Attribution modeling is a key approach to measuring marketing performance, especially in the complex, long sales cycles typical of B2B contexts. It provides a framework for assigning credit to various interactions throughout the customer journey, helping businesses identify which touchpoints contribute most to conversions. While no attribution model is perfect, each offers different levels of usefulness depending on the context. In B2B marketing, where customer interactions are numerous and extended over time, the right attribution model offers invaluable insights into which channels drive sign-ups and what content influences conversions, allowing businesses to better understand and optimize their marketing strategies.
TL;DR
Attribution modeling evaluates how different marketing touchpoints contribute to conversions. In B2B with long sales cycles, this can be complex, and while all models have limitations, they offer valuable insights. Single-touch models like First-Touch and Last-Touch give full credit to one interaction, while Multi-Touch models distribute credit across multiple touchpoints. Time-Decay models emphasize recent interactions and Influence Attribution credits, all touchpoints that impacted the deal. Choose a model based on your sales cycle, business needs, and desired insights.
What are attribution models?
Attribution models are frameworks that help analyze the customer journey and assign credit to the various touchpoints prior to the conversion. The method for assigning the credit is different for each attribution model depending on either the position of the touchpoint in the customer journey or a data-driven estimation of the significance of that touchpoint.
Additionally, businesses may need to configure these attribution models to suit their unique circumstances - such as considering an attribution window of, say, 60 days or 365 days depending on their sales cycle or performing the attribution analysis at a contact or opportunity, or account level depending on their sales motion.
With the help of these models, marketers are able to identify channels and tactics that drive more conversions and revenue, driving higher ROI for the business.
The following are some of the main reasons why attribution modeling is important.
- They provide insight into channels and campaigns that drive conversions and revenue
- They help plan and distribute spending to the right marketing channels
- Also, they help us identify the most influential channels and campaigns for each stage of the marketing and sales funnel.
There are different types of attribution model available for marketers, and we will dive into each in the coming sections.
Categories of Attribution Models
Before delving into how some of the most popular attribution models work, it’s worth understanding the mechanics of attribution modeling. A general categorization of attribution models would include two types. They are -
- Rule-based attribution models
- Data-driven attribution models.
1. Rule-based attribution models
These models use predetermined rules for assigning attribution credits to touchpoints. These pre-defined rules determine the weightage or credit for a touchpoint primarily based on its position in the customer journey. Hence, these models are also called Position based Attribution Models.
In addition to the position, you can also define custom logic to assign differential weights based on the seniority of the customer representative involved in the touchpoint (say Director and above gets higher weight) as well as the amount of effort expended by the buyer in that interaction (attending a webinar required higher effort from a buyer than clicking on a paid search ad).
2. Data-driven attribution models
These models assign attribution credits to touchpoints based on an algorithmic estimation of the significance of that touchpoint in converting the customer. Some of the popular algorithmic techniques are Markov Chain models and Shapely value-based models. Whilst data-driven attribution is seen as the north star of Multi-Touch Attribution, they are also more expensive to compute, require a large volume of conversions and touchpoints not to be biased, and are harder to debug.
Whilst each approach has its own pros and cons, a combination of these models may be leveraged to identify marketing leakage and improve ROI.
What are the different types of attribution models?
Single-Touch attribution models
Single-touch attribution models are among the most straightforward approaches used to evaluate marketing performance. These models focus on one touchpoint in the customer journey and assign all credit for the conversion to that one. While straightforward, these models might only sometimes provide a complete picture, especially in scenarios involving complex sales cycles.
Some of the most common types of single-touch attribution models include:
1. First-Touch Attribution
The first-touch attribution model assigns full credit to the initial interaction that brought the customer into the marketing funnel. This model is particularly useful for businesses with simple, transactional sales processes, such as SaaS sign-ups. By understanding which initial touchpoints are most effective at attracting prospects, marketers can better focus their efforts on top-of-the-funnel activities.
However, the limitation of first-touch attribution becomes apparent in longer sales cycles. For example, if a potential customer interacts with a brand through a blog post, attends a webinar, and finally makes a purchase, first-touch attribution would credit only the initial blog post. This approach overlooks the influence of subsequent interactions that may have been crucial in nurturing the prospect through the funnel.
2. Last-Touch Attribution
Conversely, the last-touch attribution model gives full credit to the final interaction before the conversion occurs. This model is beneficial when trying to identify what specifically triggered the conversion. For instance, if you want to determine whether a blog post, a LinkedIn ad, or a webinar was the last factor that led a prospect to book a meeting, last-touch attribution can provide clarity.
