Perfaware

Get Started
Menu
Get Started
Edit Template

IBM

By Industry, By Tech/Product, By Topic, Distribution, Manufacturing, Order Management, Retail, Salesforce, Salesforce OM

Elevate Your eCommerce Experience with Guided Selling in Salesforce Commerce Cloud

/

Overview What if your customers could find the perfect product without ever feeling lost? Guided Selling in Salesforce Commerce Cloud makes that possible — transforming browsing into a personalized, confidence-building journey. By asking the right questions at the right time, you help customers discover what truly fits their needs while capturing valuable data that sharpens your merchandising and marketing strategies. Designing the Right Experience Before building, ask: How complex should this journey be? Do your recommendations rely on a few quick choices, or do they require detailed input? Should customers enter data manually, or will you guide them through preset answers? Your answers determine whether a Simple or Robust Guided Selling model best fits your business goals. The Simple Approach Perfect for quick decisions and frequent updates. When to Use:- You want a lightweight, fast experience. – The goal is to improve completion rates and minimize drop-offs. – Content changes frequently (seasonal products, promotions). How It Works in SFCC- Built using Content Folders for flexible configuration in Business Manager. – Questions, answers, and outcomes managed via JSON for quick edits — no code required. – Enables multiple guided flows, each managed independently. Advantages- Faster to complete and maintain. – Easier to test and iterate. Trade-OffsGenerates less granular data for personalization. Offers simpler recommendation logic. The Robust Approach Designed for depth and precision, ideal for complex product sets (e.g., apparel sizing, electronics compatibility). When to Use- Your recommendations depend on multiple data points. – You want richer behavioral insights. – Customer education is part of the buying journey. How It Works in SFCC- Experience logic is built in code, with Content Assets handling visual elements. – JSON controls result mapping, while dataLayer tracking captures user inputs across steps. – Data integrates seamlessly with Google Tag Manager and Marketing Cloud for analytics, remarketing, and A/B testing. Advantages- Enables holistic data collection for advanced personalization. – Supports dynamic recommendations across your site — from pre-filtered PLPs to personalized promos using Content Slots. Trade-Offs- Longer experiences may increase drop-offs. – Changes often require development effort. Making the Experience Count Every click in Guided Selling is an opportunity to learn. Monitor where customers drop off, refine question flows, and test layouts to improve retention. Data from the journey can also fuel smarter personalization — from size suggestions to dynamic offers tailored by customer group. Result Display Options: Quick product carousel within a modal. Curated Product Listing Page (PLP). Direct link to a relevant Product Detail Page (PDP). Choose what aligns best with your brand and audience — what works for a cosmetics brand may not suit electronics or pet food. Designing for Every Screen Guided Selling is only as good as its usability. Build for all devices — mobile-first, but equally optimized for desktops, tablets, and emerging large-screen formats (up to 2100px and beyond). Poor viewport design can alienate customers before they even begin their journey. Closing Thought Guided Selling isn’t just about simplifying choice — it’s about shaping trust. Whether you start simple or go deep, Salesforce Commerce Cloud gives you the flexibility to design, test, and refine experiences that turn curiosity into confidence — and browsers into buyers. LinkedIn X Email Author Details Travis Knese Technical Architect. Over 18 years in IT, with 14 years in Salesforce B2C. I have worked with dozens of enterprise-level clients on a variety of projects. Including things like new site development, payment service migrations, troubleshooting, and other custom projects.

By Industry, By Tech/Product, By Topic, Distribution, Manufacturing, Order Management, Retail, Sterling OMS

