In a world where 87% of shoppers now begin their product search online, according to Salesforce, it is essential that ecommerce marketers understand not just where their customers are coming from, but the multiple touchpoints they interact with before finally making a purchase. However, deciphering this intricate web of interactions can be a Herculean task without the right tools.
With a multitude of channels available — from social media to email campaigns, search engine optimization (SEO) to pay-per-click (PPC) advertising — attributing sales to a single source is not just overly simplistic, but it also undermines the complexity of modern customer journeys.
This is where multi-touch attribution models come into play, providing a nuanced perspective on the customer journey, and allowing marketers to fully understand and appreciate the impact of their work.
In this blog, we delve into the world of multi-touch attribution models, discussing their role, and the various types, benefits, and best practices in the context of ecommerce marketing.
What is Multi-Touch Attribution?
Multi-touch attribution is a marketing measurement model that provides insight into how various marketing channels contribute to the customer journey, ultimately leading to a sale. It recognizes that customers interact with multiple marketing channels before making a purchase and that each interaction has a varying degree of influence on the final decision.
For example, a customer might see a Facebook ad for a product, then later search for it on Google, click on a paid search ad, and finally make the purchase after receiving an email with a discount code. Each of these touchpoints played a role in the customer’s decision to make the purchase, and multi-touch attribution helps identify each touchpoint’s value.
Types of Multi-Touch Attribution Models
There are different types of multi-touch attribution models, each with its own strengths and weaknesses. These include:
First-touch attribution gives all of the sales credit to the customer’s first point of contact. It helps determine which channels are best at getting people to know about and be interested in a product or service for the first time.
The last touch attribution model attributes the entire sale to the last touchpoint a customer interacts with. It is useful for identifying which channels are most effective at driving the final conversion and purchase.
In the linear attribution approach, each touchpoint in the customer journey is given the same amount of value. It can help you figure out how each marketing platform affects the customer journey as a whole.
The time decay attribution model gives more value to touchpoints that happen closer to the sale and less value to touchpoints that happen further away from the sale. It helps you figure out how each interaction with a customer affects the sale as the customer gets closer to making one.
Position-based attribution model assigns higher value to the first and last touchpoints and less value to the in-between touchpoints. It is useful for understanding the impact of the first and last touchpoints on the customer journey.
Benefits of Using Multi-Touch Attribution Models
Unlocking the Mystery of the Customer Journey:
With multi-touch attribution, you can see each interaction your customers have with your brand before they hit the ‘buy now’ button. It’s like having a behind-the-scenes pass to your customer’s shopping experience. You get to see what gets their attention, what they like, what they don’t, and how they finally decide to purchase.
Maximizing Your Return on Investment (ROI):
You’ve got a marketing budget, right? And you want to make sure every dime counts. Well, multi-touch attribution is your personal financial advisor. It shows you exactly where to put your money. You’ll see which channels are bringing in the dough, helping you put your resources where they’ll have the most impact. It’s all about getting the most bang for your buck.
Data-Driven Decisions:
Say goodbye to guesswork and hunches. With multi-touch attribution, you’ve got cold, hard data backing up every decision. Whether you’re planning your next big campaign or optimizing an existing one, you’re making choices based on concrete facts, not assumptions. You’re stepping into the shoes of a data scientist, using evidence to guide your marketing strategy.
Enhanced Personalization:
Understanding your customers’ journeys means you can provide them with more personalized experiences. Noticed that customers who engage with your email campaigns are more likely to convert? You might want to step up your email marketing game and tailor it to their preferences. It’s all about making your customers feel special, and they’re more likely to reward you with their loyalty.
Future-Proofing Your Marketing:
The digital landscape is always shifting and evolving. But here’s the kicker – multi-touch attribution evolves with it. As new channels emerge, you can easily add them to your attribution model. You’re not just keeping up with the times; you’re staying ahead of the curve.
Setting Up Multi-Touch Attribution Models
This can be a complex process, but it begins with understanding your customers’ behavior and identifying the touchpoints in the customer journey. It can include everything from the initial ad that a customer sees to the final purchase. Once you have a clear understanding of these touchpoints, you can begin to assign values and weights to each one.
You may assign a higher value to touchpoints that have a greater impact on the customer’s decision to make a purchase, such as a product review or a personalized email. By assigning values to each touchpoint, you can gain a more comprehensive understanding of the customer journey and the role that each touchpoint plays.
Choosing the Right Model for Your Business
Each business is unique, and what works for one may not work for another. It’s important to choose a multi-touch attribution model that works best for your specific business needs and goals. There are several different models to choose from, including linear, time decay, and position-based models.
