Demand and mix prediction
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Dynamic pricing

Pricing shaped by product role, elasticity, local demand, competitive pressure and customer propensity, with simulation that lets teams test before they act.
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Price changes happen in seconds. Their effects stay in the P&L.
WHY THIS “DYNAMIC PRICING” CHALLENGE?
One price cannot fit every store, product or moment

The challenge is not simply changing prices faster. It is deciding where a change makes sense, how far it should go and what it could mean for volume, margin, key value items and customer trust. Without a way to combine product roles, elasticity, costs, competition and purchase propensity, pricing teams are forced to act with an incomplete view. Without simulation, they discover the trade-offs only after execution.

Key benefits
Move from blanket pricing to decisions grounded in context
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Protect margin with product-level precision

Use product role and elasticity to make deliberate trade-offs instead of applying the same logic everywhere.

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Make promotional spend accountable

Measure uplift and cannibalization so promotional effectiveness is evaluated, not assumed.

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Defend price perception where it matters

Treat key value items strategically while adapting the wider assortment to local conditions.

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Test before execution

Simulate price scenarios to understand likely volume and margin implications before a decision reaches stores or stations.

How NTT DATA helps

01
Product role and elasticity modelling

Build customer and location archetypes so the model reflects how demand behaves across the network.

Differentiate pricing by product role
02
Competitive and propensity data

Bring costs, competitive signals and purchase propensity into a shared decision model.

Embed elasticity-driven decisioning
03
Price simulation and consultation platform

Give pricing teams and locations a self-service environment to compare scenarios before execution.

Strengthen price perception management
04
Promotional effectiveness

Assess uplift and cannibalization to identify which promotions create incremental value and which redistribute demand.

Optimize promotional effectiveness
05
Governance and rollout

Move from pilot to network deployment with clear decision rights, operating routines and a path for continuous learning.

Shift to economic pricing governance
Driving profitability through smarter pricing and commercial execution
Proven impact
From pricing model to network-scale decision support

A referenced fuel and convenience deployment in Mexico and Colombia indicates the potential to connect more precise pricing with sales growth, forecast confidence and adoption across a distributed station network. The figures below require source and approval validation before publication.

Results that matter
Business outcomes from pricing discipline and commercial optimization
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+10%

Reported sales increase for service stations. Validate baseline, period, attribution and source.

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95%

Reported volume forecast accuracy versus actual. Validate methodology, horizon and sample.

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130+

Reported stations using the model across Mexico and Colombia. Validate current count and rollout date.

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Validation required

No grocery or fashion pricing KPI is provided in the source. Do not publish a fourth result until approved evidence is available.

Ready to price with more precision?

Start the conversation that connects local market signals, customer perception and margin discipline before the next price decision is made.

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