Resources: understand, learn the methods, compare, look up a term
Explore the book, whitepapers and in-depth notes on the methods that inform Kuwalyst.
Understand
The pillars and guides: what MMM, incrementality and media planning are, and how they work.
Agentic media planning: what it means, and what it changes
What agentic media planning actually means: an agent that plans, monitors and tunes within guardrails you set, and how that differs from a dashboard.
UnderstandIncrementality in marketing: definition, tests, measurement
Incrementality in marketing: what it means, why platform numbers overstate it, and the three ways to measure it: geo-lift, holdouts, calibrated MMM.
UnderstandMarketing mix modeling: definition, method and calibration
Marketing mix modeling (MMM) explained: what a media mix model measures, how adstock, saturation and priors work, and how to calibrate it with experiments.
UnderstandMedia planning: definition, steps and a template
Media planning explained: what a media plan is, the five steps of the media planning process, a template to download and a worked example. And what data-driven media planning changes.
Method
The method sheets and the book: how each technique works, with its formula and its figure.
Bayesian media mix modelling
A media mix model estimates how much each channel contributes to sales while accounting for carryover and saturation. A Bayesian approach makes prior assumptions explicit and returns a range of plausible outcomes rather than a single point estimate.
8 min readMethodExcess share of voice
Excess share of voice compares a brand's share of category advertising with its share of category sales. A positive gap is generally associated with market-share growth, while a negative gap is associated with decline, making it a useful guide to brand-budget size.
6 min readMethodGeo-lift experiments
A geo-lift experiment compares regions where advertising is paused with similar regions where it continues. It measures incremental effect where user-level tracking is not possible and can calibrate a media mix model against observed results.
8 min readMethodGeometric adstock
Advertising can continue to have an effect after it has run. Geometric adstock models how much of this week's impact remains next week as a fixed proportion that decays over time.
6 min readMethodHill saturation
Additional investment often delivers less incremental effect than the initial spend. The Hill function models this relationship with a half-saturation point and a curve shape that describes how quickly returns increase and then level off.
6 min readMethodMarginal incremental ROAS
Marginal incremental ROAS focuses on the return from the next euro of spend. It considers only sales that would not otherwise have happened, rather than the average return reported across all spend, so channels can be compared more meaningfully.
7 min readMethodResponse curves
A response curve estimates what a channel returns at different levels of spend, rather than only at its current level. It helps planners understand the likely return from the next budget decision instead of relying on an average return.
6 min readMethodThe audited benchmark registry
When a brand has little history, a plan may need to start with published benchmarks. Kuwalyst's registry traces each claim to its primary publisher, audits it and assigns a status that determines whether it can be used.
7 min read
BookMarketing Science in Python
A practical guide to causal inference, media mix modelling, CLV, pricing and forecasting in Python, available as a personalised PDF.
Get the free PDF →Compare
One question per page: which method, which library, what a word means in practice.
MMM vs MTA vs incrementality: which method, and when
MMM vs MTA vs incrementality: what each method measures, what it misses, and when to use which. One table, one opinion, three short cases, and a FAQ.
ComparePyMC-Marketing vs Meridian vs Robyn: why PyMC-Marketing
Why Kuwalyst runs on PyMC-Marketing rather than Google Meridian or Robyn: parametrisation, calibration, auditability, and what it changes for your media plan.
Glossary
The terms of marketing measurement, in one sentence each, with where to read more.
- Advertising effectiveness measurementAdvertising effectiveness measurement assesses how advertising changes awareness, consideration or sales, from a model, experiments and benchmarks.
- Brand liftBrand lift is a campaign's incremental effect on awareness, consideration or another brand outcome, estimated against a comparable group that did not see it.
- Data-driven marketingData-driven marketing is marketing whose decisions rest on evidence, measured or modelled, with every figure showing where it came from.
- IncrementalityIncrementality is the part of a result that advertising caused: the sales that would not have happened without it, as opposed to the baseline.
- Marketing budget allocationMarketing budget allocation divides a budget across channels and periods; done on evidence, it follows the return each channel's next euro should bring.
- Marketing ROIMarketing ROI is the return on marketing investment: the incremental profit that marketing generated, after marketing costs, divided by those costs.
- Marketing scienceMarketing science applies statistical models and experiments to marketing decisions: measuring what marketing causes and deciding where the next euro goes.
- Media mixThe media mix is the set of channels a plan spends on and the share each one gets; media mix modeling measures what each of them contributed.
- MMM (marketing mix modeling)MMM, marketing mix modeling, is a statistical method that explains sales as a baseline plus the contribution of each marketing channel, from aggregate data.
- ROASROAS, return on ad spend, is revenue divided by advertising spend; platform ROAS uses attributed revenue and describes an average return, not the next euro.