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

Elevate Your eCommerce Experience with Guided Selling in Salesforce Commerce Cloud

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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-Offs Generates 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

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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

Agentic Commerce, B2C, eCommerce, Retail

Move over Agentic Commerce, Catalog Commerce is here: Why Amazon’s Holiday Catalog is a Stroke of Genius

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Move over, Agentic Commerce, Catalog Commerce is here: Why Amazon’s Holiday Catalog is a Stroke of Genius While the industry obsesses over social commerce and AI shopping agents, Amazon is relying on the oldest playbook in retail: the physical catalog. This isn’t corporate nostalgia; it’s strategic brilliance disguised as anachronism. The smart money missed the analog anchor effect in an era of digital overwhelm. The Power of Contemplative Browsing The Amazon catalog sits on the coffee table for weeks – dog-eared and annotated, while endless TikTok shopping feeds disappear instantly. This physical artifact creates an “analog anchor” that interrupts our digital acceleration, forcing contemplative browsing instead of impulse clicking. Consider the difference in cognitive load:  01 Digital Shopping Fractured attention across infinite streams, sponsored content, and invisible algorithms manipulating choices. 02 Catalog Shopping Liberation from choice paralysis. The catalog eliminates chaos through brutal editorial constraint: finite pages, curated selection, and linear navigation. Algorithmic personalization often optimizes for immediate conversion, not long-term satisfaction. The algorithm wants you to buy now, but the curated catalog offers a trusted, finite pathway to the right thing. Rebuilding Trust in an Era of Algorithmic Skepticism Amazon’s catalog strategy is about rebuilding trust, which has plateaued in the digital age. Gen Z and Gen Alpha assume every digital recommendation is manipulated—a consequence of hyper-personalized, engineered feeds. This algorithmic skepticism is a trust crisis. Physical catalogs entirely sidestep this issue: Transparency Everyone gets the same curated selection. There is no hidden algorithmic layer optimizing for unknown corporate objectives. Shared Reference Points When a neighbor sees the same gift suggestions, it feels authentic rather than manipulative. Commitment Printing and mailing costs force Amazon to stand behind its product curation in a way digital platforms never do. Every catalog item represents a real commitment. A Bridge Across the Generational Divide The real genius lies in household purchasing dynamics. While venture capitalists focus on AI agents, high-value and holiday purchase decisions involve multiple generations. Gen X and Boomers control disproportionate purchasing power for major categories (gifts, home goods). These demographics: Never fully migrated to social commerce. Are skeptical of personalized AI recommendations. Trust catalogs in ways they will never trust algorithmic feeds. The catalog influences the family patriarch choosing the budget or the Gen X parent deciding on household upgrades. These considerations happen in analog space, and the orders then flow through digital channels for fulfillment. This creates an omnichannel strategy that pure-play digital competitors cannot replicate. TikTok can optimize for viral discovery among teenagers, but they can’t influence major household decisions flowing from a trusted, physical artifact. Preserving the Romance of Shopping Shopping is not just about utility; it’s about aspirational identity, social bonding, and cultural participation. Catalogs preserve the romance of browsing and the serendipity of discovery – psychological dimensions that algorithms focused on efficiency inadvertently destroy. As noted by the NRF’s Vice President of Industry and Consumer Insights, Katherine Cullen, in a recent episode of the Retail Gets Real podcast, catalogs remain a familiar and trusted source of holiday inspiration. Conclusion Amazon’s “backwards” strategy recognizes that human behavior is more complex than algorithmic optimization assumes. You must meet customers everywhere. The physical catalog is a recognition that trust, contemplation, and shared cultural experiences matter more than personalization precision. This is why retailers should experiment with diverse, multi-pronged strategies instead of going 100% all-in on digital. Sometimes, the old way is the strategic way to secure a larger share of the customer’s wallet. If you are at a Retailer/Brand, what strategies have you tried this year to meet customers where they are? If you work for an Agency, what strategies have you seen your clients use to help more shoppers discover your clients’ brands? LinkedIn X Email Author Details Ranjith Maniyedath Managing  PartnerAs the Managing Partner and Co-Founder of Perfaware, I lead a team of digital transformation and omni-channel commerce experts who provide end-to-end solutions for complex eCommerce, Order and Inventory management systems. With over 23 years of experience in technical consulting and enterprise application deployment, support, and testing, I have successfully implemented, tested, and tuned multi-million dollar supply chain solutions for customers across diverse markets and industries in the US, Latin America, UK, Asia and Australia. My core competencies include global service delivery and operations, services sales, team building and leadership, problem solving, and business technology consulting. I have a strong domain expertise in supply chain management, omni-channel fulfillment, order management, warehouse management, supply collaboration, inventory synchronization, reverse logistics, and business integration. My mission is to help clients optimize their digital commerce operations at scale through innovative and customized solutions.

