Cross-Channel Interaction Patterns

If you're already running both online and offline, great. But here’s the catch: if they’re not working together, you're leaving serious money on the table. In 2025, the brands crushing it aren’t just running eCommerce alongside their stores - they’re making the two play in perfect sync. Here’s how to make that happen: 1. MAKE STORES DRIVE ONLINE SALES (NOT COMPETE) 🚫 Treating online & offline as separate businesses. ✅ Create a synergy between online & offline: - Train store staff to drive online sales (referral codes, incentives). - Enable online browsing in-store (QR codes, tablets). - Showcase online-only products in physical locations. 2. PRICE STRATEGY BEATS AD SPEND 🚫 Dumping money into ads without adjusting pricing. ✅ Use strategic pricing to drive revenue: - Bundle slow-moving inventory with bestsellers. - Offer small discounts for store pickup (cuts shipping costs, boosts foot traffic). - Adjust pricing dynamically based on demand. 3. LEVERAGE AI FOR PERSONALIZED CROSS-CHANNEL EXPERIENCES 🚫 Using generic, one-size-fits-all recommendations. ✅ Implement AI-driven personalization to connect online and offline interactions: - Use AI to send targeted offers based on in-store browsing behavior. - Personalize email/SMS campaigns based on cross-channel activities. - Deploy dynamic pricing tools that reflect both customer behavior and store traffic. 4. STREAMLINE CUSTOMER JOURNEY WITH REAL-TIME INVENTORY VISIBILITY 🚫 Letting customers face out-of-stock frustrations or mismatched inventory online and in-store. ✅ Offer real-time inventory visibility across all channels: - Provide live stock updates both online and in-store for a smooth customer experience. - Use geo-location to show nearby stores with product availability when something is out of stock online. - Automate stock replenishment and adjust inventory based on real-time demand across both platforms. 5. OPTIMIZE FOR CROSS-CHANNEL CUSTOMER SERVICE 🚫 Treating customer service as a siloed, one-off interaction rather than an integrated experience. ✅ Provide a unified, effortless service experience: - Enable store staff to access online customer data to assist in-store inquiries or resolve issues. - Use live chat, social media, and in-store assistants to offer omnichannel support. - Offer customers the flexibility to initiate returns or exchanges online and complete them in-store (or vice versa). The future of retail is effortless integration. Make your online and offline channels work together to drive growth and create a unified customer experience.

Where do your prospects like to be touched? Not in the creepy way. In the marketing way. Most teams mistake “touches” for impact. They blast impressions across channels, recycle the same content everywhere, and hope something sticks. That’s not strategy. That’s guessing. The reality is… your prospects are already telling you exactly where and how they want to engage. Every digital move they make leaves behind a signal: A pricing page visit that screams bottom-of-funnel interest A repeat ad click from a Director who’s clearly warming up A LinkedIn post comment where they reveal pain points in their own words A webinar signup that shows topic-level intent CRM data on accounts that suddenly light up The teams that win don’t force-feed campaigns into one channel — they align activation with those signals. So what does that look like in practice? 👉 If they’re consuming your thought-leadership posts on LinkedIn, retarget them with a case study ad instead of hammering them with a cold ebook. 👉 If they’ve visited your pricing page twice, don’t waste time showing them generic top-of-funnel ads. Hit them with a direct offer — demo, calculator, or comparison guide. 👉 If CRM shows dormant accounts are engaging again, sync LinkedIn + Google campaigns to surround them with contextually relevant messages while SDRs follow up. 👉 If multiple stakeholders from one company are poking around your content, that’s not a coincidence — it’s an account-level buying committee heating up. Saturate them with middle-of-funnel creative. This is signal-led marketing. It’s about listening before you touch. The payoff? Less wasted budget on noise More meaningful touches that actually move pipeline A cross-channel motion that compounds impact instead of scattering it That’s why we built DemandSense — to surface the right signals and trigger the right activation, whether that’s LinkedIn, Google, nurture, or retargeting. Stop guessing. Start listening. Your prospects are literally telling you how to market to them. Website LinkedIn Ads Agency: https://lnkd.in/guEafPKk B2B Strategies and Guides: https://lnkd.in/gB-WQ82f Impactable YouTube Channel: https://lnkd.in/emYVDn_T

