Why Full-Funnel Marketing Is Outdated

Paid advertising is full of terms like "top-to-bottom funnels" and other jargon marketers use to build campaigns and chase better ROI. At its core, it’s often about reworking old ideas to fit today’s fast-moving, digital-first advertising world. Whether it’s establishing authority in an industry or trying to fix underperforming campaigns on platforms like Meta Ads, TikTok Ads, or Google Ads, these strategies have become common practice. In this article, I want to break down the logic behind the full-funnel approach and highlight why it often misses the mark in modern online advertising.

The Full-Funnel Approach: An Idea That Doesn’t Work in Modern Advertising

The full-funnel approach, which divides audiences into awareness, consideration, and conversion stages, once served as a guiding framework for marketing campaigns. It aimed to target potential customers at every stage of their decision-making process, nurturing them along a linear path to purchase. This structure was helpful when marketing channels were limited and consumer behavior was more predictable.

However, modern advertising operates in a completely different environment. Today’s consumers don’t follow linear paths. They jump between platforms, interact with multiple touchpoints, and make decisions faster than ever before. The old funnel fails because it doesn’t align with how people actually behave online. It assumes that all users can be carefully guided through a structured journey, but the reality is far more chaotic and dynamic.

Algorithms: The Game-Changer in Advertising

Modern advertising platforms like Meta, TikTok, and Google rely on highly sophisticated algorithms to determine which ads to show to users. These algorithms don’t operate based on a linear funnel model. Instead, they use probabilistic modeling to assess the likelihood of a user taking a specific action, such as making a purchase or signing up for a service. Algorithms prioritize showing ads to users based on their probability of converting, regardless of where they might theoretically fall within a funnel. This means:

1. Ad Placement Is Dynamic: A user might see an ad at what marketers traditionally consider an “early stage” or “later stage”—but the algorithm doesn’t care about those distinctions. It cares about maximizing the chances of conversion.

2. Sequencing Is Irrelevant: The idea that users need to see a series of ads in a specific order is outdated. Algorithms may show the same ad multiple times to a high-intent user or prioritize certain creatives based on performance data, not a preconceived sequence.

3. Unified Decision-Making: Platforms analyze vast amounts of data in real-time to decide when and where to serve ads. This decision-making process integrates factors like user behavior, ad performance, and bidding dynamics into a single framework, eliminating the need for manual funnel-based strategies.

   
   

When marketers attempt to dictate sequences or enforce manual strategies, they often undermine the efficiency of these systems. The algorithm’s power lies in its ability to process data and make decisions far faster and more accurately than humans ever could. Overriding this process with outdated practices diminishes results and increases costs.

Why Objective-Based Targeting Matters

Advertising platforms are deeply informed by the data they collect, particularly through tracking pixels installed on websites. These pixels track user behavior across the internet, identifying who makes purchases, who engages with ads, and who merely clicks without meaningful intent. This data allows platforms to differentiate between high-quality buyers and low-intent users. When marketers use awareness or traffic objectives, they inadvertently target people less likely to purchase. These objectives attract users who might engage with or click on ads but are unlikely to become customers. In contrast, when conversion or sales objectives are used, marketers leverage the most important filter: targeting people who shop online and are primed to make purchases. Here’s why this matters:

1. Quality Over Quantity: Traffic and awareness objectives bring in low-quality users who might need additional retargeting to convert. However, these users are unlikely to be high-value customers, and retargeting them on other platforms often leads to wasted spend. Other platforms may interpret their activity as intent simply because they interacted with an ad or website, but these users were not high-quality leads to begin with.

2. Platform Intelligence: Platforms know who is most likely to purchase because they track this behavior through pixels and data sharing. Using sales objectives tells the algorithm to focus only on those high-value users.

3. Maintaining a Pure Funnel: By keeping the funnel focused on high-quality buyers—those with recognized purchasing behaviors—you ensure that your email marketing campaigns, retargeting efforts, and cross-platform strategies remain cost-effective and efficient. Low-intent users won’t be unnecessarily retargeted or added to campaigns where they increase costs without contributing to conversions.