By Topic, Retail

Region-Based Sourcing in Retail: Models, Challenges, and Best Practices

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Introduction to Region-based sourcing In today’s retail ecosystem, customer expectations are higher than ever. Shoppers don’t just want fast delivery; they expect accurate fulfillment from stores or warehouses closest to their location. Traditional city/state/zip-based sourcing methods often lack flexibility and can lead to higher delivery costs and longer lead times. That’s where Region-based sourcing comes into play. Region-based sourcing is an effective method of allocating orders to stores or distribution nodes based on geographical Regions. These Regions are defined by latitude and longitude rather than fixed state, city, or postal code boundaries. This system helps retailers match each order with the most suitable store in real-time. Curious to know more about this system? Let’s discuss how Region-based data sourcing works, two different implementation models retailers can adopt, and which models will suit you best. What is Region-Based Sourcing? Region-based sourcing in retail chains uses digitized geographic boundaries that accurately map store locations or service areas. Unlike traditional sourcing models that rely on rigid city, state, or zip code boundaries, Region-based sourcing defines dynamic, custom-shaped regions on a map. When a customer places an order, the system checks which Region the address falls into, and fulfillment is restricted to the stores or warehouses assigned to that region. Based on business requirements, each Region can have defined store priorities, transfer relationships, and BOPIS/STH eligibility. This approach: Ensures faster delivery times Reduces last-mile shipping costs Allows dynamic adjustments (Regions can be redrawn as business needs change) Supports compliance with local inventory regulations Are There Any Challenges with Region-Based Sourcing? Despite its clear advantages, retail chains face several technical hurdles when they implement Region-based sourcing. These challenges arise from the ever-changing nature of retail environments and the complex geographic calculations that occur in real-time. 01 Dynamic Region Boundaries Region boundaries grow as organizations expand. Systems must flexibly adapt to shifting Regions to keep fulfillment rules accurate. 02 Handling Large Numbers of Regions Some businesses define up to 192 regions in the current Region-based retail setups, demanding thousands of geographic calculations without slowing inventory checks or order creation. 03 External Services for Accurate Region Identification External apps define Regions and require live calls (latitude, longitude, zip) to locate customers. Integrations must stay stable to avoid service disruption. How to Implement Region-Based Sourcing? Implementing Region-based sourcing isn’t a one-size-fits-all process. Retailers can choose between two main approaches depending on their store network size, scalability needs, and technical capacity.  Approach 1: The Distribution Group Model One way to implement Region-based sourcing is through a distribution group model. Under this model: Each Region is treated as a distribution group. The group contains all associated stores and distribution centers(DCs). Priority rules are set for each node within the group. Advantages of the Distribution Group Model Easy to implement, uses OOTB configurations. No code/customization required. Limitations of This Approach Every model has its set of limitations, and this Region-based sourcing implementation approach may not be ideal for every