Let me hazard a guess.
You’re a marketer and you’ve been asked a similar question by your boss and/or client:
“How much revenue are these marketing campaigns generating for my business?”
Am I right?
If not, then I’m surprised.
Revenue attribution has become a buzz term in marketing in recent years, with an increasing number of discussions around the topic.
Marketers are being held increasingly accountable for the need to connect their efforts with revenue growth.
Simple lead generation is not enough.
As marketers, we’re tasked to drive leads and revenue, but don’t always get the credit for it.
In fact, 43% of marketing teams find proving the ROI of their marketing activities their biggest challenge.
Source: Hubspot Research
The attribution of revenue is paramount in a modern marketing strategy, with around three-quarters of B2B marketing teams having some form of attribution system in place.
You’ve likely heard talk regarding the attribution of revenue, and may even feel you’re fairly well-versed in the subject.
But, how much do you really know about revenue attribution?
If you’re looking to check your knowledge level, or brush up and learn a little more, read on…
What is revenue attribution?
Simply put, revenue attribution is a metric used by marketing software, which connects two different data sets (marketing and sales) to determine exactly which forms of marketing are resulting in revenue downstream.
Marketing technology continues to innovate, mature, and advance with each passing year.
As it does, there is an increasing demand for business executives to hold their marketing functions accountable where revenue is concerned.
Attribution ensures this is possible, and there is a clear line between marketing efforts and the income they generate.
The difference between attribution and conversion tracking
Conversion tracking provides a simple means of tracking the specific actions taken by people on a website.
The most frequent use of conversion tracking is in form submissions, such as a subscription to an email list.
However, conversions can also be used to track other actions taken on a page, such as clicking a button, following a link, or the amount of time spent on a page.
An action or goal is set, and when that criteria are met, it counts as a conversion.
Attribution is a little different, as it tracks the specific marketing actions taking place, and the impact they have further down the marketing funnel – ultimately, the point at which they generate revenue, and how much revenue they create.
Attribution tracks more than a single action taken by a prospect.
Instead, it keeps tabs on every engagement they make.
Attribution follows the customer journey from the first time they visit your website, to the point at which they purchase a product or service.
A proportionate amount of revenue is attributed to every marketing effort leading to those engagements, based on the marketing cause behind each prospect engagement.
Using attribution for tracking offline marketing
In an ideal world, you should use the same metrics to track every marketing effort you make.
When you do this, there’s no chance of under- or over-valuing any of your channels because they are biased by the application of your attribution.
When you hold your online and offline marketing efforts to different standards, you will never be able to effectively optimise your marketing budget.
How can you, when you don’t have a clear picture of which marketing is generating more revenue?
In addition to this, it’s important to create centralisation that will ensure fairness and channel agnostic attribution.
If you’re using one form of attribution for one channel, and a different form on another channel, you may find the data doesn’t add up.
This is because your channel-specific analytics aren’t communicating with each other, which can easily result in counting opportunities, leads, and revenue more than once.
Different revenue attribution models
While it’s important to be consistent in the manner of revenue attribution you use across your channels, there are several different forms, ranging from simple, single-factor to more advanced models.
The latter may incorporate highly complex logic and algorithms.
Yet there are positives and negatives for each method, which is one reason attribution is currently one of the most highly debated marketing topics.
Single source attribution
A single source model of attribution uses one touchpoint (usually either first or last) to assign credit.
When first-click attribution is used, all credit for revenue is assigned to the point of engagement from a lead.
For example, if they clicked through social advertising on Facebook, that would count as the first point of engagement, and revenue would be attributed to that point.
This is very easy to implement by simply tagging a lead source and assigning attribution to its final conversion, first touch methods do not account for client interactions beyond the initial point of engagement.
This can affect your perception of how effective other channels are in the conversion process, following that first point of contact.
On the other hand, last-click attribution does the opposite, attributing credit to the final point of engagement before revenue is generated.
In practice, that will likely be a final sales call or pitch.
