Digital marketing attribution models help businesses determine which particular interaction with a customer has led to a desired result. That could be a web page visit, sign-up, purchase, or other.
Accurate attribution measurement is essential for marketing efficiency and the company’s financial health. Proper lead attribution helps with budgeting and eliminates money leakages.
As the number of marketing channels grows extensively, however, it becomes more challenging for marketers to attribute customer touchpoints precisely.
Is attribution that complicated? How can digital marketing attribution be managed easily yet effectively? This article will provide the answers.
A Quick Overview of Digital Marketing Attribution Models
To start with, let’s quickly examine the major digital marketing attribution models, how they work, and their pros and cons.
First Click Model: A simple approach to attribution in which a conversion is credited to the very first customer-brand interaction. The model is useful for getting a helicopter view on a campaign attribution: TOFU (top of funnel) dynamic, metrics overview, etc. This model isn’t suitable for complex campaign analysis.
Last Click Model: Another simple model that credits the conversion to the last interaction between a customer and a brand. The model is helpful with simple and short sales cycles, but it’s not a solid option for profound marketing campaign attribution.
Linear Attribution Model: This model credits the conversions equally within all the customer touchpoints. It provides a rather balanced view of the customer journey. In contrast, it has no use when you need to accurately estimate each touchpoint’s efficiency.
Time-Decay Attribution Model: This one considers touchpoints closer to the conversion more important than earlier ones. The model imitates real-world behavior and often provides a more insightful view of the customer journey. The basic presumption underlying the model is not always true, however, especially for products or services with a long sales cycle.
Position-Based Attribution Model: an approach prioritizes the first and the last touchpoints while reattributing the rest of the credit between intermediate interactions. The model gives a balanced view of the customer journey, yet it may not work for nonlinear customer journeys.
While these models are often used solely, you can also combine and tailor them to particular marketing needs. A custom approach that embodies specific elements of different digital marketing attribution models is usually the most accurate.
Challenges Marketers Face with Digital Marketing Attribution
As campaigns become more sophisticated and a vast amount of data is collected, risks emerge for marketers. Here are six challenges you should know about when dealing with attribution.
Data: Quality and Volumes
According to The CMO Survey, more than 75% of organizations from different industries already use marketing technologies, and this number is only going to increase.
![Digital Marketing Attribution](http://www.ppchero.com/wp-content/uploads/2024/07/1.-CMO-2024-Survey-screenshot.png)
This means a lot of data to organize and use. On the one hand, the more data you have, the more accurate attribution you get in the end. But this statement is if you know how to deal with data silos and are able to maintain proper data quality.
Even if you find the perfect blend of integrated digital marketing, marketing analysis tools, and attribution models, it will only perform well enough when your data is accurate, clean, and streamlined. So, data silos may create a distorted perception of customer behavior, just like the differences in metrics used across various data collection channels.
Another typical challenge that undermines the quality and accuracy of attribution in digital marketing is the lack of a standardized approach to data collection and processing.
Multiple Touchpoints
Properly crediting each touchpoint is essential to understanding every marketing activity’s genuine role and value.
The era of a straightforward sales cycle is over. Nowadays, users interact with dozens of marketing channels before the conversion happens.
The challenge consists of two parts. First, as a marketer, you should not miss a single touchpoint in your analysis. Secondly, you should assign credit to each touchpoint based on empirical evidence instead of gut feeling.
Cross-Device Tracking
The lack of data on cross-device user journeys is another typical challenge that misleads marketers. The positive trend is that more marketers treat mobile user experience seriously and use relevant optimization strategies.
The problem is that marketers may analyze a user’s mobile and desktop journeys alone, as if a single lead cannot interact with the brand via both channels.
From this, some touchpoints in attribution tracking end up being disregarded, while the rest are misinterpreted. The important details that may contain user behavior insights remain uncovered.
Digital Marketing Attribution Tools
The market of digital marketing attribution tools grows quickly, and it takes effort to find the right tool. Most popular solutions, like those by HockeyStack, Dreamdata, or Owox BI, are expensive and sophisticated.
This might make it difficult to leverage marketing attribution software. There’s the learning curve for one thing. time. The data collection and transformation setup can also be challenging. Creating custom attribution reports may require using more than one solution. All these and other factors require substantial resources from marketing teams.
Efforts and Benefits
If you’re dealing with marketing budgets in the low to medium thousands of dollars, the marketing team likely won’t get high value from detailed attribution or marketing attribution tools.
