← Research · Part 6 of 10
The question decides the method, not the other way round
We work from a written decision map rather than from habit. It runs on four things: what kind of question is being asked, what the outcome variable actually looks like, how the data is structured, and how interpretable the answer has to be. A few of the more common cases:
| What a business actually asks | What we reach for |
|---|---|
| What is a customer worth over their lifetime? | Probabilistic buying models — Pareto/NBD or BG/NBD for repeat rate and dropout, Gamma-Gamma for spend |
| Who are our real customer segments? | Latent class analysis or finite mixture models. Not k-means, which imposes a geometry survey data doesn’t have |
| Which channel actually earned the sale? | Markov chain or Shapley-value attribution rather than last-click. Bayesian structural time series for media mix |
| Did our spend cause the lift? | Geo experiments, instrumental variables or regression discontinuity. A predictive model cannot answer this |
| Who is about to leave, and when? | Survival analysis — Cox proportional hazards or Kaplan-Meier, because the answer is a time, not a yes or no |
| How many will happen next month? | Poisson or negative binomial for counts. Ordinary regression on a count outcome is a common and costly error |
| What will demand look like? | ARIMA or Prophet for seasonal series, gradient boosting or LSTM where there are many drivers |
| Which factors are driving this? | Regularized regression, or tree ensembles read through SHAP values when the relationship isn’t linear |
| What are people saying at volume? | Topic modeling and text classification — and graph analysis where the structure between things is the point |
| What should we actually do? | Constrained optimization. Budget, inventory and capacity problems have an answer, not just a description |
And when the choice isn’t obvious, we ask. Some questions sit on a genuine methodological fault line — small samples, nested data, competing causal identification strategies. We draft the approach, then confirm it with statistics and analytics advisors before a client relies on it. Being certain is easy. Being right is worth the extra call.
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