While last-touch attribution can offer valuable insights into what ultimately led to a conversion, it has drawbacks. This model can skew results by ignoring the role of earlier touchpoints. For example, in a long B2B sales cycle, if a prospect finally signs a contract after several months of interaction, attributing the entire credit to the final step—such as a contract-signing tool like DocuSign—may not accurately reflect the contributions of earlier interactions. This can lead to an incomplete understanding of the marketing efforts that influenced the final decision.
3. Last Non-Direct Touch Attribution:
This model assigns 100% attribution credit to the last non-direct touchpoint. A non-direct touchpoint is an interaction that is guided by a specific source the business sets up (like an ad, email campaign, newsletter, etc.).
When your website traffic doesn’t come from a known source, they are considered direct traffic (traffic that came from prospects directly entering the company URL into the browser, for example).
Let’s assume that a lead interacted with your brand 5 times, each touchpoint is as given below.
- Touchpoint 1 - Prospect clicks on a PPC ad
- Touchpoint 2 - Prospect arrives at your site’s landing page
- Touchpoint 3 - Prospect subscribes to your newsletter
- Touchpoint 4 - A week later, your prospect clicks on a newsletter campaign
- Touchpoint 5 - Prospect directly visits the website and initiates a free trial before purchasing a subscription
Touchpoints 1, 2, 3, 4, and 5 constitute all the prospect’s interactions with your brand that led to them purchasing your product. Keep in mind that, in reality, businesses deal with numerous prospects interacting with several touchpoints, making the process of mapping the customer journey far more convoluted.
So if we consider the above-given example, this model would assign 100% sales credit to touchpoint 4 or the newsletter campaign clicked on, as that was the last non-direct source before the sale. This model assumes that every interaction is a consequence of the non-direct campaign, hence making it the most influential.
Is Single-Touch attribution an INEFFECTIVE model?
Many businesses and marketing aficionados are of the opinion that single-touch attribution is not an effective model on its own. It is often considered to be a one-dimensional approach that fails to faithfully represent a customer’s conversion journey down the funnel.
As we have discussed, while single-touch models may have their own relevant use cases (like for products with shorter sales cycles), it may not be as effective in identifying the most influential touch-point in a B2B customer journey.
If big data in marketing has proved anything, it's that customer journeys can be non-linear, sophisticated paths spanning several channels and mediums. Assigning 100% of the credit to a single touchpoint will rarely be sufficient.
Multi-Touch Attribution Models
To address the limitations of single-touch models, multi-touch attribution models distribute credit across multiple touchpoints in the customer journey. These models offer a more nuanced view of how various interactions contribute to conversions, making them particularly useful for complex sales processes.
Linear Attribution
The linear attribution model assigns equal credit to every touchpoint the customer interacts with along their journey. This approach highlights the importance of each interaction, providing a balanced view of how various touchpoints contribute to the final conversion. In a B2B context, where a customer may engage with a company through several channels before making a purchase, linear attribution helps ensure that no single interaction is undervalued.
However, linear attribution can also have its drawbacks. By giving equal weight to all touchpoints, this model may overvalue less significant interactions and fail to capture the varying levels of influence each touchpoint has on the conversion. For example, if a customer interacts with a blog post, attends a webinar, and then downloads a white paper before making a purchase, linear attribution would attribute equal credit to each of these touchpoints, potentially overlooking the unique impact of each interaction.
U-Shaped Attribution
The U-shaped attribution model provides more weight to the first interaction and the touchpoint that leads to conversion while giving less credit to intermediate interactions. This model strikes a balance between acknowledging the importance of initial engagement and recognizing the significance of conversion-driving touchpoints. For B2B businesses with longer sales cycles, the U-shaped model can offer valuable insights into which early touchpoints attract prospects and which final touchpoints are crucial in closing the deal.
The U-shaped model is particularly useful when you want to understand the relative importance of initial and final touchpoints. However, it may not fully account for the influence of touchpoints in between, which can also play a crucial role in nurturing the prospect through the sales funnel.
W-Shaped Attribution
The W-shaped attribution model adds more granularity by assigning credit to the first touch, the lead conversion touch, and the final deal-closure touchpoints. This model is designed to provide a comprehensive view of the customer journey, capturing the influence of key stages along the way. In a B2B setting, where a prospect's journey may include various touchpoints such as content downloads, webinars, and sales meetings, the W-shaped model ensures that significant interactions at each stage receive appropriate credit.
