Race to ROI — IR AI Playbook NRF 2026
Race to ROI — AI Playbook
Please enter your details to access the full playbook. Your information is kept confidential.
Integrated Retail  ·  NRF 2026  ·  Strategy & Innovation

Race to ROI
AI-Driven Retail Transformation

A practical, evidence-based guide to deploying AI across every commercial function in retail — built from real deployments, real data, and real outcomes.

“

Intelligence is now the only sustainable retail advantage. The retailers gaining ground across Southeast Asia are not those with the largest budgets or the most stores. They are the ones making faster, better-informed decisions — at every level, across every function, and at a speed their competitors cannot match.

That speed is AI. Not as a technology project. Not as a pilot with a dashboard nobody reads after the launch event. AI as a commercial operating system — one that compounds in value every time a new signal is captured, every customer interaction is learned from, and every operational decision is made with better data than the last.

This playbook is built from direct client experience and grounded in the commercial realities of Asian retail: multiple markets, diverse consumer profiles, messaging-native commerce, and the operational complexity of managing physical and digital channels simultaneously. It is designed for retailers who are serious about AI transformation — not as a technology ambition, but as a P&L lever.

Thirty-seven use cases. Six functional tracks. Specific platforms, specific mechanisms, specific commercial outcomes. Start where your greatest pain is. Build the data foundation. Fund each next step from the wins that precede it.

The window is open. Use it.

Integrated Retail (IR)  ·  Strategy & Innovation Practice  ·  NRF 2026
How to read this playbook
Six Tracks. One Connected System.

AI in retail is not a collection of point solutions. It is a compounding intelligence system where every use case makes the next one more powerful. These six tracks represent the full commercial lifecycle of a retail business — from the demand signals that inform what you buy, to the customer intelligence that determines how you grow.

01
PLAN
Store Network Planning · Store Layout Planning · Assortment & OTB Planning · Demand Forecasting · Promo Calendar Planning
02
BUY
Product Design · Product Attribution · Product AI Collaterals · AI-Optimised Size Curves · Buying Analytics & OTB
03
MOVE
Inventory Optimisation · Stock Transfers · Returns Optimisation · Warehouse Management · AI Workflow Automation
04
SELL
Pricing & Promotion · Discovery & Clienteling · Social Commerce & Content · Retail Media Monetisation · Conversational Commerce
05
ANALYZE
Product Intelligence · Customer Intelligence · Unified Customer Journey · Promotions Intelligence · Store Traffic Intelligence
06
GROW
New Market Entry · Brand & Product Extensions · Retail Media & New Channels · Data Monetisation · Share of Wallet
📋
Section A
What AI can do for your business?
37 use cases across 6 functional tracks — each showing the commercial problem, how AI solves it, the ROI you should expect, and the technology that enables it.
🧮
Section B
What could this be worth for you?
Enter your own revenue, margins, and operations metrics and see an indicative AI-enabled value estimate calculated live by track.
✅
Section C
The evidence — delivered and documented
Real outcomes from IR deployments across Southeast Asia alongside global industry evidence. The commercial case for AI in retail is already proven.
🗺️
Section D
How to get started — your roadmap
A practical 4-phase, implementation roadmap with 28 checkable milestones — from data foundations through full AI deployment and programme optimisation.
⚙️
Section E
The technology powering use cases
Platform profiles for every Integrated Retail and Slicer tool featured in this playbook — capabilities, performance benchmarks, and use case mapped.
01
PLAN
Demand signals into commercial precision — before a single unit is ordered or a single lease is signed.
Network · Layout · Assortment · Forecasting · Promo Calendar
01 PLAN P1

Store Network Planning & Expansion Intelligence

ROI
IMPACT
-30%
Poor-site market entry failures
+20%
Faster new store trading ramp-up
⚠ THE PROBLEM
  • 30% of new openings underperform Year 1 plan — location selection is the primary cause, not execution
  • Conventional process cannot process demographic, mobility, competitive and financial signals simultaneously
⚡ HOW AI SOLVES IT
📱
Mobility data
250M+ devices map real catchment demand
🏆
Multi-factor score
Demand, competitive risk, cannibalization ranked
🎓
Estate-trained
Models learn from existing store outcomes
✓ TOP 3 BUSINESS BENEFITS
  • Capital protected from poor-site investment decisions
  • Whitespace markets identified before competitors act
  • Cannibalization risk quantified before every commitment
ENABLING SOLUTIONS
iOptimo + Geo Intelligence Location intelligence platform combining consumer mobility analytics, competitive benchmarking, and geo-demographic scoring calibrated for Southeast Asian retail expansion decisions
KPIs TO BE TRACKED
New store vs pre-opening plan at 12MLocation score accuracy vs actualROI per locationCannibalization rate
01 PLAN P2

Visual Merchandising & Store Layout

ROI
IMPACT
+18%
Revenue per square foot
-50%
Planogram review cycle time
⚠ THE PROBLEM
  • Zone conversion variance of 300–400% within the same store — caused by intuition-based layout decisions made annually
  • High-margin product in low-traffic zones; hero items on legacy floorplans that no longer reflect shopper behaviour
⚡ HOW AI SOLVES IT
📷
FootfallCam
Live zone footfall, dwell & conversion
🔬
Layout sim
Tests changes before fixtures move
📋
Kanvas VM
Bulk store-specific VM guidelines
✓ TOP 3 BUSINESS BENEFITS
  • Evidence replaces gut-feel — planogram decisions continuously improving
  • High-margin product moves to high-conversion zones
  • New product sell-through improves from placement day one
ENABLING SOLUTIONS
FootfallCam + Kanvas VM at Scale FootfallCam captures real-time zone-level footfall, dwell time, and conversion data across the estate. Kanvas VM at Scale converts that intelligence into store-specific VM guidelines generated in bulk — aligned to live stock, sales, and shopper behaviour.
KPIs TO BE TRACKED
Revenue per sq ft by zoneDwell time in target zonesSell-through on repositioned productPlanogram update cycle time
01 PLAN P3

Assortment & OTB Planning

ROI
IMPACT
+15%
Sell-through rate lift
+7%
Gross margin improvement
⚠ THE PROBLEM
  • Uniform national ranges create 20–40pp sell-through variance between clusters — from range mismatch, not poor product
  • Right products land in wrong stores every season — the evidence to fix it exists, but is rarely acted on
⚡ HOW AI SOLVES IT
🗂️
AI clustering
Groups stores by 5 commercial factors
🔍
White space ID
Finds unmet demand and range duplication
📊
Sell-through AI
Predicts depth and breadth per cluster
✓ TOP 3 BUSINESS BENEFITS
  • Right product in right store — driven by data, not convention
  • Eliminate slow-movers caused by range mismatch, not product failure
  • Protect gross margin through demand-aligned buying depth
ENABLING SOLUTIONS
iOptimo + Kanvas Planning / OTB iOptimo drives demand-informed assortment decisions; Kanvas Planning/OTB manages depth, breadth, and open-to-buy across store clusters and channels
KPIs TO BE TRACKED
Sell-through rate by clusterGross margin per SKUAvailability score at size/colourSlow-mover ratio
01 PLAN P4

Demand Forecasting

ROI
IMPACT
-20%
Stockout reduction
+4%
Revenue recovered annually
⚠ THE PROBLEM
  • 35–42% forecast MAPE causes simultaneous stockout in urban stores and overstock in secondary markets — same season, same range
  • End-of-season markdowns driven by planning failure, not product failure — margin destroyed before sell-through ends
⚡ HOW AI SOLVES IT
🧠
Ensemble ML
Trains on 36 months of SKU-store-date history
📡
Live signals
Weather, events, social, competitor data
🎯
Exception alerts
Surfaces the 15% of SKUs driving 60% of error
✓ TOP 3 BUSINESS BENEFITS
  • Eliminate the over-buy vs under-buy trade-off simultaneously
  • Detect demand surges 10–14 days before they appear in sales data
  • Structurally lower markdown rate — every season
ENABLING SOLUTIONS
iOptimo Ensemble ML demand forecasting engine with self-healing recalibration, external signal integration, and exception-alert workflows built for multi-market SEA retail environments
KPIs TO BE TRACKED
Forecast accuracy (MAPE)Stockout rateOverstock % at season-endInventory turn rate
01 PLAN P5

