Latest news with #PallishreePanigrahi
Forbes
24-07-2025
- Business
- Forbes
How To Get The Most Out Of Your Early Product Metrics
Pallishree Panigrahi is Head of Data & Insights at Amazon Key. In the early days of a new product, the numbers we track—the metrics—shouldn't be treated as verdicts. They're not there to crown your idea a success or condemn it as a failure. Early metrics are operational breadcrumbs—signals that reveal where users get stuck, what needs fixing and which assumptions need to be rethought. It's easy to confuse early signals with signs of success—especially when dashboards look great on the surface. I've seen this firsthand across multiple launches. On paper, a dashboard can look impressive: thousands of sign-ups, high activation rates, glowing ratings. But if you look closer, what seems like traction is often friction disguised as progress. One example: In our smart access platform, we initially tracked how many times drivers successfully unlocked gates. The numbers were big and reassuring—until we realized many of those 'successful' unlocks were the same frustrated driver clicking over and over because there was no clear confirmation the gate was open. This is why early metrics should be designed to help teams learn, not just look good in an investor update. Five Metrics Every Early-Stage Product Should Track I recommend every product team start with five foundational metrics. None of them declare success. All of them force you to ask better questions. 1. Time To First Value (TTFV) How quickly does a user reach their first meaningful outcome? For an e-commerce platform, it's not when someone signs up, it's when they successfully place an order and receive their first product without issues. This metric reflects how smooth your onboarding, product discovery and checkout experience really are. If users don't get to value quickly, they often don't come back. 2. Activation Rate What percentage of new users hit a milestone that proves they've engaged meaningfully? A good activation metric might be: User adds an item to their cart and checks out within 24 hours of sign-up. This goes beyond passive browsing and captures real purchase intent. A low activation rate could point to friction in product search, unclear pricing, or trust barriers at checkout. 3. Repeat Usage In A Short Window Do users come back quickly to do the same task again? Traditional retention metrics are often too broad or slow to reveal early signals of value. Instead, track whether people return in seven or 14 days to do the same task again. Repeated use in context is a stronger indicator of product-market fit than one-time curiosity. 4. Top Drop-Off Point Where in the journey do most users abandon the process and why? It's not enough to know your overall conversion rate. Pinpoint whether users are dropping off at the product page, after adding to cart or during payment. For instance, a high abandonment rate at checkout could reveal trust issues, hidden costs or UX problems with the payment flow. 5. Qualitative Feedback Volume And Themes What are users telling you, in their own words about what's not working? Numbers show you what happened, but feedback tells you why. Categorize support tickets, surveys and reviews into clear themes. Often, your biggest opportunity hides inside the smallest complaints. These metrics aren't permanent. As your product matures, they should evolve with it. But picking the right metrics is only half the challenge, what really matters is how you interpret them. Discovery Metrics Vs. Validation Metrics One of the most common traps is treating early metrics as validation—proof that your idea is working. But discovery metrics have a different purpose: They break your assumptions so you can build the right thing faster. I ask three questions to tell them apart: 1. Is this metric helping us learn, or is it just there for reporting? 2. What decision will this help us make in the next sprint? 3. Is it tied to a hypothesis we're testing? Daily active users (DAUs), for example, often look like success. But if people aren't completing meaningful tasks, those DAUs are empty calories. A stronger early signal might be the percentage of users who complete a workflow without retrying or contacting support. Discovery metrics influence what you build next. Validation metrics only reassure you that everything's fine. Metrics guide better decisions only if they're designed well. That's where the VET framework comes in. The VET Metrics Framework To design metrics that matter, I use what I call the VET Metrics Framework. It's a simple test: • Value: Does this metric reflect an outcome that matters to users or the business? Counting clicks or pageviews doesn't help if nobody is completing the core task. • Evolvability: Can the metric adapt as your product matures? A KPI that only works in a beta test will quickly become obsolete. • Trustworthiness: Does this metric produce actionable insight? For example, average session time is ambiguous—longer isn't always better. You need clarity, not just data. When we built early KPIs for Amazon Key, we didn't settle for tracking how many times someone pressed the unlock button. We measured the percentage of deliveries completed without intervention—a metric that showed whether the system was truly solving the access problem. Of course, tracking progress is only useful if you're focused on solving the right thing. So how do you know you are? Five Ways To Know If You're Solving The Right Problem No single metric can answer this question, but you can triangulate using five lenses: 1. Repeated Use In Context: Are people coming back to solve the same problem? 