November 2022 Summaries

Abandoned cart emails are a significant remarketing tool in eCommerce, contributing to substantial revenue by re-engaging customers who leave their shopping carts without completing purchases. However, with the enforcement of GDPR, businesses must navigate new rules requiring explicit user consent for such communications to avoid hefty fines and reputational damage. GDPR mandates that consent be "free, specific, informed, and unambiguous," and businesses must clearly communicate how they will use personal data, including email addresses, for marketing purposes. Under GDPR, legitimate interest can sometimes justify sending abandoned cart emails without explicit consent, provided there is a reasonable expectation that the recipient would be interested in the content and an opt-out mechanism is included. Snowplow, a behavioral data analytics tool, aids compliance by meticulously organizing data and ensuring that all user interactions are tracked with consent, thus allowing businesses to maintain GDPR compliance while optimizing email remarketing strategies.

In the current era, often referred to as the Golden Age of data, businesses have access to a vast array of data sources, which, when effectively analyzed through data discovery processes, can provide crucial insights for strategic decision-making. Data discovery involves extracting meaningful patterns by combining and analyzing data from various sources, a process that has been significantly enhanced by advancements in artificial intelligence and machine learning. This iterative process includes steps such as identifying goals, collating data sources, cleaning the data, visualizing, and analyzing it to reveal actionable insights, which help businesses become more agile and cost-effective. The importance of data discovery has grown with the increase in data generated by remote working and digital interactions, emphasizing the need for smart, automated solutions like those provided by behavioral data analytics tools such as Snowplow. These tools enable businesses to leverage complex behavioral data, traditionally seen as challenging, to gain deeper insights and personalize customer experiences, similar to the approaches used by leading tech companies like Airbnb and Spotify.

With increasing regulatory demands on data ownership and governance, the Private SaaS or Bring Your Own Cloud (BYOC) model emerges as a compelling alternative to traditional SaaS. Unlike the multi-tenanted public cloud environment of SaaS, Private SaaS allows clients to run data pipelines in their private storage while the vendor manages maintenance, offering a blend of ownership and convenience but requiring some technical input from clients. This model provides significant control over data compliance and governance, enabling full scrutiny and auditable decision-making, unlike the often opaque operations of standard SaaS tools. While SaaS solutions like Google Analytics offer seamless integration and convenience with a wide ecosystem, they also come with transparency issues, such as limited data sovereignty and hidden data usage practices, which have led to regulatory fines under GDPR. Businesses must weigh these trade-offs when choosing between Private SaaS, traditional SaaS, or self-hosted models. Snowplow champions the Private SaaS approach, emphasizing full visibility and client control over data management, with its BDP Enterprise tool offering a fully managed service in a client's isolated cloud environment, ensuring no shared tenancy and robust integration with existing systems.

Data discovery is a significant challenge in modern data platforms due to their technical complexity, necessitating tools that enable all company members to find and understand necessary data. Snowplow's new Tracking Catalog aims to address this by providing a comprehensive list of events, entities, and properties processed over the last 90 days, allowing users to visualize the interconnectedness of data. This tool facilitates understanding for less technical team members by offering clear visuals and plain English descriptions, thus promoting collaboration and reducing the bottleneck typically caused by reliance on specialists. Currently available to Snowplow BDP customers on specific tiers, the Tracking Catalog differentiates from traditional data catalogs by being integrated directly into Snowplow’s system, allowing real-time data access and reflecting data before validation. As part of its ongoing efforts, Snowplow is also developing a Tracking Plan to help Data Product Managers manage data systematically and address challenges like compliance, value, and trust, thereby ensuring effective data pipeline ownership.