Seasonal & Promotional Calendar Planning

ROI
IMPACT
+25%
Promotional ROI improvement
-30%
Promotional planning cycle time
⚠ THE PROBLEM
  • Same events, same mechanics, same depths every season — no evidence base for what actually generates incremental sales
  • 30–40% of promotional spend delivers no measurable incremental revenue — invisible on gross metrics
⚡ HOW AI SOLVES IT
📈
Causal AI
Isolates genuine uplift from pull-forward
📅
Pre-season model
Optimal mechanic and timing per event
🧪
Scenario testing
Compare options before committing budget
✓ TOP 3 BUSINESS BENEFITS
  • Promotional calendar built on evidence, not convention
  • Eliminate the 30–40% of spend that delivers no uplift
  • Faster planning cycles — data replaces committee debate
ENABLING SOLUTIONS
Kanvas Analytics AI analytics platform providing historical promotion performance modelling, pre-launch ROI prediction, and campaign optimisation across mechanic, channel, and segment
KPIs TO BE TRACKED
Promotion ROI by mechanicIncremental revenue per campaignPromotional waste %Markdown depth vs plan
02
BUY
From trend signal to market-ready product — faster, with higher commercial accuracy than any manual process can achieve.
Design · Attribution · Collaterals · Size Curves · OTB
02 BUY B1

AI-Powered Product Design

ROI
IMPACT
+25%
New product success rate
-30%
Design research cycle time
⚠ THE PROBLEM
  • 30–35% NPD failure — trend intelligence is weeks behind consumer signals by the time the brief is written
  • By the time the product reaches the floor, the trend that informed it may have already peaked
⚡ HOW AI SOLVES IT
🌊
Trend velocity
Momentum scoring, not just trend ID
📊
Sell-through AI
Predicts success before production
📋
AI briefs
Range plans generated in days not weeks
✓ TOP 3 BUSINESS BENEFITS
  • Collections arrive ahead of demand peaks, not after them
  • Production capital directed to highest-confidence opportunities
  • Research-to-brief compressed from weeks to days
ENABLING SOLUTIONS
Kreate (Kanvas / Slicer) AI-powered product design module generating trend-scored mood boards, range ideas, and design briefs from live social and search signals
KPIs TO BE TRACKED
New product sell-through wks 1–8Time to marketNPD failure rateDesign iteration cycles
02 BUY B2

Product Attribution

ROI
IMPACT
-60%
Content creation cost per product
-70%
Time to list new products
⚠ THE PROBLEM
  • 45–60 min of copywriting per product per channel creates backlogs that directly delay revenue realisation
  • Manually written content fails SEO and is invisible to AI discovery platforms (ChatGPT, Gemini, Perplexity)
⚡ HOW AI SOLVES IT
🏷️
Auto-attribution
Full taxonomy from a single photograph
✍️
Brand LLM
Channel-specific copy via RAG architecture
🔍
GEO ready
Structured for AI discovery platform citation
✓ TOP 3 BUSINESS BENEFITS
  • Products live within hours of receipt — not weeks after buying has moved on
  • Brand-consistent, SEO-optimised copy across all channels at scale
  • Discoverable on ChatGPT, Gemini, and Perplexity from day one
ENABLING SOLUTIONS
Katalog AI-powered product cataloguing platform automating annotation, description generation, compliance metadata, and localisation at scale — 1,000+ product variants per hour, with all data internal and secure
KPIs TO BE TRACKED
Content cost per productTime-to-listSEO ranking for category pagesConversion rate on AI-attributed pages
02 BUY B3

AI Product Collaterals & Content Generation

Covers: AI Collaterals + Content Generation + GEO Optimisation
ROI
IMPACT
-60%
Content creation cost per asset
-70%
Time to list new products
⚠ THE PROBLEM
  • 45–60 min per product per channel creates content backlogs — directly delaying revenue realisation at launch
  • Manually written content fails AI discovery platforms now reshaping how consumers find products
⚡ HOW AI SOLVES IT
🖼️
Visual assets
Mood boards, images, collaterals from brief
✍️
Brand LLM
Channel-specific copy via RAG
🔍
GEO ready
Structured for AI discovery citation
✓ TOP 3 BUSINESS BENEFITS
  • Products go live within hours of receipt — not weeks after buying has moved on
  • Brand-consistent, SEO-optimised copy across all channels at scale
  • Discoverable on ChatGPT, Gemini, Perplexity from launch day
ENABLING SOLUTIONS
IR / Slicer + Kreate AI content platform generating visual collaterals, brand-anchored channel copy, and GEO-structured product data for multi-channel and AI-platform discoverability
KPIs TO BE TRACKED
Content cost per productTime-to-listSEO rankingAI platform citation rate
02 BUY B4

AI-Optimised Size Curves

ROI
IMPACT
-20%
Size-driven return rate
-8%
Size stockout rate
⚠ THE PROBLEM
  • M/L stockouts in urban stores and XS/XL overstock in secondary markets — same season, same range, every season
  • Size-related returns represent 15–25% of online apparel volume — entirely preventable with better size intelligence
⚡ HOW AI SOLVES IT
📐
Regional profiles
Sell-through at size × cluster × channel
🔄
Live update
Refreshed quarterly from actual sell-through data
👗
Checkout AI
Individual size recommendations at purchase moment
✓ TOP 3 BUSINESS BENEFITS
  • Size-driven returns reduced before the purchase decision is made
  • Fastest-selling sizes consistently in stock across the estate
  • Overstock in slow sizes structurally eliminated
ENABLING SOLUTIONS
iOptimo + Kanvas Buying & Merchandising Regional size curve modelling from live sell-through and returns data, combined with individual-level size recommendations at checkout to prevent return-driving purchase uncertainty
KPIs TO BE TRACKED
Return rate by size and categorySize sell-through by clusterStockout rate by sizeCustomer satisfaction for fit
02 BUY B5

Buying Analytics & OTB Intelligence

ROI
IMPACT
+30%
Faster ranging decisions
+12%
Sell-through on AI-scored ranges
⚠ THE PROBLEM
  • Delisting decisions deferred without objective evidence; winners under-bought without early-season performance signals
  • Full commercial potential of the range unrealised every season — by convention, not necessity
⚡ HOW AI SOLVES IT
🏅
SKU scoring
Margin × velocity × returns composite rank
⚡
Early winners
Amplify in weeks 3–4, not mid-season
💰
OTB model
Range decisions linked to margin outcomes
✓ TOP 3 BUSINESS BENEFITS
  • Objective evidence for every range and delisting decision
  • Winning products amplified before the demand window closes
  • Buying budget freed from long-tail underperformers structurally
ENABLING SOLUTIONS
Katalog + iPOSit Katalog provides AI-powered product scoring and catalogue intelligence; iPOSit surfaces AI-personalised product recommendations at POS checkout — closing the loop between buying analytics and in-store commercial activation
KPIs TO BE TRACKED
Sell-through on AI-scored rangeRanging decision timeSKU count vs margin contributionOTB efficiency ratio
03
MOVE
From reactive operations to a self-optimising fulfilment system — where every unit is in the right place at the right time.
Inventory · Transfers · Replenishment · Warehouse · Automation · BOPIS
03 MOVE M1

