Retail Customer Retention Methods

Marketing Cloud Engagement New Release info --- 🚀 Transactional Send Reconciliation: Guaranteed Delivery Status Reporting Salesforce introduced a new data extension template: 👉 Sendable Reconcilable Data Extension This finally enables something many of us have wanted for years: ✅ Per-subscriber delivery status ✅ Guaranteed send results ✅ Accurate reconciliation with external systems You can now track whether each transactional Email / SMS was: • Sent • Not Sent • Failed (with error reason) All stored in the new data view: 📊 _ReconcilableDispositionView !!!!!!!!!!!! 💡 Why this matters Until now, transactional sends were hard to fully verify. You might know a job executed… …but not whether each message actually reached the send stage. With Transactional Reconciliation, you get: ✔ Delivery monitoring ✔ Troubleshooting ✔ Resend control ✔ External system log matching ✔ Audit / compliance reporting This is especially powerful for: • Order confirmations • Shipping notifications • OTP / 2FA • Reservation confirmations • API-triggered sends ⏱ Time Window Control (1–72 hours) You can define a reconciliation window: • Short window → real-time monitoring • Long window → reporting / aggregation / compliance Examples: ⚡ 1–3 hours → immediate fallback notification 📈 24–72 hours → weekly/monthly reporting 📬 Supported Send Methods Works with: • Email Studio sends • Automation Studio email activities • Journey Builder • REST API Transactional sends ⚙ Key Setup Tips When configuring: ✅ Set Send Classification = Transactional ✅ Enable Transactional Reconciliation in Delivery Options ✅ Default window = 12 hours ✅ Enable HTS for Journey Builder (not Hyperforce) Important note: ⚠ Transactional journeys cannot use Sendable Reconcilable DEs directly Use "Triggered Send Data Extension" template instead. 📊 Example Query You can analyze results via Automation Studio: ============================ SELECT   JobId,   Channel,   Disposition,   MessageKey,   SubscriberKey,   SubscriberId,   ErrorCodeId,   ErrorName,   StartTime FROM _ReconcilableDispositionView ============================ 📌 What you can verify Per subscriber: ✅ Actually sent ✅ Failed ✅ Error reason Disposition values: • 0 = Queued • 1 = Sent • 2 = NotSent Perfect for: 👉 Marketing Cloud logs ＝ Your system logs ⚠ Retention Data kept for 7 days only If you need history: ➡ Export to Data Extension ➡ Automate storage via Automation Studio 🧠 My Take Compared to _Sent, this is: 💥 More reliable 💥 More explicit 💥 Designed for transactional guarantees For: • API sends • External integrations • Delivery audits • Error analysis This is honestly a game-changer feature for transactional messaging. Blog: https://lnkd.in/guzAp_wC More Salesforce Marketing Cloud tips coming soon 😎 Nobuyuki Watanabe #Salesforce #MarketingCloudEngagement #MomentMarketer #MarketingChampion #MarketingChampions

How To Handle Sensitive Information in your next AI Project It's crucial to handle sensitive user information with care. Whether it's personal data, financial details, or health information, understanding how to protect and manage it is essential to maintain trust and comply with privacy regulations. Here are 5 best practices to follow: 1. Identify and Classify Sensitive Data Start by identifying the types of sensitive data your application handles, such as personally identifiable information (PII), sensitive personal information (SPI), and confidential data. Understand the specific legal requirements and privacy regulations that apply, such as GDPR or the California Consumer Privacy Act. 2. Minimize Data Exposure Only share the necessary information with AI endpoints. For PII, such as names, addresses, or social security numbers, consider redacting this information before making API calls, especially if the data could be linked to sensitive applications, like healthcare or financial services. 3. Avoid Sharing Highly Sensitive Information Never pass sensitive personal information, such as credit card numbers, passwords, or bank account details, through AI endpoints. Instead, use secure, dedicated channels for handling and processing such data to avoid unintended exposure or misuse. 4. Implement Data Anonymization When dealing with confidential information, like health conditions or legal matters, ensure that the data cannot be traced back to an individual. Anonymize the data before using it with AI services to maintain user privacy and comply with legal standards. 5. Regularly Review and Update Privacy Practices Data privacy is a dynamic field with evolving laws and best practices. To ensure continued compliance and protection of user data, regularly review your data handling processes, stay updated on relevant regulations, and adjust your practices as needed. Remember, safeguarding sensitive information is not just about compliance — it's about earning and keeping the trust of your users.

