Building Customer Trust Through Capability Demonstrations

I was halfway into a demo with a couple of Directors. Their eyes shifted and posture slouched. I'd lost them. But kept going—walking them through one feature after another. Realized they weren't engaged because I hadn’t earned their attention. I was dumping features without connecting them to the problem they were trying to solve. That’s one example, but it's how my demos used to go 👆 Deals stalled. Win rates dropped. ................................................................. That's until I switched to a simple 5-step framework for presenting features on demos, which changed everything. The key difference, leading with the problem: 1. Frame the problem “Linda, you said it’s a pretty tedious process for your team to keep track of all your marketing campaigns for the month. The data is spread across a dozen spreadsheets, google docs, and emails.” • call out the problem • no product jargon • no buzzwords 2. Talk through the use case “So, when the business comes to you for a new product launch, you need to quickly start planning the campaigns. Which can be difficult given everything is scattered. You have to call sporadic team meetings to get updates, leading to product delays and potential lost revenue.” • you've uncover the use case via discovery • talk through how they’re getting the job done today 3. Show the feature “Let me show you how you can see all of this in one place and how you can cut your current process from 10 steps down to 3.” • walk through the feature • be crystal clear about what they’re seeing • it's your prospect’s 1st time seeing it, but your 100th 4. Articulate the outcome “This will help you launch your marketing campaigns 2.5x faster, meeting the business’ product launch dates.” • execs care about business outcomes • clearly state what it could look like with this capability 5. Ask a question “How do you see your team using this capability to solve for [X problem]?” • keep your prospect engaged throughout • lock in those micro-closes ……………………………………....... Have intention and purpose in your demos. Don’t be a feature dumper.

In the high-stakes arena of #B2BSales, particularly when engaging the C-suite and Boards, "back of napkin math" is more than just a display of acumen – it's a potent catalyst for building #trust. Imagine a conversation where a senior leader articulates a critical business challenge, perhaps around CAC payback or share of wallet. The seller who can immediately and fluently grasp the underlying financial equation and articulate the potential impact of their solution, without missing a beat, speaks a language that resonates deeply. This isn't about complex modeling done offline; it's the agility to understand core drivers of their success and perform quick, insightful calculations within the flow of the conversation. For instance, if a Chief Revenue Officer (#CRO) mentions a goal of reducing customer churn, a seller with this skill can instantly frame the value of their solution in terms of retained revenue and lifetime customer value, demonstrating a tangible understanding of the CRO's priorities. This competence signals the seller not only listened - but also deeply comprehends which levers to use to solve the client problem. Why is this so crucial for building trust? Because it showcases several key elements that senior leaders value: Deep Understanding: The ability to perform this kind of rapid analysis demonstrates you've done your homework and truly understand their business model, challenges, and objectives. It moves you beyond being a mere vendor to a knowledge partner. #CustomerUnderstanding Intellectual Horsepower: It signals a sharp mind and the capacity to think strategically about their business. This builds confidence in your ability to deliver real value. #StrategicThinking Efficiency and Respect for Time: Senior executives are time-constrained. A seller who quickly gets to the heart of the financial implications respects this constraint and demonstrates a focus on outcomes. #TimeEfficiency Transparency: By engaging in these on-the-spot calculations, you reveal your underlying assumptions and logic, fostering a more transparent discussion. #TransparentCommunication Credibility: It elevates your status from a product peddler to a trusted advisor who speaks the language of business results. #TrustedAdvisor Think about it: when a seller can seamlessly weave in relevant financial implications – the potential ROI, payback period, impact on key KPIs – it’s not just data; it demonstrates commitment to the customer's success. It shows you're thinking beyond the product/service features and instead - are focusing on their strategic outcomes. To be clear - "Back of napkin math" isn't about being precisely accurate in real-time. It's about demonstrating a strong intuitive grasp of financial levers that matter to the customer and the ability to articulate value in their terms, instantly. This fluency builds a bridge of trust, making conversations more meaningful and impactful. #Gartner

Pablo Palafox didn’t earn his customer’s trust with a perfect AI demo He earned it by catching a red-eye flight to fix a broken deployment In an industry obsessed with automation, it was human commitment that made his AI company indispensable. "When you’re building AI agents for logistics, there’s no room for excuses. Customers are betting their operations on your technology" HappyRobot's first major enterprise customer was skeptical. The CEO looked Pablo straight in the eyes and asked: “You want me to pay $12,000 a year for you to experiment with AI on my business?” But he took the leap of faith In those early days, Pablo served as their first Forward Deployed Engineer a fancy title for someone who gets their hands dirty implementing AI in the field He ran daily standups with customers, checked logs, and made sure no phone call went wrong Then came the night everything changed A critical issue surfaced at a customer site in Atlanta Without hesitation, he took a red-eye flight with a teammate, fixed the issue by morning, and flew back the same day That single act transformed the relationship. Because in an industry still running on paper, emails, and phone calls, they proved they weren’t just selling AI magic—they were partners committed to customer success. A year later, the impact was visible. During the company’s annual SWOT analysis, their AI agent had moved from “Threats” to “Opportunities.” Employees who once feared being replaced were now dressing up as a "Happy Robot" for Halloween. This journey revealed a simple truth about AI adoption: customers don’t just want technology, they want an AI partner who shows up. Over time, Pablo’s team learned that implementing AI in traditional industries requires them to: - Show what’s under the hood (demystify the technology) - Set realistic expectations (LLMs aren’t perfect) - Focus on outcomes, not technology - Be physically present (nothing builds trust like showing up) When MIT reported that 95% of enterprise AI implementations fail, Pablo wasn’t surprised. It’s rarely the model that fails, it’s the integration. Now, with a 65-person team, 20 focused solely on customer deployment— As one of their advisors put it: “Customers value watching you solve problems in real time more than a flawless—but distant—experience.” That’s the paradox of AI implementation: it’s not about perfection. It’s about partnership. To learn more from Pablo, watch the link in the comments