Inventory Optimisation & Real-Time Visibility

Merged: Inventory Replenishment Automation + Real-Time Inventory Visibility
ROI
IMPACT
-25%
Stockout rate
97%+
Inventory accuracy across the estate
⚠ THE PROBLEM
  • 9–12 day replenishment lag means customers who want the product find an empty shelf — and do not wait
  • Inventory accuracy averages 65–75% without RFID — one in three records potentially wrong at any moment
⚡ HOW AI SOLVES IT
🔗
ERP connected
Orders placed before stockout occurs
📡
RFID sync
Item-level accuracy across all locations
🚨
Phantom alerts
Ghost stock detected before customer failures
✓ TOP 3 BUSINESS BENEFITS
  • Replenishment lag eliminated — continuous, automated, demand-driven
  • Online availability reflects physical reality, not system records
  • Ship-from-store and omnichannel fulfilment fully enabled
ENABLING SOLUTIONS
iOptimo + Warewizer + Retail Pro iOptimo drives demand-triggered replenishment; Warewizer manages DC-level stock; Retail Pro is the POS system of record feeding real-time inventory and transaction data; RFID delivers item-level accuracy
KPIs TO BE TRACKED
Stockout rateReplenishment cycle timeATP accuracy by channelInventory accuracy rate
03 MOVE M2

AI-Driven Stock Transfers & Allocation

ROI
IMPACT
-18%
Excess stock in underperforming locations
+12%
Full-price sell-through from rebalanced stock
⚠ THE PROBLEM
  • Hero SKUs selling out in high-demand stores while identical stock heads to markdown in underperformers — simultaneously, every season
  • Manual transfer reviews too slow and infrequent to match the pace of demand imbalances across the estate
⚡ HOW AI SOLVES IT
📡
Live monitoring
Velocity imbalances spotted in real time
🎯
Optimal routing
SKU × quantity × store recommendation
💰
Net ROI check
Logistics vs sell-through uplift validated
✓ TOP 3 BUSINESS BENEFITS
  • Slow-moving stock rescued before markdown — at a fraction of the markdown cost
  • High-demand locations capture full-price revenue instead of losing to empty shelves
  • Transfer opportunity to action compressed from review cycle to real time
ENABLING SOLUTIONS
iOptimo + Warewizer + Retail Pro iOptimo identifies network-level sell-through imbalances and recommends transfers; Warewizer executes transfer orders with proof of receipt; Retail Pro provides the real-time inventory position across all locations
KPIs TO BE TRACKED
Transfer execution rateFull-price sell-through on transferred stockMarkdown rate reductionStock imbalance index
03 MOVE M3

Returns Optimisation

ROI
IMPACT
-20%
Overall return rate
+20%
Recovered stock value from returns
⚠ THE PROBLEM
  • 25% online return rate = reverse logistics on 1 in 4 items — $8–15M annual drain on a $100M online base
  • Return policy treats the symptom; purchase uncertainty is the cause — and it must be addressed before the decision is made
⚡ HOW AI SOLVES IT
🛡️
Pre-purchase AI
High-return risk flagged at checkout
🔄
Smart routing
Best disposition per item, automatically
🔍
Root cause
Fixes fed back to Buy and content teams
✓ TOP 3 BUSINESS BENEFITS
  • Return volume reduced before the purchase decision is made
  • Maximum value recovered from every unavoidable return
  • Root causes identified and fixed — not absorbed as permanent cost
ENABLING SOLUTIONS
Returns AI + iOptimo AI returns prevention engine combining purchase-point intervention, intelligent disposition routing, and root cause analytics that feeds back into buying and content decisions to prevent future returns
KPIs TO BE TRACKED
Return rate by category/channelReverse logistics cost per returnRecovery value rateRoot cause resolution time
03 MOVE M4

Warehouse & DC Management

ROI
IMPACT
-15%
DC operating cost per unit
+25%
Pick efficiency improvement
⚠ THE PROBLEM
  • DCs at 70–80% theoretical throughput — slotting, routing and labour allocation all improvable by evidence, not capital
  • Mis-picks generate returns, reprocessing costs and customer service contacts — prevention is cheaper than remedy
⚡ HOW AI SOLVES IT
📦
Smart slotting
Velocity-based positions updated continuously
🗺️
Optimised paths
Pick routes minimise floor travel per batch
👥
Labour planning
Proactive deployment by zone and hour
✓ TOP 3 BUSINESS BENEFITS
  • 25% pick efficiency gain without additional capital investment
  • Pick accuracy improved to 99%+ through AI optimisation
  • Throughput capacity recovered from existing footprint — no new space
ENABLING SOLUTIONS
Warewizer AI-powered DC intelligence platform providing velocity-based slotting, pick path optimisation, labour planning by zone and hour, and predictive throughput modelling
KPIs TO BE TRACKED
Pick accuracy rateOrders per hour per operativeDC cost per unitOutbound despatch lead time
03 MOVE M5

AI Workflow Automation

ROI
IMPACT
-60%
AP processing cost per invoice
-50%
Vendor onboarding cycle time
⚠ THE PROBLEM
  • Manual invoice processing and vendor onboarding consume finance capacity better used on strategic commercial work
  • Systematic data entry errors generate supplier disputes, delayed payments, and strained relationships at scale
⚡ HOW AI SOLVES IT
📄
Document AI
Invoices matched to PO without human touch
🏢
Auto-onboarding
Vendor docs checked and provisioned in days
🔀
Smart routing
Exceptions only are escalated to human review
✓ TOP 3 BUSINESS BENEFITS
  • Finance teams freed for strategic commercial and analytical work
  • Supplier relationships built on reliability, not processing delays
  • Error-driven disputes eliminated from the supplier base structurally
ENABLING SOLUTIONS
IR / Slicer Platform Document intelligence and process automation covering invoice processing, vendor onboarding, compliance checking, and payment reconciliation with AI-driven exception management
KPIs TO BE TRACKED
Invoice processing timeError rateAP cost per invoiceVendor onboarding cycle time
03 MOVE M6

BOPIS & Omnichannel Fulfilment Optimisation

ROI
IMPACT
-17%
Fulfilment cost vs home delivery
+10%
Incremental in-store basket on collection
⚠ THE PROBLEM
  • Failed pickups destroy BOPIS value in a single interaction — trust lost, cost advantage negated
  • Product shown online as available for collection is not physically present — the most common and most damaging failure mode
⚡ HOW AI SOLVES IT
📍
Pre-position
Stock moved before orders are placed
✅
Verified ATP
Physical stock confirmed, not system records
🔔
Exception alerts
Failures flagged before any promise is made
✓ TOP 3 BUSINESS BENEFITS
  • Every collection promise physically fulfilled — reliably, not just in theory
  • Fulfilment cost 17% below home delivery — captured consistently
  • Incremental in-store basket on every collection visit
ENABLING SOLUTIONS
iOptimo + Cegid Retail iOptimo pre-positions stock and verifies physical ATP before any BOPIS promise is made; Cegid Retail executes the unified commerce fulfilment and in-store collection workflow
KPIs TO BE TRACKED
BOPIS availability rate at order placementFulfilment cost vs deliveryPickup satisfactionIncremental basket on collection
03 MOVE M7

AI-Powered Staff Scheduling

ROI
IMPACT
-10%
Labour cost as % of revenue
+22%
Peak-hour coverage compliance
⚠ THE PROBLEM
  • Overstaffed in quiet periods; critically understaffed during peak hours that determine whether the week meets plan
  • Labour is the largest controllable cost in physical retail — and the most measurably responsive to data-driven optimisation
⚡ HOW AI SOLVES IT
📊
Demand forecast
Hourly prediction at individual store level
📋
Roster AI
7-day rolling recommendations with lead time
⚠️
Coverage alerts
Gaps flagged days ahead, not on the trading day
✓ TOP 3 BUSINESS BENEFITS
  • Labour overspend in off-peak periods structurally reduced
  • Peak hours fully staffed — conversion rate and basket protected
  • Scheduling administration eliminated for store managers
ENABLING SOLUTIONS
FootfallCam + Cegid Retail FootfallCam provides live traffic data and predicted demand peaks; Cegid Retail's Operational Excellence module translates that intelligence into store-level task and staff management
KPIs TO BE TRACKED
Labour cost as % of revenueCoverage vs demand ratio by hourScheduling admin time per store/weekEmployee satisfaction
04
SELL
Precision commerce at every touchpoint — protecting margin, converting browsers, and building the loyalty that sustains a retail brand.
Pricing · Discovery · Social · Retail Media · Conversational
04 SELL S1

