Customer Pain Point Identification

I was in a call this morning with a respected industry thought leader, and we ended up talking about one of the biggest internal challenges in Customer Success: when things go wrong for a customer, where does the blame live? Is it in Sales for setting the wrong expectation? Is it in Product for missing or broken functionality? Is it in Operations or Accounting for a confusing billing experience? There are plenty of targets, and many CS pros will instinctively point at teams across the org. And honestly, those things do matter — misalignment across functions is one of the most common structural blockers CS organizations face today. But the harder question (the one we often avoid) is this: When something isn’t working for a customer, have we looked in the mirror to see if we played a part in allowing that to happen? Customer Success has the unique privilege of representing the entire company to the customer. We build trust, advocate for outcomes, carry the company flag, and influence how the customer perceives every interaction. And with that privilege comes responsibility: the responsibility to look at ourselves first when issues arise. Not to absorb blame unnecessarily, but to approach every problem with the humility that leads with: 👉 Did we set clear enough expectations? 👉 Did we fully and accurately translate the customer’s needs internally? 👉 Did we communicate with enough context and impact to influence action? 👉 Did we partner with a spirit of collaboration rather than blame? Too often, issues become a game of “whose fault is this?” instead of “what can we learn and fix together?” When CS approaches our role as truth-teller, integrator, and co-owner of outcomes, including our own part in the narrative, the organization becomes better equipped to solve the real problem. Here are three action steps to help us get this right: 🔹 1. Self-Reflect before escalating Before sending that “Urgent Customer Issue” email, ask yourself: Did I fully understand the customer context? Did I include potential solutions or recommendations alongside the issue? 🔹 2. Translate with context, not frustration CS isn’t just reporting facts, we’re bridging perspectives. Partner feedback needs to land in a way that adds clarity and urgency, not just noise. 🔹 3. Lead with humility and accountability Admit when we could’ve done something differently. Highlight wins when the team solves something cross-functionally. Model curiosity and shared ownership rather than pointing fingers. Privilege without responsibility is entitlement. Responsibility without humility is defensiveness. When CS leads with both, we not only protect customer value, we build internal credibility and influence. Let’s keep raising the bar. 👊 #CustomerSuccess #Leadership #CrossFunctionalAlignment #Humility #ServeWell #GrowthMindset #BetterEveryDay #CSLeadership #CreatetheFuture

Selling the same sofa internationally means selling to different fears, habits, and expectations. A sofa product page should not look the same in Sweden, Romania, Germany, or Spain just because the product is the same. At first, it sounds simple. You translate the product page, change the currency, adjust the delivery details, and the product is ready to sell. 𝗣𝗲𝗼𝗽𝗹𝗲 𝗱𝗼 𝗻𝗼𝘁 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗲 𝗳𝘂𝗿𝗻𝗶𝘁𝘂𝗿𝗲 𝗶𝗻 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝘄𝗮𝘆 𝗲𝘃𝗲𝗿𝘆𝘄𝗵𝗲𝗿𝗲. In Sweden, details around circular economy, material sourcing, sustainability, and repairability can be real buying signals. People actually look for them and use them to compare products. In Romania, the same information can easily feel like generic marketing language if it is not connected to something practical and immediate. In cities where most people live in apartment buildings, package size can be one of the most important details on the page. Customers need to know if the sofa will fit in the elevator, through the staircase, or through the apartment door. In areas where most people live in houses, the same detail may be much less important. The product is the same. The data behind the product can also be the same. But the way that data is presented should not be the same for every buyer. This becomes especially important above the fold, where the page has only a few seconds to make the visitor feel that the product is relevant, understandable, and safe to buy. So the question is not only how to translate a product page. The question is how to sell the same product in different countries, to different habits, different homes, different expectations, and different buying fears, without rebuilding the entire webshop every time. This is the kind of problem we are working on at Ixaria. We centralize all product data in one platform - materials, dimensions, packages, care, warranty, images, videos, 3D models, reviews, configuration rules, and more. Then we use that data to generate product pages that can adapt to the customer’s culture, behavior, and needs. Because selling internationally is not just about showing the same information in another language. It is about showing the right information, in the right order, to the right person. #CustomerExperience #Ecommerce #Personalization #FurnitureRetail #DigitalCommerce

