AI-Driven Transformation: Wall's Ice Cream Route-to-Market
How eBest's AI-powered SFA & DMS solution — brings computer vision, machine-learning route optimization, and real-time intelligence to Wall's ice cream Route-to-Market: from AI shelf audits and season-aware routing to a unified, insight-driven dealer portal. Download the Case StudyWall’s: A Leading Global Ice Cream Brand, Powered by AI
Wall’s is a leading global ice cream brand, bringing beloved frozen treats — including classics such as Cornetto, Magnum, and Wall’s ice cream bars — to consumers across China and beyond. As a category defined by strong seasonality, heavy cold-chain dependency, and an exceptionally broad retail footprint spanning modern trade, traditional trade, convenience stores, and countless mom-and-pop outlets, Wall’s operates one of the most complex Route-to-Market (RTM) networks in the FMCG sector — and a natural proving ground for AI in FMCG field sales.
Behind every freezer and every scoop sits a vast field sales organization and an extensive dealer network. At this scale, gut-feel and manual processes are no longer enough to win at the point of sale. Wall’s needed intelligence embedded in every field and dealer workflow — putting AI to work where FMCG decisions actually happen: on the shelf, on the route, and in the dealer relationship.
The Challenge
Why Manual RTM Breaks Down at Scale
Operating a nationwide ice cream RTM means balancing seasonal surges, thousands of retail touchpoints, and a dealer ecosystem that all depend on the same data. The harder truth is that traditional, human-driven processes simply cannot keep up — and that gap is exactly where AI earns its place.
1. Siloed Systems Starve AI of a Data Foundation
The business had to connect BI, freezer systems, DIS, DS, order systems, external audit, the store-assistant app, and DMS — yet data lived in disconnected systems with no real-time flow. Without a unified data layer, there is nothing for AI models to learn from or act on.
2. Inconsistent In-Store Execution Can’t Be Policed by Hand
Perfect Store tasks required unified execution standards and scoring rules to guarantee consistent execution across the country. No team of auditors can visually check every store, every week — execution quality varied widely by region and rep.
3. Route Planning by Intuition Misses Seasonal Swings
Manually planning visit routes was time-consuming and could not adapt to seasonal demand swings, leaving coverage gaps during peak periods and wasted effort in the off-season. Human planners cannot optimize thousands of outlets against a moving demand curve.
4. Fake Visit Photos Defeat Manual Review
Store-execution photos carried a real risk of recapture and replay fraud. Reviewing millions of images by hand is impossible — Wall’s needed an automated, trustworthy validation mechanism rather than manual photo review.
5. Weak Dealer Collaboration Leaves Insights on the Table
Dealers needed to view contracts, reconciliations, and performance reports, but had no unified portal — creating friction throughout the sales chain and limiting partner growth. Disconnected partners cannot act on the insights the brand already has.
6. Chaotic Asset Management Hides Freezer Risk
In-store freezers and equipment needed tracking and inspection, with data synchronized back to third-party systems — a process that was manual and error-prone, leaving the brand blind to asset health at the edge.
The Solution
An AI-Powered SFA + DMS Platform
eBest delivered an integrated SFA (Sales Force Automation) + DMS (Distribution Management System) solution — the SFEP + CEP dual-platform system Wall’s named internally — with AI as the intelligence layer across the entire RTM. Built on WeChat Work as the unified login portal and integrated with the brand’s major commercial systems, the platform turns raw field and dealer data into automated decisions instead of manual guesswork.
A Unified Data Foundation for AI
At the core is a dual-platform design: the SFA empowers field sales at the point of execution, while the DMS connects the dealer ecosystem. Both run on a microservices PaaS middleware that supports public cloud and on-premise deployment, interconnecting BI, freezer systems, DIS, DS, order, external audit, the store-assistant app, and DMS into one unified data layer. That single source of truth is what makes every AI capability dependable — models score, route, and flag against live, consistent data.