Pricing & Promotion Intelligence

Merged: Markdown Optimisation + Pricing & Margin Management + Dynamic Pricing
ROI
IMPACT
+7%
Gross margin recovered on marked-down stock
-20%
Terminal stock at season-end
⚠ THE PROBLEM
  • Markdowns triggered by calendar dates, not velocity — margin recovery window closing when action finally begins
  • Freight, FX, and competitor pricing change monthly; manual review cycles absorb every preventable margin move
⚡ HOW AI SOLVES IT
📉
Velocity watch
Slow-movers flagged weeks 4–6, not 10–11
💹
Live monitoring
COGS, FX, competitor pricing continuously
🎯
Elasticity model
Minimum discount to achieve the commercial target
✓ TOP 3 BUSINESS BENEFITS
  • Gross margin protected before the recovery window closes
  • Real-time cost and competitive price defence automated
  • Season-end markdown variance structurally reduced every season
ENABLING SOLUTIONS
iOptimo + Kanvas Buying & Merchandising + Retail Pro iOptimo detects margin threats and markdown triggers; Kanvas B&M provides sell-through and competitive pricing analysis; Retail Pro executes approved price changes at POS across the estate
KPIs TO BE TRACKED
Terminal stock % at season-endGross margin on sold-throughMarkdown depth vs planPrice competitiveness index
04 SELL S2

Personalised Discovery & Clienteling

ROI
IMPACT
+18%
Average order value
+15%
Conversion rate on recommendation-active pages
⚠ THE PROBLEM
  • 2–4% conversion on category pages reflects the probability of finding a product by browsing — not by guidance
  • In-store: only associates with personal relationships can personalise — a structural cap on VIP service delivery
⚡ HOW AI SOLVES IT
🤖
Transformer AI
Learns sequence and combination of preferences
🌈
Diversity control
Prevents filter bubbles, surfaces new discovery
⚡
Real-time delivery
Recommendations across every digital touchpoint
✓ TOP 3 BUSINESS BENEFITS
  • Browsing sessions converted to multi-item purchases
  • Product discovery for customers who never find items by browsing
  • Repeat purchase driven by personalised post-purchase triggers
ENABLING SOLUTIONS
Kanvas Analytics + Allegory AI + iPOSit Kanvas Analytics powers personalised recommendation algorithms; Allegory AI extends discovery in-store via QR-activated product guidance; iPOSit drives upsell at the POS secondary screen with AI-personalised basket promotions
KPIs TO BE TRACKED
Average order valueRecommendation click-through rateConversion rate upliftRevenue per session
04 SELL S3

Social Commerce & Content

Merged: Social Media Management + AI Content Generation & GEO + Influencer Marketing AI
ROI
IMPACT
-50%
Content production time per asset
+25%
Organic and AI-platform discovery traffic
⚠ THE PROBLEM
  • Manual management of TikTok, Instagram, LINE and web simultaneously is unsustainable at the cadence SEA audiences expect
  • Traditional SEO misses AI discovery platforms (ChatGPT, Gemini, Perplexity) now reshaping how consumers find products
⚡ HOW AI SOLVES IT
⚙️
Auto-schedule
Optimised cadence per platform independently
✍️
GenAI content
Brand-anchored copy at social media velocity
🔍
GEO structure
Visible on AI discovery platforms simultaneously
✓ TOP 3 BUSINESS BENEFITS
  • Social presence at required velocity — without scaling headcount
  • Engagement rates lift from platform-native AI-optimised content
  • Organic discoverability built for next-generation search platforms
ENABLING SOLUTIONS
IR / Slicer + GenAI Platform Social commerce AI combining automated scheduling, engagement optimisation, brand-anchored generative content creation, and GEO structuring for both traditional and AI-powered discovery
KPIs TO BE TRACKED
Content cost per assetSocial-driven revenueOrganic search rankingAI platform citation rate
04 SELL S4

Retail Media Monetisation

ROI
IMPACT
$1–2M
Annual advertising revenue (100-store estate)
+20%
Brand campaign conversion vs untargeted
⚠ THE PROBLEM
  • 400 screens across 100 stores display brand content — a cost centre. Brands urgently need verified purchase-intent audiences
  • With third-party cookies deprecated, first-party screen inventory at point of purchase is precisely the product brands seek
⚡ HOW AI SOLVES IT
👁️
Audience AI
Demographic detection — fully privacy compliant
🎯
Matched content
Brand creative served to the right audience
💹
Programmatic
Screen inventory monetised per verified impression
✓ TOP 3 BUSINESS BENEFITS
  • New high-margin revenue stream from existing screen assets — no capex
  • Brand partners receive verified, accountable media metrics
  • Post-cookie first-party media owner position established
ENABLING SOLUTIONS
FootfallCam + Allegory AI FootfallCam delivers audience detection for screen-based retail media; Allegory AI serves sponsored product recommendations within QR-activated in-store shopper conversations — two distinct retail media surfaces, both monetisable
KPIs TO BE TRACKED
Total media revenueActive brand advertisersCPM rates vs benchmarkAttributed sales uplift per campaign
04 SELL S5

Conversational Commerce & Loyalty

Merged: Conversational Commerce (Agentic) + Loyalty Personalisation
ROI
IMPACT
+25%
Messaging channel conversion rate
3×
Loyalty offer redemption rate lift
⚠ THE PROBLEM
  • WhatsApp and LINE carry higher engagement than any ecommerce channel in SEA — most retailers remain absent from them
  • Loyalty broadcast to all members on the same Tuesday: 6–10% redemption, 90% of spend irrelevant or given away free
⚡ HOW AI SOLVES IT
💬
Agentic AI
Full transactions completed in WhatsApp and LINE
🌏
Multi-language
English, Bahasa, Thai, Mandarin natively
🎁
Individual offers
Minimum depth to trigger incremental spend only
✓ TOP 3 BUSINESS BENEFITS
  • Revenue from channels where Southeast Asian customers actually are
  • The 30–40% of loyalty spend that rewards full-price buyers eliminated
  • 24/7 commerce capability without human agent resource
ENABLING SOLUTIONS
IR / Slicer Platform + iPOSit IR / Slicer Platform powers agentic AI commerce on WhatsApp, LINE, and brand app with full transaction capability and individual-level loyalty offer optimisation; iPOSit builds repeat visit frequency through intelligent e-coupon delivery at POS
KPIs TO BE TRACKED
Messaging conversion rateLoyalty redemption vs generic controlActive member rateRevenue from conversational commerce
04 SELL S6

Outfit Recommendations, Virtual Stylist & Try-On

Merged: Outfit Recommendation + Virtual Stylist + Virtual Try-On
ROI
IMPACT
+20%
Average order value from guided sessions
-25%
Apparel return rate
⚠ THE PROBLEM
  • Products shown in isolation — customers leave without items they would have bought with guidance
  • 25–35% of apparel returns driven by fit and style uncertainty — return policy manages the cost, does not prevent the cause
⚡ HOW AI SOLVES IT
👗
Outfit AI
Cross-sell combinations from the live catalogue
💬
Virtual stylist
Guided buying for customers showing hesitation
🪞
AR try-on
Photorealistic fit before the purchase decision
✓ TOP 3 BUSINESS BENEFITS
  • AOV lifted through guided multi-item outfit sessions
  • Fit uncertainty addressed before purchase — not after via returns
  • Return rate structurally lower in every try-on-enabled category
ENABLING SOLUTIONS
AR Platform + Style Intelligence AI Style Intelligence AI generates outfit combinations from the live catalogue and guides indecisive shoppers; AR Platform delivers photorealistic virtual try-on before the purchase decision — directly reducing fit-related returns
KPIs TO BE TRACKED
AOV on guided sessionsTry-on engagement rateReturn rate: try-on vs non-try-onConversion uplift on AI-assisted sessions
04 SELL S7

