Optimizing CRM for Ecommerce Transactions

Could your team answer this today, and how long would it take? "How many of the customers who... - Signed up through our holiday marketing campaign in Q4 - On the annual family plan - paying with a Chase-issued card Had their first renewal attempt declined for ‘insufficient funds’, ? And of those... - How many were successfully recovered within 7 days - Versus how many ended up churning within 30 days?" An organization that can answer these types of questions quickly and accurately can react quickly, which results in happier customers and satisfied executives. At its core, payments optimization is only as good as the join between internal business data and transaction data. PSPs, networks, and banks give you a rich stream of authorization, settlement, and dispute data, but merchants must bring their own customer and product context in order to produce actionable insights that are relevant to their business. To make this data usable, merchants need to normalize a few key dimensions: A. Customer-level data - Unique customer identifier that persists across systems (CRM, billing, payments, support). - Cohort tags: acquisition channel, geography, subscription tier, customer tenure, annual vs monthly - Payment Event stage: Card verification, free-to-paid trial conversion, non-trial conversion, renewal (1 to N) B. Subscription contract data - Plan/tier ID (standardized across billing and payments). - Start and end dates, renewal frequency, billing currency. - Status flags: active, paused, canceled (with standardized cancel reasons). C. Invoice/order-level data - Invoice ID (must be consistently mapped to payment transaction IDs). - Line items (tier, add-ons, discounts, tax). - Net and gross amounts, including refund/credit adjustments. D. Payment transaction data - Transaction ID (gateway/PSP ID). - Decline reason codes (normalized across acquirers/networks). - Payment method type, issuer BIN, network tokenization status. - Success/settlement status, fraud signals, retries, dispute lifecycle. E. Linking logic - A clean key structure: customer_id → subscription_id → invoice_id → transaction_id. - Consistent timestamping (UTC, ISO8601, normalized across systems). - Master data management (e.g., ensuring “Invoice 12345” in billing = “Payment 12345” in PSP). When structured this way, you can slice performance by cohort (e.g., “Trial-to-paid in LatAm declines more often on first attempt”), payment method (e.g., “BIN ranges in Southeast Asia fail more often at renewal”), or customer lifecycle (e.g., “Annual renewals have higher closed account declines than monthly”). Most merchants I meet with can't answer even a fraction of that first question. Not because the data doesn't exist, but because it isn't structured. If this sounds familiar, let's talk.

Social commerce isn’t new. But intelligent orchestration between chat interfaces and CRM platforms? Unfortunately, it's still missing in 80% of APAC retail, despite the data trail screaming for action. Today, Forrester notes that 76% of APAC luxury consumers engage via chat before a purchase—yet fewer than 30% of brands convert that into structured sales journeys. Why is that and how do we solve these problems? At CLD and ChatLabs, I'm proud to see that our teams are pushing to change that. Recently, one of our teams, working for a global jewelry client, built an intelligent Salesforce + Alibaba Cloud + Weixin/WeChat Mini Program integration that went far beyond scripted automation: Here’s what the system did: 1) Parsed event-tagged message histories to segment users in real time—without relying on static rules. 2) Triggered live commerce experiences via WeCom based on user scoring thresholds—driving engagement from passive chat to active conversion. 3) Logged and synced all transaction data back into the CRM—creating a closed-loop performance layer for sales and marketing. How did it work technically? The team worked on extending our custom AI layer, which implemented a temporal intent model—using time-based and sequential interaction patterns to improve eligibility scoring across user segments. This layer is important, because it allows us and all our global clients to evolve scoring logic continuously without the need to retrain full models. The end result, is that our orchestration model is now scaling globally to places including the WhatsApp Cloud API in the UAE, as well as Meta properties across across LATAM. Sitting in an internal debrief this past weekend, I was fascinated hearing the team, including Omid Pourmomen 欧明德, disect the importance of the design and their design choices. While the the front-end interface can shift, the intelligent backbone stays the same, following this paradigm: Event tags → Behavioral scoring → Dynamic journey routing → CRM loopback. What really resonated for me from all this work? Here’s the hard truth: Most brands say they’re “doing personalization.” What they actually have is a marketing automation platform sending generic flows. What we’re building and deploying globally is fundamentally different: AI-driven inference pipelines at the edge that react to customer behavior in real time. As I tell our team and our global clients constantly, if your chat strategy ends at the inbox, you're losing the game. I'm so proud of our global team who is working tirelessly to architect systems that think, respond, and convert—across borders, languages, and platforms. #SocialCommerce #CRM #WeChat #WhatsAppAPI #RetailTech #Salesforce #MiniPrograms #LuxuryRetail #CLD #Personalization #AI #CustomerExperience #APACRetail #Agents Here is a link to the case: https://lnkd.in/gYjYDzPq

