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Consumer Products

AI for consumer products that senses demand, optimises price, and fixes your supply chain

You get AI agents for demand sensing, dynamic pricing, supply chain optimisation, and trade promotion analytics. They run on your cloud, connect to your existing POS and ERP systems, and produce the forecasts your commercial teams can act on.

or

Built on your AWS, Azure or GCP tenant. Retail-data compliant. Boardroom-ready.

Consumer products warehouse and distribution centre
30 days

Proof of concept

12-18 weeks

To measurable ROI

Your cloud

AWS, Azure or GCP

Your competitors already use AI to price, forecast, and allocate. You cannot afford to catch up later.

Consumer products companies sit on vast quantities of POS data, e-commerce signals, and supply chain telemetry. Most of it feeds static dashboards that arrive too late to change decisions. Meanwhile, your competitors use AI to sense demand shifts in days, adjust pricing in hours, and reroute supply chains before disruptions hit shelves.

We build AI agents that turn your existing data into decisions your commercial and supply chain teams can act on from SKU-level demand sensing and dynamic pricing to trade promotion optimisation and supply risk monitoring, with the audit trails your finance team requires.

Up to 65%

improvement in demand forecast accuracy with AI sensing models (McKinsey QuantumBlack, 2024)

2-5%

margin improvement achievable through AI-driven dynamic pricing (BCG X, 2024)

$100B+

annual value at stake from AI-optimised CPG supply chains globally (McKinsey, 2024)

20-30%

reduction in excess inventory with AI-powered demand planning (Deloitte Insights)

Connected

From POS signal to commercial action, in one workflow

We connect your POS feeds, e-commerce platforms, ERP, and supply chain systems to AI agents that sense demand, optimise pricing, manage trade spend, and flag supply risks before they reach your shelves.

Consumer & Supply Data

POS, ERP, e-commerce and market data

AI Agent
ModelYour choice
HostingYour cloud
Workflow Engine
  • Approval gates
  • Human-in-loop
  • Audit logging
Your Cloud Tenant

AWS, Azure or GCP

Commercial Output
  • Demand forecasts
  • Price recommendations
  • Supply alerts
5 Integrations
4 Connections

What we deliver for consumer products enterprises

Consumer Products AI

From demand sensing to supply chain optimisation, governed, auditable, enterprise-ready

Demand sensing and forecasting

Generate SKU-level demand forecasts from POS and market signals.

ROI

Forecast accuracy+65%
Lost sales reduction20-30%
Forecast cycle timeDaily

Process

1

Ingest demand signals

POS data, e-commerce traffic, weather forecasts, social sentiment, and promotional calendars fused in real time

2

Generate SKU forecasts

AI produces daily and weekly SKU-level demand forecasts with confidence intervals and driver attribution

3

Push to planning systems

Forecasts fed directly to your S&OP, production scheduling, and replenishment systems

Sources

Based on published findings: McKinsey QuantumBlack, 'AI-Driven Demand Sensing', 2024; BCG X, 'The AI-Native CPG Company' — reproduced for illustrative purposes

Dynamic pricing and revenue management

Find optimal price points across your portfolio automatically.

ROI

Margin improvement2-5%
Pricing decisions speed10x faster
Revenue uplift3-7%

Process

1

Model price elasticity

Historical sales, competitive pricing, promotion effects, and channel costs analysed at the SKU-market level

2

Simulate scenarios

AI tests thousands of pricing scenarios against your margin targets, volume goals, and competitive positioning

3

Recommend and track

Price recommendations with expected impact delivered to commercial teams, with actual vs forecast tracking

Sources

Based on published findings: BCG X, 'AI-Powered Pricing in CPG', 2024; McKinsey, 'The Art and Science of Pricing' — reproduced for illustrative purposes

Supply chain optimisation

Predict supply disruptions and recommend reallocation fast.

ROI

Inventory reduction20-30%
Service level+5-8%
Logistics cost-10-15%

Process

1

Map supply chain

Supplier data, logistics networks, inventory positions, and production capacity consolidated from all systems

2

Detect and predict risks

AI identifies supply constraints, transport delays, and demand-supply imbalances before they cascade

3

Recommend actions

Reallocation, rerouting, and production adjustment recommendations with cost and service level impact analysis

Sources

Based on published findings: McKinsey, 'Supply Chain 4.0', 2024; Deloitte Insights, 'AI-Resilient Supply Chains' — reproduced for illustrative purposes

Trade promotion effectiveness

Measure true promotion ROI and cut trade spend waste.

