The quest to accurately measure the effectiveness of advertising and marketing efforts has been a perpetual challenge. Among the various methodologies that have emerged, multi-touch attribution (MTA) is perhaps one of the most controversial. Some would call it a comprehensive approach to understanding the intricate journey customers take before making a purchase or conversion. Others would call it impossible. Or at best, reliable, inaccurate, and increasingly challenging thanks to privacy regulations.
But is multi-touch attribution truly dead?
At Stack Moxie, we believe that not only is multi-touch attribution alive and well, but it’s more crucial than ever in navigating the complexities of modern marketing.
The Evolution of Attribution
In the early days of digital marketing, measuring the success of advertising campaigns often boiled down to simplistic models like last-click attribution. These models provided some insight, but they fell short in capturing the full complexity of the customer journey. As consumer behavior became increasingly fragmented across multiple touchpoints and devices, it became clear that a more sophisticated approach was needed.
Multi-touch attribution was a paradigm shift in marketing analytics that aimed to address the shortcomings of traditional attribution models. MTA acknowledges that conversions are rarely the result of a single interaction but rather a culmination of various touchpoints encountered along the customer journey.
With MTA, marketers gained the ability to attribute value to each touchpoint a customer interacts with before making a purchase or conversion. Whether it’s a display ad, a social media post, an email newsletter, or a search engine query, every touchpoint is assigned a proportionate share of credit based on its influence in driving the desired outcome.
This holistic view of the customer journey allows marketers to better understand the effectiveness of their marketing efforts across channels and optimize their strategies accordingly. Instead of focusing solely on the last interaction before a conversion, MTA considers the entire path to purchase, providing valuable insights into the customer’s decision-making process.
As digital marketing continues to evolve, so too does the landscape of attribution. New technologies, privacy regulations, and consumer behaviors shape the way marketers approach attribution, but the fundamental principle remains the same: understanding the customer journey is essential for driving meaningful results.
Why Multi-Touch Attribution Matters
Whether we realize it or not, every data point we track influences the choices we make to shape our marketing strategies. The metrics you use to make decisions form an attribution model of sorts, even if it’s just one you keep track of in your head.
So why should that attribution model be multi-touch? Because in B2B, winning and retaining customers isn’t a straight line. It’s more like a maze, with multiple touchpoints and teams involved along the way. Unlike simpler models that focus on just the first or last interaction, multi-touch attribution recognizes the complexity of our customers’ journeys.
Sure, single-touch attribution might seem easier to grasp, but you’re seeing only part of the picture. Multi-touch attribution, flawed as it may be, gives us a more complete view. It acknowledges the teamwork and diverse interactions that shape how customers engage with our brand, and allows teams to make decisions based on reality, not just a simplified version of it.
Challenges to Multi-Touch Attribution
Multi-touch attribution holds immense promise for providing a comprehensive view of the customer journey, but I acknowledge that it is not without its challenges. Navigating these obstacles is crucial for marketers seeking to leverage MTA effectively.
So, what are the downsides of MTA?
Data Fragmentation
One of the primary hurdles in implementing MTA is the fragmentation of data across various channels and platforms. With customers interacting with brands through multiple touchpoints, aggregating and harmonizing data from disparate sources can be a daunting task. Marketers often struggle to integrate data from online and offline channels, leading to incomplete or inaccurate attribution insights.
Privacy Regulations
The increasingly stringent privacy regulations, such as GDPR and CCPA, pose significant challenges to MTA. These regulations limit the collection and usage of personal data, making it harder for marketers to track user interactions across devices and platforms. As a result, MTA models may face limitations in tracking and attributing conversions accurately.
Platform Changes
Major platforms like Google, Apple, and Facebook regularly update their policies and algorithms, affecting the tracking and attribution capabilities of marketers. For instance, changes in browser cookie policies or restrictions on third-party tracking pixels can disrupt MTA models and render them less effective. Adapting to these platform changes requires constant vigilance and flexibility on the part of marketers.
Cross-Device Tracking
With consumers switching between devices throughout their purchase journey, accurately tracking and attributing conversions across devices presents a challenge for MTA. Marketers often struggle to maintain continuity in user identities across devices, leading to incomplete attribution insights and inaccuracies in campaign performance measurement.
Attribution Modeling Complexity
Designing and implementing an effective attribution model can be highly complex, requiring sophisticated algorithms and methodologies. Marketers must decide on the appropriate attribution model, allocate credit to individual touchpoints, and account for factors like customer intent and timing. Navigating this complexity requires a deep understanding of both marketing analytics and statistical modeling techniques.
Nevertheless, multi-touch attribution remains a valuable tool for marketers looking to understand the impact of their marketing efforts and optimize their strategies accordingly. These challenges are real, but they can be addressed using tools (like Stack Moxie) that help unlock a unified view into what a lead is doing up until they convert.
Debunking Myths About Attribution
Some Stack Moxie folks attended the PLGTM conference last week, and some of my favorite insights were from a presentation given by Sarah Krasnik Bedell, Director of Growth Marketing at Prefect. She gave some of her best practices for building an attribution model, and debunked some myths about MTA that stump a lot of marketers as they try to tackle this tough topic.
I thought you’d like them too, so here’s a summary:
Myth #1: Attribution is Dead
Contrary to popular belief, attribution is far from dead. While it’s true that traditional approaches like last-click attribution may have limitations, modern attribution models, such as multi-touch attribution, continue to evolve and provide valuable insights into the customer journey. Rather than pronouncing attribution as obsolete, marketers should recognize its importance in understanding the impact of various touchpoints on conversions.
