How To Use Multi-Channel Attribution Tools To Optimize Ecommerce Performance

Multi-channel attribution, unlike single-channel or platform-specific analytics, provides a holistic view of your customer’s journey, tracing the path across multiple touchpoints and platforms before a conversion occurs. This method acknowledges that in today’s digital ecosystem, consumers interact with a brand through social media ads, search engine marketing, email campaigns, direct visits, and more—before making a purchase decision.

Multiple platforms like Facebook and Google will often both claim credit for conversions, giving you skewed revenue reports that are much higher than the figures you’ll see in your ecommerce store. Multi-channel attribution, sometimes called “multi-touch attribution” or “omnichannel attribution,” gives brands the ability to “deduplicate” credit for conversions, offering a more accurate assessment of all of the channels that contribute to sales. 

By using multi-channel attribution to analyze a customer’s journey across platforms, businesses can see the impact of different marketing efforts. They can track a customer journey from the first advertisement a potential buyer sees to the final click before purchase, bypassing the “black box” of platform-specific analytics.

But multi-channel attribution demands a strategic approach to using the right tools, such as Triple Whale or Measured, to collect, analyze, and act upon multi-channel data. 

This article aims to demystify these tools, explain the wealth of opportunities that come with successfully implementing multi-channel attribution, and tactics to take full advantage of those opportunities.

Common Attribution Models

Different attribution models provide varied lenses through which businesses can analyze the effectiveness of their marketing channels and campaigns. By applying these models in a strategic blend, brands can make better marketing decisions based on comprehensive data.

Last-Click Attribution

An old-school approach, the Last-Click model assigns 100% of the conversion credit to the final touchpoint before a purchase. Its simplicity is its limitation, as it disregards the nuanced journey a customer may take before reaching that last click.

First-Click Attribution

The First-Click attributes all the conversion credit to the initial customer interaction. This model is useful for understanding which channels are most effective at introducing potential customers to your brand or product. However, like Last-Click, it oversimplifies the customer journey.

Linear Model

The Linear model distributes credit equally across all touchpoints in a customer’s journey. It’s particularly useful for brands looking to understand the overall effectiveness of their marketing mix without overemphasizing the role of any single channel.

Triple Attribution

Triple Whale, a robust data analytics platform designed specifically for ecommerce businesses, has created its own Triple Attribution model. Similar to platform-specific attribution, Triple Whale’s Triple Attribution model offers 100% credit to each channel. This model can be beneficial for intra-channel optimization but might not offer the most accurate picture for cross-channel marketing efforts.

Total Impact Model

Triple Whale has also introduced the Total Impact model, which leverages AI to blend first-party and zero-party data, providing a more sophisticated analysis of how various touch points influence conversions. This model attempts to quantify the actual impact of each channel.

While these models offer valuable insights, no single model provides a complete picture on its own. Effective use of multi-channel attribution tools involves not just selecting the right model but understanding how to interpret its data in the context of your specific marketing goals and challenges. 

Using Triple Whale and Measured for Multi-Channel Attribution

Tools like Triple Whale and Measured stand out for their unique approaches to multi-channel attribution, each serving a distinct purpose that, when used separately or in tandem, can optimize your brand’s ROI and sales.

Triple Whale’s Approach to Marketing Attribution

By integrating data from all marketing efforts, including paid, owned, and earned, Triple Whale offers a comprehensive dashboard that highlights the real Return on Ad Spend (ROAS).

If a customer interacts with an ad on Facebook but ultimately converts after clicking a Google ad, both platforms traditionally claim full credit. Triple Whale, however, accurately attributes the conversion, ensuring marketers can see the genuine impact of each channel and the customer journey through them. 

Or if analysis shows a significant portion of conversions are influenced by email marketing, even if the final conversion happened through a paid search click, it underscores the value of integrating email marketing more closely with paid search strategies.

By analyzing performance data from all channels in one place, marketers can immediately identify which campaigns are driving the highest ROAS and adjust their strategies accordingly. 

