Store Operations Are Still a Black Box
Headquarters, regions, and stores see different numbers for traffic, conversion, basket size, stock-out, loss, and labor efficiency, making store diagnosis slow.
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SwiftMetrics Ontology FoundationSemantic capability for AI-callable enterprise dataData AgentNatural-language analytics and decision intelligenceClawTeams AI TeamGoal-driven AI team collaboration and deliveryDataHub Data AssetsCompliant data product marketplace with PSISwiftXDP Multi-Entity Tag PlatformMulti-entity tags and customer intelligenceSwiftMA Marketing AutomationCreate, execute, and optimize personalized marketing strategies
Consumer BrandsMembers, channels, inventory, and growth loopsRetail ChainsHQ-region-store operating agentsState-Owned GroupsData elements and management decisionsHigh-Tech ManufacturingQuality, delivery, and inventory attributionBankingTrusted Q&A, risk, and customer journeysSecuritiesAUM, advisory service, and asset operations
Retail Chains
Retail Chains
Retail Chains solution powered by metrics semantic ontology and Data Agent capabilities, helping enterprises become Data AI Ready and upgrade decision intelligence.
Industry
Retail Chains
Pain Signals
5
Know-how / Cases
4 / 3
INDUSTRY AGENT
Store
SKU
Member
Inventory
Supplier
Task
SEMANTIC
ANALYTIC
ACTION
Industry Intelligence
Retail Chains
Retail Chains solution powered by metrics semantic ontology and Data Agent capabilities, helping enterprises become Data AI Ready and upgrade decision intelligence.
SwiftMetricsData AgentClawTeamsDataHub
PainStore Operations Are Still a Black Box
SolutionStore-Level Operating Command Center
ValueFrom omnichannel data to member operations, supply collaboration, and decision intelligence.
Pain Points
Where business teams get blocked before AI can work.
Member, Product, and Store Data Are Split
Membership behavior, SKU performance, store inventory, and promotion execution are not connected, so people-goods-place matching depends on experience.
Promotion and Replenishment Decisions Lag
Frequent promotions and fast-changing demand require near-real-time monitoring, but manual analysis cannot quickly find the reason behind abnormal sales.
Store Managers Lack Actionable Data
Frontline managers need simple explanations, policy guidance, and next actions instead of complex BI pages and delayed reports.
Supplier and Brand Collaboration Is Underused
Supplier negotiation, joint marketing, assortment optimization, and data opening need trusted metrics and controlled asset circulation.
Solution Advantages
Turn metrics, agents, and actions into one operating loop.
Store-Level Operating Command Center
Use SwiftMetrics to unify store, SKU, member, loss, inventory, supplier, and finance metrics, then expose them to headquarters, regions, and stores.
Data Agent for Store and Region Teams
Let managers ask why a store is down, which SKUs drive loss, which members are at risk, and what action should be taken this week.
Product and Supply-Chain Co-Optimization
Build product health, assortment, replenishment, and promotion attribution models to improve gross margin and inventory turnover.
Supplier Data Asset Operations
Use DataHub to package supplier scorecards, brand marketing insights, and category analysis as controlled data products.
Industry Know-how
Reusable field method for Data AI Ready transformation.
Use Store as the Operating Unit
The metric model must let headquarters drill down to region, store, SKU, member, and employee responsibilities.
Store UnitConnect Sales, Loss, and Inventory
A sales decline is often an inventory, loss, assortment, or execution problem; Agent analysis must cross these domains.
Root CauseTurn Analysis Into Store Tasks
Insight has value only when it becomes a task for store managers, regional supervisors, or category managers.
Task LoopBuild Supplier Collaboration Assets
Supplier negotiation and brand marketing should be based on controlled, reusable, and traceable metric assets.
DataHubCustomer Cases
Representative landing scenarios across leading enterprises.
Yonghui Superstores Digital Upgrade Project
DigitForce supported user operations, supply, omnichannel management, logistics fulfillment, and decision intelligence capabilities.
Pain：Large retail operations required unified insight across users, goods, channels, logistics, and decisions.
Solution：SwiftMetrics, SwiftXDP, and SwiftMA connected metrics, tags, and operation strategies.
Value：From omnichannel data to member operations, supply collaboration, and decision intelligence.
Zhongbai Group Digital Upgrade Project
The project built a data center platform based on full-domain data and data assets to improve data availability and value output.
