Understanding marketing attribution & different methods

In today’s fast-paced digital landscape, marketing has become an intricate web of strategies, channels, and campaigns. Understanding the effectiveness of each of your marketing tactics is critical; your brand’s growth will always be limited if you don’t have an understanding of which campaigns move the needle and by how much. That’s ultimately why marketing attribution matters.

At its core, attribution seeks to answer the question, “How much does this campaign or marketing channel contribute toward my goal?” However, attribution in marketing is far from simple; it encompasses a multitude of challenges, intricacies, and data-driven puzzles that marketers must navigate to unlock valuable insights.

What is marketing attribution?

Marketing attribution in the context of Ecommerce refers to the process of identifying and assigning value to the various marketing touchpoints that contribute to a customer’s journey from initial awareness to final conversion. It involves tracking and analyzing the interactions a customer has with different marketing channels and campaigns, such as email, social media, and search ads. The goal is to be able to quantify how much a channel or campaign drives the brand toward key progress indicators (KPIs) like revenue benchmarks.

Once you understand how a campaign or channel did or did not move your brand toward its goals, you can make informed decisions about your future marketing tactics. Attribution is crucial for Ecommerce companies because it provides actionable insights into the effectiveness of different marketing efforts, allowing the companies to allocate budgets and resources more efficiently. By understanding which channels and campaigns have the greatest impact on conversions, Ecommerce companies can optimize their marketing strategies, improve ROI, and enhance customer experiences throughout the sales funnel.

To be clear, attribution is never going to tell you exactly what to do next, but the insights you get from it are directional and can help your brand get on the right path.

Marketing attribution challenges

While we’d love to tell you that something so critical to your business is easy, the truth is that marketing attribution isn’t without challenges. It is easier to avoid them if you’re aware of what you might face, though. The biggest marketing attribution challenges brands face are:

• Data Fragmentation: Gathering and consolidating data from multiple sources—such as platform reporting tools, CRM systems like HubSpot, and analytics tools like Google Analytics—can be a daunting task. Disparate data sources and formats make it challenging to create a unified view of how a customer moves through your marketing and sales channels and attribute conversions accurately.
• Cross-Device and Cross-Channel Tracking: With customers using multiple devices and interacting with various marketing channels throughout their journey, accurately tracking and attributing conversions across different devices and channels becomes complex. Identifying the touchpoints that contribute to conversions and seamlessly connecting them across devices and channels is a significant challenge. Some cross-site tracking is enabled by third-party cookies, which brings up our next challenge…
• Ad-blockers and Privacy Regulations: Ad-blockers and privacy regulations limit the ability to track and collect data on user behavior, affecting the accuracy and completeness of attribution analysis. Stricter privacy regulations and users’ increased privacy concerns pose challenges to collecting granular data necessary for attribution for many technologies, but not all. Pixels and third-party cookies are especially affected.
• Attribution Model Selection: Choosing the right attribution model (we’ll get more into the different types of marketing attribution models below) that aligns with the business goals and accurately represents how a customer interacted with your marketing channels and campaigns. Each model has its limitations and biases, and finding the most suitable model for a specific business can be tricky.
• Time Lag and Attribution Window: Attribution often involves determining the timeframe within which a touchpoint’s influence on a conversion can be attributed. Determining the appropriate attribution window is challenging as customer journeys can be lengthy, involving multiple touch points over an extended period. Balancing the time lag between touchpoints and attributing credit accurately poses a challenge. Many platform reporting tools, like on Facebook’s ads platform, have a 7-day attribution window. But if you have a more expensive product, it can take much longer than that for your customers to convert.
• Attribution of Assists: Assigning credit to touchpoints that may not lead directly to a conversion but play a supporting role in the customer journey is also a challenge. Capturing and quantifying the value of assisting touchpoints accurately can be complex, yet important to understand the holistic impact of marketing efforts. We’ve built that into our dashboard, and we’ll tell you more about how that works below.
• Data Quality and Reliability: Inaccurate or incomplete data can significantly impact the reliability of attribution analysis. Data quality issues, such as data duplication, data discrepancies, or missing data, make it difficult to trust the attribution results and make informed decisions based on them. We’re sure you’re no stranger to wondering why the reported performance of your Facebook or Google ad doesn’t align with the sales figures you’re seeing in your Shopify account.

Addressing these challenges requires a combination of technological solutions, robust data collection and integration processes, careful analysis, and a deep understanding of your brand’s goals and customer behavior.

