Adtriba 2.0: Triangulation in Marketing Measurement Webinar - Recap

Triangulation is the cornerstone of modern marketing measurement—a strategic methodology that combines different measurement approaches to gain a holistic understanding of marketing effectiveness.

If you missed our “Adtriba 2.0: Triangulation in Marketing Measurement” webinar with our Measurement Partner, Vishnu Rajendra Prasad, this article will guide you through the main points we covered and detail the examples that help visualize this powerful methodology. 

Overview of Measurement Methods

In today's digital marketing space, there are several approaches to attributing conversions and assessing campaign effectiveness. Each method comes with its own set of strengths and limitations, highlighting the need for a comprehensive strategy that combines multiple approaches. 

Independent Multi-Touch Attribution (MTA) is a vital tool in marketing analysis, examining how each interaction impacts a customer's journey to a conversion or a purchase. Unlike other methods that only credit the first or last interaction, MTA considers all touchpoints, recognizing their combined influence on the customer's decision. This method provides a more comprehensive understanding of how different interactions contribute to conversions.

Marketing Mix Modeling (MMM) is a statistical analysis technique that is used to quantify the impact of various marketing tactics on sales. It not only evaluates current marketing effectiveness but also enables the forecasting of future tactics' effects based on model results. MMM assesses the effectiveness of advertising channels, promotions, and other marketing activities, aiding in budget allocation for optimal return on investment. By taking a long-term perspective, MMM considers factors such as seasonality, internal variables like inventory levels, and external factors like macroeconomic conditions, providing a comprehensive view of marketing performance.

Platform attribution entails the attribution data provided by platforms like Facebook, TikTok, Roku, or Google Ads. It offers insights into the conversions credited to these platforms, shedding light on their perceived influence on customer actions.

Last-click attribution, despite being discouraged, remains prevalent among many large companies. This approach assigns all credit for a conversion to the last touchpoint in the customer journey.

5. Incrementality Testing: 

Incrementality testing involves running experiments, such as holdout testing or A/B testing, to find the impact of your marketing efforts on sales. For example, let’s say you are running a marketing campaign for your app and want to test its incremental lift on installs. 

Group A acts as your control group; it’s the benchmark for installs. These users have not been exposed to your ads. Group B is made up of those who are exposed to your ads. Group A had 100 installs, while Group B had 120 installs. With this information, you can calculate two key insights.

Why Do We Need to Triangulate?

Understanding the shortcomings of individual measurement methods underscores the necessity for triangulation in marketing analysis. While each approach offers valuable insights, none provides a complete picture on its own. 

MTA offers granular insights into customer journeys, but it falls short in certain areas:

• Upper Funnel Tactics: MTA struggles to accurately measure tactics like paid social, display, and video, where clicks may not be the primary mode of interaction.
• Cross-Device and Cross-Browser Journeys: Tracking these journeys is challenging due to restrictions on third-party tracking, limiting the scope of MTA's analysis.
• Short- to Medium-Term Focus: MTA typically focuses on short- to medium-term correlations, providing insights that may not capture long-term trends or effects.
  
  

While MMM provides a broader perspective, it also has its limitations:

• Data Requirements: MMM needs approximately two years of data for robust analysis, making it resource-intensive and challenging to implement in some cases.
• Aggregated Data: Working with aggregated data at a daily and weekly level limits the granularity of insights, making it difficult to drill down to the campaign or ad group level.
• Statistical Significance: MMM's reliability diminishes when analyzing data at a granular level, as there may not be enough statistical significance to draw reliable conclusions.
  
  

Platform attribution offers visibility into platform-specific actions but also comes with its own set of challenges:

• Walled Gardens: Platforms like Meta, TikTok, and Google Ads leverage their first-party data for attribution, leading to a skewed perspective as they credit conversions solely to their touchpoints.
• Limited Data Scope: Platform attribution is blind to marketing touchpoints outside the platform, resulting in a siloed view that may overestimate the platform's contribution to conversions.

