teammates setting each other up for success, getting a sale also involves a multitude of efforts, interactions, and touchpoints leading to the winning result: converting a lead into a customer. 

But only giving credit to the last touchpoint would be like if the Chicago Bulls had only paid Michael Jordan every time he scored a basket (the last touch), and not Scottie Pippen, Dennis Rodman, or any of the other teammates (multi-touch).

Imagine that each player is a different channel. All the players contribute, but who gets credit for scoring the point? 

Marketers wanting to play in the big leagues know that they can’t rely too heavily on gut feelings and guesswork anymore. To get ahead of the game, you need to get the right picture of your marketing efforts through data-validation.

But that’s easier said than done. In fact, proving the ROI of marketing activities is listed as a top challenge for the modern-day marketer.

Thankfully, there are revenue attribution models out there that can help you find out what your main lead-conversion channels are. These models do the data-crunching and credit division for you and help you connect the dots, so you can stop burning money and focus on the campaigns that you know (with confidence!) will drive revenue. 

Get to the core of the attribution question in this What is attribution, really? post.

The big question is: Which model is the right fit for you? 

Find the right attribution model with this checklist ✔️

It can be daunting having to make the call on which revenue attribution model to go with. Most marketers who start looking into attribution models do so because they’ve lost the overview and are unsure which channels are bringing in the dough.  

Attribution models can be put in one of three categories: single-touch models (e.g. First-Touch attribution or Last-Touch attribution), multi-touch models (e.g. Linear or U-shaped attribution), and Full-Path (to capture the value that post-opportunity stage marketing provides). 

Multi-touch attribution is usually the way to go, even though there are companies out there whose setup is straightforward enough for single-touch models. 

Either way, you don’t want to risk applying the wrong model to your data and get a skewed view of your high-performers. That’s a lot of pressure! To help alleviate some of that stress and confusion, you can use this checklist to point you in the right direction.  

A checklist to help you choose the right attribution model with confidence (so you can wow your CEO and CMO!):

1. Are you a B2B marketer or B2C marketer? 

B2B marketers usually go for a multi-touch attribution model because B2B often involves multiple touchpoints, multiple teams, and multiple stakeholders, making it harder and quite complicated trying to attribute credit to the right players. 

B2C marketers often go with a single-touch model because B2C tends to be more straightforward, only attributing a conversion to one single touchpoint in the customer’s journey (the first one or last one).

2. How many marketing channels do you use? Fewer than 5? More than 5?

If you’re using five or more marketing channels, no matter the spend on each, you’ll find it beneficial to use a multi-touch attribution model so you can make sense of all your data and your customer’s entire buying journey. 

If you’re using fewer than 5 channels, your setup is manageable enough that you should be able to use a single-touch model.

3. How long is your sales cycle? Longer or shorter than 1 month?

The longer your sales cycle, the more touchpoints your prospects are likely to interact with. Sure, each touchpoint may be in the same marketing channel, which makes it quite straightforward, but to find out how each one performs and contributes to conversions and revenue, you’ll need to go with a multi-touch model. 

4. How much is your marketing spend? More or less than $10.000/month?

Around $10.000/month tends to be the sweet spot where multi-touch attribution starts to pay for itself. So it might not be worth it to use a multi-touch model with a monthly spend of under $10.000. 

Check out this piece on marketing attribution models.

In sum: if you have more than one marketing channel, a sales cycle that is longer than one month, and an ad spend of more than $ 10.000/month, chances are you’re a good fit for a multi-touch attribution model.

So there’s no need for you to read all about single-touch models (you can, of course, if you really want to). Skip ahead to multi-touch attribution models.

You can take it even one step further and find out if you’re a fit for full-path instead of multi-touch by answering the bonus question below:

Or, cut straight to the chase and
use Dreamdata’s multi-touch models now

5. Do you continue marketing to your prospects post-opportunity? Yes/no?

This means you’re continuing your marketing efforts to prospects beyond the opportunity stage. Most companies do this to ensure increased engagement and retention, by giving the customer a continued positive experience. 

If you answered yes to the bonus question: a full-path attribution model is a good fit for the customer journey you’re trying to track. Skip ahead to the Full-path model. 

If you answered no to the bonus question: multi-touch is the way to go. Skip ahead to the multi-touch models.



Single-touch models

The single-touch models only attribute credit to one single player—the first one to get the ball or the last one who gets the slam dunk.