Pain：The group faced unavailable data, data silos, weak usability, and insufficient value output.
Solution：DigitForce built a full-domain data center and scenario-oriented data asset system.
Value：From data asset integration to management cockpit and operational applications.
Jingkelong Data Middle Platform Project
DigitForce helped launch group-level data middle-platform construction and upgrade operational capability for high-quality development.
Pain：Store, product, and department data needed to be integrated into a reusable operating foundation.
Solution：Data middle-platform and SwiftMetrics capabilities organized merchandise and operating metrics.
Value：From group data center to store operation, merchandise analysis, and management collaboration.
Pain Signals
Industry Pain Points
Store Operations Are Still a Black Box
Headquarters, regions, and stores see different numbers for traffic, conversion, basket size, stock-out, loss, and labor efficiency, making store diagnosis slow.
Member, Product, and Store Data Are Split
Membership behavior, SKU performance, store inventory, and promotion execution are not connected, so people-goods-place matching depends on experience.
Promotion and Replenishment Decisions Lag
Frequent promotions and fast-changing demand require near-real-time monitoring, but manual analysis cannot quickly find the reason behind abnormal sales.
Store Managers Lack Actionable Data
Frontline managers need simple explanations, policy guidance, and next actions instead of complex BI pages and delayed reports.
Supplier and Brand Collaboration Is Underused
Supplier negotiation, joint marketing, assortment optimization, and data opening need trusted metrics and controlled asset circulation.
Agent Solution
Solution Advantages
Store-Level Operating Command Center
Use SwiftMetrics to unify store, SKU, member, loss, inventory, supplier, and finance metrics, then expose them to headquarters, regions, and stores.
Data Agent for Store and Region Teams
Let managers ask why a store is down, which SKUs drive loss, which members are at risk, and what action should be taken this week.
Product and Supply-Chain Co-Optimization
Build product health, assortment, replenishment, and promotion attribution models to improve gross margin and inventory turnover.
Supplier Data Asset Operations
Use DataHub to package supplier scorecards, brand marketing insights, and category analysis as controlled data products.
Industry Know-how
How to Make Industry Data AI Ready
A Data Agent only works when industry concepts, metrics, roles, permissions, and execution workflows are modeled together.
Store Unit
Use Store as the Operating Unit
The metric model must let headquarters drill down to region, store, SKU, member, and employee responsibilities.
Root Cause
Connect Sales, Loss, and Inventory
A sales decline is often an inventory, loss, assortment, or execution problem; Agent analysis must cross these domains.
Task Loop
Turn Analysis Into Store Tasks
Insight has value only when it becomes a task for store managers, regional supervisors, or category managers.
DataHub
Build Supplier Collaboration Assets
Supplier negotiation and brand marketing should be based on controlled, reusable, and traceable metric assets.
Customer Cases
CASE
CASE
CASE
Customer Cases
SwiftMetrics / SwiftXDP / SwiftMA
Yonghui Superstores Digital Upgrade Project
DigitForce supported user operations, supply, omnichannel management, logistics fulfillment, and decision intelligence capabilities.
Pain: Large retail operations required unified insight across users, goods, channels, logistics, and decisions.
Solution: SwiftMetrics, SwiftXDP, and SwiftMA connected metrics, tags, and operation strategies.
Value Path: From omnichannel data to member operations, supply collaboration, and decision intelligence.
Online sales increased by 49.3%
SwiftMetrics / SwiftXDP / SwiftMA
Zhongbai Group Digital Upgrade Project
The project built a data center platform based on full-domain data and data assets to improve data availability and value output.
Pain: The group faced unavailable data, data silos, weak usability, and insufficient value output.
Solution: DigitForce built a full-domain data center and scenario-oriented data asset system.
Value Path: From data asset integration to management cockpit and operational applications.
Average user satisfaction reached 85%
SwiftMetrics
Jingkelong Data Middle Platform Project
DigitForce helped launch group-level data middle-platform construction and upgrade operational capability for high-quality development.
Pain: Store, product, and department data needed to be integrated into a reusable operating foundation.
Solution: Data middle-platform and SwiftMetrics capabilities organized merchandise and operating metrics.
Value Path: From group data center to store operation, merchandise analysis, and management collaboration.
Greatly improved cross-department communication and data usage efficiency