In a recent conversation with a CEO about “the next leg” of their AI transformation, the CIO proudly walked me through their annual customer requirements survey, the long list of requested features, and the research budget devoted to capturing what customers say they want. It immediately reminded me of the line famously attributed to Henry Ford: “𝙄𝙛 𝙄 𝙝𝙖𝙙 𝙖𝙨𝙠𝙚𝙙 𝙥𝙚𝙤𝙥𝙡𝙚 𝙬𝙝𝙖𝙩 𝙩𝙝𝙚𝙮 𝙬𝙖𝙣𝙩𝙚𝙙, 𝙩𝙝𝙚𝙮 𝙬𝙤𝙪𝙡𝙙 𝙝𝙖𝙫𝙚 𝙨𝙖𝙞𝙙 𝙖 𝙛𝙖𝙨𝙩𝙚𝙧 𝙝𝙤𝙧𝙨𝙚.” Customers often describe the solution they can imagine, not the breakthrough they truly need. This is exactly the trap many organisations are falling into with AI. They are using AI to optimise what is already known: faster responses, incremental efficiency, a bit more automation around existing processes and stated requirements. That is useful, but it is not transformative. The real power of AI lies in helping us see and solve for the unknown – the unarticulated needs, the patterns humans cannot easily spot, the new ways to get customers from point A to point B that no one has words for yet. Jeff Bezos framed this beautifully when he said that Amazon’s strategy is built not on guessing what will change, but on what will not change: 𝙘𝙪𝙨𝙩𝙤𝙢𝙚𝙧𝙨 𝙬𝙞𝙡𝙡 𝙖𝙡𝙬𝙖𝙮𝙨 𝙬𝙖𝙣𝙩 𝙡𝙤𝙬𝙚𝙧 𝙥𝙧𝙞𝙘𝙚𝙨, 𝙛𝙖𝙨𝙩𝙚𝙧 𝙙𝙚𝙡𝙞𝙫𝙚𝙧𝙮, 𝙖𝙣𝙙 𝙢𝙤𝙧𝙚 𝙘𝙝𝙤𝙞𝙘𝙚. Those are needs, not feature requests. In the same way, AI strategy should start from enduring customer needs and then ask: what could become possible now that was impossible before, if we stopped listening only to “faster horse” feature lists? So for all the leaders racing to “train everyone on AI” and pack roadmaps with AI features, perhaps the first mindset shift is this: move from customer requirements to customer needs – especially the unspoken and unmet ones. Use AI not just to speed up the old system, but to re‑imagine the journey itself. Are you using AI mostly being used to build “faster horses” for existing requirements, or to reveal and serve the deeper customer needs that nobody has quite been able to articulate yet? #transformation #leadership

The Problem: No Shared Definition of Customer “Need” Most organizations assume they are customer-centric, but in practice, sales, marketing, and development teams all define customer “needs” differently: • Sales teams see needs as features, benefits, or exciters that help close deals. • Marketing teams describe needs as value drivers, use cases, or personas that segment the market. • Development teams think about needs as requirements, specs, or technical solutions that guide design. Each discipline is correct in its own context, but because their definitions differ, the organization ends up misaligned on what customers truly want. This lack of agreement leads to: • Wasted investment: teams build features or campaigns customers don’t care about. • Misaligned priorities: marketing highlights one “need,” while development is solving for another. • Unreliable growth: innovation success rates remain low because there’s no common, customer-driven truth guiding decisions. The Outcome-Driven Innovation process is the solution. ODI resolves this by defining needs as customer outcomes—the metrics customers use to measure success when getting a job done. • Outcomes are solution-independent: not features or benefits, but timeless measures of what getting the job done “better” means. • Outcomes are precise and measurable: e.g., “Minimize the time it takes to gain visual access to the target structure” rather than “faster setup.” • Outcomes create a common language: aligning sales, marketing, and development around the same customer truth. With ODI, everyone agrees on what a “need” is, because it’s framed as a customer-defined metric of success — not each team member’s conflicting interpretation. Outcome statements are unambiguous, precise, knowable and discoverable, stable over time (as is the job-to-be-done), measurable and controllable, and they follow a set of time-tested rules. Companies like Bosch, Cox Automotive, and The Medicines Company aligned their teams around customer outcomes before development began, resulting in products that were not only successful, but sustained market leadership.