Single-touch models attribute a conversion to one single touchpoint in the customer’s journey (either the first one or last one). 

Pros: Single-touch models are easy to set up and great when you want to track simple conversions for specific campaigns and channels.

Cons: You don’t get the full picture and may end up giving credit to the wrong channel, overlooking key content pieces and channels that contribute to the final conversion point of a prospect.

1. First-click attribution model 

Also known as “First-interaction attribution” or “First-touch attribution”

The first-click attribution model gives all of the credit to the first touchpoint, putting the emphasis on top-of-the-funnel marketing channels. 

Pros: Implementation is easy. This is a great model for finding out which of your ads and/or channels are getting you the most new customers so you can increase your spend for these channels and get new customers even faster. 

Cons: It’s impossible to know to what extent the first touchpoint contributed to the final conversion. There are also some technical limitations that can give you a skewed view of the value of your first touchpoint because of incorrect attribution (e.g. lookback window).  

2. Lead (MQL) creation touch attribution 

Often confused with the “First-click attribution model”. This is because the website session where a lead is created is usually tracked and measured as the first session (the first touchpoint) in most marketing analytics systems. If the actual first touchpoint happened elsewhere and was anonymous, this model doesn’t (and can’t) attribute credit to that event. 

Pros: Great to help you understand which one of your channels are providing lead conversions. For B2B, it can serve as a proxy on the road to revenue. 

Cons: Marketing is about more than lead creation alone. Giving all credit to lead creation leaves none for all the other touchpoints your marketing activities may have an impact on.

3. Last-click attribution model 

Also known as “Last interaction attribution”, “Last touch attribution”, Opportunity creation touch”

The last-click attribution model gives all of the credit to the last touchpoint before conversion, which is usually direct traffic. This model puts the emphasis on bottom-of-the-funnel marketing channels. 

Pros: Simplest and most accurate model for attribution systems to measure as it has the smallest window of time for an error to occur in your analytics system. Good for finding out which channels drive the most conversions.

Cons: Not a good fit for long marketing and sales cycles, as the model ignores every touchpoint and event that happens before the last touchpoint. So take extra care when using this model in B2B.

4. Last non-direct click attribution model 

This model is a little more helpful than a standard last-click attribution model, as it removes direct traffic altogether as the last possible touchpoint before conversion. Traffic with “Direct” as the referral source can be a huge pain in the you-know-what when it comes to attributing value. It’s the proverbial dumping ground for any traffic that’s incorrectly tagged. 

Pros: Good for finding out which channels drive the most conversions without the noise of the direct traffic source.

Cons: Just like the last-click attribution model, it ignores every touchpoint and event that happens before the last touchpoint. 

5. Last [insert marketing channel] attribution model 

If first and last-click weren’t specific enough for you, it’s time to welcome channel-specific attribution models to the stage. The most commonly used model is Last AdWords-click attribution, but you can apply it to any relevant (social) marketing channel (e.g. “Last Facebook Touch model”, “Last Twitter Touch model”, etc.).

Pros: Usually come standard with their channel (plug and play). They’re useful when you want to find out which (social) marketing ads and activities are driving the most revenue for your business.

Cons: Biased to their own channel, so they may overvalue their respective impact.

Multi-touch models

The multi-touch models attribute credit to all players—from the first player who gets the ball to the last player who scores the basket, and every pass in between. 

Multi-touch models attribute credit to every content piece and channel in the customer’s journey, so you know how every single touchpoint performs and contributes to conversions and revenue. 

Pros: A better understanding of a customer’s entire buying journey rather than just the first or last step, bridges the gaps in your tracking and identification funnel, and helps you make sense of all your data. All of this will help you align the efforts between your marketing, sales, customer success, and product departments.

Ideal for B2B attribution.

Cons: Requires buy-in and cooperation of your entire company and can take several months after implementation to get rich data and find out which touchpoints are actively driving revenue. 

Read more about multi-touch attribution models.

6. Linear attribution model

The simplest of the multi-touch attribution models. It distributes credit by evenly applying credit to every single touchpoint in the customer journey before converting.

Pros: Gives credit to marketing channels throughout the multiple stages of the funnel and measures your marketing strategies holistically.

Cons: Doesn’t take into account the potential for varying impact of marketing activities as it distributes credit evenly. As such, this model won’t highlight if some marketing strategies are more effective than others.