In summary, each methodology offers valuable insights but lacks a comprehensive view on its own. Triangulation allows marketers to overcome these limitations by synthesizing insights from multiple methodologies, providing a more accurate and holistic understanding of marketing effectiveness.

What is the Solution?

The solution lies in smart triangulation—a strategic approach that harnesses the strengths of various approaches to converge toward a unified insight. Here's how it works:

1. Leveraging the Strengths:

• MMM for Incremental Impact: Marketing Mix Modeling (MMM) excels in assessing the incremental impact of media at a channel tactic level.
• MTA for Low-Funnel Channels: Multi-Touch Attribution (MTA) is adept at evaluating the effectiveness of low-funnel, click-heavy channels.
• Platform Attribution for Upper Funnel Campaigns: Platform attribution provides valuable insights into the effectiveness of upper funnel campaigns aimed at awareness and prospecting.

 2. Identifying Incrementality Factor:

• The key to effective triangulation is identifying an incrementality factor using the MMM model. This factor serves as a correction mechanism to the correlational metrics of MTA and platform-level attribution. By translating these metrics into incremental ones, marketers gain actionable insights that drive strategic decision-making.

Illustration - Paid Social Use Case:

Let's consider a scenario involving paid social campaigns across different platforms. Here's a breakdown of the data:

• Meta Platform Attribution: Meta claims significant conversions, indicating strong performance.
• Last Click Attribution: Last-click data shows promising results for retargeting but reveals challenges in prospecting.
• MTA Numbers: MTA metrics appear robust for retargeting but lack for prospecting.
• Marketing Mix Modeling: MMM analysis over a long-term data range unveils interesting insights. While the incremental impact of retargeting is lower compared to MTA and last-click metrics, prospecting shows a significantly higher incremental impact, according to MMM. However, it still falls short of Meta's reporting.

How Do We Triangulate Based on This?

Triangulating marketing data involves leveraging the strengths of different measurement methodologies to derive comprehensive insights. In this scenario, one approach is to start by examining the credits assigned by the Marketing Mix Model (MMM). For instance, if MMM credits 800 conversions to retargeting and 1500 conversions to prospecting at the channel tactic level, we have a baseline for understanding incremental impact. However, as granularity decreases beyond this level, we turn to Multi-Touch Attribution (MTA) numbers, which offer insights at the campaign and ad group levels. 

Additionally, we consider platform attribution, such as Meta's attribution numbers, for specific channels like retargeting and prospecting. By distributing MMM credits based on MTA performance, we refine our understanding of the incremental impact at a granular level. For prospecting campaigns where MTA data may be limited, we rely on platform-attributed conversions to allocate MMM credits. This process ensures that we account for incrementality across various marketing channels and tactics. Through triangulation, we can achieve a more accurate assessment of campaign effectiveness and optimize resource allocation accordingly.

Marketers can also validate the results through incrementality testing, which involves conducting controlled experiments to measure the true impact of marketing activities on consumer behavior. When marketers analyze the results of incrementality tests alongside MMM and MTA data, marketers can gain deeper insights into the incremental impact of their marketing efforts and make more informed decisions regarding resource allocation and campaign optimization.

What marketing decisions would one make in this case?

It's essential to broaden the scope beyond Facebook and encompass various channel tactic combinations. This holistic approach involves comparing Adtriba 2.0 blended CPAs across channels like Google, TikTok, and other relevant platforms. By doing so, you gain a comprehensive view of campaign performance across diverse channels.

The decision-making process involves striking a balance between incremental impact and efficiency. While low CPAs on Meta may indicate the efficiency of retargeting campaigns, Adtriba 2.0 insights may reveal untapped potential in GPA retargeting and broad prospecting campaigns. Decisions hinge on optimizing both factors.

In summary, marketing decisions in the context of triangulation prioritize a data-driven approach that considers not only CPA data but also the incremental impact of campaigns. By comparing insights across channels and diving into campaign-level metrics, marketers can tailor their strategies to capitalize on growth opportunities and maximize ROI.