Yes, it can save them 10-15% of the budget, bt those savings wouldn’t compensate for the time, money, and efforts spent implementing data management and detailed attribution analysis. That’s how improper budgeting and resource planning can challenge your marketing efficiency.
The Arrival of the Privacy-First Era
The switch-off of third-party cookies will make it even harder for marketers to manage ads’ personalization and retargeting. The removal of cookies from Google Chrome, which is scheduled for 2025, will probably mark the logical culmination of the trend.
![](http://www.ppchero.com/wp-content/uploads/2024/07/2.-Third-party-cookie-phaseout-in-Google-Chrome.png)
Third-party cookie phaseout in Google Chrome. Source: Google
Many marketers are unprepared for the mass use of first-party cookies. Proficiency in GDPR and similar laws’ requirements is essential but presents a challenge to adapt to the new digital marketing realities.
3 Ways to Simplify Your Digital Marketing Attribution
Dealing with challenges and choosing the right approach among different attribution models is possible. I’d like to share the three steps of attribution simplification.
Begin with The Simplest Attribution
Comprehending one of the simplest attribution models opens the door to operating with the most suitable model. Consider your search for a perfect blend of different attribution models as an adventure. Begin with a simple model and add complexity step-by-step.
Building a compound attribution measurement model from the start can cost a lot of time and money. In the end, you would likely end up where you started.
According to MMA Global’s research, users of multi-touch attribution models (MTA) are more satisfied with their ability to track their marketing spending effectiveness compared to those using single-touch models.
However, MMA’s research also reveals another point: almost 30% of MTA users express a negative NPS for their approach. Why are those marketers unsatisfied? Most likely, the sophisticated multi-touch models were adopted from the very start without prior experience of working with simple models.
Again, begin with the simple option. You can start with the first- or last-click attribution model. Be open to experimenting and crafting the chosen approach. Once you master the simple model and realize its merits and limitations, you can move to the next step.
Adopt a Hybrid Approach
Each marketing distribution model has advantages and limitations. This is why attribution works best when a few models are combined. Leveraging the strengths of different attribution models is the key to success.
Imagine you offer two different services, with the first having a simpler sales cycle and the second service having a more complex one. In this case, you can use the first click attribution model to analyze the first service’s customer journey, the time-decay model for the second service.
Finding the correct hybrid model mix is possible through a few actions:
- Clearly identify your marketing objectives
- Revise your existing approach to attribution in marketing
- Analyze and review your customer journey
- Testing and experiment with mixed models
You can also gain valuable insights by communicating directly with customers. Do not disregard the CustDev activities and customer services, asking how they heard about the company, at which point the purchasing decision was made, and similar.
This approach might be especially helpful to B2B companies. As I mentioned above, multiple touchpoints are one of the challenges in attribution. It’s particularly relevant in the B2B segment, in which traditional attribution models fail to track conversions properly. This is why you need to engage with your users and reach out to them to better understand your current attribution.
Stay Flexible: Review Your Attribution Model
Once you build a diversified approach to marketing attribution tracking, remember to review and adjust the model regularly.
You can hardly ever obtain a 100% accurate attribution. You can, however, achieve a close-to-reality market view. There is always room for improvement influenced by product improvements, market dynamics, customer behavior changes, and other factors.
To be flexible you need to deal with the challenges of data quality and volumes, as well as digital marketing attribution tools foremost. At Coupler.io, we process this carefully. We measure PPC campaign performance and gather tons of data from other channels – SEO, CRM, emails, social media, etc. With automation capabilities, we organize and join data in live dashboards. We also identify changes in customer behavior and review our marketing strategy regularly.
Such approaches can give you a shortcut to growth. You’ll have all the needed data visualized and available in one place. This is how you can make informed marketing decisions.
Being open to experimentation and new tech is also essential to manage attribution sustainably. Marketing opinion leaders advise industry professionals to finally start believing in AI. AI-driven transformations of conventional attribution models are about to come. Make sure you won’t miss the trend.
Yes, You Can Simplify Your Attribution Measurement
Tracking attribution in digital marketing can become either a blessing or a curse. But we need to do that accurately. To make it your ally, start using a simple attribution model while testing and adding the elements of other models step-by-step.
Once your hybrid model is in place, ensure that you work with your data properly and review the process regularly. At this point, it is worth building your own approach to attribution reporting and analysis. This will save you time, minimize the risk of mistakes, and help you extract often implicit insights from large volumes of data.
Borys Vasylchuk is a Product Marketing Manager at Coupler.io.