ROI

Trade spend ROI+15-25%
Promotion waste-30%
Planning speed5x faster

Process

1

Collect promotion data

Trade spend records, POS uplift data, baseline sales, and competitive activity aggregated across retailers

2

Decompose promotion ROI

AI separates incremental volume from pull-forward, pantry loading, and cannibalisation effects

3

Optimise future plans

Promotion recommendations by retailer, category, and mechanic with expected ROI projections

Sources

Based on published findings: BCG X, 'Revenue Growth Management', 2024; McKinsey, 'Winning with Trade Promotions' — reproduced for illustrative purposes

Consumer segmentation and personalisation

Segment consumers by behaviour and personalise at scale.

ROI

Campaign conversion+20-35%
Customer LTV+15%
Segmentation accuracy3x improvement

Process

1

Unify consumer data

Purchase history, digital interactions, loyalty data, and demographic signals combined in a privacy-compliant profile

2

Build behavioural segments

AI identifies natural consumer segments based on purchase patterns, preferences, and predicted lifetime value

3

Activate recommendations

Personalised product, content, and offer recommendations pushed to your CRM and digital marketing platforms

Sources

Based on published findings: McKinsey, 'Personalisation at Scale in CPG', 2024; BCG X, 'Consumer-Centric AI' — reproduced for illustrative purposes

New product development intelligence

Identify white-space opportunities from trend and competitor data.

ROI

NPD success rate+25%
Time to insight-60%
Market coverageComprehensive

Process

1

Scan market signals

Consumer reviews, social trends, patent filings, and competitive launches analysed across categories and markets

2

Identify opportunities

AI maps white-space opportunities, emerging needs, and category adjacencies with supporting evidence

3

Score and prioritise

Innovation concepts ranked by market size, competitive intensity, and fit with your capabilities

Sources

Based on published findings: McKinsey, 'AI-Driven Innovation in CPG', 2024; Deloitte Insights, 'Smart Product Development' — reproduced for illustrative purposes

Sustainability and ESG compliance

Automate Scope 1-3 tracking and ESG disclosure reports.

ROI

ESG reporting speed-50%
Data accuracy99%+
Framework coverageCSRD/ISSB ready

Process

1

Aggregate ESG data

Energy, water, waste, packaging, and supply chain emissions data consolidated from operational systems

2

Calculate and benchmark

AI computes Scope 1-3 emissions, packaging metrics, and sustainability KPIs against industry benchmarks

3

Generate disclosures

CSRD, ISSB, and retailer sustainability reports produced with full methodology and audit trails

Sources

Based on published findings: BCG X, 'Sustainable CPG Operations', 2024; McKinsey, 'ESG Data and AI' — reproduced for illustrative purposes

Geraldine Matchett

Co-CEO, Royal DSM (now dsm-firmenich)

Geraldine Matchett

"Microsoft Azure AI enables us to sense demand shifts across our nutrition and materials business weeks earlier than traditional forecasting. We are translating POS signals into production adjustments in near real time, which has materially reduced both waste and stockouts across our global supply chain."

Originally published: Microsoft Customer Stories — DSM — reproduced for illustrative purposes

01 / 04

How we work in consumer products environments

CPG AI is only valuable if it connects to the systems where your commercial decisions are made. We start by mapping your POS feeds, ERP, and supply chain platforms, then identify the one use case where AI will create the most immediate, measurable impact on revenue or margin.

Everything we build runs on your cloud tenant. Your POS data, your pricing models, your supply chain intelligence. None of it goes to a third-party platform. Your finance team and auditors can verify every recommendation the system makes.

01

Data and use case mapping

We assess your POS, ERP, and supply chain systems, identify the highest-value AI use case, and map it to your commercial and compliance requirements.

02

30-day proof of concept

A working AI agent on your cloud, connected to your commercial data, with demonstrable output in 30 days.

03

Governance by design

Audit trails, explainable pricing logic, and compliant data handling built in from the start. Ready for finance review.

04

Scale in 12-18 weeks

From one validated commercial workflow to measurable revenue and margin improvement across your portfolio.

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