Use Cases
Real-world retail challenges and how Katalist can help you solve them
Legacy Systems Slowing Innovation
A food retailer is seeking to increase client engagement through an omnichannel strategy, but their existing engagement platform cannot deliver the required personalization.
The business identifies a best-of-breed solution that fits their needs perfectly but does not want to risk disruption or replace reliable existing systems. They need a fast, low-risk way to introduce modern capabilities.
Katalist places a non-disruptive "bridge" between existing systems and new best-of-breed solutions:
- RBCs and Universal Connectors integrate new platforms into the existing ecosystem without heavy custom development
- A unified data layer harmonizes legacy data structures with modern applications
- A decoupled architecture allows new solutions to plug into the ecosystem without rewriting existing integrations
- New capabilities can be introduced progressively without disrupting operational systems
- Faster innovation without replacing core systems
- Lower integration risk and operational disruption
- Freedom to adopt best-of-breed technologies over time
Systems Integration Challenges After M&A Transitions
A global retail group acquires two regional chains, and immediately faces fragmented systems, broken integrations and incomplete data that limit visibility into sales, stock and customer behavior.
Time-to-synergy is slow and costly because leadership lacks the clarity needed to stabilize operations and determine which systems to keep.
Katalist acts as an M&A Operational Accelerator, solving the chaos of integration:
- All core systems are connected and data normalized into one unified structure
- Broken or missing integrations are replaced with standardized, reusable integration patterns
- Data from multiple banners and systems is centralized into a single operational view
- Redundant tools and duplicated integrations can be progressively decommissioned
- Retailers accelerate M&A transitions and reduce time-to-synergy, enabling the parent group to act on combined data within months
- Strategic decision-making is achieved through unified data centralization
Vendor Lock-In in Core Systems
A home goods retailer has been locked into the same order management system for 10 years.
The contract renewal is approaching and costs are rising. The retailer wants to test alternative OMS vendors.
However, every downstream system relies on the old vendor data structure. This makes experimentation extremely risky and costly.
Katalist decouples data dependencies, securing architectural freedom:
- A neutral language between systems is established
- Both OMSs are connected to the data hub without impacting the existing legacy OMS mapping
- Data from both vendors flows through the same unified structure
- The retailer runs both vendors in parallel and compares performance, reliability, and operational impact with zero disruption
- Freedom to break away from vendor lock-in
- Ability to validate a new solution in production before fully committing
- Greater flexibility to switch providers without rebuilding core integrations
Fragmented Customer Data Across Countries
A global retailer operates across several countries. Each local team selected its own marketing automation tool.
Because each tool works differently, each country created their own scripts, CSV uploads and private automations to sync data with the CRM.
This resulted in fragmented data, no central visibility or control, too many manual tasks with frequent data errors, compliance risks and lack of unified reporting.
Katalist centralizes and standardizes data flows across countries and systems:
- Data flows from multiple marketing platforms are connected through a unified integration layer
- Local scripts and manual uploads are replaced with standardized, monitored data flows
- Customer data from all countries is normalized into a consistent structure
- Data movements become centralized, traceable, and easier to manage
- Unified customer visibility across all countries
- Reduced shadow IT and fewer uncontrolled local data processes
- Reduced manual work and fewer data errors
- Better governance and compliance across markets
Complex ERP Transitions to the Cloud
A retailer is replacing its aging on-premises ERP with a modern, cloud-native platform to improve agility, reporting, and scalability.
However, both systems need to coexist temporarily to ensure business continuity.
The transition must be smooth, with no disruption to operations.
Katalist enables a controlled ERP transition between on-premise and cloud environments:
- Both ERPs connect to a unified data hub through the same integration layer
- Data flows are mirrored between the legacy ERP and the new cloud ERP
- Downstream systems consume data from the data hub instead of directly from the ERPs
- The legacy ERP can be retired progressively once validation is complete
- Cloud migration without operational disruption
- Reduced migration risk and technical complexity
- Faster access to cloud-native capabilities
Slow and Complex System Integrations
A retailer integrates a new loyalty platform, which uses a proprietary schema for customer data and transactions.
The typical integration would require weeks of custom mapping and testing.
Katalist simplifies system integrations through automated data mapping and reusable connectors:
- AI-assisted mapping configures transformation rules between different system schemas
- Integration flows are generated and deployed through standardized connectors
- Data transformations follow a unified structure within the integration layer
- Reusable integration patterns reduce custom development effort
- New systems can be connected in hours instead of weeks
- Less custom development and lower integration complexity
- IT teams can focus on innovation instead of integration work
Fragmented Data Silos Across Systems
An omnichannel retailer wants to combine data from disparate sources: CRM, POS, loyalty systems, and digital marketing campaigns to truly personalize the shopping experience.
