Multi-touch attribution is a marketing analytics method that assigns a share of conversion credit to every marketing interaction a customer has along their path to purchase.
It provides a comprehensive understanding of how different channels and campaigns collaboratively influence conversions.
Marketers know that every customer interaction — whether it’s a click, a page visit, or a customer service interaction —tells a story. Understanding these marketing touchpoints allows us to assign value to a customer’s journey and increase the likelihood of conversion. In today's dynamic marketing landscape, grasping the intricacies of how customers engage with our brands is essential for maximizing our return on investment (ROI).
Research shows that getting access to updated tools and technology and optimizing the marketing mix are among the top priorities for today’s marketers. These teams are also revamping their marketing metrics for a new era. The same survey shows that 41% of marketing organizations are using marketing attribution modeling as a measure of ROI.
In this article, we’ll go beyond the basics of multi-touch attribution and look at the benefits and the how-tos so that you can use it correctly to drive conversions and maximize your returns.
Multi-touch attribution is a data-driven marketing approach that assigns credit to multiple touchpoints along the customer journey, providing insights into the effectiveness of various marketing channels.
Single-touch attribution is a marketing model that assigns all credit for a conversion or sale to a single touchpoint in the customer journey, typically the first or last interaction. In contrast, multi-touch attribution considers and assigns credit to multiple touchpoints that contribute to the conversion, providing a more comprehensive understanding of the customer's path to purchase.
In a single-touch attribution model, if a customer makes a purchase after clicking on a Facebook ad, only Facebook would receive credit. However, in a multi-touch attribution model, if the customer initially discovered the product through a Google search, then engaged with a social media post, and finally clicked on a display ad before making the purchase, all three touchpoints would receive credit for their respective contributions.
Consider the benefits of using multi-touch attribution for your business:
Action all your data faster with unified profiles and analytics. Deploy smarter campaigns across the entire lifecycle with trusted AI. Personalise content and offers across every customer touchpoint.
Multi-touch attribution allows you to see the entire customer journey, from initial touchpoints to final conversions, providing a comprehensive understanding of the effectiveness of your marketing efforts.
By considering multiple touchpoints, multi-touch attribution ensures that credit is appropriately assigned to each channel or campaign that contributed to a conversion, enabling you to make informed decisions about resource allocation.
With insights into the performance of different touchpoints, you can optimize your marketing budget by investing more in channels that drive conversions and reducing spend on underperforming ones.
Multi-touch attribution helps you refine and optimize your marketing campaigns by identifying the most influential touchpoints, resulting in higher engagement and conversion rates. By attributing revenue and conversions to the specific touchpoints that influenced them, you can get a more accurate measurement of ROI.
Without the right strategy or tools, managing multi-touch attribution can be complex. These are some of the most common challenges we face as marketers.
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This involves gathering and integrating data from different sources, especially when a large volume of data and various tracking systems are involved. It will help to invest in data management tools and platforms that streamline collection, integration, and analysis. You’ll also benefit from implementing data governance practices to ensure data accuracy, consistency, and quality.
It can be tricky to choose an attribution model that aligns with your business goals and accurately reflects customer behavior. Different models have their own limitations and biases, making it important to find the one that suits your needs. To choose the right attribution model, you should conduct thorough research and experimentation. Consider using a combination of models or customizing models to better suit your unique needs. What you select of course hinges on your specific business goals and customer journey characteristics. Adding to that complexity is the need to ensure data privacy and compliance. Your business needs to be cautious about collecting and analyzing customer data while implementing robust data protection measures and staying compliant with data privacy regulations.
Tracking customer interactions across multiple devices is also a challenge, as customers often switch devices during their journey. This makes it difficult to attribute conversions accurately and understand the complete picture. Cross-device tracking solutions can help identify and connect customer interactions across different devices. Probabilistic or deterministic matching techniques can also be useful for attributing conversions accurately, even when customers switch devices.
There’s also the problem of lack of standardization. Since there’s no universally accepted standard, it’s possible to see inconsistencies in methodologies and metrics. This makes it difficult to compare results across different campaigns or organizations. You can get ahead of this problem a few ways: 1) Establish internal guidelines and standards for multi-touch attribution within your organization, 2) Participate in industry discussions and collaborate with peers to advocate for standardization efforts, and 3) Use benchmarking and industry research to gain insights into best practices and align your approach accordingly.
On top of the challenges you’ll need to address, there are some best practices to consider when thinking about reliable attribution.
Consider incorporating both online and offline touchpoints into your attribution model. This includes tracking offline interactions such as phone calls, in-store visits, or direct mail responses, which can provide a more comprehensive view of the customer journey.
Use advanced analytics techniques like machine learning and predictive modeling to gain deeper insights into customer behavior and attribution patterns. These techniques can help identify hidden patterns and correlations that may not be apparent through traditional analysis methods.