2. Feedback Alignment: Do users describe the value in their own words the way you intended? 3. Problem Substitution: What old workaround did your product replace? 4. Tolerance Of Friction: Do users keep going even when parts of the experience are clunky? 5. Value Hypothesis Testing: Can you validate demand and usability before building everything out? These signals give you a clearer picture of real-world fit. Even with the right metrics and mindset, it's easy to fall into common traps, especially when data looks deceptively positive. Measurement Traps That Sink Early Products Even experienced teams fall into familiar pitfalls: • Tracking What's Easy, Not What Matters: Just because you can measure it doesn't mean it helps. • Measuring Too Much, But Learning Too Little: A crowded dashboard is usually a sign of unclear priorities. • Overvalidating And Underexploring: Early KPIs should challenge your assumptions, not confirm them. • Lagging Indicators Masquerading As Insight: NPS and 30-day retention are too slow to guide early decisions. • Ignoring Qualitative Feedback: Pair behavioral data with user comments to see the full story. If your metrics are only telling you everything is fine, you're not measuring deeply enough. Early metrics should make you a little uncomfortable. That's their job. They exist to surface what's not working so you can fix it before you scale. This week, take a fresh look at your dashboard—not just for trends, but for blind spots. If your metrics aren't teaching you something new, you're not measuring deeply enough. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Forbes
16-06-2025
- Business
- Forbes
20 Surprising Ways AI Is Reshaping The Customer Journey
getty Businesses and consumers alike recognize that artificial intelligence plays a significant role in today's customer journeys—receiving personalized recommendations and accessing chatbot support are now standard features of many digital transactions. But AI also holds largely untapped potential for brands aiming to enhance service and deepen customer relationships. From enabling conversational product searches to equipping service reps with real-time insights that speed up issue resolution, AI can help brands improve responsiveness, personalize engagement and foster greater customer loyalty. Below, members of Forbes Technology Council discuss surprising ways AI is reshaping the customer journey—and why brands need to stay on top of what's new and what's next. One surprising way AI is reshaping the customer journey is by influencing invisible moments—optimizing logistics, predicting friction and personalizing experiences before a user even interacts with a brand. Many brands focus on front-end AI, but the biggest opportunity lies in using AI to quietly orchestrate a seamless, proactive experience long before a user clicks 'buy' or 'support.' - Pallishree Panigrahi, Amazon Key Advanced AI can predict intent based on subtle behavioral and contextual signals—location patterns, online content consumption, device usage and transactional data. Ads can then be personalized across all devices based on where the customer is emotionally in the journey. This feels 'timely' to the customer, but it's actually predictive. - Lalena Nau, Zeta Global Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify? AI is quietly transforming on-premises dining by enabling real-time, hyper-personalized guest experiences. From adapting menus to guest history or mood to triggering proactive service based on live conditions, the next frontier isn't digital—it's anticipating needs before guests voice them. Most brands haven't tapped into that yet. - Tiffany Saylor, FB Society AI is starting to reshape the customer journey through real-time emotional intelligence. By reading tone, facial cues and behavior, AI can adapt in the moment—not just to what customers do, but also to how they feel. Most brands haven't caught on yet, but those that do will create more intuitive, human-centered experiences that build deeper trust and loyalty. - Gjoko Muratovski, Australian Institute of Advanced Technologies (AIAT) People aren't Googling which running shoes to buy anymore. Instead, they're asking questions of GenAI tools like ChatGPT and receiving a direct answer, along with a link to buy. If brands aren't thinking about AI search, they're already behind. - Net Kohen, LinkMe AI is reshaping the very idea of the customer journey. While most brands aim to optimize it, the real win may lie in minimizing or eliminating it altogether. For instance, a car insurance provider could use AI to monitor market rates and auto-renew customers at the best