However, silos and fragmentation prevent real-time, accurate alignment, making sophisticated customer segmentation and personalized action impossible.
Katalist centralizes and normalizes data from every customer touchpoint into one definitive source:
- Customer data from CRM, POS, loyalty, and marketing platforms is unified into a consistent data model
- Unified data is exposed through a standardized REST API layer
- Downstream systems such as reporting, segmentation engines, and AI tools consume data from the same reliable source
- Retailers gain a true 360° view of the customer
- Better insights support strategic growth and stronger customer loyalty, based on deep, actionable insights
- Personalized actions and dynamic offers can be delivered across all channels
Operational Complexity from System Integrations
A retailer seeks to onboard new digital platforms quickly to improve operational performance across inventory and order management.
The traditional approach requires heavy custom development, long mapping cycles, and the constant struggle to handle fragmented data.
These inefficiencies slow retailers’ innovation and directly impact the business through stockouts, over ordering, and inconsistent business visibility.
Katalist is an engine for operational excellence, enabling innovation at speed:
- AI-assisted mapping accelerates configuration of data transformation rules
- Integration flows are deployed through standardized connectors
- Inventory data from warehouses, stores, vendors, and drop-ship partners converges in a unified data hub
- A monitoring layer tracks transactions and ensures reliable data movement
- A single, accurate view of inventory across systems
- Reduced stockouts, excess inventory, and operational inefficiencies
- Faster onboarding of new operational platforms
Inconsistent Accuracy Across Company
A multi category retailer struggles during peak seasons because every department relies on different inventory reports.
Supply chain uses WMS data, stores use POS data, and finance uses spreadsheet adjustments.
There is no single truth for stock on hand, in transit, or committed.
Katalist creates a unified inventory data foundation across retail systems:
- Inventory movements and stock statuses are normalized into a unified data structure
- Inventory data is centralized in a shared data hub
- Data flows are synchronized across connected operational systems
- A monitoring layer tracks inventory data consistency across systems
- A single, reliable view of inventory across the enterprise
- Better coordination between supply chain, stores, and finance
- Reduced stock discrepancies and operational inefficiencies
Supplier Data Onboarding Complexity
A retailer works with many suppliers and marketplace partners, each sending product and inventory data in different formats, through different channels and at different frequencies.
Onboarding a new partner requires multiple transformations, manual validations and long testing cycles.
This slows down time to market, increases operational effort and creates inconsistent data quality between partners.
Katalist standardizes and orchestrates supplier and partner data onboarding:
- Supplier and marketplace feeds are mapped into a unified product and inventory structure
- Partner-specific formats and protocols are managed through the data hub
- Validation rules ensure consistent data quality across suppliers
- Data filters and transformation rules automate onboarding workflows
- Faster onboarding of new suppliers and marketplace partners
- Reduced manual data transformations and validation work
- Consistent product and inventory data across partners
- Faster expansion across channels and marketplaces
Inconsistent Data for Assortment and Allocation Planning
Planning and allocation teams use data from ERP, POS, WMS and merchandising systems.
However, each system provides different structures, frequencies and levels of detail, resulting in reduced accuracy of forecasting, allocation rules and replenishment decisions.
Inconsistent data slows down the planning cycle and increases the risk of stockouts or excess.
Katalist harmonizes retail data for planning and allocation systems:
- Sales, inventory and product data are normalized into a unified structure
- Data from ERP, POS, WMS and merchandising systems is consolidated in the data hub
- Allocation and planning tools consume harmonized data through standardized feeds
- Transformation and validation rules automate data preparation workflows
- More accurate forecasting and allocation decisions
- Faster planning cycles with less manual data preparation
- Reduced risk of stockouts and excess inventory
- Greater confidence in planning and merchandising strategies
Fragmented Returns Management Across Channels
A retailer handles returns across stores, e-commerce, and marketplaces.
Each channel uses different processes, reasons and data structures, causing inconsistencies in refunds, stock updates and customer communication.
Inventory adjustments arrive late or incomplete, and customer service relies on manual checks.
Reporting becomes difficult because return events are not aligned across systems.
Katalist standardizes and orchestrates returns data across retail channels:
- Returns events from stores, ecommerce and marketplaces are normalized into a unified structure
- Returns data is centralized and distributed to ERP, finance, CRM and inventory systems
- Transformation rules align channel-specific return reasons and processes
- Monitoring ensures consistent processing of returns events across systems
- Faster and more reliable refund processing, improving customer satisfaction
- Accurate inventory updates after returns
- Reduced manual reconciliation across channels
- Clearer reporting on returns performance