A/B testing or controlled experiments can help validate the effectiveness of different marketing channels or campaigns. By comparing the performance of different strategies in a controlled environment, you can gain more confidence in the accuracy of your attribution model.
Attribution is an ongoing process, and it's important to regularly monitor and refine your attribution model. Keep track of changes in customer behavior, market dynamics, and technology advancements to ensure your model remains relevant and effective.
Accurate data is indeed one of the biggest hurdles for many marketers when it comes to multi-touch attribution. Dealing with data discrepancies and measurement gaps can be a significant interference, as it can lead to incomplete or inconsistent insights. Marketers need to invest in robust data collection and integration processes, ensure data quality and consistency, and regularly validate and reconcile data sources to overcome this challenge and achieve more reliable attribution results.
Implementing multi-touch attribution means understanding the different model types and taking the right steps to ensure accurate and reliable results regardless of your choice. On top of that, you need to factor in data quality, consistent tracking mechanisms, and resource allocation.
Making the right selection for you is crucial. Here’s a quick breakdown of some of the different types of multi-touch attribution models:
In order to have an effective attribution model, you must use data-driven insights for analysis. This will allow you to continue to improve your models with each initiative.
Let’s look at a fictional example to illustrate how a business can implement this effectively. Meet XYZ Blog, a popular online platform that publishes articles on various topics. They want to understand the impact of their marketing efforts on user engagement and conversions. Initially, XYZ Blog used a simple first-touch attribution model, which assigned all credit to the first touchpoint a user encountered. However, they realized that this model didn't provide a comprehensive view of their marketing performance.
To improve their attribution model, XYZ Blog started collecting data on user interactions across different touchpoints, such as social media, email campaigns, and search engine referrals. They used analytics tools to track user behavior and measure the impact of each touchpoint on user engagement and conversions. By analyzing the data, XYZ Blog discovered that while social media played a significant role in driving initial awareness, email campaigns were more effective in nurturing leads and driving conversions. They also found that search engine referrals had a strong influence on user engagement and time spent on their website.
Knowing this, XYZ Blog decided to implement a multi-touch attribution model. They chose a time-decay attribution model, which assigned higher weights to touchpoints closer to the conversion event. This allowed them to give credit to multiple touchpoints along the customer journey. As they continued to analyze the attribution results, XYZ Blog noticed that certain types of articles performed better when promoted through specific channels. For example, technology-related articles had higher engagement rates when shared on social media platforms, while educational articles performed better when sent through email campaigns.
XYZ Blog optimized their marketing strategies with these data-driven insights. They allocated more resources to email campaigns and tailored their content promotion strategies based on the performance of different article categories and channels. Over time, XYZ Blog saw a significant improvement in user engagement and conversions.
Cover these basic implementation steps and you’ll be on your way as well:
Cover these basic implementation steps and you’ll be on your way as well:
Multi-touch attribution enables you to make data-driven decisions, allocate resources, and optimize your marketing strategies. This level of optimization leads to improved campaign performance, increased conversions, and ultimately, drives growth for your business.
With multi-touch attribution, marketing campaigns provide a comprehensive view of the customer journey and the impact of different touchpoints. But in order to do it correctly, you must identify high-performing channels and touchpoints.
By understanding what works, you can pour targeted efforts and budget into these channels. When you get it right, multi-touch attribution helps you measure ROI and prove the value of your marketing efforts.
So what are the channels commonly recognized as high-performing channels? It's important to note that the effectiveness of marketing channels can vary depending on the industry, target audience, and specific campaign goals. Answering those questions for yourself is goal number one.
Here are a few channels that are often considered high-performing:
Understanding the stories of customer interactions is no longer a luxury, it’s a necessity. By embracing the power of multitouch attribution, your business can unlock invaluable insights into your customers' journeys. When done properly, you can optimize your marketing efforts, and ultimately, elevate your bottom line.
Multitouch attribution is a marketing measurement model that assigns credit to multiple touchpoints a customer interacts with on their journey before making a conversion, providing a more holistic view of marketing effectiveness and allowing marketers to identify potential weak links in their journeys.
It helps marketers understand the true impact of each channel, optimize spending, and make data-driven decisions to improve overall marketing ROI by revealing influencing touchpoints.
Single-touch models credit only one touchpoint (e.g., first or last click), while multitouch models distribute credit across all significant interactions in the customer journey.
Common models include Linear, Time-decay, Position-based, Algorithmic,, and custom models, each distributing credit differently based on the stage and influence of the touchpoint.
It requires comprehensive customer journey data, including interactions across all marketing channels, website visits, ad impressions, email opens, and CRM data.
Benefits include more accurate ROI measurement, optimized budget allocation, improved customer journey understanding, and better cross-channel marketing strategy.