While the W-shaped model offers a detailed view of the customer journey, it can also be complex to implement and interpret. The model’s emphasis on multiple key touchpoints may lead to a more detailed understanding of the customer journey but may require more sophisticated tracking and analysis.
Time-Decay Attribution Model
The time-decay attribution model assigns more credit to touchpoints closer to the conversion event, assuming that later-stage interactions significantly impact the final decision. This model recognizes that earlier interactions are essential but less influential than those closer to the conversion point.
The time-decay model can help identify which touchpoints are most influential in the final stages of the customer journey. For instance, if a lead interacts with various marketing channels over several months, the time-decay model would attribute more credit to the interactions that happen closer to the conversion date while still acknowledging the role of earlier touchpoints.
However, it may undervalue early interactions that played a crucial role in initial engagement. By focusing more on recent touchpoints, this model may not fully capture the cumulative impact of the entire customer journey.
4. Linear Attribution
A linear attribution model assigns attribution credits evenly among all touchpoints. While this model is far more illustrative than any of our single-touch attribution options, it's a relatively simplistic approach when compared to its nonlinear variants.
Let’s assume that the total number of touchpoints in our PMS example is four: An advert, a blog, a review, and a retargeting campaign. Linear attribution would reward 25% of attribution credits to each of these touchpoints.
Of course, in reality, the number of touchpoints a B2B customer goes through is significantly higher — so the weights for each one are likely to be far smaller.
5. U-Shaped Attribution
The U-shaped model assigns attribution credits to all touchpoints — but assigns higher credits specifically to the first and last touchpoints. This would imply that your customer’s first and last interactions prior to the conversion milestone are the two most valuable touch-points in their journey.
Consider the same four touch points as with the previous example (Ad, Blog, Review, and Retargeting campaign). This time, maybe 40% of the credits will be assigned to the first and last touch points each. The two touchpoints in-between will receive only 10% each as they are deemed less influential to the conversion decision.
The model laid out in a bar graph takes the shape of the letter ‘U’, hence the name.
6. Time Decay Attribution
Time decay attribution assigns attribution credits in an ascending cascade.
What this means is that each touchpoint is given progressively higher credit, with the first touchpoint having the least credit and the last touchpoint having the most. This is an effective tool in mapping out a customer’s conversion journey.
The model works on the assumption that touchpoints closer to the conversion were far more influential than touchpoints further away from the conversion. Again, using our handy four touchpoint PMS example, a time decay model would assign attribution credits in this manner: 5% for the advert, 15% for the blog, 20% for the reviews page, and 60% for the retargeting campaign.
7. W-shaped attribution
This type of attribution model is similar to the U-shaped model we discussed earlier.
The first and the last touchpoints are also given importance in this model, just as in the U-shaped model. But during the middle of the sales funnel, if you generate quality leads, then that touchpoint is also considered influential. And therefore is given equal importance as that of the first and last touchpoint.
So, if there are 5 first touchpoints in total, the first, middle, and last touchpoints will be given 30% each and the rest only 5%.
To give you a clear-cut idea, take five touchpoints. For example, an advert, a blog, a case study, reviews, and finally, retargeting campaign.
A prospect got in touch with your business through an advertisement, prompted to read your blogs, where they decide to subscribe to your business’s newsletter. Thereby generating a lead towards the middle of the process. The lead then continued to follow up on their research by constantly staying in touch with the business through newsletters. And finally, the lead converts by signing up for a free trial. Following is an example of a graphical representation of the W-shaped attribution model for the given example.
Influence Attribution
Influence attribution, or custom attribution, is a flexible approach that assigns credit to all touchpoints that have influenced the deal. This model allows marketers to analyze the impact of different channels and interactions on the final conversion, providing a comprehensive view of how various touchpoints contribute to the customer journey.
While influence attribution offers valuable insights into channel impact and the relative effectiveness of different marketing efforts, it carries the risk of double-counting revenue. By assigning credit to all touchpoints involved in the conversion process, this model may attribute more value to each touchpoint than is warranted, potentially leading to inflated performance metrics.
Choosing the Right Attribution Model
Selecting the right attribution model depends on several factors, including the complexity of your business, the length of your sales cycle, and the specific insights you want to gain. Here are some key considerations to keep in mind:
- Business Complexity and Sales Cycle Length
Single-touch models may provide sufficient insights for simple, transactional businesses. For more complex B2B sales processes, multi-touch and time-decay models offer a more detailed understanding of how various touchpoints contribute to conversions.