Last-click is the most commonly used attribution model, but it does fail to account for prior engagements, such as social media views or website visits and consequently, misses core insights into your other marketing channels.
So, it helps to have insight into both first and last-click revenue attribution to get the bigger picture of your marketing efforts.
As the name suggests, multi-touch attribution (or MTA) models assign credit to every channel that contributes to the final conversion.
This ensures the whole of the client journey is accounted for and gives attribution to every touchpoint.
While it’s a more impartial model than single-point attribution, the drawback of MTA is that it can’t assign credit to channels proportionately, and is usually highly complicated to implement.
There are also various off-shoots of multi-channel methods, including:
- Linear attribution – which assigns every touchpoint an equal amount of credit.
- Time decay attribution – which assigns more credit to more recent touchpoints, and is generally used for longer sales cycles, such as B2B.
- U-shaped attribution – which assigns credit to the first point of engagement, the creation of the lead, and everything in between. Credit is attributed by giving 40% to the first touch, 40% to the lead creation, and dividing the remaining 20% between the remaining touchpoints in between.
- W-shaped attribution – this is similar to the U-shaped model, but with the inclusion of an additional point of contact – the creation of the opportunity. All three of the main touchpoints receive 30% of the credit, while the remaining points share the last 10%.
- Full path attribution – offering an extension of W-shaped attribution by factoring in the final point of closure. While most of the credit is applied to the key milestones along the client journey, the touchpoints between are given a lower weight of credit. This model comes with the big benefit of accounting for the follow-up interactions carried out post-opportunity by your sales team and assigning them an equal weight of credit to early marketing activities.
- Custom attribution – which gives you the chance to assign credit according to your own custom model. This is arguably more sophisticated than other models, as it enables your team to determine their own weighting percentages, using the specific marketing channels, industry, and typical client behaviour relevant to your business.
Weighted multi-source attribution
Weighted multi-source models of attribution enable you to fully account for every interaction through the entire sales cycle and giving a higher weight of credit to touchpoints that did the bulk of the work.
These models are incredibly difficult to apply due to their complexity, however, they are worth it as they give you an accurate view of the client journey.
The importance of sales data to revenue attribution
B2B companies have long since separated out marketing and sales activities. with the only goal of marketing to generate more leads for the sales team to step in and transform those leads into customers.
The problem with this is that optimising your marketing for a higher volume of leads results in lower quality, which works against the efforts of your sales team.
It’s important for both teams to work together, using the same goals and metrics, with revenue as the primary objective in order to optimise your whole process.
That’s why we came up with the Closed-Loop Framework.
The Closed Loop Framework is an approach to marketing measurement that focuses on revenue and connects marketing with sales – the easy way.
Marketing and sales are connected so that closed revenue can be automatically matched to the marketing activity that generated.
Allowing sophisticated marketers to optimise and measure campaigns by revenue growth, and not just by how many goals they’ve seen in Google Analytics.
We have an eBook dedicated to our Closed Loop Framework which you can download here.
Or, if you consider yourself a visual learner (like myself), then you can watch our CLF video presented by the founder of the Closed Loop Framework, Ian Leadbetter.
The most important thing to know about revenue attribution is that, when you’re considering solutions, find the one that fits in best with your existing marketing stacks, such as your CRM and automation platform.
This is the key to unlocking the data you need to attribute revenue back to your most valuable marketing activities.
What’s the best revenue attribution model?
This is the big question all marketers are asking.
Generally speaking, how successful an attribution model is will depend largely on the business to which it’s applied.
In a survey produced by AdRoll, 72% of company respondents agree that a perfect attribution model is
impossible to achieve.
With a variety of great tools *cough, cough* and the ability to use trial and error, it’s possible to test and compare different models to find the one that will work best for your company.
Regardless of which touchpoint in the journey you assign the most credit to, consider that it is going to be continually supported and budgeted for, in order to maintain high performance.
This can cause upstream channels to suffer due to the (often inaccurate) perception that they aren’t effective.
Multi-channel methods of attribution enable you to see value over all your channels, which can ensure budgets are allocated more fairly.