Is Growth Marketing Really Dead?

There has been a bit of a buzz in the marketing world as more experts are advocating towards brand-led marketing and away from growth marketing tactics. In this unscripted 15 minute discussion, myself and Candice Ren discuss the reasons for this trend, the difficulties with attribution and how companies should assign their budget to the right marketing mix.

Overview

The marketing world is undergoing a significant transformation. In recent years, a trend has emerged where marketers are pivoting back to brand marketing and moving away from growth-centric tactics. Data shows that approximately 40% of the budget previously allocated to growth marketing has been redirected towards brand-building efforts. But why is this happening? The core of this shift lies in the challenges marketers face in accurately attributing growth marketing efforts, making it difficult for them to evaluate their performance based purely on data-driven outcomes. Consequently, there is a renewed interest in more generalised brand marketing approaches that were prevalent before the data revolution took hold.

Understanding Brand Marketing vs. Growth Marketing

To fully grasp this trend, it's essential to differentiate between brand marketing and growth marketing. Both approaches aim to drive business success, but they do so in fundamentally different ways:

Brand Marketing focuses on building and maintaining a company's identity, reputation, and relationship with its audience over the long term. It encompasses creating a strong brand image and emotional connection with consumers, thereby fostering customer loyalty and advocacy. The goal of brand marketing is not just to make an immediate sale but to cultivate a memorable and positive association that keeps the brand top-of-mind for consumers. Traditional methods such as TV ads, radio spots, sponsorships, print media, storytelling, and content marketing are common in brand marketing. These methods may not always show an immediate return on investment (ROI), but they help build a strong brand foundation that can drive sales over time.

Growth Marketing, on the other hand, is highly data-driven and focused on rapid, measurable growth and customer acquisition. It involves strategies like performance marketing, pay-per-click (PPC) campaigns, social media ads, influencer marketing, search engine optimisation (SEO), and email marketing. These tactics aim for direct and immediate results, emphasising metrics such as clicks, conversions, and customer acquisition costs. Growth marketing is iterative and constantly optimised based on data and feedback, allowing marketers to tweak campaigns in real-time for maximum impact. This agility enables companies to rapidly scale their customer base and revenue, but it can also lead to a heavy reliance on performance metrics.

Why the Shift Back to Brand Marketing?

Marketers are re-evaluating their focus on growth marketing due to several key challenges. The primary issue is attribution—the ability to directly link specific marketing activities to customer actions, sales, or other desired outcomes. While digital channels provide an unprecedented ability to track user behavior and measure engagement, achieving precise attribution remains elusive. The reasons are multifaceted:

1. Data Gaps and Fragmentation: Companies often have incomplete or fragmented data stacks that make it difficult to see the full picture. For example, a customer might interact with a brand through multiple touchpoints—social media, email, website, physical store—but tracking their journey across all these channels seamlessly is challenging. This fragmented data leads to incomplete or misleading insights.

2. The Limitations of Last-Click Attribution: Many growth marketing strategies rely on "last-click" attribution models, which credit the final interaction before a sale as the sole driver of that conversion. However, this model oversimplifies the customer journey and ignores the cumulative effect of multiple brand touchpoints that could have influenced the decision.

3. The Complexity of Multi-Touch Attribution: Advanced attribution models, like multi-touch attribution, aim to provide a more comprehensive view by assigning value to all interactions that lead up to a conversion. However, these models can be complex to implement and still rely heavily on assumptions and estimations.

4. Changing Privacy Regulations and Data Restrictions: The landscape of data privacy is shifting, with regulations like GDPR in Europe and CCPA in California restricting the ways companies can collect, store, and use customer data. Additionally, tech companies are making moves to limit third-party tracking, such as Apple's App Tracking Transparency feature. These changes make it even more difficult for marketers to attribute growth efforts accurately.

5. The Decline of Third-Party Cookies: With major web browsers phasing out third-party cookies, a vital tool for tracking user behavior across the internet is disappearing. This change forces marketers to rethink their approach and rely more on first-party data, which can be limiting.

Due to these attribution challenges, growth marketers find it increasingly difficult to prove the effectiveness of their strategies. They may face difficulty defending budget allocations when data-driven results appear ambiguous or unreliable.

The Case for Brand Marketing

As growth marketing faces scrutiny, brand marketing is enjoying a resurgence. Businesses are realising that a strong brand foundation is crucial for long-term success. Here are some reasons why companies are shifting back to brand marketing:

1. Building Trust and Credibility: A well-established brand creates a sense of trust and reliability among consumers. Brand marketing focuses on consistency in messaging, values, and customer experience, which fosters trust and can lead to greater customer loyalty.

2. Creating Emotional Connections: Unlike growth marketing, which often focuses on short-term wins, brand marketing emphasises emotional engagement with customers. By telling compelling stories and standing for something beyond just selling products, brands can create deeper emotional connections with their audience. This emotional resonance can lead to greater customer loyalty and advocacy.

3. Future-Proofing Against Algorithm Changes and Ad Fatigue: Digital marketing channels, especially social media, are susceptible to algorithm changes, increased ad costs, and ad fatigue. A strong brand can weather these changes better by maintaining consumer interest and engagement regardless of platform dynamics.

4. Maximising the Impact of Growth Marketing: Brand marketing can amplify the effectiveness of growth marketing. When customers recognise and trust a brand, they are more likely to respond positively to performance-driven tactics. A strong brand can serve as a foundation for more effective customer acquisition and retention efforts.

A Data-Centric Approach

For marketers grappling with the complexities of attribution, the root of the problem often lies within their data infrastructure. A poorly integrated or incomplete data stack can significantly hinder a marketer's ability to accurately measure and attribute their efforts. Without a robust and well-connected data stack, companies may lack a holistic view of their marketing activities, leading to fragmented insights and incorrect conclusions about performance.