Utilizing the Adtriba UI for Triangulation

During our webinar, we showcased an example of how Adtriba’s new dashboard makes triangulation easier. Here’s a round-up of what can be taken away from the demonstration; 

Adtriba seamlessly integrates MMM numbers, MTA numbers, and other relevant metrics, offering a comprehensive view of campaign performance across various channels. This inclusive approach extends beyond paid social or search, encompassing all pertinent channels for a holistic analysis.

Adtriba emphasizes the importance of incremental impact in marketing measurement. By utilizing marketing mix models and triangulating data sources, users can validate the true impact of marketing efforts, moving beyond the limitations of last-click attribution and multitouch models.

Adtriba offers valuable insights for TV advertising, leveraging MTA peak detection and third-party TV data to refine the analysis. This approach enables marketers to understand the incremental impact of offline-online channels, providing actionable insights for optimizing TV ad campaigns.

In essence, the Adtriba 2.0 UI serves as a powerful tool for marketers seeking to implement triangulation strategies in their measurement efforts. By integrating diverse data sources, conducting granular analyses, and validating incremental impact, users can make data-driven decisions to maximize the effectiveness of their marketing campaigns.

The Adtriba Advantage

The Adtriba solution offers several distinct advantages that empower marketers to optimize their marketing strategies effectively. Here's how Adtriba sets itself apart, in terms of triangulation:

One of the primary advantages of Adtriba is its real-time nature. The platform runs its marketing mix model daily, ensuring that users have access to up-to-date insights. By leveraging the last two to three years' worth of data, Adtriba provides a comprehensive view of marketing performance, enabling marketers to make informed decisions based on the latest information.

Adtriba seamlessly integrates platform conversions and last-click conversions through partnerships with data providers like Funnel or via API calls. This comprehensive approach allows marketers to analyze data from various sources within a single platform, facilitating a more holistic understanding of campaign performance.

Adtriba goes beyond traditional attribution models by focusing on incremental impact. By comparing incremental impact with correlational impact provided by MTA or platform data, marketers gain deeper insights into the true effectiveness of their marketing efforts. This approach enables users to translate incremental impact from channel tactic level to discrete campaigns, leveraging platform-attributed numbers for more accurate distribution.

Unlike traditional media mix models, Adtriba's marketing mix model considers control information such as inventory levels or seat per kilometer, if you’re a mobility provider, for example, making it more robust and tailored to specific business needs. This integration of control information enhances the accuracy of insights generated by the platform, enabling marketers to make data-driven decisions that align with their business objectives.

Ultimately, Adtriba aims to make triangulation easier for marketers. By providing a user-friendly interface, integrating multiple data sources, and focusing on incremental impact, Adtriba enables marketers to navigate the complexities of marketing measurement with confidence. With Adtriba, marketers can discover valuable insights and drive superior business outcomes through data-driven decision-making.

Let’s wrap up…

The webinar on triangulation in marketing measurement, presented by Adtriba, underscores the importance of combining various attribution models for a comprehensive understanding of campaign performance. While each model has its strengths and limitations, triangulation emerges as a powerful solution to overcome these challenges.

By leveraging independent multi-touch attribution, marketing mix modeling, platform attribution, and last-click attribution, marketers can gain valuable insights into their campaigns. Triangulation allows for a more holistic approach, enabling marketers to identify incrementality factors and make informed decisions.

With Adtriba's solution, marketers benefit from continuous monitoring, integration of multiple data sources, and the scientific distribution of incremental impact. 

In conclusion, adopting a triangulation approach is essential for uncovering valuable insights and maximizing marketing ROI in today's dynamic digital landscape. By embracing triangulation, marketers can stay ahead of the curve and make data-driven decisions that drive success.

If you would like to watch the webinar in full, we invite you to check it out on Spotify or YouTube. 

Discuss your measurement needs and see how triangulation can be of benefit, chat to us today!