Building customer trust with smart monitoring

Not all friction is bad in banking. It might sound counterintuitive, especially coming from me (someone who’s always pushing to remove unnecessary friction in banking) 🤭 But here’s the BUT 👇 Sometimes, adding a bit of friction is the most powerful way to show customers you care: about their financial safety, their money, and their peace of mind. A few months ago, I identified security features launched by digital banks to protect customers from scams and fraud. Since then, I’ve come across even more examples, and some of them are pretty smart: - Monzo Bank pops up a friendly prompt when it thinks you’re about to make a duplicate payment. - Nubank has a smart feature that checks which Wi-Fi you’re using, if it’s unknown, lower limits apply. - Revolut delays transfers, when they are large or to new beneficiaries, to give you time to cancel in case it’s a scam or customers have been "forced". - Ubank lets you link your device using passkeys instead of passwords — a secure, passwordless way to protect your account. - Trust Bank Singapore lets you lock your savings pots so the money stays put. These aren’t blockers. They’re boundaries, built to protect trust. In the age of instant everything, a thoughtful delay or a security check can actually make customers feel safer, and more loyal. Because trust isn’t built by saying “we care”. It’s built by showing “we’ve got your back.” #DigitalBanks #CX #FraudPrevention #FinTech #Trust #Technology #Design

Leadership in service industries, particularly in trades like HVAC, plumbing, and electrical services, must address shifting customer expectations. As you foster innovation, improve processes, and lead the way with cultural changes, it always needs to be transformational though, not just transactional. Modern customers have access to more information and expect clarity and honesty in all interactions. Transparency builds trust, which is critical for repeat business and referrals in a competitive marketplace. ➡️ Equip technicians and customer service teams with mobile apps or platforms that provide real-time updates on service schedules, technician locations, and estimated arrival times. ➡️ Use GPS-enabled dispatch systems to show customers a technician's location in real-time. ➡️ Train teams to offer clear, itemized quotes before service begins. Use AI or digital tools to generate standardized pricing based on project scope, minimizing disputes. ➡️ Make sure your employees are always honest about delays, unexpected costs, or project timelines. Transparent communication, even when things go wrong, enhances credibility. ➡️ Actively solicit and share customer reviews and feedback. Addressing concerns publicly (e.g., on review sites) demonstrates accountability and transparency. No doubt, changing customer expectations are a challenge that may require overhauling  legacy systems and processes, training employees in new ways, and balancing transparency with operational complexities. When you get it right though, it’s worth it. 

The question that separates the Data-Driven from the Guessers… “Hey… how’s the job coming along?” If you don’t have machine monitoring, you’re suddenly transported into a game of mental gymnastics, juggling spreadsheets, tribal knowledge, and the vague recollection of a machine’s sound from 40 feet away. Amazon delivers toothbrushes overnight and Uber Eats tracks your sushi in real-time, your customers expect the same transparency, even when you’re making titanium landing gear components instead of tuna rolls. Machine monitoring bridges that expectation gap. It transforms your shop from a series of isolated machine events into a connected, intelligent ecosystem that tells you: • What’s running • What’s idle • What’s broken • What’s on time • What’s behind • And why any of it is happening Think of machine monitoring like your shop’s brainstem. It’s coordinating movement, making decisions, and ensuring survival. It helps you… Answer customer questions with confidence, not speculation. Find bottlenecks before they become disasters. Reduce downtime, because you’ll actually know when it happens. Justify investments in new machines, operators, or shifts with real data. Coach your team, with evidence, not gut feelings or blame games. Modern machine monitoring platforms, like Datanomix, tuen raw data into digestible, actionable insights. No clunky interfaces. No extra operator input. Just pure, real-time clarity. And when your customer calls and asks, “How’s the job coming along?”, you can answer in seconds. “We’re 65% complete, trending 10% ahead of schedule. The spindle utilization is at 92%, and we’ve had zero unplanned stops today.” (For example) That’s how you earn trust. That’s how you win repeat business. That’s how you run a shop in 2025. The shops that monitor their machines quote tighter, run leaner, deliver faster, and sleep better. This testimonial filmed at OPTIMA Greg Lisa Ember Andrew Brendan Jake Thai Duane Dwayne Marina Dale

