Customer Experience In E-Commerce

AI in Customer Support isn’t new. I’ve been rethinking how we actually use it. Customer Support is moving past basic "faster replies" and learning to implement Claude as a core part of our workflow. The goal? Shifting from reactive firefighting to structured, scalable systems. It’s a work in progress, but here is the blueprint we’re using to turn Claude into a true CX reasoning engine: 1️⃣ It’s not about speed. It’s about structure. Yes, you can draft replies faster. But the real value comes from setting it up properly: → align it with your tone and guidelines → connect it to your knowledge base → define clear boundaries (what it can and can’t say) → train it to understand context, not just keywords That’s how you get consistent, reliable output across the team. 2️⃣ It helps move Support from reactive → proactive Used well, it’s not just answering tickets. It’s helping you: → detect sentiment and urgency → identify recurring friction points → surface gaps in self-service → spot early churn signals That’s where Support starts influencing the whole customer experience. 3️⃣ It fits into your existing workflows (not replaces them) The most effective setups I’ve seen are simple: → Claude + Zendesk → ticket analysis → Claude + Zapier → automate workflows → Claude + Gong→ review calls → Claude + Intercom → inbox support → Claude + n8n → workflow automation → Claude + Notion → knowledge management No complex rebuilds. Just better use of what you already have. 4️⃣ The quality of output = quality of input Small things make a big difference: → assign a role (support agent, CX lead, analyst) → provide context (customer, goal, constraints) → iterate with examples (good vs bad responses) Without this, you get generic answers. With it, you get something your team can actually use. From a leadership perspective, this isn’t about “adding AI.” It’s about designing how your Support team operates at scale. Because the goal isn’t to answer more tickets. It’s to build a system where fewer things break, and when they do, the experience still feels consistent. If you’re already using AI in Support, what’s actually working for you? 👇

A hairdresser and a marketer came into the bar. Hold on… Haircuts and marketing? 🤔 Here's the reality: Consumers are more aware than ever of how their data is used. User privacy is no longer a checkbox – It is a trust-building cornerstone for any online business. 88% of consumers say they won’t share personal information unless they trust a brand. Think about it: Every time a user visits your website, they’re making an active choice to trust you or not. They want to feel heard and respected. If you're not prioritizing their privacy preferences, you're risking their data AND loyalty. We’ve all been there – Asked for a quick trim and got VERY short hair instead. Using consumers’ data without consent is just like cutting the hair you shouldn’t cut. That horrible bad haircut ruined our mood for weeks. And a poor data privacy experience can drive customers straight to your competitors, leaving your shopping carts empty. How do you avoid this pitfall? - Listen to your users. Use consent and preference management tools such as Usercentrics to allow customers full control of their data. - Be transparent. Clearly communicate how you use their information and respect their choices. - Build trust: When users feel secure about their data, they’re more likely to engage with your brand. Make sure your website isn’t alienating users with poor data practices. Start by evaluating your current approach to data privacy by scanning your website for trackers. Remember, respecting consumer choices isn’t just an ethical practice. It’s essential for long-term success in e-commerce. Focus on creating a digital environment where consumers feel valued and secure. Trust me, it will pay off! 💰

Turning Bugs into Badges: A Playful Approach to Quality Assurance Let’s face it, bug bashes can be a bit… monotonous. But what if we could inject some fun into the process? About a year ago, my team at Google was getting ready for a major launch. We were working hard for months, and the bug bash was our final hurdle. But how could we get everyone excited about finding bugs? Enter: Gamification! I’m a sucker for anything with points, badges, and leaderboards (and I have my 1,940-day Duolingo streak as proof of that). So, I decided to apply the same principles to our bug bash. First, the hype. I designed a catchy logo (see pic), plastered it everywhere, and scheduled a kickoff meeting to get the team pumped. Then came the good stuff - Prizes! Who doesn’t love some swag? I leveraged my network to secure some awesome branded goodies. I created a point system for different bug severities and a leaderboard with eye-catching badges (and yes, I automated everything I could, because efficiency is key!). And to top it all off, we had a real-time dashboard displaying the leaderboard and badges, fueling some friendly competition. The result? Our most successful bug bash EVER! Engagement was through the roof! People were excited, actively hunting for bugs! We shipped a high quality product and had a blast doing so. Key Takeaways: - Gamification Works: Tapping into our innate competitive spirit can make even mundane tasks fun and engaging. - Foster a Culture of Celebration: Recognizing achievements, big and small, boosts morale and builds a stronger team. - Don't Be Afraid to Experiment: Sometimes, shaking things up and trying something new can lead to unexpected breakthroughs. So, next time you're facing a daunting task, consider adding a little gamification magic. You might be surprised at the results! What are your favorite ways to boost team morale and engagement? Share your tips in the comments! 👇 #TPMlife #SoftwareDevelopment #Gamification #Innovation #Google #LifeAtGoogle