AI Route Planning (SRP)
Machine learning automatically generates SRP (Smart Route Planning) routes based on visit start date, visit frequency, and season — scheduling 5×8 coverage in the off-season and scaling up to 7×12 during peak season. Managers view and adjust visit plans on a calendar, add unplanned outlets, and request changes to future visits for agile coverage.
AI Store Execution
Computer vision scores Perfect Store from a single shelf photo — main shelf, POSM, and special displays — automatically calculating contract achievement and shelf share. A built-in anti-recapture check blocks screenshots and reused photos, and a rule engine scores results in real time, auto-generating remediation tasks for failures.
AI Asset Management
The module syncs in-store freezer and equipment asset data with third-party systems and supports on-site asset inspections, with inspection data written back to the external system. Combined with the unified data layer, this gives the brand a single, auditable, AI-ready view of freezer health across the retail network.
Intelligent Order & Reconciliation
During a visit, reps place orders with assortment suggestions, push them for customer confirmation, and run suggested orders, pre-orders, and stock applications. The solution manages contract templates, signing tracking, payable/receivable reconciliation, and deduction-detail viewing — making dealer back-office self-service.
Dealer Portal (DMS): Insight-Driven Enablement
The DMS gives distributors a Content Center (news, campaigns, product info, policies), Performance Reports (Tier-1 & Tier-2 sales, store execution, customer health), and DIS unmatched-store supplementation — turning raw data into partner action.
Data Integration & Customer Service
The platform connects BI, freezer, DIS, DS, order, external audit, the store-assistant app, and DMS on a microservices PaaS middleware. A built-in service desk lets users raise questions, close and rate tickets, with answerer management, quick-reply maintenance, and tag groups for fast, consistent support.
Key Capabilities
🗺️
AI Smart Route Planning (ML / SRP)
Season-aware machine-learning scheduling (off-season 5×8, peak 7×12) maximizes coverage efficiency and visit quality, replacing intuition with optimization.
📸
AI Image Recognition & Anti-Recapture
Computer vision scores Perfect Store from a single photo, while a built-in replay validation blocks fraud — trustworthy execution data without manual review.
🏪
Dealer Self-Service Portal (DMS)
Orders, content, performance reports, and reconciliation in one place — empowering the distribution ecosystem with insight.
🧊
Freezer Asset Management
In-store asset sync and inspection with third-party systems for a single, auditable, AI-ready asset view.
🔗
Unified Data Ecosystem
One PaaS middleware breaks silos across BI, DIS, DS, DMS, and more — the live, consistent foundation every AI model learns from.
📑
Contract & Reconciliation
Online contract signing and reconciliation viewing reduce dealer back-office friction.
🎯
AI Perfect Store Scoring
Rule-engine scoring with automatic remediation tasks drives consistent national execution in real time.
💬
Built-in Customer Service
Ticket raising, rating, quick replies, and tag groups deliver fast, consistent support.
👥
Multi-Role Support
One platform serves MTR/DSR, ASR/SR, supervisors, dealers, and Admin — each with tailored workflows.
The Results
AI-Driven Outcomes
eBest’s AI-powered SFA & DMS solution delivered measurable transformation across Wall’s ice cream Route-to-Market — connecting field sales, dealers, and headquarters on a single platform where intelligence, not manual effort, drives execution.