business because of the following factors: Requires upfront knowledge of which stores belong to which Regions. Poor scalability as Regions grow dynamically. During inventory inquiries or order creation, large numbers of static groups can degrade performance. Approach 2: The Dynamic Sourcing Model The Dynamic Sourcing Model is an alternative to implementing Region-Based Sourcing. Under this model: A common distribution group is created for all fulfilling stores Transfer relationships defined between stores remain unchanged A sourcing correction user exit (or plug-in) calls an external service in real time based on the ship-to address (latitude and longitude data fetched) The external service identifies the correct Region and returns the list of eligible stores Advantages of the Dynamic Sourcing Model No need for static mapping of stores to Regions. Supports dynamic region expansion with minimal reconfiguration. Better scalability across large or changing regions. Some Drawbacks of This Approach The Dynamic Sourcing Model requires a fallback plan in case external service calls fail It can become complex if multiple sequencing rules or capacity constraints are later introduced Note –  Many organizations implement a temporary cache or table to store frequently accessed region data, with a toggle to enable or disable it. This reduces data latency without sacrificing accuracy Comparing Distribution Group Model vs. Dynamic Sourcing Model Feature Distribution Group Model Dynamic Sourcing Model Code Customization None; configuration only Required for external integration calls Scalability Poor with many Regions Handles growth better Mapping Static, must be maintained Loaded dynamically in real time Risk Lower (out-of-box support) Higher; must handle integration failures Performance Degrades with large region set Relies on efficient external calls and caching Choosing the Right Approach to Implement Region-Based Sourcing The choice between the Distribution Group Model and the Dynamic Model depends on business maturity and growth stage: Smaller, stable retailers may benefit from the simplicity of the Distribution Group Model. Scaling, multi-region enterprises should invest in the Dynamic Model for long-term agility and accuracy. Both models highlight one truth: retailers must align sourcing strategies with evolving geographic and operational realities. Technical Considerations for Retail Chains to Use Region Data To make Region-based sourcing work at scale, retail chains need more than just accurate maps; they need strong technical foundations. Here are some basic considerations every retailer must keep in mind: REST API Integration Since Region data is often managed in an external application, the order management system must integrate through Rest APIs. Caching and Fallback Strategies A local cache of frequently used Region data minimizes the impact of external call failures. Performance Testing Simulate large region counts (e.g., 192+) and heavy order volumes to ensure acceptable response times. Inventory Transfer Logic Clearly define transfer relationships between stores  when inventory dips, to avoid back-order loops. Business Impact and Outcomes of Region-Based Sourcing The shift to Region-based sourcing delivered clear benefits: Higher fulfillment accuracy Orders were sourced only from appropriate stores within the correct Region. Reduced delays and mis-shipments Improved customer satisfaction by ensuring local relevance. Scalability Able to handle the client’s 192 regions without a performance bottleneck. Flexibility New Regions and stores could be added without reconfiguring large