Benefits of marketing attribution

You’re already here, which means you already know that marketing attribution is important for your brand. Getting a better understanding of the impact your marketing activities have on your brand’s profitability may have some benefits you haven’t realized yet, including:

• Optimized Marketing Spend: One of the primary benefits of marketing attribution is the ability to optimize marketing spend. By understanding which marketing channels, campaigns, or touchpoints in your marketing mix are most effective in driving conversions, brands can allocate their budgets more efficiently. Attribution data helps identify underperforming channels, allowing marketers to reallocate resources towards high-performing ones. This optimization reduces wasted spend, maximizes the impact of marketing efforts, and improves overall marketing effectiveness.
• Increased ROI (Return on Investment): Marketing attribution enables companies to measure the true return on investment for each of a particular brand’s marketing activities. By attributing conversions to specific touchpoints, brands gain insights into the channels or marketing campaigns that deliver the highest ROI.
• Armed with this information, they can refine their marketing strategy, invest more in the most profitable channels, and eliminate or optimize low-performing activities. Ultimately, this data-driven decision-making results in increased ROI, ensuring that marketing efforts generate the desired business outcomes.
• Improved Personalization: Marketing attribution provides valuable insights into behavior and preferences at different stages of the customer journey. This data allows brands to personalize touchpoints with which the customer interacts to deliver relevant and targeted messaging. By understanding which touchpoints resonate most with their audience, brands can create more tailored and engaging experiences. Improved personalization enhances customer satisfaction, increases engagement, and boosts conversion rates, ultimately driving business and profitability growth.

Overall, marketing attribution enables smarter decision-making and drives more efficient resource allocation, ultimately leading to improved marketing performance and business success. If you use attribution findings to optimize campaigns, it also creates a better customer experience.

Marketing attribution tools and methods

Ecommerce marketing teams employ various tools and resources to tackle the challenges of marketing attribution effectively. Here are some commonly used ones:

1. Multi-Channel Analytics Platforms: These platforms, such as Google Analytics, Adobe Analytics, or Mixpanel, offer data tracking and analysis across multiple marketing channels. They provide insights into customer behavior and conversion paths, allowing teams to understand the impact of each channel.
2. UTM Parameters: UTM (Urchin Tracking Module) parameters are tags added to URLs to track the performance of specific campaigns or channels. By appending UTM parameters to the destination URLs of marketing assets like ads, emails, or social media posts, Ecommerce teams can capture page-level information in their analytics platforms.
3. Pixel-Based Tracking: Tracking pixels are snippets of code placed on websites to track user activity. Platforms like Facebook Pixel or LinkedIn Insight Tag help marketers measure and attribute conversions resulting from ad campaigns on social media platforms. Pixels aren’t social media specific, though, and can be added to ads across a variety of digital platforms.
   
   The biggest problem with pixels is that they’ll soon be obsolete (at the time this article was published). Restrictions that help protect user privacy already severely limit the ability of pixels to collect data, and it’s hard to find actionable insights when your information is incomplete.
4. CRM and Marketing Automation Systems: Customer Relationship Management (CRM) systems, such as Salesforce or HubSpot, and marketing automation platforms, like Marketo or Mailchimp, also track interactions and help with attribution marketing efforts. Ecommerce teams can use them to tie customer interactions, leads, and conversions to specific marketing touchpoints if the CRM has an integration for it (Pardot—which was renamed Account Engagement—works with the CRM portion of Salesforce to capture information about user email engagement, for example).
5. Attribution Modeling and Data Analysis: Ecommerce marketing teams can also employ sophisticated attribution models to assign value to different marketing touchpoints. These attribution models can be rule-based (e.g., first touch, last touch, or multi-touch attribution) or algorithmic (e.g., data-driven models like linear, time decay, or position-based). Data analysis techniques, such as regression analysis or machine learning algorithms, are used to analyze large datasets and derive meaningful insights from complex attribution scenarios.
   
   If marketing attribution models sound complicated, well, that’s because they are. Brands don’t always have the time or resources to handle this type of data analysis in-house or the budget to hire a team of data scientists to build custom attribution models.
6. Post-Purchase Surveys: Post-purchase surveys are feedback forms sent to customers after they have completed a purchase or that appear along with the purchase confirmation on some Ecommerce websites. They’re used to gather valuable insights about customer satisfaction, product performance, and overall shopping experience.