𝗜𝗳 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗗𝗼𝗻'𝘁 𝗥𝗲𝗽𝗲𝗮𝘁-𝗕𝘂𝘆 𝗙𝗿𝗼𝗺 𝗬𝗼𝘂𝗿 𝗕𝗿𝗮𝗻𝗱, 𝗛𝗲𝗿𝗲'𝘀 𝗪𝗵𝗮𝘁 𝘁𝗼 𝗜𝗺𝗽𝗿𝗼𝘃𝗲. Repeat rate below 30%? You're not running a business – you're renting customers. Here's the brutal truth most founders avoid. 𝗧𝗵𝗲 𝗥𝗲𝗽𝗲𝗮𝘁 𝗣𝘂𝗿𝗰𝗵𝗮𝘀𝗲 𝗔𝘂𝗱𝗶𝘁 𝐑𝐮𝐧 𝐭𝐡𝐞 90-𝐃𝐚𝐲 𝐓𝐞𝐬𝐭: Pull data. What % of customers who bought 90 days ago bought again? If it's under 25%, your product isn't solving a recurring problem – it's a one-time novelty. 𝐌𝐚𝐩 𝐏𝐮𝐫𝐜𝐡𝐚𝐬𝐞 𝐅𝐫𝐞𝐪𝐮𝐞𝐧𝐜𝐲 𝐑𝐞𝐚𝐥𝐢𝐭𝐲: Skincare lasts 60 days. Coffee lasts 30. If your reorder rate doesn't match product depletion cycle, either product quality is off or post-purchase engagement is dead. Fix one or both. 𝐊𝐢𝐥𝐥 𝐭𝐡𝐞 "𝐓𝐡𝐚𝐧𝐤 𝐘𝐨𝐮" 𝐄𝐦𝐚𝐢𝐥 𝐓𝐫𝐚𝐩: Stop sending "Thanks for your order!" Start sending "Here's how to get maximum results" guides on Day 3, "You're halfway through" reminders on Day 30, and "Reorder now, get 15% off" on Day 50. Time it to usage, not vanity metrics. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐞 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧 𝐖𝐢𝐭𝐡𝐨𝐮𝐭 𝐀𝐬𝐤𝐢𝐧𝐠: Don't force subscriptions. Offer "auto-refill" as convenience. Pause anytime. Customers hate commitment but love convenience. Frame it right. 𝐓𝐡𝐞 𝐏𝐨𝐬𝐭-𝐏𝐮𝐫𝐜𝐡𝐚𝐬𝐞 𝐀𝐮𝐝𝐢𝐭: Call 20 customers who didn't reorder. Ask bluntly: "Why didn't you buy again?" You'll find patterns in 5 calls – price, quality, forgetfulness, competition. Data beats assumptions. Repeat customers cost 5x less to acquire than new ones. If you're only hunting new customers, you're choosing the expensive path to failure. Fix retention before scaling acquisition. #D2C #customerretention #business #strategy #repeatpurchase

Amazon just overtook Walmart in total sales, reporting $187.8B last quarter vs. Walmart’s $180.5B. But this isn’t just about revenue—it’s about customer experience, innovation, and long-term loyalty. Here’s what CX and business leaders can take away from Amazon’s strategy: ✅ Frictionless CX Wins – Amazon’s one-click shopping, hyper-personalization, and seamless returns keep customers coming back. How easy is it for your customers to do business with you? ✅ Speed = Loyalty – Advanced fulfillment and last-mile delivery make Amazon’s shipping faster and more reliable. Customers expect convenience at scale—are you meeting those expectations? ✅ Membership Models Drive Retention – Prime isn’t just a subscription; it’s a loyalty engine that adds value beyond transactions. How are you building long-term engagement with your customers? ✅ Tech-Driven Experiences Matter – AWS funds aggressive innovation, giving Amazon an edge. Walmart, despite its massive footprint, lacks this same tech-driven advantage. Are you investing in AI and digital transformation to future-proof your business? Amazon and Walmart’s battle isn’t just about sales—it’s about who delivers the best customer experience. As Amazon continues to dominate with frictionless shopping, fast delivery, and tech-driven innovation, it’s clear that customer expectations are higher than ever. With that in mind… what keeps you coming back to a brand—speed, convenience, personalization, or something else? Follow Blake Morgan for more! #CX #CustomerExperience #Amazon #Walmart #Ecommerce #BusinessStrategy #Loyalty #customerexperience #AWS

