Charlie Franklyn’s Post

Customer Success: A place of diversity Customer Success, still being a relatively new field, has an open door for everyone. It was interesting to see, in a CS meet-up, people from different academic, professional, and neurodivergent backgrounds leading and living CS. The people from CS provide us with many different perspectives and business cases due to the flexibility of their roles and responsibilities. However, I would be remiss if I don't highlight that, as much as there is room for flexibility, there should be some definition of boundaries in CS roles to identify CS. As my manager pointed out, in the SaaS world, CS is the human side of technology. To which I agree; the core of our job lies in understanding and interacting with humans. In the age of AI and tech, we sell human understanding Planhat Meet-up

These hacks will 10x🚀 your productivity! Become a Prompt Master with these 5 Tips 1. Be specific and clear: Outline what you want, including specific elements or constraints. 2. Provide context: Give background information to understand the prompt. Example: "Write a job description for a software developer at a tech startup." 3. Ask open-ended questions: Encourage detailed responses. Example: "What strategies can improve customer satisfaction?" 4. Include examples: Provide samples of the desired response. Example: "Write a product review like this one: [example review]." 5. Keep it concise: Be specific but avoid unnecessary details. Using these tips can help create prompts that yield high-quality, relevant, and detailed responses. #PromptEngineering #AIGeneration #ContentCreation #BusinessStrategy

People will always find the most efficient way to hit a target. That can lead to some unintended consequences: • You goal your Marketing team on the # of leads generated and end up with a lot of low-quality SMB leads that don’t convert • Facebook uses engagement to decide which posts should be shown to more people and you end up with click bait and rage bait • Schools evaluate teachers based on how their students are doing on tests, so the teachers start “teaching to the test” You can’t really blame people for doing this; it’s your job to set the right targets (and therefore incentives), and their job to find the optimal way to hit them. As a result of these dynamics, there’s a saying that once a metric becomes a target, it’s no longer a good metric; this is also known as Goodhart’s Law. But there are ways to address this. For example, you can pair metrics together to prevent people from over-optimizing for one thing. When I started at Uber, we only had targets for the reliability of a market. Not surprisingly, Operations Managers would spend like crazy on driver incentives to hit these targets. Only once they also got a target for the cost per trip, they would start prioritizing efficiency. Similarly, measuring your customer support team only by the number of cases they solve is ill advised; instead, combine a productivity metric like “cases solved per hour” with a guardrail on customer satisfaction. Metrics are not the problem; it’s how we operationalize them. __ 👉 If you want to go deeper, check out my full blog post on how to design better metrics at OperatorsHandbook[dot]com

Three scrappy but powerful ways even the smallest of teams can gather customer experience insights: 1️⃣ Auditing Sales Calls Ask your sales team if you can sit in as a silent observer. This is a goldmine for understanding what prospective customers are looking for. Listen closely to their questions and pain points—what problems are they hoping your product will solve? 2️⃣ Customer Support Ride-Alongs If you’re not already listening in on CS calls, start yesterday. There’s a wealth of data here. What common issues are users facing? What uses are they finding for your product? Understanding these can reveal both pain points and potential opportunities for new features. 3️⃣ Leveraging Early Access Users Proactively engage with your early access or beta users. Ask for a commitment to providing weekly feedback. You can use methods like email surveys or even ask them to maintain a journal. Consider setting up a dedicated communication channel, such as a Slack or Discord server, for realtime feedback. Customer discovery is a cornerstone of agile product development, and opportunities for it abound no matter what size or stage your company is. Whether you're a founder CEO or a new engineering hire, investing a few hours each month in learning from your customers is one of the most valuable uses of your time.