   
   

Rethinking Ad Roles: Moving Beyond Assumptions

When creating advertising campaigns, many marketers think about ads in terms of predefined roles. For example, they may assume that an introductory brand ad is best suited for awareness and that catalog or retargeting ads belong at the end of the funnel to drive purchases. This mindset is heavily influenced by traditional marketing concepts, like how products are positioned in physical stores—branded items near the entrance and impulse buys near the checkout.

However, advertising platforms don’t follow these assumptions. Instead, they prioritize ad placement based on probabilities. For example, an ad you thought was perfect for retargeting might perform exceptionally well as an initial touchpoint in one region, while the same ad could function effectively as a conversion driver in another. The algorithms dynamically adjust, showing users the ads they’re most likely to engage with at any given moment, regardless of the marketer’s intended sequence.

This approach highlights the importance of letting the platform decide how to use your ads. Marketers may believe they’re optimizing by assigning specific roles to ads, but this can restrict the algorithm’s ability to perform. Trusting the platform’s decision-making enables better outcomes because it’s based on real-time data rather than outdated concepts.

AI-Driven Insights: Beyond Human Thinking

Just as computers revolutionized chess by beating human grandmasters with moves no one anticipated, advertising algorithms operate in ways that often defy traditional human logic. AI systems don’t rely on intuition or conventional wisdom; they rely on data modeling and probability. Platforms pull data from pixels and analyze user behavior in real-time to identify patterns humans might miss. For instance, an ad that seems like a perfect fit for the end of a funnel might instead be the ideal first touchpoint for a user already browsing similar products.

The predictive nature of these systems means they don’t adhere to rigid structures like warm or cold targeting. A campaign structured with broad targeting may end up being dynamically adjusted to reach users closer to conversion if the algorithm predicts better results. Platforms continuously train their AI models using massive datasets, ensuring that ad delivery adapts to maximize conversions. This dynamic decision-making isn’t just about placing ads but structuring entire campaigns on the fly. Platforms aim to generate the highest probability of results by optimizing ad delivery, even if it contradicts traditional marketing strategies. It’s a system designed to beat human thinking, reshaping how ads are delivered and to whom.

Core Audiences: The Modern Approach to Advertising

Instead of relying on rigid funnel structures, successful marketers are shifting their focus to core audiences—the groups most likely to engage with and purchase from your brand. By honing in on these high-intent users, you can simplify your strategy and maximize your budget’s efficiency. Jason Burlin, in his insights, often highlights how targeting the right people is more impactful than building elaborate campaigns for every stage of the funnel. Platforms thrive when given concise targeting data, and focusing on core audiences allows you to:

1. Simplify Campaigns: Modern advertising platforms favor simplicity. Core audience strategies reduce unnecessary segmentation, making campaigns easier to manage.

2. Maximize Budget Efficiency: By targeting those most likely to engage, you’ll reduce wasted spend on broad, low-intent audiences.

3. Let Algorithms Work: Platforms like Meta and TikTok are optimized to detect and prioritize opportunities for conversions. They’re designed to do this without marketers needing to manually create pathways or sequences.

   
   

The Path Forward: Focus on Core Audiences and Sales Objectives

Here’s why the traditional full-funnel approach no longer works:

1. Overcomplication: Building campaigns for every stage of the funnel creates unnecessary complexity. This can dilute creative efforts and make tracking performance more difficult.

2. Outdated Assumptions: Funnels rely on the assumption that consumer behavior is predictable and sequential. Modern consumers don’t follow a step-by-step process; they’re influenced by a mix of touchpoints and make decisions unpredictably.

3. Algorithmic Prioritization: Platforms are built to optimize ad delivery based on user intent and conversion probability, not on funnel stages. Trying to dictate which ad to show when undermines the algorithm’s ability to perform efficiently.

   
   

Conclusion

The full-funnel approach may have been a useful tool in its time, but it’s no longer effective in today’s fast-paced, fragmented advertising landscape. Modern advertising calls for a focus on core audiences, simplicity, and a deep understanding of how algorithms work. By trusting platforms to make data-driven decisions and aligning with sales-focused objectives, marketers can create campaigns that truly resonate with how consumers behave today. Abandoning outdated practices and leveraging platform intelligence will not only save costs but also drive meaningful results in the ever-evolving digital ecosystem.