Skip to content
PERINGER Data Solutions, back to home

Back

Solution

Dynamic pricing

A price may be out of line with stock, demand or strategy, but an automated rule can also harm trust, margin or fairness. This remains exploratory: commercial and legal governance, simulation, a limited trial and a stop path come before automation.

The gains from pricing

In practice

  • Explicit pricing rules: floors, ceilings, rounding, maximum movement, frozen items
  • Input signals chosen with you: stock, seasonality, occupancy, observed prices
  • Simulation over history before anything goes live, to see what the rule would have done
  • Gradual rollout: one category, area or time slot first, with a control group
  • A log of every price change with its cause, kept for audit
  • Immediate stop: one control that hands back manual pricing, with no redeploy

Systems involved

  • Online shop and point of sale
  • Stock management and ERP
  • Booking and ticketing systems
  • Price observations and supplier catalogues
  • BI tool for margin monitoring

Service lineData →

What makes a price move

The same work, against each sector’s own constraints. Every card opens the full sector.

How it runs

  1. Rules

    What you allow yourself, written down. This step is commercial before it’s technical.

  2. Simulation

    The rule is replayed over an available representative period. Simulation has a cost and exposes risks without perfectly predicting real customer response.

  3. Controlled trial

    A restricted scope and a control group, long enough that the result isn’t a coincidence.

  4. Rollout

    Gradual extension, with margin tracked in your own tool and the stop procedure tested.

Test the fit: Dynamic pricing

Describe the context, constraints and decision you need to make. The first conversation qualifies scope, boundaries and the next useful step.

Describe the situation