To protect your customers' data effectively, you must start by gaining a comprehensive understanding of the data you're safeguarding. This involves going beyond a surface-level awareness of its sensitivity. Instead, you should delve into the specifics of the data you handle, categorizing it based on its nature. For instance, the data could fall into categories like Protected Health Information (PHI), Personally Identifiable Information (PII), or cardholder information. It's crucial to pinpoint the exact kind of data you're processing. To achieve this, we recommend a more precise approach. Begin by identifying the data types within your ecosystem and tracing their origins. Create a visual map that outlines the sources of this data, building a clear understanding of your customers and the data they provide. By comprehending the paths data takes within your system, you can establish a more robust data protection strategy. In summary, by categorizing and deeply understanding the data you handle, as well as mapping its flow within your organization, you can develop a more effective and tailored approach to protect your customers' data.

Microsoft just dropped their AI job impact list. Customer Service ranked #6 out of 40 most "AI-applicable" roles. Here's what this actually means for support leaders: 𝗔𝗜 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝗯𝗶𝗹𝗶𝘁𝘆 ≠ 𝗷𝗼𝗯 𝗲𝗹𝗶𝗺𝗶𝗻𝗮𝘁𝗶𝗼𝗻. It means transformation, not termination. Think about it: AI excels at: • Password resets • Order tracking • Basic troubleshooting • Pattern recognition Humans dominate: • Complex problem-solving • Emotional intelligence • Creative solutions •Strategic thinking 𝗧𝗵𝗲 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝘁𝗿𝘂𝘁𝗵? The work AI handles is the work that burns people out. The work humans excel at is the work that matters most. When AI takes the repetitive tasks, your team's uniquely human skills become MORE valuable, not less. 𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲 𝘀𝗺𝗮𝗿𝘁𝗲𝘀𝘁 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝗮𝗿𝗲 𝗱𝗼𝗶𝗻𝗴: They're not fighting this change, they're leading it. ✅ Training teams to orchestrate AI, not compete with it ✅ Upskilling beyond scripts into strategic thinking ✅ Positioning their people as AI-empowered problem solvers ✅ Building the human skills AI can't replicate Remember: 2.8 million people work in customer service. That's not a workforce you replace. That's a workforce you elevate. Because at the end of the day: Companies still need happy customers AI can't build genuine relationships AI can't show real empathy AI can't think beyond its training The question isn't whether AI will change support. It's whether you'll lead that change or be left behind. What surprised you most about Microsoft's list? Which roles did you expect to rank higher or lower? P.S. Your team needs to see this. Hit that repost button ♻️

What if you could turn your UX research into a fun and enlightening experience? Introducing game-like elements into your usability testing might just be the secret sauce you’re looking for 🎮🪄 Dive deeper into how gamification can transform your research efforts into a captivating and productive journey for both you and your users. It's time to pioneer a new era in UX research. By integrating gamification with traditional usability testing, we enhance the UX research process. While conventional methods provide essential insights into user behavior, adding gamification leads to even deeper understanding and increases participant engagement. Benefits of gamification in usability testing: 1. Increased engagement: Gamification makes standard tests more interactive, encouraging better user involvement. 2. Deeper insights: Active participants are more likely to disclose nuanced details that might be missed in standard testing. 3. Improved retention rates: Fun testing experiences help participants better recall their interactions during subsequent feedback sessions. Here’s how to design gamified usability tests: ↳ Add game mechanics: Incorporate elements like scoring systems, leaderboards, badges & achievements, narratives, timed challenges, and avatars. ↳ Escalate challenges: Begin with simple tasks and progressively add complexity, educating users step by step. Offer customized feedback to guide their journey. ↳ Dynamic feedback: Use immediate visual/audio feedback to keep participants engaged. As tasks increase in complexity, adjust feedback to keep up with users’ growing skills. ↳ Thoughtful rewards: Provide meaningful rewards to enhance engagement. However, avoid placing too much emphasis on rewards to prevent shallow interactions and unauthentic feedback. Key reminders: ↳ Focus on research goals rather than merely adding gamification. ↳ Continuously refine and iterate on your tests. ↳ Keep it simple and avoid overcomplication. ↳ Ensure inclusivity for all users. ↳ Uphold ethical standards in research. I’d love to hear about your experiences or any questions you might have about gamifying usability testing! 👇