Customer service reps are super important because they connect companies with customers. But as things change, so do their jobs. Let's talk about some big changes happening: 1. More online chats: Now, reps don't just answer phones. They handle emails, chats, and social media too, because that's how people like to communicate. 2. Being understanding: It's not just about fixing problems anymore. Reps need to understand how customers feel and show empathy. This helps build strong relationships. 3. Robots helping out: AI is a big deal. It helps with simple questions, so reps can focus on harder stuff. This makes things faster and easier for everyone. 4. Doing lots at once: Reps have to be good at multitasking. They handle many things at once, like talking to customers and using different tools. 5. Always learning: Customer service is always changing. Reps need to keep learning new stuff to stay good at their jobs. #customerexperiencemanagement #multitasking #continuousimprovement

Scaling your business shouldn't mean scaling headaches. Ever feel like you're drowning in customer calls? You're not alone. Many growing companies face this challenge: Missed leads = lost revenue Hiring sprees drain resources Inconsistent service frustrates customers But what if you could handle thousands of calls simultaneously without hiring a single new person? AI-powered systems are transforming how businesses manage growth. They're not just answering calls – they're qualifying leads, booking appointments, and providing 24/7 support. One retail company saw a 30% jump in customer satisfaction within 3 months of implementation. Another saved $500,000 annually by automating 80% of routine inquiries. The future of customer service is here. Are you ready to grow smarter, not harder? #BusinessGrowth #CustomerService #AIInnovation

Running Coram AI has taught me valuable lessons about customer support. Our customers love our support team. Even with rapid customer growth, we haven't needed to expand our support team. You would think more customers mean more support staff. We've learned that support issues are product issues. Reducing software bugs reduces tickets. Adding features and controls without making the product clunky reduces confusion. We've enabled customers to unblock themselves. Having excellent documentation has been helpful. With LLMs and foundation models, we've created an easy-to-use chatbot. It can answer deep technical questions instantly, often with step-by-step instructions and helpful videos. This helps customers feel supported even without direct contact. Speed to resolution is key. I review every support ticket and customer question. Being hands-on allows me to quickly identify and fix gaps in our software and documentation. This approach is part of our culture of customer support through automation, not just manpower. Any other early-stage startups trying this?

Customer support industry is experiencing its biggest crisis in 17 years! With 7-8% monthly agent turnover and 59% quiet quitting. That’s what "The Crisis in Contact Center Management" by 5th Talent is reporting. And it’s negatively impacting almost every company in the world, while the need for human support is now crucial for customers. In fact, recent research points to 3 things: 1️⃣ Customer Demand for Human Support: Customers want access to human support when issues are urgent, complex, or dissatisfying. They seek agents who can act as their advocates and build a human-to-human relationship. 2️⃣ Agent Turnover: High agent turnover is a major issue, especially for outsourced centers. This leads to increased costs and poorer performance. 3️⃣ Impact of AI: While AI is excellent for transactional interactions, it can't replace the human touch needed for building trust, showing empathy, and creating emotional connections. This situation, while really complicated for companies, can also be a huge competitive advantage! As the bar is so low, improving in this field can change a business's future. But something must change… As a customer experience expert, I believe that we need a solution that integrates advanced AI for transactional tasks and perfectly trains humans for relational tasks. That’s why we created Smart Role. To help businesses drastically reduce their costs while providing the highest customer support quality. And so far, it’s working! We found that by providing deeply immersive and personalized training/onboarding experiences, agents are excelling in their roles. And they are not leaving anymore, as we are able to reduce turnover by 25-50%. The customer support industry is drowning as it still uses the “good old methods” that are costly and highly unproductive. I believe that companies need to start working on this. (and the first to do it, will gain a significant advantage over the competition) What do you think about this crisis? - Thibaut 🦊 PS: To discover the platform that is changing businesses' lives, click here: https://www.smartrole.ai/

How are customer support teams using AI today in *production*? We put together a guide based on our experience working with some of the fastest-growing startups! Here are some of the results teams are seeing by adopting AI: - Reduced response times - Faster onboarding of new reps - Fewer internal questions - Higher customer satisfaction Check out our new guide with AI use cases for product and technical support teams: https://lnkd.in/gx-2DriH #customersupport #aiassistants

Customer Success is evolving, and I couldn’t agree more with these 4 key skills that will set CSMs apart. 1️⃣ Accountability for Success/Adoption Plan execution. 2️⃣ Storytelling tied to specific customer outcomes. 3️⃣ Executive connections and multithreading. 4️⃣ A sixth sense for customer potential. I would add one more 5️⃣ Operational Excellence In a CS 5.0 world (AI-First Era), mastering operational excellence will be critical. The CSMs with the best data hygiene who can feed AI platforms with the best data will drive the most accurate, predictive outputs. And when that’s paired with compelling storytelling, they’ll lead the pack in value creation.