Recently, I walked into a client's manufacturing facility facing a familiar scene: tension between their desire for certainty and the inherent uncertainty of innovation. "What will we get? When will we see it? How can we be sure?" The questions came quickly. They'd been scarred by traditional software approaches. Big design up front, scope creep, missed expectations. They needed an AI solution but couldn't share data externally due to strict security requirements. The challenge was clear: deliver value quickly while building trust. Day 1 focused on understanding their domain. I sketched lean manufacturing processes, examined their data, and explored possibilities. All while being transparent that I didn't have all the answers yet. By morning of Day 2, I had a plan. "Based on what I've seen, I believe we can deliver something valuable today." Their expressions showed cautious optimism, but doubt lingered. Throughout that second day, I invited them in whenever they passed. "Look at this. What do you think about that?" Each small demonstration built confidence. Each question refined our direction. Sixty seconds before our end of day meeting, the solution worked. In just 48 hours, we went from uncertainty to impact. This is how AI projects should work: rapid iteration, continual demonstration, and building while discovering. Don't let not knowing what or how get in the way. Start small, figure it out. This is how the best companies are integrating digital intelligence. #AdvantageThroughAI

If you've got a new service, or product, or if you enter a new vertical, even if your partners are ushering you into their market, expect skepticism. Even with the best partners advocating for you, decision-makers may hesitate and many companies will put you at the bottom of their priority list until you can prove your value. It’s crucial to get traction quickly, or risk being overlooked. Here’s what I would do to break through that initial skepticism and gain momentum: 1. Pilot Programs: Offering a limited-time trial can help, but only if it's designed to deliver clear value from day one. - Set clear success metrics with your customer before the pilot begins. Establish measurable outcomes like improved productivity, user engagement, or cost savings. - Don’t just give them the product—ensure their teams are trained and equipped to use it effectively during the trial. This maximizes the chance of success and measurable impact. 2. Feedback Loops: Regular, structured communication with your partners and customers is key to refining your offering. - Set up bi-weekly check-ins to gather both quantitative data (usage rates, performance metrics) and qualitative feedback (user experience, pain points). - Use this feedback to adapt your approach in real time. Whether it’s tweaking features, adjusting pricing, or improving support, make sure you’re iterating based on what you hear. 3. Case Studies: Success stories build trust and reduce uncertainty for potential customers. - Create detailed case studies highlighting real results from your pilot programs or early adopters. Focus on specific benefits—whether that’s operational efficiency, cost savings, or user satisfaction. -Share these case studies with future prospects to showcase the value and credibility of your service. Timely, relevant examples can turn a hesitant prospect into a committed customer. Gaining traction with a new service takes time, but with the right strategies you can overcome skepticism and build momentum.

Trust is a bridge. You can’t invoice someone until they believe it will hold their weight. Enterprise sellers? They rent bridges from their brand. That’s why “no one gets fired for buying the G2 darling or the top-right on Gartner.” Brand = pre-built steel and concrete. Small business? You don’t have that bridge (yet). You have a face. A voice. A calendar full of humans. So your job is different: build trust one plank at a time—fast. The fastest material on earth for that job is video. Ask any gen Z consumer :). Why video works (especially when you’re small): It makes your face the logo and your voice the jingle. It turns “maybe later” into “I know this person.” It compresses months of emails into 60 seconds of felt credibility. How to build the bridge in public (steal this cadence): 30s “Who I Help + Why” — webcam, eyes on camera. State the painful moment you fix. 60s “Show Your Work” — quick screen-share solving a specific problem; narrate decisions. 90s “Receipt Reel” — stitch a customer clip, a before/after, or a Vidyard reply. No polish. 10s CTA — invite one action Rules that separate closers from posers: Ship imperfect > wait for perfect. Talk to one ICP per video. Teach one thing. Show one proof. Ask one next step. Big companies can rely on the logo to do the trusting. You can’t. But the upside? When you’re small, one great video can do what a Fortune 500 brand mark does—at 1/1,000,000th the cost. Be willing to be known well before you’re well-known. Hit record. Build the bridge. Walk them across.