Additionally, changes in data collection practices by major companies like Google have also contributed to the challenges in visibility. With the phasing out of third-party cookies and new privacy regulations, marketers have lost some of the granular insights they once relied upon. However, it's important to note that first-party data—information that a company collects directly from its customers—remains highly accurate and provides valuable visibility into customer behaviors and preferences. Leveraging first-party data is crucial for gaining a clearer picture of how marketing efforts are performing and where budget allocation should be adjusted.

To better understand why attribution is difficult, marketers need to dig deeper into the mechanics of how data is collected, processed, and reported across various platforms. One of the most common issues cited is data discrepancies between platforms. For instance, Google Analytics might report that a campaign generated 200 visitors to a website, while Meta’s (formerly Facebook) platform shows that only 100 of those visitors converted into customers. These discrepancies can be confusing and lead to mistrust in the data.

Why Data Discrepancies Occur

The core issue lies in the way different platforms collect and interpret data. Each platform tends to operate in a silo, tracking user interactions and conversions only within its own ecosystem. Google, Meta, LinkedIn, and other platforms all have their tracking mechanisms and attribution models, which can lead to discrepancies. Here are some reasons why this happens:

1. Different Attribution Models: Platforms often use different attribution models to credit conversions. Google Ads, for example, might use a "last-click" model where the final touchpoint receives all the credit for a conversion. In contrast, Meta might use a "data-driven" attribution model that distributes credit across multiple touchpoints. These differing approaches can result in vastly different metrics for the same user journey.

2. Overlapping Audiences: A single consumer might be exposed to ads from multiple platforms, such as Facebook, Instagram, and Google, as they move along the conversion path. Each platform may claim credit for the same conversion if it contributed to the customer's journey, leading to "double-counting." For example, if a user sees a Facebook ad, then searches for the product on Google and converts, both platforms may report the conversion as their own.

3. Varying Tracking Mechanisms: The way platforms track users can also lead to data discrepancies. Some platforms use cookies, while others might rely on pixels or device IDs. Additionally, users can have multiple devices (e.g., mobile, desktop, tablet), and if tracking isn’t synchronised properly across these devices, it may result in inaccurate visitor counts and conversion rates.

4. Data Collection Windows: The timeframe in which platforms track conversions can differ. Meta might track a conversion that happens up to 28 days after an ad click, while Google might use a different window. This variation in "conversion windows" can cause numbers to diverge, particularly for longer sales cycles.

5. Ad Blockers and Privacy Measures: Increasing use of ad blockers, browser privacy settings, and privacy features like Apple’s App Tracking Transparency (ATT) framework means some user interactions are not tracked consistently across platforms. This loss of data can further exacerbate attribution challenges and create gaps in understanding the full customer journey.

The Complexity of the Consumer Journey

Another major factor contributing to attribution challenges is the inherent complexity of modern consumer behavior. Today’s consumer journey is far from linear; it involves multiple touchpoints across various channels and devices. A potential customer may first hear about a brand through a podcast, see a display ad on Facebook, research the product through a Google search, and finally convert by clicking a retargeting ad on Instagram. This non-linear journey creates a scenario where no single platform has complete visibility into all the steps that led to a conversion.

To complicate matters further, some conversions occur offline. For example, a customer may see an ad online but choose to visit a physical store to complete the purchase. Without sophisticated tracking and data integration, this offline conversion may not be attributed to the initial online marketing effort, creating gaps in understanding marketing ROI.

Moving Towards a Unified Attribution Approach

To overcome these challenges, marketers need to adopt more holistic attribution models that consider the entire customer journey across multiple touchpoints and channels. This involves:

1. Implementing Multi-Touch Attribution (MTA): Multi-touch attribution models assign value to each touchpoint that contributed to a conversion, providing a more comprehensive view of how different channels work together to drive results. While MTA can be more complex to implement, it provides a clearer picture of the customer journey and helps marketers optimise their spend across the funnel.

2. Using Marketing Mix Modelling (MMM): MMM is a statistical analysis that measures the impact of various marketing tactics on sales and other key performance indicators, often using regression analysis. Unlike digital-only attribution models, MMM can incorporate both online and offline channels and account for factors such as seasonality and market trends.

3. Building a Connected Data Stack: A connected data stack ensures that all customer interactions, from first click to final conversion, are captured and analyzed in one unified system. This requires integrating data across platforms, such as CRM, social media, web analytics, and ad platforms, to create a single source of truth. Tools like Customer Data Platforms (CDPs) can help centralise and clean data, making it easier to attribute conversions accurately.

4. Investing in First-Party Data Collection: With third-party cookies on the decline, first-party data is becoming even more critical. Companies should focus on collecting and utilising data directly from their customers—through website interactions, email sign-ups, purchase history, and customer feedback. This approach not only helps build trust but also provides more reliable insights for attribution purposes.

5. Collaborating with Cross-Functional Teams: Effective attribution often requires collaboration between marketing, sales, IT, and data analytics teams. By working together, these teams can align on goals, share insights, and ensure that the data infrastructure is set up to capture the most accurate picture of marketing performance.

Conclusion

Attribution remains one of the most challenging aspects of modern marketing, especially as consumer journeys grow more complex and fragmented. While data discrepancies between platforms like Meta and Google may seem frustrating, understanding the underlying reasons for these discrepancies can help marketers take proactive steps to address them.

Thought Of The Week: Growth marketing is not dead and first-party data is the rocket fuel that will help to lower costs and finetune the algorithm going forward.