Incrementality and Attribution Approach Measured

Measured diverges from traditional multi-touch attribution by focusing on incrementality, offering a scientific approach to measuring the true incremental impact of marketing efforts. It harnesses first-party data from tens of thousands of companies, employing this vast repository to build algorithmic models that segment data into industry-specific cohorts. This methodology allows for sophisticated predictive analytics, offering businesses insights not just based on past performance but on future potential. 

A core feature of Measured is their approach is the incrementality coefficient, which quantifies the additional revenue each dollar invested in a specific channel or tactic is expected to generate. The application of this coefficient allows businesses to make nuanced decisions about where to invest their marketing budget. 

Measured complements omnichannel strategies by providing a layer of analysis that goes beyond past metrics. It offers a scientific, data-driven basis for understanding how each channel contributes to incremental revenue, allowing for more sophisticated budget allocation across channels. 

Synergistic Use of Triple Whale and Measured

When used together, Triple Whale provides the foundational understanding of cross-channel performance while Measured layers over this foundation, highlighting not just effective channels but those that are genuinely additive to the business’s bottom line.

For example, a business using Triple Whale alone may come to the conclusion that investing in Meta and Google leads to higher ROAS than TikTok or email campaigns. This may be good, accurate information that leads to positive returns.

However, a business using Measured in addition to Triple Whale may get the insight that Google shows a slightly higher incrementality coefficient than Meta, suggesting that, while these two platforms may both be suitable for increased spending, Google may yield higher overall revenue gains. 

This decision-making process, informed by both platforms’ insights, exemplifies the synergistic potential of integrating broad channel performance analytics with focused incrementality analysis.

Applying Multi-Channel Attribution

Getting started with multi-channel attribution involves strategic planning, integration, and continuous optimization. The ultimate goal is to leverage these sophisticated tools to maximize ROI and improve overall performance. However, navigating this landscape is far from simple; it demands industry expertise, a keen analytical mind, and a strategic approach to data utilization.

• Platform Integration: Integrate your marketing platforms with an attribution tool like Triple Whale. This integration should be seamless, pulling in data automatically once you’ve logged in and connected your platforms.
• Input Business Costs: Accurately inputting all business costs, including Cost of Goods Sold (COGS), shipping, payment processing fees, and marketing expenses, is crucial. This data informs the net margin and marketing efficiency ratio metrics, enabling real-time, profit-driven decision-making.
• UTM Tracking: Implementing Urchin Tracking Module (UTM) parameters across all marketing channels facilitates the understanding of click-through and view-through data, providing a holistic view of the customer journey. Without UTMs or with incomplete integration, the data becomes unreliable.

Once a multi-channel attribution system is in place, businesses can begin analyzing the data to identify which channels and campaigns are driving conversions and adjust the marketing mix and budget allocation accordingly:

• Start with a Problem or Question: Identify the primary goal. Is it to increase conversion rates, enhance brand awareness, or something else? The objective will dictate which attribution model to use and what data to focus on.
• Select the Right Attribution Model: Depending on the goal, you may choose from models like Last-Click, First-Click, or the Total Impact model recommended by Triple Whale for a nuanced understanding of channel influence.
• Analyze and Adjust: Use the insights gained from the selected attribution model to reallocate your marketing budget. For instance, if first-touch attribution reveals that social media platforms like TikTok or Meta are effective in introducing your brand to potential customers, it might be wise to allocate more budget there ahead of peak sales periods.