In today’s always-on world, downtime isn’t just an inconvenience — it’s a liability. One missed alert, one overlooked spike, and suddenly your users are staring at error pages and your credibility is on the line. System reliability is the foundation of trust and business continuity and it starts with proactive monitoring and smart alerting. 📊 𝐊𝐞𝐲 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐌𝐞𝐭𝐫𝐢𝐜𝐬: 💻 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞: 📌CPU, memory, disk usage: Think of these as your system’s vital signs. If they’re maxing out, trouble is likely around the corner. 📌Network traffic and errors: Sudden spikes or drops could mean a misbehaving service or something more malicious. 🌐 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧: 📌Request/response counts: Gauge system load and user engagement. 📌Latency (P50, P95, P99):  These help you understand not just the average experience, but the worst ones too. 📌Error rates: Your first hint that something in the code, config, or connection just broke. 📌Queue length and lag: Delayed processing? Might be a jam in the pipeline. 📦 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 (𝐌𝐢𝐜𝐫𝐨𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐨𝐫 𝐀𝐏𝐈𝐬): 📌Inter-service call latency: Detect bottlenecks between services. 📌Retry/failure counts: Spot instability in downstream service interactions. 📌Circuit breaker state: Watch for degraded service states due to repeated failures. 📂 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞: 📌Query latency: Identify slow queries that impact performance. 📌Connection pool usage: Monitor database connection limits and contention. 📌Cache hit/miss ratio: Ensure caching is reducing DB load effectively. 📌Slow queries: Flag expensive operations for optimization. 🔄 𝐁𝐚𝐜𝐤𝐠𝐫𝐨𝐮𝐧𝐝 𝐉𝐨𝐛/𝐐𝐮𝐞𝐮𝐞: 📌Job success/failure rates: Failed jobs are often silent killers of user experience. 📌Processing latency: Measure how long jobs take to complete. 📌Queue length: Watch for backlogs that could impact system performance. 🔒 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲: 📌Unauthorized access attempts: Don’t wait until a breach to care about this. 📌Unusual login activity: Catch compromised credentials early. 📌TLS cert expiry: Avoid outages and insecure connections due to expired certificates. ✅𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 𝐟𝐨𝐫 𝐀𝐥𝐞𝐫𝐭𝐬: 📌Alert on symptoms, not causes. 📌Trigger alerts on significant deviations or trends, not only fixed metric limits. 📌Avoid alert flapping with buffers and stability checks to reduce noise. 📌Classify alerts by severity levels – Not everything is a page. Reserve those for critical issues. Slack or email can handle the rest. 📌Alerts should tell a story : what’s broken, where, and what to check next. Include links to dashboards, logs, and deploy history. 🛠 𝐓𝐨𝐨𝐥𝐬 𝐔𝐬𝐞𝐝: 📌 Metrics collection: Prometheus, Datadog, CloudWatch etc. 📌Alerting: PagerDuty, Opsgenie etc. 📌Visualization: Grafana, Kibana etc. 📌Log monitoring: Splunk, Loki etc. #tech #blog #devops #observability #monitoring #alerts

In today’s digital landscape, complexity is the new normal. With over 150 SaaS apps, hybrid clouds, and ever-rising user expectations, the old ways of monitoring just don’t cut it anymore. Too many organizations still treat monitoring as a back-office IT task, but the reality is: it’s now a strategic lever for resilience, customer trust, and growth. Catchpoint’s latest piece on “Monitoring in the Age of Complexity,” by Mehdi Daoudi is a must-read for any CIO or tech leader rethinking their approach. The article busts five outdated assumptions—including the idea that more data always means better visibility, or that downtime is the only metric that matters. In fact, slow performance can erode trust long before an outage ever hits. A few takeaways that resonated with me: ·      Monitoring must be tied to business outcomes, not just technical KPIs. ·      Actionable insights matter more than data volume—AI can help, but only if your data is clean and contextual. ·      True visibility means looking beyond your firewall to the actual user experience, wherever your customers are. ·      Proactive, experience-centric monitoring is the new standard for competitive advantage. Check out the blog here: https://lnkd.in/ekjCJ4yg