- Key Insights
Determine what questions you want to answer. Are you interested in understanding what drives initial sign-ups, or do you need to know which touchpoints are most effective in closing deals?
- Ease of Implementation
Choose a practical and feasible model for your marketing and sales teams to implement. While multi-touch models provide more detailed insights, they may require more sophisticated tracking and analysis.
- Goals and Metrics
Adapt your attribution model based on whether your goal is to track revenue, measure the effectiveness of touchpoints, or evaluate overall marketing performance.
Here’s a summary table to help you choose the right attribution model based on your needs:
Limitations of Attribution Models
Single-touch attribution models (like first-touch, last-touch, and list non-direct touch) are simple to implement but have several disadvantages. They oversimplify the customer journey by assigning credit to a single touchpoint, ignoring the contributions of other touchpoints. Similarly, these models also neglect the aggregate effect of multiple touchpoints over time. What results is inaccurate credit allocation, because the model disregards individual customer behavior and other factors.
On the other hand, multi-touch attribution models are definitely more complex because they work with complicated algorithms and technology. This often requires expert knowledge and pro- marketing knowledge of marketing software. The impressions from data can be misleading because of shortcomings like wrong assumptions and wrong weightage assigned to each marketing activity. To add on, while multi-touch attribution models are efficient for data- rich digital marketing campaigns, they are not equipped to measure external factors like word-of-mouth, seasonality or pricing.
Like single touch attribution models, multi-touch attribution models can also miss out on giving the full picture. Linear attribution models assume that all touchpoints have equal influence on customer behavior, which is not always the case. U-shaped, W-shaped and Time-Decay models run the risk of oversimplifying the customer journey since they assign more credit only to some touchpoints, while neglecting others. This could cost the model some valuable insights and paint an incomplete picture. The time-decay attribution model considers the recency of the customers close to the conversion event, but it can still overlook the significance of earlier touchpoints.
Takeaway
Needless to say, all attribution models are not appropriate for all use cases. Different attribution models aid different types of marketing campaigns and can reveal different insights into the customer journey.
In the end, a lot of the use cases for these types of attribution models are subjective. The decision to opt for a specific model can be based on several reasons spanning from the nature of your product to the extent of your brand equity. It may also vary based on the specific kind of insight you want to achieve.
More often than not, you will find yourself using more than just one model with several stipulations and custom values for each variant. Fortunately, the progressive ingenuity of AI and constant innovations around attribution modeling will render your experience less of a trial by fire and more of an intuitive, insightful practice.
Leveraging the right marketing analytics platform will be the first step in deciding the attribution model required for your company/business. As we said, it's best to rely on more than one model to improve your desired results. And for that, you will need an expert team, like Factors, that understands your requirements and guides you in leveraging the right techniques.
With Factors.ai, you can easily track the effectiveness of your campaigns and content, identify which channels are driving the most conversions, and optimize your marketing efforts for maximum results. The tool also offers a user-friendly interface and customizable dashboards, making it easy for you to access and interpret your data.
Interested? Sign up here for a FREE trial, or contact our team to get a Free consultation now. Here is the contact email for your reference - solutions@factors.ai
Bonus FAQs
1. How do I choose the right attribution model for my business?
In order to choose the right attribution model, you will need to know the target market, the target audiences, and so on. And once you have everything set, consider the following.
- Define your business goals. The attribution model you select must align with your business goals. Is it sign-ups? Leads? SQLs? Or just organic traffic.
- Once you have defined the goal, understand the types of attribution models and how each model allocates credits to the touchpoints.
- Evaluate the data you have to get an idea of the current touchpoints where your business is driving conversions [goals].
- Test out different models to see which is more effective.
- And finally, constantly review the results and update the models according to the business needs.
2. How do attribution models help find the gap in the customer journey?
As we discussed earlier in the blog, each attribution model provides insights into your customers' touchpoints with your business. Which itself gives the different paths each customer has taken to reach your service.
Thereby helping you understand the customer journey and find the touchpoints you missed during your initial marketing campaign.
3. How do attribution models help in improving the conversion rate?
Attribution models help improve the conversion rate by identifying which touchpoints in the customer journey are most effective in driving conversions.
They enable data-driven decisions helping businesses optimize their marketing budget and allocate resources efficiently to boost conversion rates.