Big brands have a lot to learn about building community from this small East London shop. If you follow me you know I’m obsessed with pinpointing the places, moments and margins where culture appears, often outside the mainstream. Waste! is an independent store in Hackney specialising in handmade, self-published and DIY artist products that also serves as a meetup for makers and fans of the niche and novel. Big brands can spend millions chasing community. Yet genuine bonds form in the unlikeliest corners. By giving people a place to belong and a stake in the story, you can create evangelists rather than consumers. Here’s some of the playbook: → Look beyond the obvious Which subculture have you never visited? Find the one that aligns with your brand values and surprise them with an IRL activation made just for them. → Host micro-experiences Think smaller than a giant pop-up. Small scale means deeper conversations, stronger friendships and stories that spread far beyond the room. → Invite people behind the scenes Jack and Roydon modelled the shop on their childhood bedrooms. Everything feels handpicked and personal. → Celebrate genuine connections At Waste! customers aren’t just buying things. They swap ideas, share projects and spark new collaborations. Create spaces online or offline where people can connect, chill and feel like insiders. → Reinvest in your community Every penny from sales goes back into buying more stock from friends and local artists. That reinvestment shows you care about real people not just profit margins. → Turn every interaction into a collectible moment Limited-edition patches, secret passwords, custom playlists or tiny zines tie physical mementos to emotional experiences. Superfans will wear, share and trade these badges of honour. → Measure passion not just reach Track repeat attendees, social shout-outs from community insiders and user-generated content. A hundred truly engaged superfans create more long-term value than ten thousand casual followers. Sometimes the best way to build real community is the scrappy, DIY, heartfelt route ✌️💚

If your brand doesn’t have a community, it’s just another product. People don’t want to be “sold to.” They want to belong. And that’s exactly why community-led businesses are winning in 2024. They don’t just sell, they create movements. Look at the brands that are thriving right now: ✅ Glossier → Built an empire by making customers feel like insiders. ✅ Oura Ring → Grew from a niche health product to a loyal wellness tribe. ✅ Ellevest → More than a fintech company, it's a financial movement for women. So, how exactly have they done it? - Make your customers part of the brand. Don’t just market to them, create WITH them. User-generated content, ambassador programmes and real conversations build that loyalty. - Talk like a human, not a corp. Ditch the polished, robotic messaging. Community-led brands feel personal and relatable. - Give value FIRST. Want people to engage? Teach, entertain, inspire before EVER asking for a sale. - Make customers feel seen & heard. When people feel like they matter, they stick around. Engage in DMs, respond to comments and highlight your audience in your content. Bottom line: Transactional brands die. Community-driven brands thrive. Which are you building?

📊 While referring to data privacy laws, one pattern stood out to me: Every serious conversation about compliance eventually circles back to GDPR and the risk DNA built into it. Why? Because GDPR is more than a European law. It’s the architectural blueprint behind most modern data privacy frameworks worldwide. And at its heart, GDPR is risk-based: 📌 Article 24 → Security measures must match the level of risk. 📌 Article 25 → Privacy by design/default is driven by risk thinking. 📌 Article 32 → Processing security relies on risk assessment. 📌 Article 35 → DPIAs are mandatory for high-risk activities. Yet GDPR tells us what to achieve, not how to achieve it. That’s where the ISO ecosystem steps in: 🔐 ISO 27001 — the management system. Certifiable proof that controls are in place and risks are continuously managed. 🌍 ISO 31000 — the framework. A backbone for embedding privacy and cyber risks into wider business risks. 📊 ISO 27005 — the methodology. Practical techniques to identify, analyze, and treat risks — perfect for DPIAs. Together, they form one powerful bridge: (ISO 31000 + ISO 27005) × ISO 27001 = GDPR in action. 👉 GDPR defines the obligations. 👉 ISO 31000 and ISO 27005 provide the risk logic. 👉 ISO 27001 proves it all works in practice. In the AI era, where data is both fuel and liability, this alignment is no longer optional - it’s the algorithm of trust. 💡 Sharing Venn diagram to make this intersection simple. #GDPR #ISO31000 #ISO27005 #ISO27001 #RiskManagement #CyberResilience #ComplianceStrategy #DataPrivacy

