Jordan Craig review for WorkMagic Attribution
March 7, 2025
WorkMagic has been one of, if not the most important tool in our tech stack. As a profit-driven company, we need to understand which channels we can scale profitably for both new customer acquisition and retention. It’s not just about ROAS; it's about the incremental value added. While we have used some of the popular attribution tools, none of them emphasize incrementality or data accuracy as much as WorkMagic. In addition to having extremely accurate and proven data, their team is committed to continually improving the platform. Since signing on, we've provided numerous suggestions. With most vendors, these get added to a queue, and it takes months to see any progress (if at all). However, WorkMagic's team typically completes our feature requests within 3 to 10 days. This doesn’t just help us—it benefits all of their clients. Despite working with many respected ecommerce clients, they always make us feel like we’re their only one. They offer ad-hoc analysis when we need it, and if we have a request, they take care of it promptly. Recently, we asked them to analyze some marketing data, requiring it within 24 hours. They completed it in less than 8 hours. This isn’t a one-off, but rather a consistent track record of over-performing our already high expectations. WorkMagic is universally loved by our entire team. The executive team values having accurate data that enables strategic decision-making. The acquisition team appreciates being able to easily access data and make changes directly in WorkMagic, instead of having to log into each individual platform. The data analytics team values having all the data in one clear space and being able to find exactly what they’re looking for. It’s rare to find a platform that can make everyone's life easier. Overall, there are not enough positive things we can say about WorkMagic and their team. If you're running ads and care about profit, WorkMagic is a must. There’s no replacement for accurate, incrementality-based data.