Picture this…A customer searches your site for “3/4 inch hydraulic hose” but your product page doesn’t include that size anywhere in the description. Nothing shows up so they leave and buy from a competitor instead. Here’s where it breaks down: Your product data is incomplete. The size isn’t listed clearly, so your website can’t match it to the search. And because the data’s missing, your AI and CRM can’t do much with it either. No product data = no discovery. No discovery = no sale. But clean data changes everything. Now imagine that hose has complete specs: inner diameter, pressure rating, end fittings, SAE standards, the works. Suddenly: Customers can find exactly what they need Your AI can suggest compatible fittings or alternatives Your CRM can build quotes automatically Your rep gets the lead, with full context of what they're looking at online That’s why we built Proton PIM. To power: -Better AI match rates -Smarter product recommendations -Higher ecommerce conversions -Automated quotes and workflows Because clean product data isn’t just about staying organized, it’s the foundation of your entire revenue engine. Here’s how it all connects... 1. PIM ensures your product pages are complete and searchable 2. ecomm turns that data into demand signals like product views and cart activity 3. CRM uses those signals to guide reps on who to call, what to sell, and when to reach out, while AI handles the admin tasks like quote and order entry for them in the background. When your systems speak the same language, customers find what they need, reps sell more, and your team gets to spend less time chasing data and more time building relationships. That’s why we built Proton PIM. To make your tech stack smarter and your team more human. https://lnkd.in/eFe_F8mz

You just chose a CRM now - HOW to start well? Here’s the thing: great firms invest in the best CRM, but struggle in getting real results. Why? Because they focus on the tool, not what matters: conversions. Here’s how I approach it. And I NEVER speak about vendor (sorry Salesforce, Hubspot, Zoho etc.) 1️⃣ Forget the fancy features. The platform is the vehicle. What matters is how you’re driving. If you’re not tracking (and improving) conversions, you’re wasting time. PERIOD 2️⃣ Map the customer journey. Do you really know where your customer is dropping off? Can you point to the exact stage where you’re losing sales? Map out every touchpoint and get specific. Peter Cohan says "you don't know what you don't know". (read Doing Discovery) 3️⃣ Analyze conversion data. Data is your best friend. Map them into your CRM analyze the conversion rates at each stage. Focus your energy where matters. 4️⃣ Optimize relentlessly. The journey doesn’t stop at setup. It’s about continuous optimization. Personalization and timing are key. BONUS takeaway: IF conversion is primary focus. CRM platform takes a backseat. It’s all about understanding your customer, mapping their journey, and refining every interaction for max results. Stop focusing on the tool. Start focusing on outcomes. PS slide in italian - sorry for that - concept is clear.

99% of companies out there use their CRM as an expensive contact list. Here's how you can use your CRM to make people buy more. The reality is that your best customers are already telling you exactly how to make everyone spend more. Here's a simple plan to transform your CRM into a revenue machine: Map your high-value customer journey: → Identify what actions your top 10% of spenders take before purchasing. → Look for patterns in their behavior, not just demographics. Track the right KPIs: → Ignore vanity metrics like total users. → Focus on purchase frequency, average order value, and time between purchases. → Set up custom conversion events for key micro-commitments. Segment based on behavior, not just attributes: → Create dynamic segments based on specific actions. → Prioritize recency and frequency indicators. Build behavior-triggered campaigns → Abandon time-based sequences that ignore customer context. → Create personalized triggers based on your top spenders' patterns. → Automate responses to high-intent signals. Test cross-channel orchestration → Your best customers engage across multiple touchpoints. → Build consistent experiences across email, in-app, push, and SMS. → Use Braze's Canvas tool to coordinate messaging. Measure incremental lift, not just opens → Track how campaigns actually increase spending. → Use control groups to validate your approach. → Optimize for revenue, not engagement. Your CRM already contains the blueprint for massive growth. It shouldn't just be a database of contacts. Stop using it as an expensive contact list. Start using it as the revenue engine it was meant to be. 📌 PS. Do you want help with this? Send me a DM with "VALUE" We've helped 50+ brands increase their profit by optimising their CRM and finding high value customers.