If I were the VP of Support at an enterprise company dealing with repetitive customer support tickets, here’s how I’d use AI to power KCS and improve ticket resolution while turning my support agents into “heroes”: First, some context: - Most support tickets are recurring, yet agents have to field every single one of them individually (this is unscalable).  - Agents are only rewarded based on the number of tickets resolved and have a hard time improving support quality (can be unrewarding) The best way to go about this problem? Enabling agents to externalize documentation on their own and improve support quality with every logged request, using AI to power Knowledge-Centered Support (KCS) Here’s how I’d implement this at an enterprise company: 1) Democratize knowledge creation Support agents know customer issues best, so it doesn’t make sense to wait for technical writers (who are already swamped) to create knowledge articles. With the help of AI, you can enable support agents to generate knowledge articles on their own, just by clicking a button. 2) Externalize new knowledge All new knowledge articles can be pushed to your external customer help center/knowledge hub right away. With that, customers can either resolve issues on their own or ask an AI Chatbot (that has immediate access to all knowledge articles). 3) Iterate & improve knowledge Now that recurring tickets are handled, support agents can dedicate their time to tickets that *actually* need human help. AI can then help them update existing articles as similar requests come in. This is WAY more efficient than relying on technical writers because your agents are already “on the ground.” 4) Gamify support process On the backend, AI can track & display: - Which customer issues were resolved  - Which knowledge articles were referenced - How many customers were assisted by each agent - How many tickets were resolved or deflected This makes it easier to boost support morale because agents see the REAL impact of what they’re doing for customers and the company – in short, they become “heroes.” (We do this ourselves at Ask-AI) TAKEAWAY An AI-powered KCS will help you improve your overall customer experience. You can resolve customer issues faster, your support agents are empowered – and the VP of support can report better TTR and CSAT metrics. Any thoughts on this?

Most stakeholder ‘engagement’ is just a Slack message and a prayer. But engagement doesn’t happen at the end of research. It happens in the middle. If you’re just sending people a link to your insights repo and hoping something sticks, you’re not activating research, you’re archiving it. This is the mindset I’ve been building into my workflow with Condens. Not just to store insights, but to make stakeholder engagement actually happen as the research unfolds. Here’s what that looks like in practice: 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿 𝗙𝗮𝗻𝘁𝗮𝘀𝘆 𝗟𝗲𝗮𝗴𝘂𝗲 Set up a leaderboard: +1 point: attends a session +2: submits a question +3: shares a takeaway Track it in Condens. Celebrate the MVP. 𝗖𝗹𝗶𝗽 𝗥𝗼𝘂𝗹𝗲𝘁𝘁𝗲 Drop a random 30-second highlight from Condens into Slack. Ask: “What would you build based on this?” Best answer gets pinned. 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 𝗕𝗶𝗻𝗴𝗼 Build a bingo board with your most common tags in Condens: “User skipped onboarding” “Trust issue” “I guess I expected it to…” Let stakeholders fill it in during playback. It’s research, gamified. 𝗧𝗵𝗲 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿 𝗦𝗼𝘂𝗻𝗱𝗯𝗼𝗮𝗿𝗱 Use Condens clips + emoji reactions in Slack: 👍 = makes sense 👀 = didn’t expect that 💡 = sparked something Engagement without a meeting 𝗦𝘆𝗻𝘁𝗵𝗲𝘀𝗶𝘀 𝗣𝗮𝗿𝘁𝘆 Host a 30-min co-synthesis jam. Highlight a few clips in Condens. Play music. Invite reactions. Low-stakes, high-reward collaboration. 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿-𝗮𝘀-𝗨𝘀𝗲𝗿 𝗗𝗮𝘆 Have a stakeholder narrate their experience using the product. Upload their recording to Condens. Compare it to real user clips. Perspective unlocked. These are systems for participation and Condens is the infrastructure that makes them possible, fast, flexible, and friction-free. If you want stakeholders to care, stop sending them links. Start giving them reasons to show up. Check out five other ways I engage stakeholders through the research process below. What’s the most creative thing you’ve done to get stakeholders involved?