Post-purchase surveys aren’t without pitfalls, though. Since they rely on the customer to fill them out and do so honestly and accurately, the helpfulness of their findings can be limited. Customers may skip them altogether or (consciously or unconsciously) inaccurately report which channel led them to you. That can make it challenging to attribute the success of marketing efforts to specific touchpoints in the customer journey.

By leveraging these tools and resources, Ecommerce marketing teams can gain a holistic view of their marketing efforts, track customer journeys, and attribute conversions accurately, leading to more informed decision-making and improved marketing ROI.

If you’re looking for something as advanced as custom attribution models but don’t have the team or the budget to make it happen, that’s where a service like Prescient AI comes in. We built these algorithms to pull from our clients’ multiple data sources—like their Shopify, Facebook, Instagram, and TikTok—and figure out which campaign was statistically the most likely to have triggered a conversion. That means all your data is in one place, and you don’t have the overhead of the team or resources needed to create this kind of dashboard for yourself.

Marketing attribution models

Attribution modeling refers to the methods and rules used to assign credit or value to different marketing touchpoints along a customer’s journey. Essentially, each of these models assigns different attribution weight to steps along the path a customer takes from awareness to purchase. Here’s an overview of three common types of attribution models:

1. First-Click Attribution: In the first-click attribution model, also known as “first touch,” all credit for a conversion is given to the first marketing touchpoint that attracted the customer’s attention. This model emphasizes the role of awareness-building channels and provides insights into the sources that introduced customers to a brand or product.
2. Last-Click Attribution: Conversely, last-click attribution, also referred to as “last touch,” assigns all the credit for a conversion to the last marketing touchpoint with which a customer interacted before purchase. This model prioritizes the channels or marketing campaigns that directly influenced the final action and provides insights into conversion-driving touchpoints.
3. Multi-Touch Attribution: Recognizing that customer journeys are often complex and involve multiple touchpoints, multi-touch attribution models distribute credit across various marketing touchpoints. These models use different rules and algorithms to assign value based on each touchpoint’s contribution to the conversion. Some common multi-touch attribution model types include:

• Linear Attribution: In the linear attribution model, equal credit is assigned to each marketing touchpoint along the entire customer journey. It provides a balanced view of the contribution of all touchpoints, regardless of their position in the funnel.
• Time Decay Attribution: This model assigns higher credit to touchpoints closer to the conversion while progressively decreasing the value of touchpoints that occurred earlier in the customer journey. The built-in assumption of the time-decay attribution model is that touchpoints closer to the conversion are more influential.
• Position-Based Attribution: Also known as “U-shaped” or “W-shaped” attribution, a position-based attribution model assigns higher credit to the first and last touchpoints, with the remaining credit distributed evenly among the touchpoints in between. It recognizes the significance of both initial awareness-building and final decision-making touchpoints.

These are just a few examples of attribution models, and there are several other variations and custom models that organizations can use based on their specific needs and objectives. You can see what assumptions are built into each of these models, and you may pick one to use based on how its assumptions align with how your brand thinks about the customer journey.

Prescient is no exception—we built our own marketing attribution model because we believe marketers needed something that better triangulated the source of a purchase within a long and potentially complex customer journey. Our marketing attribution software uses a marketing attribution technique that’s based on statistics. (You can read more about our media mix model or MMM here.)

All of your attribution data is pulled into our platform during onboarding; whatever you use, we can use. So if you’re using Google Analytics, pixels, and platform reporting tools through Meta and TikTok, we pull attribution data from all of them and our custom attribution model figures out which campaign was statistically the most likely to have triggered a conversion.

We also include reports on “halo effects,” because touchpoints along your marketing funnel don’t exist in a vacuum. Just as a football player could pass to another to make a touchdown, your Facebook ad could lead to more organic search or direct traffic. We wanted marketers to be able to see those interactions and measure the attribution of assists.

Choosing the right marketing attribution software for your brand

Since different marketing attribution models prioritize different points of the funnel, it may take some time to decide which service is right for you.

• Business Goals and Objectives: Whichever attribution model software you choose should align with your brand’s specific business goals and objectives. A big part of this, which we’ll expand on a bit below, is figuring out if you absolutely need person- or order-level metrics from your attribution software or whether you’re able to use anonymized attribution data. This is critical to choosing the right product for you.
• Data Integration and Compatibility: Whether you go with single-source attribution models or multi-touch attribution, the software you choose needs to be able to integrate with your brand’s existing data sources, such as analytics platforms, CRM systems, advertising platforms, and other relevant data repositories. Compatibility with these systems ensures seamless data collection, consolidation, and analysis.
• Data Accuracy and Reliability: Accurate data is crucial for reliable attribution analysis. The software should have robust data collection mechanisms, quality control measures, and data validation processes to ensure the accuracy and reliability of the attribution data. It should also provide transparency into data sources, methodologies, and any potential limitations or biases in the attribution model.
  
