Best Practices in Marketing Attribution: Harnessing Advanced Data Insights for Precision Marketing

While it’s common to look at best attribution practices from the perspective of attribution models for optimizing marketing tactics, we want to take a deeper look into the foundation and why having high-quality data is crucial for marketing attribution. Precision and accuracy in data handling are more than perks — they are necessities. Let’s dive into the key data practices ensuring reliable attribution modeling: preserving data quality, employing deeper granularity, data normalization, data governance, and implementing multi-touch attribution (MTA) models.

High-Quality Data: The Keystone of Reliable Analytics

The foundation of impactful marketing attribution lies in the quality of data collected. Utilizing robust ETL/ELT (Extract, Transform, Load) platforms, marketers and analysts can cleanse, verify, and validate data to ensure accuracy. This may include the use of advanced algorithms for anomaly detection and automated error correction, which help maintain the integrity of the data pipeline.

For instance, Improvado uses moving averages over historical data to detect anomalies, which then undergo automated quality checks to verify whether they were caused by normal behaviors or malfunctions. Normal behaviors include a marketing campaign coming to an end, a pause in marketing activities, or budget changes, whereas malfunctions include issues such as data source API failures. The process is performed at both the data flow and platform levels to quickly identify and resolve any possible threats to data pipeline integrity. The algorithms are applied twice to minimize risks: during data extraction and data loading. Roman Vinogradov, VP of Product at Improvado, says this about comprehensive data:

Deploying automated data collection, harmonization, and validation ensures that our data goes beyond comprehensive. It’s also credible and compliant.

Implementing marketing data quality frameworks can lead to a measurable increase in campaign ROI by ensuring that decision-makers are not misled by corrupted or skewed data insights. This precision leads to an average uplift in marketing ROI of up to 70% by focusing efforts on genuinely effective strategies.

Granularity: Micro-Level Data Analysis

Granularity allows marketers to dissect broad datasets into finer segments, enabling detailed performance analysis of each campaign element. Techniques such as data segmentation and micro-targeting are employed to refine the granularity, which involves breaking down user interactions by demographic, geographic, and behavioral data points. Roman Vinogradov, VP of Product at Improvado says this about data granularity:

We see exploring deeper data granularity as a natural next step once your key data pipelines and visualizations are established. With attribution, marketers then can switch from campaign-level analytics to tracking performance of campaign creatives or various age groups. To enable this, we extract over 48,000 metrics and dimensions from available data sources as well as support extracting customizable sets of metrics and dimensions.

Leveraging granular data can increase conversion rates by up to 50%, as it allows for the optimization of campaigns at a much more individualized level.

Data Normalization: Creating a Cohesive Analytical Environment

Normalization is critical when integrating data from multiple sources. This process adjusts disparities in data formats and scales, enabling a unified view that is crucial for accurate cross-channel analysis. Implementing consistent data schemas and using various data transformation tools foster standardization, making data actionable across platforms.

By standardizing data, marketing analytics platforms enable marketers to gain cross-channel insights and compose customer journeys. Automating data harmonization reduces the time spent on manual data preparations by 20-30%, thereby speeding up the cycle of insights generation and application.

Governance: Ensuring Data Security and Compliance

Strong governance frameworks are essential to safeguard data integrity and compliance. This includes establishing clear policies for data access, retention, and usage that align with global data protection regulations such as GDPR and CCPA. It’s also a good practice to preserve campaign compliance. The approach is similar to data governance: you develop an internal campaign guideline document, and then check each campaign against it. The process can be manual or automated.

Effective governance minimizes legal risks by up to 70% and strengthens stakeholders' trust in data-driven insights used for strategic decision-making. With attribution, the trust is crucial, since navigating through various attribution models is used to optimize budget allocation.

Multi-Touch Attribution: Seeing Through Customer Journeys

Multi-touch attribution (MTA) models track each touchpoint's contribution to the final conversion, employing various weighting functions to assign appropriate conversion credit across the customer journey. While single-touch models (such as first-touch or last-touch) attribute conversions and revenue to a single point in a consumer journey, MTA models allow to identify key channels, supporting channels, and everything in between. As customer journeys are becoming increasingly more complex, MTA models are becoming an industry standard for tracking marketing performance.

Employing MTA models often leads to a 50% improvement in marketing effectiveness by ensuring budget allocation to the most impactful channels.

The Best of Both Worlds: AdRoll Cross-Channel Attribution Powered by Improvado

By embracing a technically sophisticated approach to marketing attribution, businesses can achieve unprecedented clarity and precision in their marketing efforts. The strategic alliance between Improvado and AdRoll exemplifies how the right mix of high-quality data, granular insights, robust governance, and multi-touch attribution can revolutionize marketing impact, making sophisticated analytics and data-driven action accessible to all.

Last updated on June 11th, 2024.