8 App Gamification Strategies In collaboration with AppsFlyer, we analyzed the best gamification approaches to keep app users hooked. 𝟭. Points & Rewards 🪙 • Reward users for daily actions • Trigger dopamine to build habits • Example: Starbucks Rewards program 𝟮. Progress Bars & Streaks 🔥 • Visually track streaks and tasks • Motivate users to keep the streak • Example: Duolingo streak features 𝟯. Challenges 🏆 • Set clear goals and achievements • Offer time-based windows for urgency • Run 7, 14, or 30-day challenges 𝟰. Leaderboards 📊 • Rank users for friendly competition • Match skills using tiered boards • Drive engagement through rivalry 𝟱. In-App Currency 💎 • Create a virtual app economy • Earn currency for daily check-ins • Establish user investment • Example: Roblox in-app currency 𝟲. Interactive Quizzes ❓ • Personalize the user experience • Tailor content to user preferences • Make the app fully interactive • Avoid passive user experiences 𝟳. Unexpected Rewards 💥 • Drop surprise mystery boxes • Hook users with unpredictability • Use these rewards sparingly • Example: Pokémon GO surprises 𝟴. Badges & Achievements 🏅 • Tap into the completionist mindset • Showcase progress visually • Use trophies as status symbols • Example: Apple Fitness badges Duolingo Execution: • XP points offer instant dopamine • Fire icons create intense FOMO • Quests offer short-term goals • Leagues trigger competitive engagement • Gems prevent churn after missed days • Bite-sized tasks keep learning active • Random boosts hook longer sessions --- Learn more about keeping your users engaged with AppsFlyer's knowledge base on YouTube (link in the comments 👇).

What’s really blowing me away lately is the 𝗹𝗮𝘁𝗲𝗻𝘁 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝗼𝗳 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗶𝗻 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲. Until now, we’ve mostly thought of Support AI Agents as tools to automate inbound support. But traditional support was built for a world of expensive, rigid human agents. 𝗦𝗼 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲𝘀 𝗱𝗶𝗱 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝘁𝗵𝗲𝘆 𝗰𝗼𝘂𝗹𝗱 𝘁𝗼 𝗮𝘃𝗼𝗶𝗱 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗻𝗲𝗲𝗱𝗶𝗻𝗴 𝘀𝘂𝗽𝗽𝗼𝗿𝘁. 𝗕𝘂𝗿𝘆 𝘁𝗵𝗲 𝗽𝗵𝗼𝗻𝗲 𝗻𝘂𝗺𝗯𝗲𝗿, 𝗴𝗮𝘁𝗲 𝘁𝗵𝗲 𝗰𝗵𝗮𝘁, 𝗱𝗲𝗳𝗹𝗲𝗰𝘁 𝘄𝗵𝗲𝗿𝗲𝘃𝗲𝗿 𝗽𝗼𝘀𝘀𝗶𝗯𝗹𝗲. AI agents flip that equation. They’re fast to deploy, easy to scale, and operate at a fraction of the cost. And that’s unlocking entirely new use cases across the customer journey. I recently had a fascinating conversation with the CIO of a major media company who’s rethinking CX from first principles. 𝗧𝗵𝗲𝘆’𝗿𝗲 𝗲𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴 𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘇𝗲𝗱 𝗰𝗵𝗮𝘁 𝗮𝗻𝗱 𝘃𝗼𝗶𝗰𝗲 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝘁𝗵𝗿𝗼𝘂𝗴𝗵𝗼𝘂𝘁 𝘁𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝗮𝗻𝗱 𝗮𝗰𝘁𝗶𝘃𝗲𝗹𝘆 𝗲𝗻𝗰𝗼𝘂𝗿𝗮𝗴𝗶𝗻𝗴 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝘁𝗼 𝗲𝗻𝗴𝗮𝗴𝗲 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲𝗺.  • AI agents on the website and app during activation to assist with onboarding and product-related questions  • Specialized seller agents for retention, cross-sell, and upsell across billing and churn-related web/app flows  • A unified experience across IVR, Help Center, and in-product touchpoints They’re not just unhiding the support number. They’re thinking about promoting it. It’s a subtle but powerful shift: 𝗙𝗿𝗼𝗺 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗻𝗴 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘁𝗼 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝘁𝗵𝗲 𝗲𝗻𝘁𝗶𝗿𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝘄𝗶𝘁𝗵 𝘁𝗮𝗿𝗴𝗲𝘁𝗲𝗱 𝗮𝗻𝗱 𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘇𝗲𝗱 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀.