June 2020 Summaries

To effectively support real-time applications and informed decision-making, businesses must prioritize high-quality data collection, starting with robust and consistent tracking implementation. However, many companies face challenges due to tracking errors, as developers often prioritize other tasks and assume data issues can be rectified later. As businesses seek increasingly detailed data, these errors become more prevalent, leading to incomplete or inaccurate data that undermines product quality and decision-making. Snowplow addresses these issues by providing tools like Snowplow Mini and Snowplow Micro, which help developers implement correct tracking and identify problems early. These tools offer real-time QA environments and allow developers to write tests to ensure events are correctly emitted and formed. Despite these measures, monitoring the data pipeline remains crucial to detect and resolve issues that slip through, with Snowplow offering near real-time data quality scores and breakdowns to facilitate swift resolution.

In a guest post by Mitra Muehlman, challenges and solutions surrounding accurate revenue attribution in the context of Apple’s Intelligent Tracking Prevention (ITP) are discussed, particularly its impact on e-commerce businesses and their reliance on web analytics like Google Analytics. The introduction of ITP with iOS 13 and Safari 13 in 2019 significantly shortened cookie lifespan, complicating the ability to track customer journeys and attribute revenue accurately, especially affecting Safari users who often generate higher per capita spending. The post highlights a real-world case where an e-commerce client switched from Google Analytics to a custom solution combining ITP-compliant, first-party cookies and Snowplow analytics, resulting in more accurate attribution and a record-breaking sales season due to better-informed ad spending decisions. The analysis illustrates that Google Analytics began underreporting attributable revenue post-ITP implementation, leading to a misinformed marketing strategy unless complemented by a robust, integrated data solution.