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40 results
  1. MSC-P-001How do you turn a marketing claim into a testable question?Decision Science↗
  2. MSC-P-002Correlation or causality: what can an analysis actually support?Marketing Measurement↗
  3. MSC-P-003How should uncertainty in a marketing result be expressed?Decision Science↗
  4. MSC-P-004Statistical significance or effect size: which result should be interpreted?Decision Science↗
  5. MSC-P-005How do you measure a marketing construct that is not directly observable?Market Research↗
  6. MSC-P-006How do you design and validate a measurement scale?Market Research↗
  7. MSC-P-007Alpha or omega: how should scale reliability be assessed?Market Research↗
  8. MSC-P-009PCA, EFA or CFA: which method should you choose?Market Research↗
  9. MSC-P-010When should you run a marketing experiment?Marketing Measurement↗
  10. MSC-P-011How do you design an A/B test that actually estimates an effect?Marketing Measurement↗
  11. MSC-P-012How many observations does an experiment need?Decision Science↗
  12. MSC-P-013How do you measure campaign incrementality with a control group?Marketing Measurement↗
  13. MSC-P-017How do you detect selection, contamination and attrition in an experiment?Marketing Measurement↗
  14. MSC-P-018Predictive or causal regression: what are you trying to estimate?Marketing Models↗
  15. MSC-P-019How do you diagnose a marketing regression before interpreting it?Marketing Models↗
  16. MSC-P-022How do you estimate price elasticity and its uncertainty?Pricing Science↗
  17. MSC-P-026Logit vs Probit: how do you choose for purchase probability?Customer Science↗
  18. MSC-P-029Which customers have the highest probability of churn?Customer Science↗
  19. MSC-P-027TAM, UTAUT or UTAUT2: which framework should be used to study technology acceptance?Market Research↗
  20. MSC-H-001Measurement and causality: how can a marketing effect be established?Marketing Measurement↗
  21. MSC-H-002Marketing response models: shape, delay and saturationMarketing Models↗
  22. MSC-H-003Pricing science: connecting price, demand and contributionPricing Science↗
  23. MSC-H-004Customer and choice science: behavior, value and heterogeneityCustomer Science↗
  24. MSC-H-005Measurement science: building valid indicatorsMarket Research↗
  25. MSC-H-006Statistical decision methods: choose, quantify, validateDecision Science↗
  26. MSC-P-008How do you validate a marketing measurement scale?Market Research↗
  27. MSC-P-014How do you design a marketing geo experiment?Marketing Measurement↗
  28. MSC-P-015How do you estimate an effect with difference-in-differences?Marketing Measurement↗
  29. MSC-P-020How do you address price endogeneity?Pricing Science↗
  30. MSC-P-021Fixed or random effects: which panel model should you choose?Marketing Models↗
  31. MSC-P-023How do you estimate a demand function?Pricing Science↗
  32. MSC-P-024How do you simulate a price-volume-margin scenario?Pricing Science↗
  33. MSC-P-028How do you estimate CLV with BG/NBD and Gamma-Gamma?Customer Science↗
  34. MSC-P-030How do you analyze retention with a survival model?Customer Science↗
  35. MSC-P-031How do you build a useful customer segmentation?Customer Science↗
  36. MSC-P-032How do you test segmentation stability?Customer Science↗
  37. MSC-P-033How do you validate a marketing forecast?Decision Science↗
  38. MSC-P-034How do you build a Monte Carlo simulation for a marketing decision?Decision Science↗
  39. MSC-P-035How do you model saturation and adstock?Marketing Models↗
  40. MSC-P-039Which statistical test should you choose?Decision Science↗
← All methods
METHOD DOSSIERMSC-P-014Experimentation and causality

How do you design a marketing geo experiment?

A geo experiment compares test and control regions before and during an intervention. The design must limit contamination, pre-period imbalance and temporal dependence.

Direct answer

Estimate an aggregate incremental effect in the studied regions and period.

A geo experiment compares test and control regions before and during an intervention. The design must limit contamination, pre-period imbalance and temporal dependence.

Model or deliverableEffect = Ytest,post − Ŷtest,post(no treatment)

Vaver & Koehler, geo experimentsBrodersen et al., CausalImpact

ESTIMAND

Estimation profile

Unit of analysis
Assigned unit × group × periodControlled scientific terminologygeo × period
Exact estimand
Incremental outcome in treated geographies
Model or deliverable
Effect = Ytest,post − Ŷtest,post(no treatment)

01—08

Verifiable analysis framework

  1. 01
    Question

    How do you design a marketing geo experiment?

  2. 02
    Estimand

    Incremental outcome in treated geographies · geo × period

  3. 03
    Data

    geo_id · date · treatment · outcome · pre_period_covariates

  4. 04
    Model or deliverable

    Effect = Ytest,post − Ŷtest,post(no treatment)

  5. 05
    Declared calculation

    Effect = Ytest,post − Ŷtest,post(no treatment) → Incremental outcome in treated geographies

  6. 06
    Uncertainty checks

    Pre-period fit · Spillovers · Power at geo level · Distinguish randomized geo design from BSTS control · Placebo periods

  7. 07
    Method-specific validation

    Check data, estimate stability and interpretation limits. Pre-period fit · Spillovers · Power at geo level · Distinguish randomized geo design from BSTS control · Placebo periods

  8. 08
    Limitations

    Attribute the effect to each individual or extrapolate unreservedly to other markets.

Required variables

  • geo_id
  • date
  • treatment
  • outcome
  • pre_period_covariates

Checks · Controlled scientific terminology

  • Pre-period fit
  • Spillovers
  • Power at geo level
  • Distinguish randomized geo design from BSTS control
  • Placebo periods
Possible decision

Estimate an aggregate incremental effect in the studied regions and period.

Not supported

Attribute the effect to each individual or extrapolate unreservedly to other markets.

Scientific sources

2 sources

  1. Vaver & Koehler, geo experiments
  2. Brodersen et al., CausalImpact

Method connections

Parent territoryMeasurement and causality: how can a marketing effect be established?Compare withWhen should you run a marketing experiment?Compare withHow do you estimate an effect with difference-in-differences?

Read next

MSC-H-001Measurement and causality: how can a marketing effect be established?→MSC-P-010When should you run a marketing experiment?→MSC-P-015How do you estimate an effect with difference-in-differences?→MSC-P-013How do you measure campaign incrementality with a control group?→