Smart Clienteling & In-Store AI

Merged: Smart Clienteling + In-Store Experience AI
ROI
IMPACT
+15%
In-store basket size (clienteled transactions)
+15%
Repeat purchase rate for clienteled customers
⚠ THE PROBLEM
  • Only associates with personal relationships can personalise — a structural cap on estate-wide VIP experience delivery
  • High-value loyalty members receive generic service from associates who have no access to their customer intelligence
⚡ HOW AI SOLVES IT
📱
Customer brief
History, preferences, next-best-action on device
🎯
Visit-specific
Recommendations calibrated to current browse context
💰
Revenue link
Every interaction attributed to purchase outcome
✓ TOP 3 BUSINESS BENEFITS
  • Every associate delivers VIP-level service to every loyalty customer
  • Basket size lifted through contextually relevant, data-driven recommendations
  • Repeat visits driven by customers who feel genuinely known
ENABLING SOLUTIONS
Kanvas Analytics + Cegid Retail Kanvas Analytics surfaces customer intelligence and next-best-action on the associate device; Cegid Retail provides the in-store associate platform and task management layer for clienteling delivery
KPIs TO BE TRACKED
Basket size: clienteled vs non-clienteledClienteling conversation rateRepeat purchase rateCustomer satisfaction
04 SELL S8

Trade Promotion Optimisation

ROI
IMPACT
+15%
Trade ROI improvement
-15%
Wasted trade spend
⚠ THE PROBLEM
  • Trade spend driven by relationships and convention — low-ROI mechanics persist without a data-based challenge framework
  • No systematic evidence to distinguish genuine sell-out uplift from pull-forward and category cannibalisation
⚡ HOW AI SOLVES IT
🔬
Causal model
True uplift separated from pull-forward and cannibalization
💰
Spend optimiser
Allocation across brands, channels, mechanics
📊
Partner dashboard
Evidence shared with brands for joint planning
✓ TOP 3 BUSINESS BENEFITS
  • Trade investment directed to mechanics that genuinely drive sell-out
  • Wasted spend recovered as gross margin or reinvested
  • Evidence-based brand planning replaces relationship negotiation
ENABLING SOLUTIONS
Kanvas Analytics Trade promotion intelligence providing mechanic-level ROI attribution, spend optimisation modelling, and partner-facing performance dashboards for evidence-based joint planning
KPIs TO BE TRACKED
Trade ROI by brand/channelSell-out rate on supported productsTrade spend as % of revenueBrand partner satisfaction
04 SELL S9

AI Couponing & Triggered Promotional Mechanics

Merged: AI-Powered Couponing + Hourly Deal Triggers
ROI
IMPACT
3×
Coupon redemption vs generic offer
+15%
Targeted product sales in triggered windows
⚠ THE PROBLEM
  • Generic coupons reward customers who would have bought anyway — 60–70% of offer spend is commercially wasted
  • Static promotional calendars miss real-time inventory and traffic signals that should be determining when and to whom to offer
⚡ HOW AI SOLVES IT
🎯
Propensity AI
Right offer, right customer, right moment
⚡
Live triggers
Traffic and inventory signals auto-launch offers
🧪
A/B learning
Every campaign improves precision of the next
✓ TOP 3 BUSINESS BENEFITS
  • Only customers who genuinely need an incentive receive one
  • Slow-movers cleared in real time by triggered demand
  • Offer precision compounds — each campaign better than the last
ENABLING SOLUTIONS
IR / Slicer Platform Propensity-based personalised offer engine with real-time inventory and traffic signal triggers — delivering AI-timed promotional interventions at the individual customer level and live in-store commercial moment
KPIs TO BE TRACKED
Coupon redemption rate vs controlAOV uplift from couponsCost per redemptionSlow-mover clearance in triggered windows
05
ANALYZE
From data density to commercial intelligence — the engine that makes every other track smarter with every transaction processed.
Product Intel · Customer · Journey · Promotions · Traffic
05 ANALYZE A1

Product Intelligence & Sentiment AI

Merged: Product Performance Scoring + Long-Tail SKU Rationalisation + Sentiment Analysis
ROI
IMPACT
+10%
Sell-through on AI-scored range
-25%
Issue detection-to-resolution time
⚠ THE PROBLEM
  • Long-tail SKUs persist without objective scoring — buying budget consumed by underperformers every season without challenge
  • Quality failures amplify on social channels for days before appearing in management metrics — preventable damage absorbed as cost
⚡ HOW AI SOLVES IT
🏅
SKU scoring
Margin × velocity × returns composite rank
💬
NLP sentiment
100% of reviews and social in real time
🔔
Action alerts
Intelligence routed to the right function
✓ TOP 3 BUSINESS BENEFITS
  • Delist decisions made on objective, reproducible evidence
  • Quality issues caught and closed in days, not weeks
  • Customer feedback closes the loop to buying — structurally
ENABLING SOLUTIONS
Kanvas Analytics + Allegory AI Kanvas Analytics scores SKU performance and monitors NLP sentiment across reviews and social; Allegory AI feeds anonymised real-time shopper query intelligence from in-store interactions — closing the loop between what customers ask and what buyers decide
KPIs TO BE TRACKED
Sell-through on AI-scored rangeRanging decision speedAverage product rating trendIssue resolution time
05 ANALYZE A2

Customer Intelligence

Merged: Customer Segmentation + High-LTV Segment + Churn Prediction
ROI
IMPACT
15%
Churned revenue recovered in first campaign cycle
+25%
Revenue from top customer segments
⚠ THE PROBLEM
  • High-LTV customers treated identically to infrequent transactors — value leakage across the most commercially important cohort
  • Churn identified after full lapse (3–5% recovery) not at first signal (20–30% recovery) — timing is the entire difference
⚡ HOW AI SOLVES IT
🗂️
Segmentation
Behaviour-based clusters from actual purchases
👑
High-LTV AI
Precision upsell and premium experience activation
⚠️
Churn signals
90-day prediction before full lapse occurs
✓ TOP 3 BUSINESS BENEFITS
  • Marketing investment directed to highest-return customers only
  • Upsell activated before the purchase window closes
  • At-risk customers recovered at 20–30%, not 3–5%
ENABLING SOLUTIONS
Kanvas Analytics AI analytics platform combining behavioural segmentation, high-LTV identification, and 90-day churn prediction — enabling precision marketing investment and automated retention interventions at individual customer level
KPIs TO BE TRACKED
Churn rateWin-back campaign conversionCLV by segmentUpsell/cross-sell conversion rate
05 ANALYZE A3

Unified Customer Journey

Merged: Unified Customer Profile + Customer Journey Analytics + Retail Data Platform (CDP)
ROI
IMPACT
+20%
Campaign response rate on unified profiles
-15%
Cart abandonment rate
⚠ THE PROBLEM
  • Customer data sits in 5–9 disconnected systems — every downstream AI use case runs on a fragment of the customer
  • A customer with 10 years of purchase history appears as a new visitor online — and is treated as one
⚡ HOW AI SOLVES IT
🔗
Identity AI
Probabilistic match across all source systems
👤
Live profile
Updated within hours of every interaction
🗺️
Journey map
Drop-offs and CX investment ranked by ROI
✓ TOP 3 BUSINESS BENEFITS
  • Every system sees the same complete, real-time customer
  • Cross-channel attribution becomes accurate and commercially defensible
  • CX investment prioritised by evidence of commercial impact
ENABLING SOLUTIONS
IR / Slicer Platform + Retail Pro + RFE Bridge Retail Pro feeds POS transaction data into the IR / Slicer Platform; RFE Bridge connects ERP and WMS systems through a governed integration layer; IR / Slicer Platform unifies all customer data via probabilistic identity resolution and surfaces the unified omnichannel journey
KPIs TO BE TRACKED
Profile completeness rateData latency (event to profile)Cross-channel attribution accuracyCart abandonment rate
05 ANALYZE A4

Promotions Intelligence

Merged: Promotion Effectiveness Prediction + AI Campaign Performance Prediction
ROI
IMPACT
+35%
Promotion ROI improvement
+30%
Campaign ROAS improvement
⚠ THE PROBLEM
  • 30–40% of promotional spend delivers no measurable incremental revenue — invisible on the gross metrics every post-mortem uses
  • Post-mortems reach the same inconclusive conclusion every time — because the causal evidence infrastructure does not exist
⚡ HOW AI SOLVES IT
🔬
Causal model
Separates uplift from pull-forward and cannibalization
🔮
Pre-launch AI
Predicts ROAS before a dollar is committed
📊
Post-campaign
Root cause built into the next planning cycle
✓ TOP 3 BUSINESS BENEFITS
  • Underperforming campaigns avoided before they run and waste budget
  • ROAS optimised on causal evidence, not correlation
  • Promotional intelligence compounds — better with every campaign
ENABLING SOLUTIONS
Kanvas Analytics AI promotional intelligence platform combining historical ROI attribution (separating genuine uplift from pull-forward and cannibalization) with pre-launch campaign performance prediction and post-campaign causal root cause analysis
KPIs TO BE TRACKED
Promotion ROI by mechanic/segmentCampaign ROASMedia budget efficiencyPromotional waste reduction %
05 ANALYZE A5

Store Traffic Intelligence

Merged: Traffic Monitoring & Analytics + Store Traffic Prediction
ROI
IMPACT
-25%
Average customer wait time
+10%
In-store conversion rate
⚠ THE PROBLEM
  • Staffing and stock react to demand instead of anticipating it — peak hours lost to under-preparation that was preventable
  • Queue build-ups detected when customers are already frustrated — not 48 hours earlier when a roster change was still possible
⚡ HOW AI SOLVES IT
👁️
Live vision
Footfall, queue, congestion in real time
📈
Traffic AI
Daily and hourly forecasts with days of lead time
🔔
Action alerts
Specific roster and stock recommendations
✓ TOP 3 BUSINESS BENEFITS
  • Peak periods planned days ahead — not scrambled for on the day
  • Queue intervention before customers decide to leave the store
  • Live footfall shared input that sharpens VM, scheduling and promotion AI
ENABLING SOLUTIONS
FootfallCam + Kanvas Analytics FootfallCam captures live bi-directional footfall, zone dwell time, queue formation, and conversion rates across the estate; Kanvas Analytics builds predictive traffic models and surfaces actionable staffing and stock recommendations
KPIs TO BE TRACKED
Queue length and avg wait timeStaffing efficiency vs demandIn-store conversion rateNPS for in-store experience
06
GROW
The capabilities built in Tracks 1–5 create assets. The GROW track points them outward — toward new markets, new revenue streams, and a structurally superior business model.
Market Entry · Extensions · Media · Data · Wallet · Equity
06 GROW G1

New Market Entry Intelligence

ROI
IMPACT
-35%
Poor-site market entry failures
+20%
Faster trading ramp-up in AI-scored markets
⚠ THE PROBLEM
  • 30% of new openings underperform their Year 1 plan — location selection is the primary identified cause of failure
  • Real estate visits and local research cannot simultaneously process the volume of signals that determine location success
⚡ HOW AI SOLVES IT
📱
Mobility data
250M+ devices verify actual catchment demand
🏆
Multi-factor score
Demand, risk, and cannibalization ranked
🎓
Estate-trained
Models calibrated on actual performance outcomes
✓ TOP 3 BUSINESS BENEFITS
  • Capital protected from poor-site market entry decisions
  • Whitespace markets captured before competitors act on the same signal
  • Expansion decisions compressed from months to weeks of analysis
ENABLING SOLUTIONS
iOptimo + Geo Intelligence Platform Location intelligence platform combining existing estate performance data, mobility analytics, competitive mapping, and demographic scoring to produce evidence-based market entry rankings for SEA expansion decisions
KPIs TO BE TRACKED
New market vs pre-entry plan at 12MDecision lead timeExpansion ROI vs historicalCannibalization rate on existing estate
06 GROW G2

Brand & Product Extensions via AI Intelligence

ROI
IMPACT
+20%
Incremental revenue from new category or brand entry
-40%
New product range failure rate vs convention-driven entry
⚠ THE PROBLEM
  • Range expansion driven by supplier relationships and buyer intuition — not evidence of what existing customers are actively seeking but not finding
  • Adjacent category demand sits in customer behaviour data but is never surfaced — missing incremental revenue available from the existing base
⚡ HOW AI SOLVES IT
🔍
Demand gap AI
Adjacent categories customers buy elsewhere
🏆
Opportunity rank
Scored by demand, whitespace, supply access
🧪
Test & learn
AI-optimised range trials with early scoring
✓ TOP 3 BUSINESS BENEFITS
  • Extend into categories where customer demand is already evidenced — not assumed
  • Reduce extension failure risk through AI-scored demand validation before commitment
  • Grow revenue from existing customers without new acquisition cost
ENABLING SOLUTIONS
Kanvas Analytics + IR / Slicer Platform AI demand gap and market opportunity analysis identifying adjacent category and brand extension opportunities from existing customer purchase behaviour and market signals
KPIs TO BE TRACKED
Incremental revenue from new categoriesNew range sell-through vs baselineCustomer adoption rate of extensionsExtension ROI vs conventional range entry
06 GROW G3

Retail Media & New Channel Revenue

Merged: Full-Stack Retail Media Network + New Channel Orchestration
ROI
IMPACT
$4–10M
New high-margin annual revenue potential
70%+
Gross margin on media and platform revenue
⚠ THE PROBLEM
  • CDP, screen inventory and commerce AI built for operations have already created three monetisable commercial assets
  • With cookies deprecated, brands urgently need verified purchase-intent audiences — retailers with first-party data have them now
⚡ HOW AI SOLVES IT
📺
Media network
Screens monetised — in-store and online
🛒
New channels
TikTok Shop, Shopee, WhatsApp activated by AI
🔗
Closed-loop
Every impression attributed to purchase outcome
✓ TOP 3 BUSINESS BENEFITS
  • New revenue at 70%+ gross margin from assets that already exist
  • Multi-channel commerce activated without proportional headcount increase
  • Brand partner relationships strengthened as first-party media owner
ENABLING SOLUTIONS
IR / Slicer + Retail Media Platform Full-stack retail media and new channel commerce platform combining programmatic screen advertising, sponsored digital placements, and AI-orchestrated multi-channel commerce activation with closed-loop purchase attribution
KPIs TO BE TRACKED
Total media revenueActive brand advertisersNew channel GMVGross margin on platform revenue streams
06 GROW G4

Data Intelligence Monetisation

ROI
IMPACT
$1–5M
Annual data intelligence recurring revenue
85%+
Gross margin on insights products
⚠ THE PROBLEM
  • 4M verified purchase records held — brand partners would pay significant fees to access this intelligence, and most do not know it
  • Unlike digital platform data, retail transaction data is verified purchase behaviour — the gold standard of consumer intelligence
⚡ HOW AI SOLVES IT
📊
Productised data
Intelligence packaged as tiered subscriptions
🤖
AI analysis
Reports auto-generated at scale from raw data
🔒
PDPA compliant
Clean rooms protect raw customer-level data
✓ TOP 3 BUSINESS BENEFITS
  • High-margin ARR from an asset continuously enriched by normal trading
  • Brand relationships become strategic intelligence partnerships
  • Data network effects compound — more transactions, more value, structurally
ENABLING SOLUTIONS
IR / Slicer Platform + RFE Bridge + Data Intelligence Infrastructure IR / Slicer Platform packages first-party purchase data into tiered brand intelligence products; RFE Bridge provides the secure integration control plane; privacy-preserving collaboration meets PDPA compliance
KPIs TO BE TRACKED
Annual recurring revenue from data productsBrand/supplier subscribersData product NPSSubscriber renewal rate
06 GROW G5