𝐈 𝐫𝐞𝐜𝐞𝐧𝐭𝐥𝐲 𝐥𝐞𝐚𝐫𝐧𝐞𝐝 𝐚𝐛𝐨𝐮𝐭 𝐚 𝐒𝐚𝐥𝐞𝐬 𝐕𝐏 𝐚𝐭 𝐚 𝐝𝐞𝐚𝐥𝐞𝐫𝐬𝐡𝐢𝐩 𝐓𝐡𝐞𝐢𝐫 𝐛𝐢𝐠𝐠𝐞𝐬𝐭 𝐞𝐪𝐮𝐢𝐩𝐦𝐞𝐧𝐭 𝐝𝐞𝐚𝐥 𝐭𝐡𝐢𝐬 𝐲𝐞𝐚𝐫? 𝐂𝐥𝐨𝐬𝐞𝐝 𝐛𝐲 𝐚 𝐬𝐞𝐫𝐯𝐢𝐜𝐞 𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐢𝐚𝐧, 𝐧𝐨𝐭 𝐚 𝐬𝐚𝐥𝐞𝐬𝐩𝐞𝐫𝐬𝐨𝐧 Here's what happened: The company was in the final stages of a major deal that could transform their quarter from good to great. Everything seemed lined up: The equipment fit, financials made sense, and delivery timelines worked. But the customer hesitated: "We're concerned about downtime and maintenance costs," That's when the Sales VP made a brilliant move. Instead of sending another brochure or discount, the Sales VP brought in their veteran service technician for the final meeting. This wasn’t just any technician. With grease-stained hands and 15 years of hands-on experience, he spoke candidly about: 👍 The common maintenance challenges they'd likely face 👍 The specific steps their dealership had in place to minimize downtime 👍 The exact response times they could expect when issues arose No jargon. No BS.  Just straight talk from someone who understood what keeps equipment managers up at night. The result? The customer signed the deal that same day. Their exact words:  "Your technician's presence was the deciding factor. It showed us you're invested in our long-term success, not just making a sale." That day, the technician was the MVP on the sales team. The takeaway is clear: Expert service technicians are powerful sales enablers. Their real-world knowledge and commitment to solving problems build trust no slick presentation can ever match. Involve your best service people in sales. It shows prospects you’ll be there when things go wrong. And in equipment sales, that’s worth more than any discount you could ever offer.

Most climate tech websites hide their process. Big mistake. Here's what I've learned after designing for deep climate tech startups: Your potential customers want to see the journey before they take it. Our recent work with Nira Energy on their "Path to Smarter Queue Decisions" workflow we showed exactly that. Instead of just saying "we optimize energy dispatch," we showed exactly how. Step 1: Data collection from multiple sources Step 2: Real-time analysis of grid conditions Step 3: Scenario modeling for optimal decisions Step 4: Automated queue recommendations We mapped out three different scenarios. Peak demand. Grid instability. Renewable surplus. For each scenario, visitors can see the exact process flow. This isn't about giving away trade secrets. It's about building trust through transparency. When someone visits your website, they should understand: • What working with you actually looks like • How you solve their specific problem • Why your approach works better • What results they can expect The companies that win don't make potential clients guess. They show the path forward clearly. Your process becomes your competitive advantage. Not something to hide behind vague promises. Before Nira's prospects even hop on a call, they already understand the value. They've walked through the workflow mentally. Trust is built before the first conversation starts. What part of your process could you showcase to build more trust upfront? --- If you’re scaling climate solutions, Get similar tips and strategies for customer focused storytelling at : https://lnkd.in/gWcvue25

From Skepticism to Scale: Building Confidence and Capability in AI Adoption   95% of AI projects fail. We were determined not to be part of that statistic.   Our client, a leading global financial services firm, faced a familiar dilemma: they knew AI was critical to competitiveness but were paralyzed by risks of failure and unclear ROI.   So, they chose a different path. Instead of a massive, risky upfront investment, they adopted AI one phase at a time with our AI Impact Framework.   The result? In 6 months, they moved from uncertainty to:   1.    A board-approved AI roadmap 2.    A functioning internal AI Center of Excellence 3.    A pilot project on track for a 40% efficiency gain   Most importantly, it protected their bottom line and their reputation. By identifying critical governance gaps early, they avoided a costly and public failure down the line.   This phased approach de-risked every step, built internal confidence, and delivered measurable outcomes at every milestone - transforming skepticism into scalable capability.   The full case study lays out the exact 5-phase process, the key deliverables, and how they built consensus and proved value at each step.   This wasn't just a new process; it was a new mindset. We replaced "big bang" risk with incremental confidence, turning their AI ambition into a guaranteed, pay-as-you-go journey.   Access to the full case: How a Financial Leader Built AI Confidence is available if anyone wants to read the real success story of AI introduction.   The question isn't if you should adopt AI, but how you can do it without betting the farm. This is the model to de-risk that bet.     What phased strategies have you used for AI adoption? Share your story below!   Transform Partner – Your Strategic Champion for Digital Transformation Image Source: McKinsey