OpenSearch in IBM OMS SaaS & Beyond

/

OpenSearch in IBM OMS SaaS & Beyond: A Modern, Open, and Scalable Foundation for Commerce Observability As digital commerce platforms continue moving toward SaaS architectures, real-time visibility into order and inventory transactions, integrations, and the associated events has become a core operational requirement. For IBM OMoC, i.e., Order Management on Cloud (OMS SaaS)customers, IBM’s transition from Graylog to OpenSearch brings next-generation observability and log analytics capabilities to their Digital Commerce operations. OpenSearch is not just an open-source search engine; it has become a foundational component of the OMS SaaS observability model, enabling faster troubleshooting, deeper analytics, and richer insights across all OMS workloads. Why OpenSearch Matters in the IBM OMS World IBM has adopted OpenSearch as its strategic platform for logging, search, and analytics in the Next Gen OMS Platform (OMoC 2.0). This shift brings several important benefits: Unified Observability Across OMS Components Instead of relying on distributed log viewers or siloed monitoring tools, customers gain: A centralized view of OMS logs High-speed search for order and integration flows Standardized event formats across applications and system components This drives clearer visibility for operational, support, and integration teams. The dashboards below represent the Server and OMS health errors – Handling Large Numbers of Regions OpenSearch improves the ability to quickly spot and diagnose issues such as: Slow or failing APIs Delayed message queues Payment or tax service failures Integration delays across commerce systems Interactive dashboards make problem detection significantly faster. Built for High-Volume Retail and Peak Seasons Designed for distributed, high-ingest workloads, OpenSearch scales seamlessly to match the log volume generated by large retailers — particularly during major seasonal peaks. Comparing Distribution Group Model vs. Dynamic Sourcing Model Capability Graylog OpenSearch Examples Full-Text Search Basic Lucene-powered, enterprise-grade Quickly search thousands of OMS logs for a specific order number, API error, or correlation ID using fast, Lucene-based indexing. Scalability Moderate Distributed, high-ingest Handle massive log spikes during holiday peaks or flash sales without performance degradation, due to distributed high-ingest clustering. Machine Learning No Yes, with anomaly detection OpenSearch’s anomaly detection can automatically identify unusual patterns without predefined rules – • Unexpected drops in API throughput for core flows like createOrder or releaseOrder. • Abnormal increases in message queue delays for integrations with WMS, ERP, or tax systems. Extensibility Restricted Plug-ins, ML models, open ecosystem OpenSearch allows additional plug-ins or ML-based features that extend the platform: • Supports ML plug-ins for predicting order volume or latency trends. • Allows visualization plug-ins for richer OMS dashboards. These advancements make OpenSearch a more flexible and future-ready fit for OMS observability. How OpenSearch Enhances Digital Commerce Operations OpenSearch plays a critical role in strengthening observability across digital commerce and OMS implementations, providing deeper operational insight and faster issue resolution. 1. Faster Diagnostics Across the Order Lifecycle OpenSearch dashboards enable teams to: Trace order journeys from capture to fulfillment Detect integration failures in real time Identify API issues, routing problems, or custom logic errors quickly Perform detailed log analysis to accelerate root-cause identification These capabilities help reduce Mean Time to Resolve (MTTR) for OMS-related incidents and improve overall system reliability. 2. Improved Monitoring for Peak Readiness During high-demand periods such as holidays, flash sales, and promotional events, OpenSearch provides visibility into: Log volume spikes and traffic patterns API latency and throughput Fulfillment delays and routing bottlenecks JVM and infrastructure behavior across OMS components This insight supports proactive capacity planning and smoother peak-season operations. 3. Greater Visibility Into Custom Extensions Many OMS implementations incorporate custom elements—such as payment adaptors, inventory or allocation services, specialized order-routing logic, or external commerce integrations.  Here are a few relevant examples: Example 1 – Payment Adaptor MonitoringAn organization using a custom payment adaptor (e.g., for gift cards, or third-party payment gateways) can create an OpenSearch dashboard to track authorization failures, timeout rates, and retry patterns in real time—helping teams detect issues before they impact checkout. Example 2 – Allocation or Inventory Service TrackingIf an implementation uses a custom ATP service to determine inventory availability, OpenSearch can visualize trends such as response latency, allocation decision outcomes, exceptions, or API degradation—ensuring smoother order promising. Example 3 – Custom Order Routing LogicOrganizations with bespoke routing rules (store-first, region-first, cost-based routing, etc) can use OpenSearch to monitor routing decisions, identify bottlenecks, and detect mis-routed orders through custom logs. Example 4 – External Commerce or ERP IntegrationsFor integrations with SAP, Salesforce Commerce, Shopify, or warehouse systems, OpenSearch dashboards can highlight message failures, queue delays, or payload anomalies, enabling faster triage when an external dependency slows down the OMS. OpenSearch enables the creation of targeted dashboards to monitor these custom components alongside core OMS flows, ensuring unified observability across the entire digital commerce ecosystem. OpenSearch dashboards enable teams to: Trace order journeys from capture to fulfillment Detect integration failures in real time Identify API issues, routing problems, or custom logic errors quickly Perform detailed log analysis to accelerate root-cause identification These capabilities help reduce Mean Time to Resolve (MTTR) for OMS-related incidents and improve overall system reliability.During high-demand periods such as holidays, flash sales, and promotional events, OpenSearch provides visibility into: Log volume spikes and traffic patterns API latency and throughput Fulfillment delays and routing bottlenecks JVM and infrastructure behavior across OMS components This insight supports proactive capacity planning and smoother peak-season operations. Many OMS implementations incorporate custom elements—such as payment adaptors, inventory or allocation services, specialized order-routing logic, or external commerce integrations.  Here are a few relevant examples: Example 1 – Payment Adaptor MonitoringAn organization using a custom payment adaptor (e.g., for gift cards, or third-party payment gateways) can create an OpenSearch dashboard to track authorization failures, timeout rates, and retry patterns in real time—helping teams detect issues before they impact checkout. Example 2 – Allocation or Inventory Service TrackingIf an implementation uses a custom ATP service to determine inventory availability, OpenSearch can visualize trends such as response latency, allocation decision outcomes, exceptions, or API degradation—ensuring smoother order promising. Example 3 – Custom Order Routing LogicOrganizations with bespoke routing rules (store-first, region-first, cost-based routing, etc) can use