AI-Powered Share of Wallet Expansion

ROI
IMPACT
+15%
Revenue per existing customer within 12 months
3–5×
Return vs equivalent new customer acquisition spend
⚠ THE PROBLEM
  • Every existing customer spends more in total than they spend with you — AI identifies precisely where the spend is going
  • 3–5× higher return vs equivalent new customer acquisition spend on the same commercial growth objective
⚡ HOW AI SOLVES IT
🔍
Gap analysis
Category spend leaking to rivals identified
📊
Opportunity rank
Wallet gaps ranked by recovery probability
🎯
Precision activation
Targeted campaigns with incrementality tracking
✓ TOP 3 BUSINESS BENEFITS
  • Revenue from customers already won — at a fraction of acquisition cost
  • Marketing investment directed to highest-return wallet expansion targets
  • Higher share of wallet hardens competitive displacement — structurally
ENABLING SOLUTIONS
Kanvas Analytics + IR / Slicer Platform AI wallet gap analysis combining first-party purchase history with category spend benchmarking and lifestyle signals to identify and activate targeted share-of-wallet expansion opportunities per customer and segment
KPIs TO BE TRACKED
Share of wallet by segment and categoryRevenue per customer YoY growthCross-category purchase penetration rateCustomer spend concentration vs estimated total addressable spend
06 GROW G6

Customer Equity as a Strategic Asset

ROI
IMPACT
+20%
Capital allocation efficiency to highest-equity segments
Measurable
Business valuation uplift where customer equity growth is demonstrated
⚠ THE PROBLEM
  • Revenue tells you where you have been. Customer Equity tells you where you are going — and most boards cannot see it
  • Capital allocated by historical trading, not forward customer value — the metric sophisticated investors use to assess future worth
⚡ HOW AI SOLVES IT
💰
CLV modelling
Forward value for every customer in the base
📈
Equity dashboard
Real-time base health visibility for leadership
🎯
Capital AI
Investment linked to forward equity return
✓ TOP 3 BUSINESS BENEFITS
  • Customer base valued as the compounding financial asset it is
  • Strategic decisions anchored to forward customer value, not historical revenue
  • Retention elevated to board-level growth imperative with financial language
ENABLING SOLUTIONS
Kanvas Analytics + IR / Slicer Platform AI customer equity modelling platform quantifying the forward revenue value of the entire customer base by cohort, segment, and lifecycle stage — providing leadership with a financial asset lens for capital allocation and strategic planning
KPIs TO BE TRACKED
Total customer equity value by cohort and segmentCustomer equity growth rate YoYRevenue contribution from top 20% equity tierCustomer equity per new market or channel entered

Interactive ROI Calculators

Two purpose-built AI ROI calculators. Adjust the sliders — results update instantly on the right.

Katalog — ROI Calculator

Model the annual savings Katalog generates by automating product cataloguing. Adjust the sliders to match your business inputs.

About Katalog

Katalog automates product cataloguing at retail scale — eliminating manual effort across annotation, description generation, compliance metadata, and localisation. Built on purpose-specific LLMs with Retrieval-Augmented Generation tuned to your cataloguing schema, Katalog processes 800+ product variants per hour. All data stays internal on distilled local models. The result: faster time-to-shelf, superior product discoverability, and measurable ROI within weeks of deployment through labour savings alone.

Your Business Inputs
Product Volume
New Products per Month250
Number of new product variants introduced per month
Effort per Product (minutes) & Relevance Factor (%)
Annotation effort10 min
Relevance to your business100%
Product descriptions (AEO)20 min
Relevance to your business100%
Compliance content20 min
Relevance to your business100%
Attribute localisation10 min
Relevance to your business100%
Set to 0% for single-market retailers
Metadata confirmation audit5 min
Relevance to your business100%
0% fashion · 100% health supplements
Economics
Scale reduction factor50%
Reduction from economies of scale and supplier data quality
Annual salary — cataloguing resource$50,000
Katalog license fee$200/mo
Your ROI — Live Results
Human effort / month
—
person-hours
Katalog time / month
—
hours
Annual labour saving
—
USD per year
Annual Katalog cost
—
license + tokens
Saving by activity
Annotation—
Product descriptions—
Compliance content—
Localisation—
Audit—
Net annual saving
—
Return on investment
—
Payback period—

Excel model: 833 products/hr · 2,208 FTE hrs/year · $10/mo token cost (fixed). Indicative only.

The evidence — delivered and documented

Real outcomes from IR deployments across Southeast Asia alongside global industry evidence. The commercial case for AI in retail is already proven.

📋
Real outcomes. Real deployments. IR-delivered results from Southeast Asian retail clients (brand names withheld) alongside publicly documented global evidence.

IR-delivered — SEA retail deployments

03 MOVE 4 deployments
Online-to-offline integration & operations standardisation
A SEA multi-brand lifestyle group
Reduced data confirmation delays by 5–6 days. WMS, CRM, ecommerce and financial reporting unified for the first time.
Online-to-offline sales fulfilment at scale
A global footwear retailer
38% of total sales fulfilled via online-to-offline — omnichannel fulfilment as a primary revenue channel, not a workaround.
Operational cost reduction & process automation
A specialty lifestyle retailer
20% reduction in promotions set-up and vendor reconciliation — one man-month per month saved across a team of five.
Inventory & financial reporting acceleration
A fashion group
Month-end sales close reduced by 15–20 days. Seamless O2O inventory reporting and financial accounting achieved simultaneously.
04 SELL 2 deployments
Omnichannel customer engagement and loyalty
A fashion & accessories omnichannel brand
+20% incremental sales from omnichannel engagement — the direct result of connecting channels around a unified customer identity.
Messaging commerce & digital modernisation
A sportswear & lifestyle brand
LINE chatbot commerce deployed — one of the first messaging-channel deployments for this retailer. Full IT stack migrated to cloud.
05 ANALYZE 3 deployments
CRM operations, data integration & cost reduction
A global beauty group
10 mandays/month eliminated from CRM reconciliation. Full API integration with global ERP template achieved.
Data-driven operations & loyalty deployment
A multi-brand retail group
Sales reporting to brand partners reduced from 14 days to 7 days. Customer loyalty programme deployed for profiling and engagement.
Unified real-time data for faster commercial decisions
A specialty baby & maternity retailer
Online and offline customer profiles unified in a single platform. Real-time data enabled faster commercial decisions.

Global industry evidence

Inditex
Inditex / Zara PLANBUY
  • RFID-integrated AI demand sensing enables mid-season assortment adjustments at individual store level based on actual customer behaviour, not pre-season forecasts.
  • The result is consistently among the lowest markdown rates in global fashion alongside one of the highest inventory turn rates in the industry.
Sephora
Sephora Beauty Insider SELLANALYZE
  • Virtual Artist AR try-on reduced beauty return rates measurably in participating categories.
  • Beauty Insider loyalty AI personalisation delivers consistently higher redemption rates versus broadcast campaigns.
JD.com
JD.com Logistics MOVE
  • Fully automated DC operations with AI-directed robotic picking approach 99.
  • 9% order accuracy with materially higher throughput per square metre versus conventional DCs.
Alibaba
Alibaba New Retail ANALYZEGROW
  • Uni Marketing framework unifies customer intelligence across physical and digital touchpoints, enabling attribution connecting online discovery to physical purchase.
  • Retail media business generates revenues reported as a rapidly growing proportion of group revenue.
Grab
Grab Super-App SELL
  • Evolution from ride-hailing to super-app demonstrates the commercial viability of messaging-native, conversational commerce at scale in Southeast Asian markets.
  • In-app merchant commerce through chat-based interfaces shows how WhatsApp and LINE-style purchasing patterns generate incremental revenue for retailers who build the AI layer to make those conversations commercially productive.
Shein
Shein Design Intelligence BUY
  • AI trend velocity model identifies emerging social signals and moves from trend detection to test batch production within days.
  • Live sell-through data on test batches directly informs size curve and quantity decisions before scaled production.