Myth #2: Ad-Blockers Render Attribution Useless
While ad-blockers pose challenges to traditional tracking methods, they do not render attribution useless. In fact, the majority of user signups are still trackable through cookies, even in the presence of ad-blockers. By implementing strategies like server-side tracking and reverse proxying, marketers can mitigate the impact of ad-blockers and continue to gather valuable attribution data.
Myth #3: Anonymous Data is Sufficient for Attribution
While anonymous data can provide some insights, it is often insufficient for accurate attribution. Platforms like Google Analytics may not capture all relevant data points needed for attribution, highlighting the importance of proper identity resolution. By tying multiple online identities back to individual users, marketers can ensure more accurate attribution and gain deeper insights into customer behavior.
Myth #4: You Need Advanced Data Science Models for Attribution
Advanced data science models like marketing-mix modeling have their place, but they’re not always necessary for effective attribution. Simple attribution models like first-touch or last-touch attribution can still provide valuable insights into the customer journey, especially for businesses just starting with attribution. The key is to choose the right model based on your specific needs and objectives.
Myth #5: Attribution is Set-and-Forget
Attribution requires ongoing monitoring and optimization, rather than a set-and-forget approach. As new attribution sources emerge and consumer behavior evolves, attribution logic and tracking methods may need to be adjusted accordingly. By continually testing and refining attribution models, marketers can ensure that they are accurately capturing the impact of their marketing efforts.
Stack Moxie Can Help
With those myths busted, you can start to see that multi-touch attribution can still be a powerful way for marketers to understand the journey their customers take before a conversion, and how they can make it even better.
These days, there are tools that can help make this easier. Stack Moxie is one of them. Testing and monitoring empowers marketers to overcome the challenges inherent in attributing conversions across multiple touchpoints and channels.
Specifically, these are some of the ways a tool like Stack Moxie helps:
- Unified View of Revenue Infrastructure: Stack Moxie provides marketers with a unified view of their revenue infrastructure, offering insights into every stage of the customer journey. By consolidating data from disparate sources and channels, we enable marketers to gain a comprehensive understanding of the factors influencing conversions and revenue generation.
- Identifying Lost Leads: One of the key functionalities of Stack Moxie is its ability to identify lost leads, a common challenge faced by marketers. Marketers can uncover missed opportunities and re-engage with potential customers, thereby maximizing revenue potential.
- Improving Reliability: We’re like a watchdog for marketers, alerting them to any issues or anomalies in their revenue infrastructure in real-time. By proactively monitoring the health and performance of key systems and integrations, this enables marketers to maintain reliability and minimize disruptions to their revenue-generating activities.
- Reducing Testing Costs: With Stack Moxie, marketers can automate quality assurance and monitoring processes, reducing the cost and effort associated with testing campaigns and workflows. By ensuring error-free executions and efficient campaign launches, this helps marketers optimize their testing budgets and drive greater ROI.
- Comprehensive Monitoring: From tracking uptime and health of systems to validating campaign flows and email cadences, monitoring equips marketers with the insights and capabilities they need to succeed in today’s competitive landscape.
Implementing Effective Attribution
During her PLGTM presentation, Sarah also gave some tips to implement solid attribution.
1. Event Tracking: Start by implementing robust event tracking across your digital properties. Event tracking tools allow you to capture valuable data such as page views, button clicks, and form submissions. Ensure that event tracking is configured for both frontend and backend events, and consider automating the tracking of essential metrics like page views and UTM parameters.
2. Identity Resolution: Establish a clear strategy for identity resolution to tie multiple online identities back to individual users. This involves assigning unique user IDs, coordinating identity across domains, and integrating identify calls seamlessly into your tracking infrastructure. Don’t hesitate to add identity calls liberally to ensure accurate attribution and a unified view of customer interactions.
3. Attribution Logic: Choose an attribution model that aligns with your business objectives and customer journey. Whether it’s first-touch, last-touch, or a more sophisticated multi-touch model, ensure that your attribution logic accurately reflects the impact of different marketing touchpoints on conversions. Be intentional in assigning credit to each touchpoint and consider testing different attribution models to find the most effective approach for your business.
4. Reporting and Analysis: Establish clear metrics for measuring attribution success and regularly analyze attribution data to identify trends, patterns, and areas for improvement. Pair attribution data with contextual information to gain deeper insights into customer behavior and campaign performance. Use reporting tools to visualize attribution data and communicate findings effectively across your organization.
5. Testing and Optimization: Attribution is not a one-time endeavor but requires ongoing testing and optimization. Continuously evaluate the effectiveness of your attribution model, tracking methods, and data sources. Test different attribution models, adjust attribution logic as needed, and stay informed about changes in consumer behavior and marketing technology.
6. Partnering with Stack Moxie: Okay, Sarah didn’t actually say this during her presentation. But I still think it’s a great idea! Stack Moxie literally invented Revenue Observability, and our tool helps with everything from identifying lost leads, to improving reliability, to reducing the cost of testing.
Empower Your Strategy with Stack Moxie’s Attribution Solutions
Whether you’re looking to refine your attribution model or you thought attribution was dead up until five minutes ago and are just starting your attribution journey now, Stack Moxie has the tools and expertise to support your efforts. Sign up for a free account today and discover how Stack Moxie can empower your business to thrive in today’s competitive landscape.
