Customer Alert Systems

👁️ Transaction monitoring (TM) is often thought of as a reactive process - flagging suspicious activities after they happen… But, in today’s environment, this approach is far from enough. Effective TM should be proactive, dynamic, and risk-based. 🎯 From personal experience, here’s what I’ve seen a lot of firms get wrong: ⛔️ Basic rule-based systems - While rule-based alerts can flag obvious issues, they’re also prone to creating a flood of false positives, overwhelming your team and making it harder to focus on genuine threats. 🔍 Not considering context - Transactions can look suspicious when taken out of context. It’s important to assess the full picture - what’s normal for this customer or this region? Without this, you’re likely to miss or misinterpret signals. 🕰️ Infrequent system reviews - Regulatory environments and criminal tactics are constantly evolving. If you aren’t regularly fine-tuning your monitoring systems, they’ll quickly become outdated. 🔑 My Monday Tip: Instead of static rules, implement a risk-based approach to TM. Rather than applying the same thresholds to every customer, focus on high-risk individuals and transactions. Consider using machine learning to reduce false positives and better detect unusual patterns over time. Monitoring isn’t just about setting up alerts - it’s about understanding your data, investigating red flags thoroughly, and staying agile in the face of new risks. Don’t let outdated systems hold you back. 📊 #TransactionMonitoring #AMLCompliance #RiskManagement #ProactiveCompliance #FinancialCrime #GRC

A criminally underrated part of building software is how engineering and Customer Success work together. Our customers rave about Clueso’s support and routinely rank us above every other tool they use. Obviously, all of the credit goes to our CS champ Anirudh Kumar, who always goes the extra mile. My role - and the entire engineering team’s - is to make sure he can keep being a hero for every customer. Here’s how we set him up to win. ⏰ Proactive alerting We pipe every critical event—failed recordings, stalled exports, anything that could spoil a user’s day—from PostHog straight into Slack. Sentry still catches the deep-dive logs for engineers, but Slack is Anirudh’s early-warning siren. The alert comes with the user’s name and just enough context for him to act. By the time the customer even notices the on-screen error, Anirudh is already in their inbox saying, “Hey you might have faced an issue - I'm looking into it.” That two-minute head start turns a potential customer meltdown into an instant win. The same feed also flags dormant or brand-new users, giving him a perfect cue to offer a refresher call and quietly open the door to future expansion. 🪲 Bug-fix cadence Bugs and new features are forever wrestling for attention. To keep the balance, Anirudh and I huddle every other day for a focused fifteen minutes. We look at customer-reported issues and ask a single question: “Does this need a same-day fix, or can it wait for the next bug sprint?” Anything that blocks work or risks data jumps the queue immediately; everything else goes onto a scheduled punch-list so feature development keeps moving. 🔨 Internal tooling Whenever a task drags engineers into the same manual step twice - spin up an ad-hoc subscription plan, tweak a custom voice, nudge a stuck job - we carve out a tiny sprint to add that control to our internal dashboard. A few hours of work on Retool now saves countless Slack pings later, freeing both Anirudh and the dev team to focus on higher-value work. (Side note: definitely think there's opportunity for AI led disruption here! ) 🪚 Smoothing the “small but broken” flows Core features in the product always get love; it’s the side doors - user invite flows, seat management, odd edge-case modals - that quietly pile up support tickets. Anirudh feels that pain first, so he keeps a living “small but broken” list of every micro-friction that slows users down or eats his time. Once a month the whole dev team pauses feature work and blitzes that list. The result: fewer pings, faster resolutions, and a calmer CSM who can spend more time delighting customers instead of firefighting. The playbook keeps evolving, but the principle stays the same: stay close to customers, stay even closer to the person who supports them every day, and keep tuning the tech so that person can continue to be the hero. PS: If you're a cracked engineer who wants to be in a team that cares about its customers, please reach out!