🚀 Thrilled to share our latest research in the Journal of Marketing Research (JMR)! 📢 📱 Title: Cross-Channel Effects of Failure in a Retailer’s Mobile App 🔗 Read here: https://lnkd.in/dXfSBeD7 💡 Key Takeaways: 👉 When a retailer’s mobile app malfunctions, the impact extends far beyond digital interactions—negatively affecting consumer behavior across online and physical stores. 👉 Surprisingly, the decline in purchases across channels primarily stems from reduced purchases in stores rather than the online channel. 👉 The predominant reason is that shoppers who use the app primarily for search but complete their purchases in stores, are unable to use the app for search and curtail their offine purchases following the app failure. In contrast, shoppers who use the app primarily to purchase, simply pivot their purchases to another online channel such as the website. 👉 App failure affects different shoppers differently. Shoppers with a lower monetary value of past purchases and more recent purchases are more sensitive to an app failure than others. 👉 Retailers must act swiftly to recover from app failures—not just to retain app users but to protect their broader customer base. A huge thank you to the editorial team at JMR, led by Raghu Iyengar, for their proactive and constructive review process. 🙌 Your feedback elevated our work, and we truly appreciate the rigorous yet supportive approach! 🙏 It was a pleasure to work with the brilliant and "never-say-die" co-authors, Unnati Narang (Gies College of Business - University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign) & Sridhar Narayanan (Stanford University Graduate School of Business, Stanford University). 📢 Excited for discussions on how brands can safeguard their omnichannel experience in an increasingly mobile-first world! Let’s connect and explore the implications. #CustomerEngagement #MarketingResearch #RetailTech #Omnichannel #CustomerExperience #JMR #AcademicResearch #MobileApps #ConsumerBehavior #DigitalMarketing #MobileMarketing #Retailing #Retail #ServicesMarketing #CRM SMU Cox School of Business Southern Methodist University Brierley Institute for Customer Engagement

In today’s hyperconnected world, understanding your customers no longer means tracking clicks or counting conversions - it means decoding the full narrative of how people move, decide, and connect across every channel. Customer Journey Analytics turns fragmented data into a unified, behavioral map that reveals the true flow of experience behind every purchase, sign-up, or interaction. Journey analytics follows behavior as it unfolds - how someone discovers a brand on social media, compares options on mobile, signs up through an email, and completes a purchase in-store. Each of these steps reflects both data and intention, and when linked together, they reveal the underlying logic of decision-making. This clarity allows organizations to see where attention drifts, where delight occurs, and where friction stops momentum. At the heart of the practice is journey mapping - the process of visualizing the full customer lifecycle from awareness to advocacy. By combining behavioral data with emotional and contextual signals, teams can understand what customers feel at each stage and design experiences that match those expectations. Touchpoint analysis adds another layer of insight by evaluating which interactions truly drive engagement and which need rethinking. The modern customer journey is fluid. People start on one device, switch to another, and complete their actions elsewhere. Cross-channel optimization connects those pathways, merging data from social, web, mobile, and physical environments. Machine learning models can then detect patterns and predict what happens next, empowering teams to act at the right moment with precision and empathy. Path and attribution analysis refine this even further. Rather than crediting the last click, advanced models assign value across every contributing touchpoint - ads, emails, search, and referral traffic- clarifying which combinations of actions actually lead to conversion or retention. But data alone isn’t enough. The most effective journey analytics strategies blend quantitative patterns with qualitative understanding - surveys, interviews, and sentiment analysis that explain the emotional “why” behind behavioral “what.” A drop-off on a checkout page might be clear in the numbers, but only customer feedback reveals whether it’s caused by confusion, lack of trust, or poor usability. Leading organizations already use journey analytics to bridge this gap between insight and action. Retailers link online behavior to in-store experiences, streaming services personalize recommendations in real time, and airlines trace the entire travel journey to enhance loyalty. Each case demonstrates how connecting data and human understanding reshapes the way companies anticipate needs, reduce friction, and build stronger relationships.

