The Top 5 B2B Attribution Models of 2023
In 2023, B2B marketers have continued to rely on attribution models to better understand customer interactions and the effectiveness of their marketing efforts.
However, not all attribution models are created equal.
Each one of the many models offers unique insights and is suitable for different marketing objectives and customer journey complexities. The choice of the model depends on the specific goals, the channels used, and to some extent the nature of the sales cycle.
But what attribution model stands out above the others for the majority of B2B marketers?
Well, we’ve crunched the numbers and have found our customers’ top 5 models for this year.
In this post, we’re listing the top 5 attribution models, and also highlighting their key features and the reasons behind their popularity.
Multi-touch attribution
Before diving into the list, you might be interested in this brief overview of various attribution models and their setup:
Attribution models are only as good as the data
There’s an obvious caveat that needs to be set out at every and any mention of attribution.
Attribution models are only as good as the data that’s fed into them. So any model applied to a dataset that's not representative of the actual journey will risk misleading you.
So before selecting an attribution model, you need to first collect all the data on your customer journeys - every touch, of every user, of every account.
This account-based journey tracking is essential to B2B attribution, as the modelling takes into account touches by all the stakeholders involved (see the simple customer journey below 👇).
Once you’re collecting all these multi-touch, multi-stakeholder journeys, you need to link them to revenue. That's typically done by joining sales pipeline data from a CRM.
Only once this is in place, can you start considering attribution models.
You might be interested in this thought-provoking piece on What is attribution, really? →
5. Custom attribution model
Over the year 4.8% of users have opted for their own custom attribution model. Where they weigh touches based on their unique requirements.
Custom attribution models are tailored to the specific needs and unique customer journey of a B2B company. They allow marketers to assign custom weight to different touchpoints based on their importance in the sales cycle.
This flexibility helps businesses accurately reflect their marketing strategy and customer behaviour, leading to more precise and relevant insights.
Use Case: Best for businesses with unique customer journeys that don’t fit standard models, or with a desire to weigh a particular touchpoint or ‘position’ (where a touchpoint lies in the journey) more heavily.
Example: Companies can develop a custom model that aligns with their specific marketing strategies, customer behaviours, and business goals.
4. W-shaped attribution model
In fourth place, we have the W-shaped model, with 10.4% of Dreamdata users opting for this model.
The W-Shaped model assigns credit to three key touchpoints: the first touch, the middle touch, and the last touch before deal closure.
Each of these moments receives a substantial portion of the credit (usually around 30% each), with the remaining credit distributed among other interactions. You can get more details on the model here.
This model highlights the importance of both early and late-stage marketing efforts.
Use Case: Ideal for complex customer journeys where lead nurturing and mid-funnel interactions are important.
Example: A B2B marketing team that in addition to valuing the first and last touchpoints, needs to evaluate key mid-journey interactions (often a lead conversion event), to gain a more comprehensive view of the entire funnel.
3. First-touch attribution model
In third place with 22.9% of total model use is the first-touch model.
In a B2B setting, the First-Touch model assigns full credit to the very first interaction a prospect has with your brand. This model is useful for understanding which marketing efforts are most effective at generating initial awareness and capturing leads.
It's particularly valuable for evaluating top-of-the-funnel activities and demand-generation campaigns for successful outcomes, that is, the first-touch model is most powerful when evaluating the first-touch impact on late-stage outcomes, such as Sales Qualified Leads or Closed Won deals.
Use Case: Ideal for marketers, typically paid marketers, focused on demand generation or lead acquisition. It helps in identifying which channels or campaigns are most effective at initiating customer journeys.
Example: If a paid marketer runs multiple campaigns across different platforms, using first-touch attribution, allows them to identify which campaign a lead first interacted with, thereby assessing the performance of those campaigns in generating demand.
What model is best?
Are you wondering what attribution model to use? As we’re already seeing, who you are matters. Listen to what Steffen, Dreamdata CMO has to say about choosing your model 👇
2. Linear model
In second place was linear attribution, with just over a quarter of users choosing it to run their reports.
The Linear model is a straightforward approach where each touchpoint in the customer journey is given equal credit for the sale or conversion. This model is beneficial for B2B marketers who want to ensure a fair and balanced view of all marketing efforts across the entire sales cycle, from initial awareness to final decision.
Use Case: Best suited for B2B go-to-market teams looking for equal distribution of credit across all touchpoints.
Example: In a scenario where a customer interacted with multiple campaigns before converting, linear attribution assigns equal credit to each touchpoint, providing a balanced view of marketing effectiveness.
1. Data-driven attribution model 🥇
Finally, in first place (up from fourth place last year), our data-driven attribution model, launched last year, with 29.8% of users running reports with the model.
Data-driven models use advanced algorithms and machine learning to analyse all touchpoints and assign credit based on how much each interaction influenced the final decision.
In a B2B context, where sales cycles are often long and complex, this model provides a highly sophisticated and accurate understanding of which marketing tactics are most effective at driving conversions.
Use Case: Ideal for complex, multi-channel B2B marketing strategies. It evaluates the impact of each touchpoint in a customer's journey, helping to identify which interactions most effectively drive conversions.
Example: A B2B company uses SEO, paid ads, and webinars for marketing. Using data-driven attribution, they find that although clients first discover them via SEO, webinars are key in final conversions. This insight helps them focus on optimising their webinar strategy for better results.
What models have you been using this year? Not using attribution? Start today with Dreamdata!