  Alternatively, you can consider an adjust service like Elevar or SurceMedium that provides data enrichment techniques for attribution and modeling to get your data in order.
• Reporting and Visualization Capabilities: Effective visualization and reporting features are essential to interpret and communicate attribution insights effectively. When choosing a service, look for clear and intuitive visualizations, customizable reports, and dashboards that allow marketers and stakeholders to understand and analyze attribution results easily. The ability to drill down into specific touchpoints, channels, or campaigns for deeper insights is also valuable.
• Scalability and Performance: Any software using an attribution model should be able to scale with your business—after all, the whole point is to empower you to grow. That means, despite an influx of more data (whether that’s a wider marketing mix or more digital campaigns) the marketing attribution model and its dashboard should still process data and provide insights quickly.
• Support and Training: Adequate customer support and training resources are essential for successful implementation and utilization of the software. Although an attribution tool should, ideally, be easy to get up and running, you should still be given support and ongoing assistance where needed.

All the SaaS solutions out there for attribution models work differently, but we’ve worked hard to make sure our onboarding is quick and simple: it takes just 10 minutes to connect all of your data sources and our model gives you insights in just 36 hours. Our attribution model uses all of these data sources to triangulate what’s moving the needle for your brand’s profitability, and you can dig deeper into the halo effects of your digital marketing campaigns. (This blog is about attribution, but our dashboard also allows you to simulate different ad spends to understand potential outcomes of future campaigns.)

Person- or order-level attribution vs anonymized attribution

We can—and eventually will—write a separate article about this topic because it’s critical for choosing the right software for your business. But, at a high level, making this decision involves figuring out whether your brand values seamless, uninterrupted reporting or more granular reporting more.

Person- or order-based attribution in marketing refers to tracking and attributing the success of marketing efforts to specific individuals or orders. This approach involves tying marketing touchpoints to individual customer accounts or specific transactions, allowing for a more personalized and targeted analysis of marketing performance. This is what provides more granular attribution data—but it’s also far more likely to get interrupted or rendered obsolete by future changes in data privacy regulations.

Anonymized attribution, on the other hand, focuses on aggregating data at a broader level without identifying specific individuals or orders. It aims to protect customer privacy by using anonymized data sets that do not contain personally identifiable information (PII). This approach provides a more generalized view of marketing performance but ensures compliance with data privacy regulations. This is the type of attribution we do here at Prescient AI because we want our clients to know how their ad campaigns are working without interruptions as cookies and pixels go away.

How Prescient view attribution

Marketing and attribution have always gone hand-in-hand—there’s no question you need to know as best as you can what’s working and what isn’t for your brand. But attribution is getting a lot more complicated now that user data privacy is more of a focus.

At this point, no one can offer The Truth of exactly what happened with your marketing campaigns—and we suggest you run fast and far from anyone telling you they can. The best we can do in this ever-more-complex digital marketing world is triangulate what happened and get as close to the truth as possible, and that’s why platforms like Prescient are valuable. You don’t need more than one tool when you have one that can pull data from your entire media mix, blend their findings together, and backtest it all. Our dashboard does that.

We also firmly believe that generic demos are worthless. If you’re curious about our dashboard, we’d love to show you around using your own historical data so you get a real feel for what working in it is like and the insights you could discover. Book a demo so we can show you around.

Marketing attribution FAQS

Why is marketing attribution important?

Marketing attribution helps teams more effectively use their budget by capturing information about how well each marketing channel of the marketing mix of a particular brand contributes to lead generation and sales. With this information, marketers can cut back on or remove channels that are less effective and focus on those moving the needle the most.

How do you use marketing attribution?

Once you have your marketing attribution model chosen—which is an important first step for brands—you can use the information it collects to optimize your marketing activities. Digging into the data from your attribution model can reveal valuable marketing channels (those that contribute most in your sales cycle) so you can plan your digital marketing efforts to be as effective for profitability as possible. The model gives insights into which aren’t working as well so you can stop spending money on marketing activities that don’t help.