| Metric | Result |
|---|---|
| Intelligence Layer | AI across routing, shelf audit, scoring & fraud prevention |
| Field Sales Roles Empowered | MTR/DSR · ASR/SR · Supervisors · Admin |
| Dealer Ecosystem Connected | Via unified DMS portal |
| Enterprise Systems Integrated | BI · Freezer · DIS · DS · Order · Audit · Store Assistant · DMS |
| Visit Scheduling | AI-driven SRP — off-season 5×8, peak 7×12 |
| Store Photo Fraud Risk | Blocked by built-in anti-recapture AI |
| Perfect Store Scoring | Real-time, AI / rule-engine driven |
| Deployment | Public cloud & on-premise (microservices PaaS) |
eBest Mobile has helped Wall’s with:
- Putting AI to work across the ice cream Route-to-Market
- Season-aware ML route planning that flexes from 5×8 to 7×12 coverage
- Computer-vision Perfect Store scoring with built-in anti-recapture validation
- A unified, insight-driven dealer portal for content, performance, and self-service
- Full-lifecycle freezer asset tracking and on-site inspection
- Closed-loop contract signing and reconciliation for dealers
From Manual Execution to Intelligent RTM
This case shows how a leading ice cream brand can transform its entire go-to-market model by unifying field sales operations with a dealer enablement portal — and by making AI the engine of execution rather than a bolt-on feature. Wall’s achieved something rare: smarter field representatives, more capable dealers, and better-informed headquarters — simultaneously.
The key insight was recognizing that digital transformation in ice cream RTM is not about monitoring people more closely. It is about giving reps intelligent automation, trustworthy execution data, and dealers a connected platform — so everyone aligns around shared growth at the point of sale.
“The future of ice cream Route-to-Market lies not in tighter control, but in equipping every rep and dealer with smart automation, trustworthy data, and a single connected platform.”
— Wall’s RTM Digital Transformation Team
Frequently Asked Questions
How does AI improve FMCG field sales effectiveness?
AI shifts FMCG field sales from manual, reactive execution to data-driven, proactive coverage. On the Wall's ice cream RTM, computer vision audits shelves from a single photo, machine learning builds season-aware visit routes (5×8 off-season, 7×12 peak), and rule engines score Perfect Store compliance in real time — so reps execute consistently and managers act on trustworthy data instead of manual review.
What is SFA (Sales Force Automation) in FMCG field sales?
SFA (Sales Force Automation) — the Sales Front-End Platform that Wall's internally calls SFEP — runs on WeChat Work as a unified login portal. It digitizes visit management, in-store execution, order capture, and contract and reconciliation workflows for field sales roles such as MTR/DSR and ASR/SR, connecting them to headquarters and dealer systems in real time.
How does AI image recognition prevent fake visit photos in field sales?
Every photo captured in the app — main shelf, POSM, and special displays — passes through a built-in anti-recapture (replay) validation check that flags screenshots or reused photos. An AI engine then scores Perfect Store compliance, automatically calculating contract achievement and shelf share, so managers trust the data without manual review.
What is a DMS (Distribution Management System) dealer portal?
A DMS (Distribution Management System) — the Customer Enablement Portal that Wall's internally calls CEP — is a unified dealer portal where distributors access a content center (news, campaigns, product info, policies), performance reports (Tier-1 and Tier-2 sales, store execution, customer health), and self-service tools for orders and reconciliation, replacing fragmented, manual dealer communication.
How does AI route planning handle seasonal demand in ice cream?
Machine learning generates SRP (Smart Route Planning) routes automatically based on visit start date, visit frequency, and season. In the off-season it schedules 5×8 coverage; during peak ice cream season it shifts to 7×12, so coverage intensity flexes with demand without manual replanning.
How does SFA manage in-store freezer assets with AI?
The asset management module syncs in-store freezer and equipment data with third-party systems and supports on-site asset inspections. Inspection results are written back to the external system, giving the brand a single, auditable, AI-ready view of freezer health across the retail network.
What enterprise systems does eBest SFA integrate with?
The solution runs on a microservices PaaS middleware and integrates with BI, freezer systems, DIS, DS, order systems, external audit, the store-assistant app, and DMS. It supports both public cloud and on-premise deployment and uses WeChat Work as the unified identity portal.
Ready to put AI to work across your Route-to-Market?
Discover how eBest’s AI-powered SFA & DMS solution — the SFEP + CEP approach Wall’s uses internally — can bring computer vision, ML route optimization, and real-time intelligence to your field sales and dealer network.
Related case study: Unilever SFA & CEP Digital Transformation