CASSANDRA S.R.L.

Marketing investment decisions have long been complicated by a fundamental measurement problem: in a world where customers encounter a brand through dozens of different channels — paid search, social media, television, out-of-home, email, influencer content, organic search — how do you know which part of your marketing is actually driving results? The attribution models that have dominated digital marketing measurement for years are built on simplified assumptions about customer journeys that frequently misrepresent reality, allocating credit to the last click or the most recent touchpoint rather than to the full sequence of influences that actually drove a conversion. Cassandra was built to replace those oversimplifications with something genuinely rigorous. The platform integrates three complementary approaches to marketing measurement into a single environment: marketing mix modelling, incrementality testing, and always-on incrementality measurement. Each addresses a different dimension of the measurement challenge, and together they provide a comprehensive, scientifically defensible picture of how marketing investment is actually creating business outcomes. Marketing mix modelling provides a statistical decomposition of how different channels and tactics have contributed to business outcomes over time, accounting for the many non-marketing factors — seasonality, pricing changes, competitive activity, macroeconomic conditions — that affect sales and making it possible to isolate the specific contribution of each marketing input. This retrospective view allows marketers to understand the relative effectiveness of their past investment decisions and to model how future budget allocation changes would affect overall performance. Incrementality testing establishes through controlled experiments what the causal impact of specific marketing interventions actually has been — the genuine lift attributable to a campaign or channel, measured against a comparable control group rather than inferred through attribution modelling. This causal rigour is what separates meaningful measurement from the correlation-based analysis that has historically been sold as attribution. Always-on incrementality extends this experimental approach to a continuous monitoring capability, giving marketing teams an ongoing read of what is and is not working without waiting for a quarterly modelling cycle or commissioning a one-off experiment. The result is a measurement infrastructure that operates at the speed of marketing decision-making rather than lagging behind it. Cassandra is designed for the leading marketing teams across every sector that makes substantial data-informed media investments. The platform is built to deliver rigorous measurement capability without requiring the intensive technical expertise that previous implementations of marketing mix modelling have demanded. The growth strategy is built on partnerships and ecosystem development, making scientific marketing measurement accessible to the organisations that need it most.