value, removing the need for them to shop around. The shorter the journey, the better the experience for both brand and customer. - Deepak Tiwari, Ernst & Young The proliferation of AI is diluting customer demographics in ways we're only beginning to notice. Segmentation across similar customer profiles is blurring or vanishing completely as AI becomes our personal purchasing consultant—shaping our perception of a product before we've hit the landing page or even seen the pitch. It knows us and what we like and is the invisible hand guiding our choices. - Evan J. Schwartz, AMCS Group AI silently empowers frontline staff, providing language translation and giving them real-time insights, sentiment cues and summaries of conversations. It makes interactions more personal and empathetic without the customer ever knowing AI is involved. - Martin Taylor, Content Guru Financial companies will be able to analyze payment behavior and flag anomalies in real time. Enhanced security and fraud prevention will balance the speed of instant payments, while granular payment data offers opportunities for personalization. - Taira Hall, Citizens AI is quietly redefining the customer journey by predicting needs before customers articulate them. Through passive intent recognition across platforms, AI anticipates user desires and triggers hyper-personalized experiences in real time. This shift transforms marketing from reaction to intuition, turning brands into proactive companions rather than reactive service providers. - Nicola Sfondrini, PWC We have seen a game-changing trend where brands are incorporating voice AI agents to improve CX and provide support. In the future, every SaaS product could ship with fully automated support that is available 24/7. - Fenil Suchak, OpenFunnel AI is beginning to reshape the timing of customer engagement, not just the message. By predicting when a person is most likely to respond or convert, AI can optimize outreach windows on an individual level. This subtle shift from 'what' to 'when' is underutilized by many brands and can dramatically improve outcomes without changing the message itself. - Antara Dave, Microsoft Corporation One surprising thing about AI in customer experience is how it's exposing the gap between what companies think customers want and what they actually value. Many brands are still using AI to push more personalization, despite data showing that customers often prefer simplicity and consistency. The real opportunity lies in using AI to challenge your assumptions, not reinforce them. - Ishaan Agarwal, Square AI can create hyperrealistic 'digital twins' of customers for risk-free testing of products and experiences, uncovering hidden needs before a real launch. Many brands haven't fully grasped this deep personalization potential beyond basic data analysis. - Ambika Saklani Bhardwaj, Walmart Inc. The reality is that brands will no longer own the shopping journey altogether. It used to start with a Google search, visits to a few brand sites and then a checkout. Now, shoppers turn to AI agents like ChatGPT to decide what to buy—and, importantly, buy it right there. The future of e-commerce is agent-led, not brand-owned. Retailers want control, but the shift is underway. Welcome to agentic commerce. - Kamal Nahas, pap! Agentic AI, powered by emerging standards like Model Context Protocol, decomposes interactions into reusable, context-aware conversation modules, enabling companies to deploy tailored experiences across platforms (phone, chat, voice assistants, AR/VR and so on) without rebuilding interfaces. This model stands to change how we think about customer journeys, adapting dynamically to individual preferences. - Nick Burling, Nasuni AI is collapsing linear customer journeys into instantaneous decision moments, often before a user even signals intent. By balancing what to remember and when to forget, AI crafts emotionally resonant, frictionless experiences that challenge brand assumptions and optimize for discovery in an AI-first world. - Mark Mahle, NetActuate, Inc. AI is quietly reshaping CX by learning when not to personalize, strategically forgetting past interactions to avoid user fatigue or creepiness. By tuning memory thresholds based on user psychology, AI creates emotionally safer experiences that feel familiar, yet not intrusive—something most brands haven't optimized for. - Jagadish Gokavarapu, Wissen Infotech AI enables shoppers to summarize thousands of product reviews across platforms into clear pros and cons within seconds. This strips away cherry-picked testimonials and forces transparency. Brands still banking on curated praise haven't realized they're competing with the customer's personal research analyst. - Andrew Siemer, Inventive AI is reshaping the customer journey by becoming a post-purchase concierge. Beyond conversion, AI can now orchestrate personalized onboarding, usage tips, proactive issue resolution and even product education, transforming support into a continuous value experience. Yet most brands still treat post-sale moments as transactional, missing a massive opportunity for loyalty and upsell. - Pawan Anand, Ascendion
