An Introduction to Product Adoption Forecasting
Using Bass diffusion and Bayesian uncertainty to reason about adoption curves before and after launch
Read featured articleBlogs & Case Studies
Practical writing and worked examples covering marketing measurement, Bayesian modelling, incrementality and forecasting.
Browse practical writing on marketing measurement, Bayesian modelling, incrementality and forecasting. Case studies will be added here as suitable work becomes available to publish.
Your Campaign Is Working. You May Still Be Overspending.
Using a geo-experiment and CausalPy to separate incremental transactions from demand that already existed
Can MMM Measure How Channels Work Together?
Moving from channel-level contribution reporting towards explicit cross-channel measurement
Measure What Matters: Attribution vs Incrementality
Using CausalPy's Interrupted Time Series to separate real performance changes from measurement updates
Improving Marketing Measurement with Hierarchical MMMs
A practical DTC example using Bayesian partial pooling in PyMC
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