Integrating Multi-Channel Attribution with Other Marketing Efforts

Integrating insights from multi-channel attribution tools with broader marketing strategies, including email, SMS, and paid ads, is essential for brands looking to maximize their ROI and enhance overall performance. Here’s how businesses can strategically incorporate multi-channel attribution insights into their marketing efforts:

Strategic Integration Across Channels

• Holistic View: Begin by adopting a holistic perspective that considers all marketing efforts as part of a unified strategy. Multi-channel attribution provides a bird’s-eye view of how different channels interact and influence each other, helping to identify synergies and optimize the marketing mix.
• Customized Messaging: Use insights from multi-channel attribution to tailor messaging across channels. For instance, if attribution data reveals that customers who first engage with an email tend to complete their purchase after seeing a paid ad, consider customizing email content to prime recipients for the paid ad they’re likely to encounter next.
• Data-Driven Decisions: Let multi-channel attribution data guide your decisions on budget allocation and channel prioritization. Allocate more resources to channels that consistently contribute to conversions and explore new strategies for underperforming channels.

Leveraging Email and SMS Effectively

• Retention Tactics Evaluation: Compare the performance of email and SMS with your paid media tactics. This comparison can reveal how well your retention strategies are working and where there’s room for improvement. 
• Campaign Performance Analysis: Dive deep into the performance of individual email and SMS campaigns to understand their impact on Average Order Value (AOV) and how they overlap with other channels. This analysis can uncover valuable insights into customer behavior and preferences.
• Customer Journey Mapping: Utilize tools that map out the customer journey post-email or SMS interaction to gain insights into subsequent actions. Adjusting your strategy based on where customers go after interacting with your message can lead to more effective cross-channel campaigns.
• Incorporating the Halo Effect: Even if customers don’t directly engage with every message, frequent communications can still influence purchasing decisions by keeping your brand top of mind. 

Limitations and Challenges of Multi-Channel Attribution Models

The advent and evolution of multi-channel attribution models have offered businesses unprecedented insights, but those insights are hard-wrought and come with their own challenges, particularly in the wake of stricter privacy regulations and the ongoing shifts towards a cookieless world. You can do more with data than ever before, but getting it is harder than ever before as well. 

Privacy Regulations and Tracking Technologies

One of the most significant hurdles facing multi-channel attribution today is the stringent privacy laws and the gradual elimination of third-party cookies. Server-to-server (S2S) tracking is becoming more important. It allows data to be collected directly from servers instead of relying on browser cookies. But implementing S2S tracking requires a robust technical understanding and significant adjustments to existing marketing frameworks.

Technical Complexity and Data Integration

Integrating multiple platforms and ensuring the seamless flow of data between them presents another challenge. Tools like Triple Whale facilitate this process by pulling in data from various sources, but setting it up and maintaining these integrations can be complicated and time-consuming. 

Future of Multi-Channel Attribution

The transformative power of AI and machine learning is set to revolutionize multi-channel attribution. Analyzing and optimizing marketing strategies will become easier, more intuitive, and more accessible. With advancements like AI-driven predictive analytics, conversational interfaces for real-time insights, automated decision-making, and enhanced customer journey mapping, brands are on the brink of unlocking unprecedented strategic insights.

As we look ahead, the synergy between AI and multi-channel attribution stands to not only enhance ROI but to forge deeper, more meaningful connections between brands and their audiences, ensuring that brands at any revenue level can leverage these advancements to take their performance to new heights.

About the Author: Hailey Branham is a Director of Client Partnerships at adQuadrant with 10+ years of digital marketing and advertising experience. She graduated from the University of Texas in 2014 with a Bachelor of Science in Corporate Communication Studies before starting her career at a SaaS company, building and executing paid social media strategies for clients like Shoes.com, Target, Caterpillar, National Instruments, Aramark and more. From there, she worked as an Agency Partner Manager at Meta, where she partnered with best-in-class agencies across the country, adQuadrant being one of them. She joined the adQuadrant team in 2019 and has spent the last 5 years helping ambitious DTC brands unlock their potential and achieve profitable growth at scale. In 2021, Hailey was awarded the Amazing Women in eCommerce Award, which spotlights the impressive women pushing the eCommerce industry forward. A native Texan, she’s a lover of sunshine, hot sauce, and margaritas, and can always be found traveling, hiking, or spoiling her dogs.