You may need to experiment with different models before finding the right fit for your business. It’s essential to consider factors such as the length of your sales cycle, the complexity of your products or services, and the channels that you use to reach your customers.
Analyzing and Optimizing Ecommerce Marketing Performance
Marketing is a crucial aspect of any ecommerce business. It’s what drives traffic to your website, generates leads, and ultimately results in sales. However, not all marketing efforts are created equal. To truly optimize your marketing performance, it’s important to evaluate the effectiveness of your marketing channels and tactics.
Evaluating Marketing Channel Effectiveness
Multi-touch attribution is a powerful tool that allows for a deeper understanding of marketing channel effectiveness. By tracking and analyzing each touchpoint in the customer journey, multi-touch attribution provides insight into the contribution of each marketing channel to the overall conversion process.
Let’s say a customer discovers your website through a Facebook ad, then later clicks on a Google search result before finally making a purchase. Without multi-touch attribution, you may only attribute the sale to the last touchpoint (in this case, the Google search result). However, with multi-touch attribution, you can see that the Facebook ad played a crucial role in the customer’s decision to make a purchase.
This information can be used to make informed decisions about which marketing channels to prioritize or adjust. By understanding the impact of each channel on the customer journey, you can allocate your budget and resources more effectively.
Identifying High-Performing Marketing Tactics
In addition to evaluating marketing channels, multi-touch attribution can also help identify high-performing marketing tactics. By understanding which touchpoints have the most influence on the customer journey, you can optimize and tailor your marketing efforts to better align with your customers’ behavior.
For instance, if you find that customers who receive a promotional email are more likely to make a purchase, you may want to invest more resources into email marketing campaigns. On the other hand, if you find that social media posts have little impact on the customer journey, you may want to adjust your social media strategy.
Adjusting Marketing Budgets Based on Attribution Insights
Attribution insights can also drive budget decisions. By understanding which touchpoints impact the customer journey, you can allocate your budget more effectively, focusing on the channels and tactics that provide the most return on investment.
So, if you find that paid search ads have a high conversion rate and provide a strong return on investment, you may want to allocate more of your budget toward that channel. On the other hand, if you find that display ads have a low conversion rate and provide little return on investment, you may want to reduce your spending on that channel.
Overall, multi-touch attribution is a powerful tool for analyzing and optimizing ecommerce marketing performance. By understanding the effectiveness of your marketing channels and tactics, you can make informed decisions that drive growth and increase revenue.
Challenges and Limitations of Multi-Touch Attribution Models
Multi-touch attribution models have become increasingly popular among ecommerce businesses as they provide a more comprehensive view of the customer journey and help businesses make data-driven marketing decisions. However, despite their benefits, there are some challenges and limitations that businesses need to be aware of when implementing multi-touch attribution models.
Data Accuracy and Tracking Issues
One of the biggest challenges of multi-touch attribution models is ensuring the accuracy and completeness of the data used. Incomplete tracking or data inaccuracies can skew results and undermine the value of the attribution model. For example, if a customer interacts with a touchpoint that is not tracked, the attribution model may not give credit to that touchpoint, leading to an incomplete view of the customer journey.
Another common issue is the lack of standardization in tracking methods across channels. Each channel may have its own tracking methods, which can make it difficult to compare and combine data across channels. This can result in inconsistencies in the data and make it harder to draw meaningful insights from the attribution model.
Model Bias and Overemphasis on Certain Channels
Multi-touch attribution models can produce different results depending on the model used. Each model may prioritize certain channels over others, leading to an overemphasis on those channels. For example, a model that gives more weight to the first touchpoint may overemphasize the importance of awareness-building channels like display advertising, while downplaying the importance of conversion-focused channels like search advertising.
It’s important to apply critical thinking and contextualize the results of the attribution model, rather than relying on them blindly. Businesses should consider factors like their specific goals, customer behavior, and market trends when interpreting the results of the model.
Dora Moldovan, Co-Founder & MD at Braidr shares her thoughts on position-based attribution:
(Continue reading: 5 Common Mistakes To Avoid In Marketing Attribution)
Conclusion: Evolving Customer Behavior and Market Trends
Multi-touch attribution is not a static process, and changes in customer behavior or market trends can impact the model’s reliability. For example, if a new channel emerges that is not currently tracked, it may be overlooked in the attribution model, leading to an incomplete view of the customer journey. Similarly, changes in customer behavior, such as a shift towards mobile devices, may require businesses to adjust their tracking methods to ensure accuracy.
It’s important for businesses to remain agile and adjust their multi-touch attribution model and tactics based on new insights and trends. This may require ongoing testing and experimentation to ensure that the model remains accurate and relevant.