👀 I recently saw a post from someone who tried expanding into a new market and blamed the failure on poor translation. While translation is important, it's just one piece of a much larger puzzle. 📌 Expanding internationally isn’t just about translating your website or content. It’s about localisation; deep, thoughtful, cultural adaptation. Take UX for example: 💳 In Germany, people expect invoice-based payments. In the Netherlands, iDEAL dominates. If your checkout doesn’t support local habits, people drop off. 🧠 And translation itself? It’s not about swapping words, it’s about conveying meaning. A lot of world-famous books like Harry Potter have multiple translations within the same language to suit local cultures. The French version has been adapted differently for France vs. Québec. Same with The Little Prince, subtle shifts in tone or idiom can completely change how a message lands. 🎯 If your product slogan works in the UK, don’t assume it’ll resonate in Italy. The cultural context, humour, and emotional triggers might be totally different. ✅ Here’s what you should be thinking about when entering a new market: Native-speaking copywriters, not just translators Payment methods and trust signals local users recognise Legal disclaimers or data collection messages (GDPR, but also local variants) Search intent and SEO; people don’t just search in different languages, they search differently Customer service expectations (e.g. phone support vs. chat, or response time norms) 🌍 In short: translation is the start, not the solution. Winning in a new market takes cultural empathy, native expertise, and a UX that feels familiar to your new audience.

Most teams skip the hardest part of creating OKRs: translating validated customer problems into meaningful metrics. You've done the discovery work. Your interviews revealed that drivers on your ridesharing platform struggle with shift planning—they can't predict which areas will be busy, leading to wasted time and lower earnings. But instead of jumping straight to "build demand forecasting," you need one more step: defining what behavior change would tell you the problem is actually solved. 𝗧𝗵𝗲 𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 I see teams make this leap constantly: Customer problem → Solution idea → Cross fingers and hope. What's missing is asking: 𝗪𝗵𝗮𝘁 𝘄𝗼𝘂𝗹𝗱 𝘂𝘀𝗲𝗿𝘀 𝗱𝗼 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗹𝘆 𝗶𝗳 𝘄𝗲 𝘀𝗼𝗹𝘃𝗲𝗱 𝘁𝗵𝗶𝘀 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝘄𝗲𝗹𝗹? An outcome describes a change in human behavior, not a company aspiration. "Increase driver satisfaction" is what the business wants. "Drivers spend less time in low-demand areas" describes how humans would behave differently. 𝗔 𝗦𝗶𝗺𝗽𝗹𝗲 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗧𝗵𝗮𝘁 𝗪𝗼𝗿𝗸𝘀 When you've validated a customer problem worth solving, structure your outcome similarly to what Joshua Seiden and Jeff Gothelf suggest in their book "𝗪𝗵𝗼 𝗗𝗼𝗲𝘀 𝗪𝗵𝗮𝘁 𝗕𝘆 𝗛𝗼𝘄 𝗠𝘂𝗰𝗵?" [𝗦𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗔𝘂𝗱𝗶𝗲𝗻𝗰𝗲] + [𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿 𝗖𝗵𝗮𝗻𝗴𝗲] + [𝗛𝗼𝘄 𝗬𝗼𝘂'𝗹𝗹 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗜𝘁] Compare these examples: 𝗩𝗮𝗴𝘂𝗲: "Improve user engagement by 20%" 𝘞𝘩𝘰 𝘦𝘹𝘢𝘤𝘵𝘭𝘺? 𝘋𝘰𝘪𝘯𝘨 𝘸𝘩𝘢𝘵 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘵𝘭𝘺? 𝘞𝘩𝘺 𝘥𝘰𝘦𝘴 20% 𝘮𝘢𝘵𝘵𝘦𝘳? 𝗖𝗹𝗲𝗮𝗿: "Part-time drivers in suburban markets reduce unpaid waiting time from 30+ minutes per shift to under 10 minutes." 𝘚𝘱𝘦𝘤𝘪𝘧𝘪𝘤 𝘴𝘦𝘨𝘮𝘦𝘯𝘵, 𝘤𝘭𝘦𝘢𝘳 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘤𝘩𝘢𝘯𝘨𝘦, 𝘮𝘦𝘢𝘯𝘪𝘯𝘨𝘧𝘶𝘭 𝘮𝘦𝘢𝘴𝘶𝘳𝘦𝘮𝘦𝘯𝘵 Before settling on any Key Result, ask yourself: "𝗪𝗵𝗮𝘁 𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗺𝗲𝘁𝗿𝗶𝗰 𝘄𝗼𝘂𝗹𝗱 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘁𝗲𝗹𝗹 𝘂𝘀 𝘄𝗲'𝘃𝗲 𝗮𝗰𝗵𝗶𝗲𝘃𝗲𝗱 𝘁𝗵𝗶𝘀 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿 𝗰𝗵𝗮𝗻𝗴𝗲?"

