The fifteen analyses

Every post is filed under the analysis it is about. These are the fifteen analyses tea runs, in the order of the catalogue.

Trend Analysis (3): The structural slope of a series, with its confidence band, read before anything else gets credit for growth. Where a trend line helps, and where it averages two different businesses into one.
Baseline Forecast (3): What the next weeks look like with nothing new in them: the business-as-usual number a plan should be measured against, and the cases where the past is not a baseline at all.
Time Series (ARIMA) (1): Forecasting with ARIMA models chosen on the data, read through their residuals and their intervals. How far ahead a forecast stays useful, and how to tell.
Seasonality & Event Impact (1): Separating the calendar from the campaigns: seasonal indices, moving holidays and one-off events, measured with everything else held constant.
Lag & Carryover (3): How long a euro of media keeps working after the week it ran. Adstock, half-life and the distribution of an effect over time, and the files where it cannot be identified.
Saturation Curves (1): Response curves per channel: where the returns flatten, what the next euro is worth, and how wide the interval on the bend really is.
Contribution & Driver Decomposition (1): Marketing mix modeling in practice: what each driver added, week by week, with the intervals that say which numbers to believe.
Base vs Incremental (2): The split a board asks for: the year you would have had anyway, and what marketing added on top of it.
Budget Optimization (2): Moving the same budget to where the next euro returns most, under real constraints, and knowing when a recommendation is too thin to follow.
Price Elasticity (3): How demand answers a price move, measured with its band: when a rise pays, when a cut does, and when the file holds no price variation to learn from.
Promo Elasticity (1): What a promotion really bought, net of the demand it pulled forward, and why a calendar full of discounts cannot be measured against itself.
Cross-Elasticity (1): Which competitor takes your volume when they move their price, and which one only sits next to you on the shelf.
Scenario Simulation (1): Running the plan you are considering against the measured effects before committing money, and knowing where a simulation stops being evidence.
Geo / Segment MMM (0): The same model per region or segment, with partial pooling: where the national average hides two different markets.
Competitive Pressure (2): Share of voice against share of market, excess share of voice, and what competitor activity structurally costs you.