Your roadmap

4 phases · 18 months · 28 checkable milestones
Each phase funded by returns from the one before. Start with the highest-pain track. Build from evidence.
Phase 1
Foundation
Months 0–3
Phase 2
Pilot
Months 3–6
Phase 3
Scale
Months 6–12
Phase 4
Optimise & Grow
Months 12–18
Your progress: 0 / 28 completed
Phase 1 Foundation Months 0–3
Phase 2 Pilot Months 3–6
Phase 3 Scale Months 6–12
Phase 4 Optimise & Grow Months 12–18

The technology powering every use case

15 platforms. All deployed or partnered by IR across Southeast Asia. Every use case in this playbook is enabled by a specific tool — no theoretical capabilities, no vendor speculation.
Note on metrics: Performance figures sourced from vendor-published specifications (slicerpl.ai, Warewiser deck, FootfallCam documentation) and one verified IR client deployment outcome. Where IR has proprietary performance data, these placeholders should be replaced with documented figures before final publication.
📦
Katalog
AI Product Cataloguing Platform — Buy Track

AI product cataloguing platform processing 1,000+ variants per hour via purpose-specific LLMs and RAG. Automates annotation, descriptions, compliance metadata, and localisation — all on-device for data security. Faster time-to-shelf and superior product discoverability.

1,000+ product variants / hrPurpose-specific LLMs + RAGOn-device — data stays internalFaster time-to-shelf
Powers: B2B5
🖥️
iPOSit
Smart POS Secondary Screen — Sell Track

AI-powered POS secondary screen platform surfacing personalised basket promotions at checkout and delivering intelligent e-coupons to build repeat visit frequency. Multi-variate AI personalisation by customer segment and basket composition — measurable ROI from every transaction, no hardware capex.

AI personalisation per basketE-coupon frequency buildingNo hardware capital expenditureRetail media upside additional
Powers: S2B5S5
◈
iOptimo
Demand Intelligence & Planning Platform

AI-powered stock optimisation platform eliminating overstock and preventing stockouts through intelligent inter-store inventory redistribution. AI forecasting, anomaly detection, trend analysis, and automated transfer orders — integrated via API or ERP connection.

−20% stockout rate−10% excess inventory−9pp markdown rate12–16 month payback
Powers: B4G1M1M2M3M6P1P3P4S1
🔗
RFE Bridge
Retail Integration Control Plane — Grow & Analyze Track

Retail integration control plane connecting Cegid Retail with ERP, WMS, Salesforce, SAP, and Shopify through a single governed platform. Multi-tenant with automated retry/recovery, secure credential vault, and end-to-end audit trails. 60% fewer integration tickets, 10× faster onboarding.

60% fewer integration support tickets10× faster flow onboarding99.95% transfer success rateMulti-tenant, audit-ready
Powers: G4A3
✦
Kreate
AI Product Design Intelligence (Kanvas / Slicer)

AI product design module generating mood boards, range ideas, tech packs, and visual collaterals from trend signals and past performance — compressing research-to-brief from weeks to days.

30% faster design cycle40% faster attribute creation35% trend analysis enhancement−30% NPD failure rate
Powers: B1B3
📊
Kanvas Planning / OTB
AI Buying & Assortment Platform (Slicer)

AI buying and assortment platform with store cluster analysis, OTB management, and sell-through modelling. Used by Charles & Keith, Lifestyle International, and Raymond Group.

40% better L4L analysis35% size distribution efficiency20% faster assortment planning15% margin improvement
Powers: P3
🏬
Kanvas VM at Scale
Visual Merchandising Intelligence (Slicer)

Generates store-specific VM guidelines in bulk from each store's live stock and sales data — centralised management with store-level commercial relevance.

30% fewer assortment gaps50% increase in store VM coverage100% storewide updates achievedIncreased sell-through from inventory-aligned displays
Powers: P2
📈
Kanvas Analytics
AI Retail Analytics & Intelligence (Slicer)

AI retail intelligence engine for customer segmentation, churn prediction, campaign performance, product scoring, promotion ROI, and traffic analytics — action-routable, not just descriptive.

50% faster insights to decision25% better planning accuracy40% reduction in stock imbalances90-day predictive churn horizon
Powers: A1A2A4A5G2G5G6P5S2S7S8
⬡
IR / Slicer Platform
CDP, Attribution & Content Intelligence

Core CDP with AI identity resolution, product attribution from visual inputs, brand-anchored LLM content generation, and omnichannel integration. The data foundation every other use case depends on.

89% profile completeness in 72hrsLLM content generation via RAGProbabilistic identity resolutionReal-time API access: all downstream
Powers: A3G2G4G5G6M5S5S9
⬢
Warewizer
Distribution Centre Intelligence (IR)

AI-native WMS with live dashboard, AI bin advisor and Q&A chatbot, RFID module (built-in), 3D warehouse digital twin, and 60+ modules covering the full warehouse lifecycle. Role-aware, audit-ready, and fully integrated with ERP, TMS, and OMS via API hub.

60+ modules40+ WMS & RFID report typesAI Built-In: bin advisor + chatbotRFID-ready from day one
Powers: M4M1M2
🛍
Kanvas Buying & Merchandising
Merchandise Intelligence (Slicer)

AI sell-through analysis, top/bottom seller identification, markdown suggestions, and OTB modelling. 95% accuracy identifying performance outliers early in the trading cycle.

25% markdown optimisation30% improved stock accuracy20% sell-through improvement15% new launch performance lift
Powers: S1B4
🏪
Cegid Retail
Unified Commerce & AI-Enabled POS Platform

Cloud-native unified commerce POS for 1,000+ retailers in 75 countries. Cegid Pulse AI layer enables natural language store management, intelligent operational agents, real-time inventory control, and AI-enhanced task management across the estate.

1,000+ retail clients75 countries deployedAI-enhanced operations via Cegid PulseOmnichannel + supply chain unified
Powers: M6S7M7
🗣️
Allegory AI
In-Store AI Product Storytelling (powered by Graffiti)

QR-activated AI product assistant trained on the full catalogue. Ready in 3 seconds, provides smart recommendations, answers unlimited product queries, and feeds anonymised shopper insight from every interaction — with no staff requirement.

3-second response timeFull catalogue knowledgeSmart product recommendationsLive shopper insight generation
Powers: S2A1S4
🖥️
Retail Pro
International Retail Management System (Nayax Company)

International POS and retail management across 130+ countries, 54,000+ stores. Hardware-agnostic, multi-language, multi-currency, deep integration capability — the transaction and inventory foundation that AI analytics builds on top of.

130+ countries54,000+ stores9,300+ customersHardware-agnostic POS
Powers: M2M1A3S1
FC
FootfallCam
People Counting & In-Store Traffic Analytics (IR Product)

IR-partnered people counting platform providing real-time footfall, zone dwell time, conversion rate tracking, and heat mapping across the full store estate. Integrates with POS and CRM. Privacy-compliant — no PII collected. Deployed by L'Occitane, Tommy Hilfiger, GANT, and Puma.

Real-time bi-directional countingZone dwell time & conversion ratePOS + CRM integration readyGDPR/PDPA compliant — no PII
Powers: A5P2M7S4