Multi-touch attribution (MTA) is a data-driven approach to measuring the impact of various marketing channels and touchpoints on a consumer’s journey toward making a purchase or completing a desired action. Unfortunately, marketers struggle with gaining such a view because most solutions make it difficult, if not impossible, to centralize data and deliver data-driven insights in real-time.
Unlike single-touch attribution models, which assign 100% credit to a single touchpoint (such as the first or last interaction), MTA distributes credit among multiple touchpoints, providing a more comprehensive understanding of the customer journey. As a result, campaign managers can direct marketing funds and focus on building growth strategies backed by data and based on revenue contribution per channel. This approach enables companies to decrease customer acquisition costs (CAC) and boost their return on ad spend (ROAS).
First-party customer data that describes user behavior throughout the buying journey greatly enhances the accuracy and utility of attribution modeling. It also streamlines the delivery of marketing strategies that deliver relevant and timely insights and offers to increase audience response and revenue. Whether your organization uses elementary attribution modeling or has built data-intensive machine learning models for MTA, the challenge lies in extracting campaign data that profiles conversion journeys and integrates all of your crucial marketing data quickly and securely at scale.
That’s where Snowplow and Snowflake come in. Snowplow, a leading behavioral data collection platform, empowers organizations to generate first-party customer data to build granular customer journey maps in the Snowflake Data Cloud—a cloud-built data platform for organizations’ critical data workloads, such as marketing analytics. Together, Snowplow’s data collection capabilities, combined with the Snowflake Data Cloud, enable marketers to easily build customer data models to deliver more accurate measurements for powerful campaigns.
The Challenge with Attribution Modeling & How We Solve It
Slow and unreliable attribution modeling begins with the traditional, cumbersome, and time-consuming ELT/ETL processes to ingest ad data. The deprecation of common identifiers such as third-party cookies and mobile IDs further exacerbates this problem.
The critical challenges that marketers continually face are the accuracy and completeness of data along with time-to-insights. In order to perform multi-touch attribution (MTA) analytics, the underlying data must be both accurate and complete. Otherwise, the analytics will fail to produce meaningful insights and could lead to making the wrong decisions for your marketing programs, and for your company.
With our MTA solution, the real power lies in the accuracy and completeness of the underlying data. Snowplow and Snowflake allow you to define and generate your first-party customer data in near-real time, so you can model and analyze conversion journeys with first-party, click-event data from advertising campaigns. With Snowplow, organizations can generate, enrich, and model click-event streams to help understand the performance of their advertising campaigns. Once loaded, any organization can easily analyze and respond to what’s happening with their ad campaigns in near real-time with a unified single source of data in Snowflake.
Leveraging the joint power of Snowplow and Snowflake, marketers can raise customer lifetime values and minimize customer acquisition costs. This is enabled by developing superior MTA models that employ more accurate and regular data analysis at a speed previously unattainable for most organizations. Consequently, marketers can swiftly and confidently adapt and redistribute marketing budgets to the most impactful projects.
Snowplow + Snowflake: Transforming Marketing Attribution through Innovation
Utilize Snowplow and Snowflake to leverage your first-party customer data and benefit from:
- Transparent Analytics: Obtain full insight into your customer’s behaviors and actions by creating and managing your attribution models built from Snowplow with the transparency and adaptability that opaque modeling from Google Analytics and other pre-built solutions don’t always offer.
- Comprehensive Customer Perspective: Swiftly and efficiently analyze trends at scale by merging Snowplow’s extended first-party cookies and the capacity to track even where Intelligent Tracking Prevention is present, known as ITP on Safari & iOS. Note: (ITP is the privacy feature implemented in Apple’s Safari browser and iOS devices that aims to limit third-party tracking and improve user privacy by restricting access to cookies and other storage devices.)
- Near-time Data Streaming: Continuously extract and upload data from your Snowplow pipeline to the Data Cloud with minimal latency.
- Compliance at scale with Snowplow: Support compliance with global data privacy regulations by using a secure SaaS delivery model, PII pseudonymization, per-event consent tracking, and genuine data lineage.
Real-World Story: Digital Virgo
Digital Virgo, a leading telecom carrier billing service provider, made the switch from Google Analytics to Snowplow and Snowflake. This move allowed a reduction in data latency by 90%, while eliminating data silos, so Digital Virgo could acquire the critical insights needed to make business decisions backed by data. For the first time, the company was able to track ad campaign traffic, collect more accurate session data and accurately measure campaigns, all in real-time. Lastly, Digital Virgo was able to standardize reporting for all 40 countries where it operates by using a single source of truth. The result, Digital Virgo achieved higher net-new subscribers during their 2022 FIFA World Cup advertising campaign, for example, by monitoring campaign performance and reallocating budget to the most effective campaigns. This optimization strategy maximized their return on investment and improved the efficiency of their marketing resources during the four weeks of the World Cup.
“Before Snowplow, we had Google Analytics 360. We did not have any data sets of events available in real-time in our AWS infrastructure. Snowplow and Snowflake open up a world of possibilities for us because we can provide data to our team to analyze trends in campaigns, analyzing what’s happening within five or 10 minutes. We are now able to gain a perfect matching between clicks and sessions, thanks to the complete server-side implementation of Snowplow tracking,” said Anthony Gianastasio, Head of Analytics, Digital Virgo.
- MTA (Multi-Touch Attribution) enhances marketing strategies by providing data-driven insights on revenue contribution per channel, allowing for effective resource allocation and scalable growth.
- Snowplow and Snowflake offer a comprehensive solution for real-time attribution modeling and analysis, enabling organizations to collect, enrich, and model click event data for near-real-time analysis.
- By leveraging Snowplow and Snowflake, marketers can achieve higher customer lifetime value, reduce customer acquisition costs, and improve time to value, leading to better campaign performance and business outcomes.
- Real-world example: Digital Virgo switched to Snowplow and Snowflake, resulting in significant improvements in insights and campaign performance, including net-new subscribers during the 2022 FIFA World Cup.