Incorporating Data Privacy Clauses in NDAs 🔐 As someone deeply involved in data protection, I have seen firsthand how critical it is to protect sensitive information in our collaborations. In today’s landscape, integrating robust data privacy clauses into Non-Disclosure Agreements (NDAs) is no longer optional—it's essential. Why This Matters: 1. Regulatory Compliance: With regulations like GDPR and CCPA shaping our practices, we must ensure our NDAs reflect these legal requirements. I've witnessed the repercussions of non-compliance, and it's not something any organization can afford. 2. Data Classification: Clearly defining what sensitive data looks like is crucial. For example, specifying categories like PII or financial data helps everyone understand what’s at stake. 3. Access Controls: Establishing who can access sensitive information—and under what conditions—helps uphold the principle of least privilege. I’ve found that clarity here builds trust among all parties involved. 4. Breach Notification: It’s vital to have a breach notification protocol outlined in the NDA. Knowing how to respond swiftly can make all the difference in minimizing damage. 5. Data Transfer: In our globalized world, addressing cross-border data transfers in NDAs ensures we remain compliant with international standards. By embedding these technical aspects into our NDAs, we reinforce our commitment to data integrity and privacy. It’s not just about legal compliance; it’s about cultivating trust in every partnership. Let’s prioritize data privacy in our agreements and foster a culture of accountability in our industry. #DataPrivacy #NDA #LegalCompliance #DataSecurity #RiskManagement #cybersecurity #dataprotection

 “Just send an email.” It looks like a one-liner: await sendEmail(to, subject, body); But in production, that line explodes into a full subsystem. Here’s what you actually end up building 👇 1. Reliability - never send inline Sending directly inside a request works… until latency spikes or the provider times out. You decouple it using a queue (Kafka, SQS, or RabbitMQ) -> a background worker processes sends. Each message gets a unique message_id for idempotency, retries use exponential backoff, and you persist status = pending/sent/failed. 2. Deliverability - “sent” != “delivered” Your API logs “200 OK,” but user didn't get it. You need webhooks from SES/SendGrid to capture delivered, bounced, or spam events. Those callbacks update your DB, mark bad addresses inactive, and feed a delivery analytics dashboard so you actually know what happened. 3 Spam filters & domain reputation You can write the best emails, and still end up in spam if you skip the basics: Set up SPF, DKIM, and DMARC. Warm up new domains gradually (start with low send volume). Use a dedicated sending domain (e.g., mailer.myapp.com) and separate IPs for transactional vs marketing. Without this, your whole app’s communication pipeline can get blacklisted overnight. 4 Personalization at scale You’re not just sending static HTML. Each email has dynamic placeholders ({{user.name}}, {{order.id}}), localized text, and sometimes attachments. You pre-render templates (Liquid/MJML), cache HTML in Redis, and bulk fetch user data to avoid DB thrash. At high volume, even template rendering becomes a performance bottleneck. 5 Observability & throttling At scale, email providers rate-limit you. You’ll need token-bucket throttling, multiple provider fallbacks, and metrics (Prometheus/Grafana) for latency and bounce trends. When one region hits its SES quota, your system should automatically failover to another provider without losing events. That “forgot password” email that lands in 2 seconds? It’s backed by queues, workers, webhooks, templates, cryptographic signatures, and deliverability tuning.

Your data can be secue and still be misused. That’s the part most people miss. In cybersecurity conversations, privacy and data protection are often used interchangeably they shouldn’t be. They solve two very different problems. Here’s the clean way to think about it: Privacy is about intent. What am I allowed to do with someone’s data? Data protection is about execution. How do I technically safeguard that data? A daily-life example You share your Aadhaar copy with a society office to issue an entry pass. • Privacy expectation: Use this document only to verify my identity for access. Don’t reuse it. Don’t share it. Don’t retain it forever. • Data protection responsibility: • Is the file encrypted? • Who can access it internally? • Is it stored on a personal laptop or a secure system? • Is it deleted after the purpose is fulfilled? • What happens if that system is compromised? Now here’s where organizations fail: • A company can respect privacy (use data only for the stated purpose) but still fail data protection (poor access control, weak security, breaches). • Another can have strong security controls but still violate privacy by over-collecting data or using it beyond consent. From a cybersecurity perspective, this distinction matters because: • Privacy failures break trust • Data protection failures break systems • Regulators penalize both Frameworks and laws already recognize this split: • Privacy focuses on lawful purpose, consent, minimization • Data protection focuses on controls, encryption, access, incident response Good organizations secure data. Better ones respect intent. Mature organizations do both by design, not by accident. If you’re building systems, policies, or assessments and treating privacy as a checkbox under security, you’re already behind. #PrivacyVsDataProtection #CyberSecurity #DataPrivacy #DataProtection #GRC #RiskManagement #Compliance #TrustByDesign #SecurityAwareness #PrivacyByDesign