7 early warning signals showing your customers are about to cancel their subscription: Your customers tell you they're leaving long before they hit "cancel." Here are the red flags I've spotted: 𝟭. 𝗧𝗵𝗲 𝗴𝗵𝗼𝘀𝘁 𝗽𝗮𝘁𝘁𝗲𝗿𝗻 They stop: • Opening your emails • Using key features • Logging in regularly Silent customers = future cancellations 𝟮. 𝗧𝗵𝗲 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘀𝘂𝗿𝗴𝗲 Sudden increase in: • Basic how-to questions • Feature complaints • Response time frustrations They're questioning their investment. 𝟯. 𝗧𝗵𝗲 𝘂𝘀𝗮𝗴𝗲 𝗰𝗹𝗶𝗳𝗳 Watch for: • Dramatic drop in logins • Fewer team members active • Core features ignored Low engagement = high risk 𝟰. 𝗧𝗵𝗲 𝘃𝗮𝗹𝘂𝗲 𝗯𝗹𝗶𝗻𝗱𝗻𝗲𝘀𝘀 They can't answer: • How much time they save • What ROI they're getting • Why they need you No clear value = easy goodbye 𝟱. 𝗧𝗵𝗲 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝘃𝗼𝗶𝗱 Red flags: • Ignore your surveys • Stop giving feedback • Don't join user calls Silence isn't golden. It's dangerous. 𝟲. 𝗧𝗵𝗲 𝗱𝗼𝘄𝗻𝗴𝗿𝗮𝗱𝗲 𝗱𝗮𝗻𝗰𝗲 Warning signs: • Ask about cheaper plans • Compare competitor pricing • Question feature value Price sensitivity spikes before churn. 𝟳. 𝗧𝗵𝗲 𝗼𝗻𝗯𝗼𝗮𝗿𝗱𝗶𝗻𝗴 𝘀𝘁𝗿𝘂𝗴𝗴𝗹𝗲 Look for: • Incomplete setup • Skipped tutorials • Missing key milestones They never really started = they'll never stay. 𝗛𝗼𝘄 𝘁𝗼 𝘀𝗽𝗼𝘁 𝘁𝗵𝗼𝘀𝗲 𝘀𝗶𝗴𝗻𝘀: ✅ Build a warning system ↳ Track these metrics weekly ✅ Set trigger points ↳ Define when to intervene ✅ Create rescue plays ↳ Have ready-to-go save strategies ✅ Measure intervention success ↳ Track what actually works The best churn strategy? Stop it before it starts.

Yesterday, Arsh Khandelwal and I talked at LinkedIn HQ about Orb's technical investment around Orb's alerting features at the scale of 1M+ events/sec. This is an incredibly important feature for Orb's customers to provide timely notifications to *their* customers on hitting a spend cap or usage limit → your customers don't like surprise overages, you don't want to swallow spillover infra costs for excess use. What makes implementing real-time alerting for billing hard? Why isn't this a solved problem a la Datadog? A preview of what's tricky: - Flexibility: Orb is the only billing system that lets you configure your billing metrics with SQL. This makes computing incremental query results significantly harder; traditional stream processing approaches don't work out of the box. Approximates aren't good enough... and remember that the number of groups explodes here quickly since each customer on each timezone has a different timeframe you're evaluating. - Business complexity: usually, your customers want to get alerted on accrued spend across all metrics they're subscribed to. You'll need to factor in a combination of credit burndown for some metrics, rollovers, minimums, tiered pricing, etc. This is a lot of domain data to load in a perf-critical path. Billing doesn't operate on a single p x q anymore. - Varying requirements: You might want to alert on a subset of self-serve, high risk customers with a much higher SLO than your trusted enterprise accounts. Being able to fast-lane some customers is critical.