Deutsche Telekom, Europe's most valuable brand Discovered a hard truth: Perfect service in the wrong language is still terrible service: The numbers were clear: 72% of customers need native language support 56% care more about language than price 42% never buy in foreign languages Ever. Deutsche Telekom tried everything: Hired bilingual agents Built German knowledge bases Created perfect processes Optimized response times But customers kept struggling. Because they couldn't understand any of it. Then DT changed one thing: Let customers speak their native language. All of them. No more: "Sorry, German only" "Please translate this" "Can someone help?" "I don't understand" Instead: Ukranian customers speak Ukranian Polish customers speak Polish Every language, any time Zero compromise The transformation was instant: NPS scores jumped Resolution times dropped Loyalty increased Costs decreased The expensive illusion? Thinking support quality matters More than understanding it. Because here's what every company misses: The best answer in the wrong language Is worse than No answer at all. Deutsche Telekom learned: You can't build loyalty If you can't build understanding. Stop perfecting processes. Start speaking your customers' language first. Because in global business: The most expensive words Are the ones your customers can't read.

At IKEA and Accenture, I saw global brands win international customers, then lose them in the immediate experience that followed. The hardest customers to keep are often the ones you thought you’d already won. We would translate the visible parts of an experience, launch in a new market and watch signups climb. It looks like success on a dashboard. Then people would reach an onboarding flow or a billing page (still in English) and give up. A customer's whole experience shapes how they see you, from the first click to the error message at 11 pm when a payment fails…and the help center is English-only. That's where your ultimate fate is decided. Before we enter a market, I want to know whether a customer there can find us, understand us, buy, use the product, and get help, all in their own language. When the answer is yes, they stay past the first few weeks. A translated homepage may win the signup. A localized experience wins the customer.

A prospect just burned $500K on marketing tech that's gathering dust. Why? Marketing couldn't explain what they wanted. IT built what they thought was right. Nobody talked to each other. Here's how to fix the translation problem killing your ROI: 1. Hire a translator, not another developer Companies have marketers who dream and developers who code. Nobody speaks both. Need someone who knows "personalization" means segmentation, triggers, dynamic content - not blast emails. Worth their weight in gold. 2. "Promote this" means nothing "Promote this product" isn't a specification. Which segments? What triggers messages? What's the journey? Otherwise tech blasts same message to a million people 3x weekly. Seen this 100 times. 3. Your broken tech is bleeding money Broken cart button? Half of those who added items never reached checkout - the icon disappeared. Marketing didn't know. IT didn't know it mattered. Regular check-ins catch profit leaks. 4. Delete vanity metrics Marketers love open rates. The CFO doesn't care. They want transactions, retention, and lifetime value. Tech and marketing align on REAL metrics = magic. Doubled one client's email revenue focusing on purchases and blocking out noise. 5. Start with one test Pick one campaign with both teams in one room. Define success. Map requirements. Test for two weeks. Added "popular" flag to products - 10% revenue jump. Small wins build trust. 6. Fix data before dreams Client wanted AI personalization. Data in seven systems, no unified profile. Another spent millions on outdated code missing analytics. Clean data first, features second. 7. Make failure cheap Salesforce disaster happened going all-in without testing. Start small. One client's two-month test yielded $1M+ revenue. Then scaled. 8. Marketing strategy + technical skills = money You need someone who understands marketing AND technical. They translate "better targeting" into "use data showing New Yorkers book Florida." Travel client - 53% booking increase. 9. Same tools, different conversation An education client wanted "better emails." Tech heard "more emails." After bridging the gap: triggers, segmentation, personalization. Revenue $2.83M to $5.74M. Same tools, different conversation. 10. Smaller teams, bigger results You don't need bigger teams. You need better translation. Run multi-million campaigns with 4-5 people - everyone understands both sides. Quality beats quantity. TAKEAWAY: Companies bleed money through the marketing-tech gap. Not lacking tools or talent. Nobody translates between dreamers and builders. Fix translation. Fix revenue. Your move.

Most feature requests need translation before you can act on them. Here's how to break down vague requests into work you can act on: → Ask what job they're trying to do. "Reporting" is a solution. The job might be "prove ROI to my boss" or "track trends over time." → Get specific use cases. Ask them to walk through exactly how they'd use the feature. What would they do first? Then what? → Explore visualization preferences. Some people want raw data exports. Others want pretty charts. These are different builds. → Identify the trigger. What moment makes them think "I need this"? That context shapes the solution. → Separate related but distinct ideas. "Reporting" might break into five smaller features. Track evidence for each one separately. → Collect supporting evidence over time. One request is an anecdote. Ten requests with similar use cases is a pattern. → Define scope before estimating effort. You cannot estimate "build reporting." You can estimate "create a dashboard showing X metric with Y filter." → Validate your interpretation. Before building, describe what you understood back to the customer. Make sure you got it right. Vague requests are not bad requests. They're starting points for better conversations. Your job is to dig deeper until you have clarity on what to build and why.