Ever called customer service after buying online and felt like a total stranger? Customers don't think in channels.  They think brand. Yet many brands still act like five different departments talking to one customer at once. You know the story: → The app knows your cart. The call centre doesn't.  → The store can't find your online order.  → You get the same promo three times: email, SMS, and pushed to your digital wallet. Sounds like multi-chaos, not omnichannel. And it's costing you. 73% of customers use multiple channels during their shopping journey. But when those channels don't talk to each other, 86% say they'll take their business elsewhere. This is the "E" in my C.L.I.E.N.T. Growth Framework - 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Across Channels.  One conversation.  Many touchpoints.  Seamless and human. Here's what the best brands do differently:  Consistency over confusion.  Customers should start something on one channel and finish it on another, without friction. Sephora is a great example: their Beauty Insider members can check purchase history, book services, and access rewards across the app, web, and store. Their omnichannel customers spend 2.5x more than single-channel shoppers. Nice!   • Personal touch over spray & pray.   • Don't blast the same message everywhere.   • Meet customers where they respond best.   • SMS has a 98% open rate vs. 20% for email, if used strategically.   • Digital wallet passes get opened at 48% within 48 hours.   • Send the urgent cart reminder via text.   • Save the story for email.   • Put the time-sensitive offer in their wallet. Know the difference. Service is the new marketing.  61% of customers will switch to a competitor after just one poor service experience.  But here's the opportunity: companies with strong omnichannel customer service retain 89% of their customers. One support call does more for loyalty than ten clever marketing emails.  I've seen brands turn their worst customer moments into their best testimonials by being human and helpful across the right channel at the right time.  So here's my challenge:  Map your customer journey.  Find the handoffs, those messy transitions between channels.  Fix one, and you'll feel the lift immediately. 👉 Where does your customer experience still feel disconnected? 𝘗.𝘚. 𝘌𝘯𝘨𝘢𝘨𝘦𝘮𝘦𝘯𝘵 𝘈𝘤𝘳𝘰𝘴𝘴 𝘊𝘩𝘢𝘯𝘯𝘦𝘭𝘴 𝘪𝘴 𝘫𝘶𝘴𝘵 𝘰𝘯𝘦 𝘱𝘪𝘦𝘤𝘦 𝘰𝘧 𝘮𝘺 𝘊𝘓𝘐𝘌𝘕𝘛 𝘍𝘳𝘢𝘮𝘦𝘸𝘰𝘳𝘬. 𝘐𝘧 𝘺𝘰𝘶 𝘸𝘢𝘯𝘵 𝘵𝘰 𝘴𝘦𝘦 𝘩𝘰𝘸 𝘵𝘩𝘦 𝘧𝘶𝘭𝘭 𝘴𝘺𝘴𝘵𝘦𝘮 𝘩𝘦𝘭𝘱𝘴 𝘣𝘳𝘢𝘯𝘥𝘴 𝘣𝘶𝘪𝘭𝘥 𝘵𝘳𝘶𝘴𝘵, 𝘤𝘳𝘦𝘢𝘵𝘦 𝘭𝘰𝘺𝘢𝘭𝘵𝘺, 𝘢𝘯𝘥 𝘥𝘳𝘪𝘷𝘦 𝘴𝘶𝘴𝘵𝘢𝘪𝘯𝘢𝘣𝘭𝘦 𝘨𝘳𝘰𝘸𝘵𝘩, 𝘭𝘦𝘵'𝘴 𝘤𝘰𝘯𝘯𝘦𝘤𝘵.

📣 Breaking the silos = unlocking serious growth in FMCG retail. We’ve been testing and measuring integrated marketing campaigns across different touchpoints — from digital media to in-store activations. The results are clear: 📈 Integrated campaigns drive 157% higher ROI compared to single-channel efforts. But here’s the real kicker: 🛒 When digital ads are aligned with in-store promotions, basket size increases by 34%. That’s not a small lift. That’s category growth. So what’s really happening? Consumers don’t think in channels — they don’t care if your brand message comes from a shelf, a screen, or a sample. They respond to consistency, timing, and relevance. Here’s what our top-performing cross-channel campaigns had in common: ✅ Clear product positioning across both physical and digital assets ✅ Time-bound, in-store rewards that matched online promotions ✅ Dynamic creative on digital based on real-time stock and store locations ✅ Retail media placements that complemented in-store visibility (not duplicated it) This is where many FMCG brands are still missing the mark: Marketing runs digital. Trade runs in-store. Sales tries to connect both… usually too late. 💡 Integration isn’t about working more. It’s about working together earlier. When media buyers, brand managers, and sales teams co-create one unified plan — built around the same campaign objective — you unlock efficiency and effectiveness. 🧠 So here’s a question worth asking on your next campaign review: Are we pushing a message — or orchestrating a journey? And if your in-store mechanics aren’t supporting your online media spend (or vice versa), then part of your budget is leaking. 🔄 What you can start doing now: Bring your trade, brand, and media planning calendars into the same war room — earlier. Use store-level data to tailor digital creative and target based on supply reality. Push retailers to enable closed-loop measurement where possible — it’s worth it. Measure campaign success beyond impressions or sell-out. Look at cross-channel impact on basket size, units per transaction, and repeat purchase. We’re in an era where execution beats strategy — but only if your execution is connected. Would love to hear: What’s been your biggest unlock (or challenge) with cross-channel retail campaigns? Let’s learn from each other — we all win when shoppers win. #RetailMarketing #FMCG #CPG #IntegratedMarketing #OmnichannelRetail #DataDrivenMarketing #TradeMarketing #RetailExecution #ShopperMarketing #CustomerJourney #RetailMedia #InstoreMarketing #MarketingAnalytics #RetailGrowth #MarketingEffectiveness #CrossChannelStrategy #ConsumerBehavior

Day 3 of my “Real-World Oracle OIC Patterns” series Most Oracle Fusion Cloud customers don’t have one order source. They have Salesforce or another CRM, a web store, CPQ, EDI feeds, marketplaces… all of them trying to push orders into Oracle Fusion Cloud Order Management. Without a clear pattern, teams end up with: • Different payloads and mappings for every channel • Duplicate orders when retries aren’t idempotent • Inconsistent order status between CRM / e-commerce and ERP A pattern that has worked well for me is a “canonical order hub” on Oracle Integration Cloud (OIC): 🔹 Channel-specific adapters in OIC (Salesforce Adapter, REST, files, B2B/EDI) accept orders from each source in its native shape. 🔹 OIC translates them into a canonical sales order model and invokes Oracle Fusion Cloud Order Management using the Sales Orders for Order Hub REST APIs for online orders, or FBDI for large batch loads. 🔹 Idempotency keys and sequencing live in OIC, so retries don’t create duplicates and late messages don’t overwrite the latest version of the order. (Crucial when channels or networks are “eventually consistent”, not perfect.) 🔹 Order status, shipment updates and exceptions flow back from Order Management as business events and REST calls through OIC, which normalizes them and pushes them back to Salesforce, the web store, or other channels. The result is a single, Oracle-aligned order backbone: • Fusion OM/GOP remains the system of record for order orchestration and promising • Each channel stays loosely coupled with its own data model • Business users get consistent order status everywhere (CRM, storefront, ERP) Question for you: How are you handling multi-channel order capture into Oracle Fusion today – point-to-point per channel, or a centralized pattern like this on OIC? — Aman Khurana #OracleIntegrationCloud #OracleCloudERP #OracleSCMCloud #OrderManagement #OracleOrderManagement #OIC #SalesforceIntegration #Ecommerce #EnterpriseArchitecture #IntegrationPatterns

🌊 Surfing vs Structuring: Same Data, Different Stories in AML & Fraud Detection In AML and fraud, it’s not always about how much money moves—often, the real signal lies in how and where it moves. 🔍 🧱 Structuring Splitting large amounts into smaller transactions to stay just below regulatory reporting thresholds. Detection: Rule- and threshold-driven Velocity rules Cumulative amount checks Cash-intensive behavior patterns Example: A customer deposits ₹9,800 daily for 7 days across different branches instead of a single ₹68,600 deposit—intentionally avoiding automatic reporting. 🌐 Surfing Focuses on behavioral movement, not transaction size. A customer rapidly “surfs” across: Channels Devices Products Geographies …in ways that deviate from their historical profile. Example: A domestic user suddenly logs in from a new device, adds multiple payees, and sends small transfers via card, wallet, and instant payments to different countries within an hour. 📢 Why it matters: These patterns often appear in fraud, mule networks, and scam activity, even when transaction values are low. 🧠 Why Modern Risk Teams Care Systems focused only on structuring catch under-the-threshold transactions but may miss agile, low-value surfing patterns. Structuring detection: Rules & thresholds Surfing detection: Behavioral analytics, device intelligence, network analysis ⚖️ In a Mature Financial Crime Program, Both Must Coexist ✔️ Structuring lenses: Protect against traditional placement and layering ✔️ Surfing lenses: Capture cross-channel, cross-entity journeys that seem “small” in isolation but “loud” in context 🚀 The real edge for AML & fraud teams: It’s not choosing between surfing or structuring—it’s designing monitoring that can tell the story the data is showing today.