By Tech/Product, IBM, Uncategorized

Ensuring Data Privacy: End-to-End PII Access Logging in IBM OMS

/

Global Data Privacy Regulations: What Enterprises Must Comply With As digital commerce expands across regions, enterprises must navigate a wide range of data privacy laws. Each country sets its own expectations on how customer information is collected, processed, accessed, and retained. For organizations running global ecommerce and omnichannel platforms, especially those handling PII in IBM OMS, understanding these requirements is essential. To operate globally, enterprises must comply with multiple regulations that dictate how customer data can be used and who may access it. Why Information Security Management System Compliance Matters for Order Management System (OMS) Any OMS processes sensitive customer information such as names, phone numbers, email addresses, and sometimes payment-related data. Because of this, every OMS must ensure: Access transparency Controlled and authorized usage of customer data Secure audit logging Rapid breach detection Full traceability for compliance reviews Different platforms approach this differently. This article focuses on how IBM Sterling OMS supports ISMS-aligned controls and PII access visibility. A centralized PII logging framework is not yet a universal ISMS requirement. It is currently emphasized in markets such as Korea, but as more countries align with ISO-27001, similar expectations are likely to emerge globally. For enterprises using IBM OMS, this translates into the need for a robust audit mechanism that records when sensitive data was accessed, who accessed it, and which fields were retrieved. Regulations such as GDPR (Europe), CCPA (US), ISMS (Korea), and DPDP (India) require enterprises to maintain transparent and tamper-proof audit trails. Failing to do so can lead to penalties, loss of customer trust, and barriers to operating in regulated markets. Since IBM OMS frequently processes customer names, addresses, and contact details, a consistent and traceable logging framework is essential for both API and database access. End-to-End PII Access Logging This solution supports a simple & dependable flow to track how customer information is accessed. This gives teams a clear view of who accessed what data, without adding load on day-to-day OMS operations. Capturing API Access All API calls that read or return customer information are tracked. The framework identifies when PII is involved and records:– Who initiated the request– The channel used (OrderHub, Call Center, mobile app, website, integrations)– The type of customer data accessed Capturing Database Access The same level of visibility is applied to database activity. When a user or service runs a query on customer-related tables, the framework captures:– Who executed the query– When it was run– What customer information was retrieved This removes a common audit blind spot and supports markets where PII access logging is mandatory. Adding Useful Context Every log includes the basic information an auditor or security team would need, such as the user, timestamp, source application, and the part of the customer record that was accessed. This makes it much easier to answer questions during compliance reviews. Asynchronous and Secure Processing Log collection does not interrupt OMS transactions. Events are processed separately and stored in secure cloud storage. This keeps the system responsive even during peak order volumes. Integration with SIEM Tools The stored logs are forwarded to security platforms such as Google Chronicle SecOps, Splunk, IBM QRadar, and many others. These tools help teams:– Monitor access patterns– Detect unusual or excessive access– Conduct audits efficiently Performance Considerations The framework is designed to avoid any impact on OMS performance. Logging uses lightweight filters that add negligible overhead to API and database operations. Processing occurs outside the OMS JVM to prevent spikes in memory or CPU usage. Because the architecture is fully decoupled and asynchronous, OMS can handle high workloads without affecting SLAs. Compliance logging remains invisible to users while maintaining operational stability. Real-World Scenarios Where This Helps – A call center agent views the customer address → captured as an API log – Mobile app retrieves order details → logged with source & PII fields – DBA runs SQL on YFS_PERSON_INFO → logged with SQL text & tables – Security team detects abnormal access volume → SIEM sends alert Governance & Monitoring Recommendations To maximize compliance: Review SIEM dashboards weekly Set alerts for unusual access patterns Conduct quarterly access audits Enforce identity-based access policies Validate cloud storage access control (IAM) Good governance strengthens both compliance and internal security posture Key Benefits Audit Readiness Centralized logs simplify ISMS audits and regulatory reviews. Full-Stack Visibility Covers both OMS APIs and direct DB queries, eliminating blind spots. Zero Performance Impact Asynchronous processing ensures no slowdown in order workflows Cloud-Native Security Logs stored with IAM policies, encryption, and firewall-controlled access. Scalable Across Regions Framework supports GDPR, CCPA, DPDP, and global expansion. LinkedIn X Email Author Details Sureesh Deenadayalan Solution ArchitectOver 13 years of experience in IBM Sterling OMS, foundation, next-generation call center, and store Apps, upgrades and cloud migration. Have designed end-to-end order management, sourcing, and post-purchase workflows for large-scale retail systems.

    This will close in 0 seconds

    Scroll to Top