Product

WebDesktop

Elasticity Analysis

Bayesian price elasticity — in the browser, or fully inside your network.

The analysis layer

Where the numbers come from.

Elasticity Analysis is the analytical side of pricing. Walk your product hierarchy from category to SKU, fit Bayesian elasticity posteriors per segment, and produce optimal prices grounded in how demand actually responds — not point estimates that hide their own uncertainty.

Every result rolls up to the hierarchy node you’re looking at. Inspect price–quantity scatter and timeseries at every level. Review diagnostic plots and posterior distributions before a single price moves — and carry the credible intervals through to the optimiser so every price ships with the uncertainty you actually have.

Spec


Inference
Bayesian posteriors
Input
Sales transactions
Output
Optimal prices + credible intervals
Model
Proprietary hierarchical model
Runs in
Your browser, or your network
Pairs with
Resolve

The analyst’s core loop, as building blocks.

The things you do in Elasticity Analysis, over and over — aggregate data, vizualise it, fit the model, optimise the price.

Hierarchy walk with scatter at every levelCategorySub-categorySKU64 SKUsQTYPRICEsame view at every level of the hierarchy

Aggregate data

Determine which level of aggregation (product, category, region, etc.) to analyze data. Results roll up to whichever node you're standing on.

Elasticity scatter with fitted slopeSCATTER · LOG–LOGn = 1,284LOG QLOG Pslope = −1.42price–quantity response at the segment level

Elasticity scatter

Price–quantity scatter and timeseries at every level of the hierarchy. See the response before you commit to a model — and inspect the fit, not just its number.

Posterior distribution over elasticityPOSTERIOR · εε = −1.42 ± 0.12−2−1.5−1−0.5068% CI95% CIposterior over elasticity · not a point estimate

Posterior fits

Bayesian elasticity per segment, expressed as a posterior distribution — not a point estimate. You see the uncertainty, not just the median, before a single price moves.

Price optimisation curveOBJECTIVE · REVENUEp* = $1,200REVPRICEminmaxoptimumcvxpy · optimal under your constraints

Price optimisation

Optimal prices solved directly from the fitted model. Credible intervals carry through the optimisation, so every price ships with the uncertainty you actually have.

Analyst loop

One tight loop, five steps.

Elasticity Analysis is structured around how pricing analysts actually work — not how data scientists ship notebooks.

  1. 01
    Import

    Connect transaction history from your warehouse, ERP, or a flat CSV export.

  2. 02
    Aggregate

    Navigate the product hierarchy. Inspect scatter and timeseries at every level.

  3. 03
    Fit

    Run Bayesian fits per segment. Posteriors in seconds, not overnight.

  4. 04
    Optimise

    Solve for optimal prices under your margin and demand constraints.

  5. 05
    Roll up

    See the result at whichever node you're standing on — SKU, brand, or category.

Runtime

Web service, or fully inside your network.

Elasticity Analysis is one codebase shipped two ways. Desktop exists because some clients can’t put transaction data in a SaaS — and we don’t want that to be the reason a pricing project doesn’t happen.

Capability
WebWeb serviceHosted, shared, always-on
DesktopDesktop, inside your networkNo data leaves the perimeter
Data locationOur managed cloudFully inside your network
OnboardingSign inInstall on analyst workstation
Access modelShared team workspaceSingle workstation, per user
Security reviewStandard SaaS reviewStandard enterprise software review
Best forIn-house pricing teams wanting always-on shared accessConsultancies, regulated industries, procurement-locked clients

Contact

Let's talk pricing.

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