7. Time-decay attribution model

Similar to Linear attribution as it spreads out credit across multiple touchpoints. Unlike Linear attribution, the Time Decay model gives more credit to the touchpoints closest to the conversion. It makes the assumption that the closer to the conversion, the more influence the touchpoint had on the conversion.

Pros: Effective for determining which channels regularly drive conversions and which are primarily top-of-funnel channels. Good for particularly long sales cycles (e.g. expensive B2B purchases).

Cons: Will never give a fair amount of credit to top-of-the-funnel marketing efforts (as those that will always be the farthest away from the conversion).

Start your multi-touch attribution journey now

8. U-shaped attribution model

A position-based model. Tracks every single touchpoint, but rather than give equal credit to all touchpoints (like the Linear model), it gives 40% credit to the anonymous first touch and 40% credit to the lead conversion touch. The remaining touchpoints get 20% split between them. 

Pros: Tells you which marketing channels are best for getting leads and which are best for conversion.

Cons: Doesn’t consider marketing efforts beyond lead conversion. Downplays and hides the potential value of the in-between touchpoints.

9. W-shaped attribution model 

Another position-based model. Same as the U-shaped model, but the W-shaped model emphasizes the opportunity creation touchpoint (not just the anonymous first touch and the lead conversion touch). These three key touchpoints receive 30% credit each, and the last 10% is split evenly among the remaining touchpoints.

Pros: Highlights the three key funnel transitions that marketing impacts in the customer journey (the beginning, middle, and end).

Cons: Can be trickier to set up depending on how you track new leads and may place too much emphasis on channels that generate leads, not conversions.

10. Full-path attribution model (Also known as “Z-shaped attribution”)

But why stop at the W-shaped model? With the Full-path model (yup, yet another position-based model!) you can look at the value of your marketing efforts beyond the opportunity stage. It attributes 22.5% to the anonymous first touch, the lead conversion touch, the opportunity creation touch, and the customer close. The last 10% is split evenly among the remaining touchpoints.

Pros: A true, start-to-finish overview of all the touchpoints in the customer journey. Allows you to pinpoint which strategies work and are worth investing in.

Cons: Only suitable for organizations that do marketing to existing sales opportunities. Relies on heavy alignment with the sales team.

11. Data-driven attribution model

Analyzes your data with algorithms to predict which channels will have the biggest impact on conversions. Uses past data to attribute credit. 

Pros: Determines which channels are actually driving the most success so you can retire ineffective players and optimize the Jordans on your team.

Cons: Highly complex solution and aimed at historical data. Requires an analytics platform that can generate targeted insights, and a lot of data to make the model useful when it comes to analysis. So be careful when applying this model to B2B. 

Read more about data-driven attribution here

12. Custom attribution models

If you want to go for a custom solution, you can have a data scientist build an attribution model that best suits the customer journey specific to your buying process and analyzes your existing customer data.

Pros: Catered to your company setup, and allows you to see which marketing channels get too much (or too little!) credit. 

Cons: Probably the most difficult and time-consuming model to build, maintain, and use. Has inherent bias towards what you attribute credit to, even though those activities/events/channels may not actually be the best for your business.

Revenue Marketing

Once you have identified which marketing and sales activities contribute to revenue, you can best support revenue marketing. This is the process of aligning marketing activities with sales objectives to generate measurable revenue. Learn more about revenue marketing here. 

You’ve got this!

Choosing the right attribution model helps you give credit where credit is due, so you know what players to invest more in and which ones you need to retire. Some players may have served you well in the past, but they haven't been keeping up with the times. That’s why taking the time to look through all the different models can pay off in the long run.

It can be intimidating to choose a model and get started, but it’ll give you the edge you’re looking for in your marketing strategy and ensure you’re ahead of the game. Thankfully, there are companies out there with platforms that specialize in doing the technical setup and data analysis for you, like Dreamdata and LeanData. They make it easy to find out how much a given effort/person/team (input) turns into revenue (output).

Some of the platforms are more geared towards people who have strong technical skills, a passion for data analysis, or the need to customize their solution. While others are great for people who want to focus on the creative work, letting the tool do all the data-crunching and visualization work for them. Choose the platform that best suits your needs and go for that 3-pointer!

Once you’ve implemented your model of choice, you’ll reap the benefits in the form of much more efficient marketing activities, the most accurate picture of the customer journey you’ve ever had, and measurable results you can take to the bank.

(And if that’s not a slam dunk, what is?!)