AI, By Industry, Health and Lifescience (HLS), IBM, Inventory, Retail, Salesforce, Salesforce OM, Service Cloud, Sterling Intelligent Promising, Sterling OMS

Why Modern HLS Organizations Must Rethink Order Fulfillment — and How Salesforce OMS Helps

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The Healthcare and Life Sciences (HLS) industry is undergoing a massive shift. Driven by the need for digital-first, patient-centric, and omnichannel experiences, HLS organizations are rethinking every aspect of how they engage providers, patients, and partners, especially when it comes to order fulfillment. Yet many still rely on legacy systems that are fragmented, inflexible, and not designed for the modern healthcare delivery landscape. At Perfaware, we believe it’s time to modernize fulfillment and that Salesforce Order Management System (OMS) offers a powerful path forward. The Problem: Fragmented Systems, Broken Experiences For many HLS enterprises — whether pharma, medtech, digital therapeutics, or biotech — order fulfillment is a patchwork of disconnected platforms, manual workarounds, and compliance risks. This leads to: Lack of visibility across the order lifecycle Delays in sample shipments and product delivery Frustrated providers and patients Compliance and cold chain tracking challenges Missed opportunities for engagement These problems aren’t just operational — they affect patient outcomes, field rep effectiveness, and brand trust. The Opportunity: Unified, Intelligent Fulfillment with Salesforce OMS Salesforce OMS enables HLS organizations to unify their order capture, fulfillment, and servicing on a secure, scalable, cloud-based platform — fully integrated with Salesforce Customer 360 and compliant with industry standards like HIPAA. End-to-End Visibility Track every order from initiation to delivery across providers, patients, clinical sites, and partners. Compliance at Scale HIPAA-compliant architecture with role-based access, audit logs, and traceability for samples, cold chain, and investigational products. Automation & Intelligence Reduce manual errors through workflow-driven orchestration, approval automation, and AI-powered anomaly detection. Seamless Integration Connects with ERP, supply chain, WMS, CRM, clinical trial systems, and marketing platforms — no more silos. Real Impact Across the HLS Value Chain Whether you’re supporting clinical trial logistics, patient access programs, field sales, or digital marketing, OMS becomes the operational glue that improves: Function OMS Impact Clinical Trials Compliant sample and site shipments Supply Chain Demand planning + cold chain tracking Sales Reps Real-time order placement and tracking Patient Services SLA-based fulfillment of starter kits Marketing Campaign-triggered ordering for samples Customer Support Integrated service for order issues Perfaware’s POV: How We Approach the Transformation At Perfaware, we’ve developed a phased roadmap tailored to HLS clients: Phase 1: Foundation & Enablement Secure, HIPAA-compliant order capture Core workflows: tracking, reshipments, exchanges API connectivity to ERP, WMS, and trial systems Phase 2: Operational Scale Study-specific configurations and forms Real-time shipment and carrier integration Role-based dashboards and insights Phase 3: Intelligence & Automation AI for replenishment and anomaly detection Mobile-ready order UX Intelligent routing and compliance workflows Phase1Foundation & Enablement • Secure, HIPAA-compliant order capture •  Core workflows: tracking, reshipments, exchanges •   API connectivity to ERP, WMS, and trial systems Phase2Operational Scale • Study-specific configurations and forms • Real-time shipment and carrier integration • Role-based dashboards and insights Phase3Intelligence & Automation • AI for replenishment and anomaly detection • Mobile-ready order UX • Intelligent routing and compliance workflows Why Perfaware We are not just Salesforce experts — we are also HLS domain veterans. From Fortune 500 companies to small and mid-sized businesses, our team brings deep industry expertise, operational excellence, and a proven track record of success. Headquartered in Dallas with teams in Mexico, Chile, and India, we bring agility and scale to every engagement. LinkedIn X Email Author Details Srinivas Hanmandlu Managing Partner

AI, IBM, Inventory, Retail, Sterling Intelligent Promising

AI-Powered Enhancements to SIP

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AI-Powered Enhancements to SIP In today’s fast-paced world driven by rapidly evolving technologies, every industry is striving to stay ahead. Over the past decade, the retail sector has undergone a significant transformation, enhancing customer experience through innovations like same-day delivery and drone-based logistics. One of the leading providers of supply chain solutions is IBM Sterling Commerce, which is continuously evolving to adapt to the dynamic needs of this industry. Its comprehensive suite of offerings includes Distributed Order Management (DOM), Sterling Intelligent Promising (SIP), Sterling Store, Sterling Call Center, and more. Now, as we enter the era of Artificial Intelligence (AI), the retail industry stands to gain even more. AI offers numerous opportunities to optimize operations and elevate the customer experience. AI is today’s reality and businesses are fast adopting the same.  What is one of the top priorities in the retail industry? A smarter, more efficient, enhanced and an accurate way to manage inventory. Retailers seek real-time inventory visibility into their stock to avoid stockouts, meet demands effectively and fulfill orders seamlessly across multiple channels. By reducing fulfillment times and streamlining service processes, retailers strive to exceed customer expectations and deliver a superior shopping experience that leads to greater customer satisfaction. The Premium edition of IBM Sterling Intelligent Promising (SIP) helps retailers lower fulfillment costs and improve inventory efficiency by leveraging predictive AI and machine learning. As a retailer, if we are facing challenges with inventory management or struggling to forecast and optimize orders, SIP can offer significant advantages. By analyzing historical data, its AI capabilities help reduce order cancellations, avoid stockouts and markdowns, and optimize costs. But how can we go beyond what SIP already offers? What does SIP really need to perform at its best? The answer is data—accurate, timely, and dynamic data. An AI-powered agent can be introduced that automatically updates the data fed into SIP in real-time. AI-Powered Dynamic Config Updates in SIP – SIP relies on extensive data configuration related to carrier services, such as zone definition, transit duration, and transit rates to accurately identify the most optimized fulfillment node for delivery. Some of these configurations can only be updated via REST APIs, with no user interface to verify or modify the uploaded data. This can make maintenance and updates challenging. However, by introducing an AI-powered assistant, these changes can be automatically captured and pushed to SIP in real time. This makes the system more responsive and adaptive to real-world changes. Store associates, logistics personnel, or admin users would only need to send a simple message about the change, such as a text or voice command and the AI would handle the rest, ensuring SIP has the latest information to make the smartest fulfillment decisions. It need not be limited to just logistics data, it could also update catalog information in real-time, thus reducing the manual work of navigating multiple screens or applications to update the data. AI-Powered Optimizer Data Diagnostics –  Another valuable use case for applying AI in SIP is the detection of exceptions in optimizer results, which are often caused by errors in the initial data configuration. During a recent go-live experience with the optimizer for one of our clients, we found that most issues were caused by zone data mismatches, missing capacity or calendar definitions, or incorrect delivery method setups.   An Agentic AI can proactively alert the business users about a missing calendar or capacity or any other configuration. AI Agent can continuously monitor the configuration data setup for all stores or zones and proactively take action. This would significantly reduce the risk of errors occurring in the production environment. Additionally, an AI-powered assistant can analyze optimizer results to quickly and accurately identify the specific data that led to unexpected results. For example, the AI could help explain why a particular node was selected as the winner—how it achieved the highest score and what factors contributed to that outcome.  This way, we could enhance the optimizer explainer output by not only providing clearer insights into the results but also offering actionable options to correct configuration anomalies. This approach would greatly reduce manual investigation efforts and significantly shorten the turnaround time for resolving production issues. Conclusion We can conclude that AI offers significant potential to enhance the capabilities of SIP for its clients. While we have explored only a few high-level use cases here, the opportunities extend far beyond, into business-specific scenarios that can be addressed through thoughtful AI integration. Looking into the future, we are aiming to explore and implement these advanced use cases, harnessing the full power of AI to drive innovation and efficiency. If you are looking to innovate your brand with AI solutions, we would love to collaborate. Reach out to us to explore these or similar fresh perspectives to bring your vision to life. LinkedIn X Email Author Details Divya Ravi Senior Manager – Technology A Senior Manager in the OMS practice at Perfaware, she has been leading key client engagements for over four years. With more than 15 years of experience specializing in IBM Sterling, she has successfully delivered go-live implementations across the US, Europe, LATAM, and Asia. Her expertise spans IBM Sterling OMS, including Call Center and Web Store solutions, and she has led several agile teams to success. She is passionate about leveraging emerging technologies to drive innovation and deliver scalable, future-ready solutions for global clients. Divya Ravi Senior Manager – TechnologyA Senior Manager in the OMS practice at Perfaware, she has been leading key client engagements for over four years. With more than 15 years of experience specializing in IBM Sterling, she has successfully delivered go-live implementations across the US, Europe, LATAM, and Asia. Her expertise spans IBM Sterling OMS, including Call Center and Web Store solutions, and she has led several agile teams to success. She is passionate about leveraging emerging technologies to drive innovation and deliver scalable, future-ready solutions for global clients.

By Tech/Product, By Topic, Order Management, Salesforce OM

Overcoming Disconnected Business Workflows Using Salesforce Order Management

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Introduction In an order management system, disconnects between teams—whether internal or external to Salesforce—can lead to delays, errors, and a lack of visibility throughout the order lifecycle. These challenges become even more significant when teams do not have direct access to Salesforce, making it difficult to manage workflows efficiently. In this post we share three critical business challenges we resolved using innovative email integration solutions in Salesforce. We also outline the solution approach adopted that significantly eliminates manual work and improves customer experience and financial accuracy: Business Challenges & Solutions 1. Tax Exemption Determination and Customer Communication The Challenge: The Tax Team, which operates outside Salesforce, needs to verify whether a customer is eligible for tax exemption. They communicate approval decisions via emails containing keywords like “approved” or “denied.” However, there was no direct link between these emails and the corresponding Salesforce order records, leading to inefficiencies. The Solution: We built a custom email tracking solution that captures emails from the Tax Team and scans them for keywords like “approved” or “denied.” By embedding unique references such as OrderId@businessname.com in email headers, the system automatically linked the emails to relevant orders. Another unique reference, TaxExempt@businessname.com, ensured that Salesforce order records were updated in real-time, allowing for accurate tax calculations. 2. Credit Application Review and Order Status Updates The Challenge: The Finance Team manually reviewed credit applications and updated order statuses in Salesforce. Manually linking the credit decision to the corresponding order was time-consuming and prone to human error. The Solution: We automated the update process by intercepting emails from the Finance Team containing credit decisions. Using unique email headers, the system automatically updated the order records in Salesforce without manual intervention. This solution streamlined the workflow, ensuring faster order processing and reducing the risk of errors. 3. Wire Payment Tracking and Updates The Challenge: The Cash Management Team needed to track wire payments, often relying on email notifications. However, there was no automated link between wire payment details and Salesforce order records, leading to delays and data entry errors. The Solution: We implemented a custom email integration that intercepted wire payment emails from the Cash Management Team. The system extracted relevant payment details—such as amount received and transaction date—and updated the corresponding order records in real-time. This eliminated manual data entry, ensuring accurate and prompt payment tracking. Key Benefits of Custom Email Integration Solutions Technical Approach: Customizing Salesforce for Email Integration We leveraged Salesforce’s email capabilities while implementing custom solutions tailored to our needs: Conclusion: Driving Efficiency with Custom Email Integration Salesforce Order Management provides the framework for managing orders, but custom email integrations optimize the process. By automating inter-team communication and linking emails directly to order records, we addressed key business challenges such as tax exemption processing, credit application reviews, and wire payment tracking. With real-time updates and seamless workflows, businesses can streamline their order management, minimize errors, and enhance collaboration—resulting in faster, more efficient order processing.   LinkedIn X Email Author Details Iftekhar Hussain Associate Architect

By Topic, Payments

How payment processing automation helps the business?

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We’ve all been there—processing a payment, only for it to fail due to a server error, a bad request, or an intermittent connection issue. These hiccups can delay transactions, frustrate customers, and create unnecessary manual work for your team. In today’s fast-paced eCommerce environment, relying on manual intervention to re-capture failed payments is no longer sustainable. The good news? Salesforce Order Management System (OMS) offers the flexibility and integration capabilities to automate payment re-capture processes, ensuring seamless transactions and improved operational efficiency. While Salesforce OMS doesn’t provide an out-of-the-box solution for automatic payment re-capture, its robust API and customization options allow businesses to build tailored solutions that meet their unique needs. In this blog, we’ll explore the key steps and considerations for automating payment re-capture in Salesforce OMS, along with real-world scenarios to help you design an effective solution Salesforce Payment Automation Swift Payment Collection Cost and RiskReduction Enhanced customer Experience Increased visibility and Insights Why Automate Payment Re-Capture? Payment failures are inevitable, but how you handle them can make all the difference. Automating payment re-capture offers several Benefits: Reduced Manual Effort: Eliminate the need for manual intervention, freeing up your team to focus on higher-value tasks. Improved Customer Experience: Ensure timely payment processing, reducing delays and enhancing customer satisfaction.Enhanced Efficiency: Streamline payment workflows, minimizing errors and improving reconciliation processes. Fraud Prevention: Automatically flag and handle fraudulent transactions, protecting your business from potential losses. BY ALIGNING THE BUSINESS’S STRENGTHS WITH OPERATIONAL CAPABILITIES, SALESFORCE ORDER MANAGEMENT (OMS) HELPS CREATE A SMOOTH CONNECTION BETWEEN CUSTOMER EXPECTATIONS AND FULFILLMENT PROCESSES, ENSURING EFFICIENCY AND OPTIMAL SERVICE AT EVERY TOUCHPOINT. 6 Key steps to automate payment re-capture in salesforce oms that will streamline your payment processes and boost your operational efficiency. Identify Failed Captures The first step in automating payment re-capture is identifying invoices that failed during the initial capture attempt. Salesforce OMS allows you to use custom fields or flags on order or invoice records to track payment status. For example, you can create a custom field like “Capture Status” to mark invoices as “Failed,” “Pending,” or “Success.” This makes it easy to pinpoint which payments need re-capture. Configure Re-Capture Attempts The first step in automating payment re-capture is identifying invoices that failed during the initial capture attempt. Salesforce OMS allows you to use custom fields or flags on order or invoice records to track payment status. For example, you can create a custom field like “Capture Status” to mark invoices as “Failed,” “Pending,” or “Success.” This makes it easy to pinpoint which payments need re-capture. Leverage Transaction Responses to Guide Actions Payment gateways provide detailed transaction responses that can guide your re-capture logic. For instance, if a transaction is voided or the authorization has expired, your system can switch to an alternative API call, such as Auth + Capture, instead of simply retrying the capture. This level of customization ensures that your solution can handle a variety of scenarios effectively. Handle Fraudulent Payments Not all failed payments are worth retrying. If a payment is flagged as fraudulent, it’s critical to mark it as failed and avoid further re-capture attempts. By integrating fraud detection logic into your re-capture process, you can protect your business from potential losses and ensure compliance with security standards. Update Salesforce Records Upon Success Once a payment is successfully re-captured, it’s essential to update the relevant Salesforce records to reflect the successful transaction. This includes updating the payment line, marking the invoice as paid, and linking the relevant objects to the successful transaction. Salesforce’s flexible object model makes it easy to keep everything in sync. Ensure Reconciliation and ERP Integration The final step in the process is ensuring that the payment re-capture triggers the necessary updates in your ERP system. This includes posting the sale, updating inventory levels, and reconciling the invoice. By integrating Salesforce OMS with your ERP system, you can ensure that all systems are synchronized and that your financial records are accurate Takeaway/Insights Automating payment re-capture in Salesforce OMS is a game-changer for businesses looking to streamline their payment processes, reduce manual effort, and improve customer satisfaction. While Salesforce OMS doesn’t offer an out-of-the-box solution for this, its flexibility and robust integration capabilities make it the perfect platform to build a custom solution tailored to your business needs. By focusing on key considerations like re-capture logic, transaction response handling, fraud detection, and ERP integration, you can design a solution that ensures your payments are processed securely and efficiently. Re-capture is just the basics of payment processing; we’ve also tackled more advanced challenges like payment sequencing, re-authorization, scheduled voids, refund sequencing, refunds and integrations with PayPal, credit cards, After pay, Pay By Link, hosted payment pages, and more. At Perfaware LLC, we specialize in implementing seamless payment processing systems using Salesforce OMS. Our team of payment experts brings years of experience and deep technical expertise to help you solve payment re-capture challenges and elevate your order management system to the next level. Reach out to us for a personalized demo. Let’s turn your payment challenges into opportunities for success. WHAT ARE YOUR THOUGHTS ON AUTOMATING PAYMENT RE-CAPTURE? HAVE YOU FACED SIMILAR CHALLENGES ? LinkedIn X Email Author Details Renuka Nagaraj Lead Technical Consultant

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