If everything is an alert… nothing is. Let’s fix that. Here’s how: 1️⃣ Define your risk parameters. Start with clear criteria: transaction size, velocity, geolocation, high-risk merchants, etc. The more precise, the better. 2️⃣ Segment customer profiles. Different risk levels require different thresholds. A first-time crypto trader shouldn’t trigger the same alerts as a seasoned investor. 3️⃣ Use historical data. Look at past transactions to set realistic thresholds. If your system flags 90% of transactions, it’s not helping, it’s drowning you in noise. 4️⃣ Set up layered alert levels. Not all alerts should be treated equally. Low-risk anomalies? Review queue. High-risk red flags? Immediate escalation. 5️⃣ Automate escalation workflows. Who gets notified? What actions follow? Manual reviews? SAR filings? Define the process in advance to avoid bottlenecks. 6️⃣ Test and tweak regularly. Set it and forget it? Nope. Monitor alert effectiveness, refine thresholds, and adjust rules as customer behavior evolves. 🔹 Tired of false positives eating up your time? OMNIO automates transaction monitoring with smart alerts, risk-based prioritization, and real-time adjustments so you only focus on what truly matters. How do you fine-tune your alerts? Let’s swap notes in the comments! 👇

If you’re only thinking about digital CS as a means to engage your customers, you’re missing a critical part of its value. Internal communication and automation is a severely undervalued use case for digital CS. You should be using digital internally in two ways: 1. Trigger alerts or notifications to internal stakeholders based on customer behavior 2. Automate repetitive manual CSM tasks Utilizing digital like this is powerful. It’s so often overlooked, and this is a huge missed opportunity. Not only does it make everybody’s job easier, but by cutting out so much manual work, it also leads to huge increases in efficiency and productivity. Less copy and pasting or searching for information means more time for more important things. Sometimes that looks like the ability to increase the number of accounts assigned to each CSM, other times it simply opens up time in their week to actually be able to have the strategic conversations we all want them to be having. Here are some examples of how to effectively use both: Alerts & notifications - Notify a CSM 6 months before a customer’s renewal date so they’re planning early for how to retain and grow the account - Alert a CSM if a customer has too many open support tickets or if they haven’t logged in for 30 days - Notify a digital CS program manager when customers renew at more than double their prior year spend - include a reminder to ask their CSM if the account is a candidate to provide a testimonial or case study or become a reference - Alert a frontline manager if one of their CSMs has a sudden increase in accounts with “red” customer health, so they can provide any additional support that team member needs Repetitive manual tasks: - Renewal reminders sent to customers automatically at your preferred cadence - Self-service usage dashboards customers can look at whenever, so they don’t have to bug their CSM to find out how many open licenses they can still assign or how much their team is actually using the product - Pre-populated EBR decks, or better yet, entirely automated EBRs - Anything that currently requires your CSMs to copy and paste the same thing over and over There are unlimited possibilities here! How else have you used digital CS to improve operational efficiency internally? #customersuccess #digitalcustomersuccess #digitalcs #internalcommunication

🚨 Did you know that missing a customer signal can be the difference between renewal and churn? I’ve seen firsthand how proactive alerts can transform customer management. Setting up notifications for important events—like low customer health scores or upcoming contract renewals—can help you address issues before they become problems. This isn’t just about keeping track but being one step ahead in customer success. You create stronger, lasting relationships when you can anticipate your customers' needs. 💬 How are you using alerts and notifications in your customer management process? #CustomerSuccess #ProactiveService #CustomerRetention

3️⃣ Intent alerts update 3/3... and maybe the most powerful. ↗ Introducing, Webhook Alerts by Flywheel Flywheel already supports email and Slack notifications out-of-the-box. But now, alerts can trigger actions in any tool that accepts webhooks. Including Zapier zaps. For a quick reminder, Flywheel Alerts are triggered by user actions anywhere in your product or website. Pricing page visits? Easy. New customer notifications? Done. Upgrade button clicked? Simple. Plus, alerts can be filtered by any Flywheel or custom field before they're sent. Company size, feature usage, title, department, etc etc. It's the end of alert fatigue and spam. Here are a few ways our customers are already using webhook alerts today: - Triggering personalized onboarding emails based on Feature adoption - Sales team outreach for new signups that match their ICP - Sending weekly KPI updates to their organization - Triggering Zapier zaps when customers enter custom segments Webhook alerts are a huge step for Flywheel's ability to drive your entire go-to-market motion. It's our goal to make sure every user has a unique, personalized experience with your product — and now they can. Check out webhook alerts today in the comments!