Customer-Centric Innovation Methods

Most problems in GTM can be solved with one thing: a better understanding of your customers. Sounds simple, right? It’s not. Especially if your systems are siloed and you don’t have an analyst on your team. Here’s the good news: It’s something AI is phenomenally good at – if it has the right data. If you’ve used ChatGPT’s deep research feature, you know how good it is at analyzing vast amounts of data and producing detailed insights. If you’ve used HubSpot, you know that it unifies structured and unstructured data and has full context across the customer journey. Today, I’m super excited to share that HubSpot is the first CRM to launch a deep research connector with ChatGPT. That means you can now do advanced analysis of context-rich customer data – and immediately take action on those insights. The result? Better experiences for your customers. Better outcomes for your business. Here are some use cases: - Marketers, you could ask for a list of 'VP' and 'C-Level' leads who opened an email in the past week but have no next activity scheduled – then run a hyper-targeted follow-up campaign. - Sales leaders and reps, you could pull up a summary of why your high-potential deals are stalling – then create an email sequence that addresses the most common objections. - Customer success leaders, you could generate a list of at-risk customers and a unique renewal plan for each one – then take proactive steps to retain them. I can’t wait to see what our customers achieve with the power of deep research and unified data, right in their flow of work. If you’re a HubSpot customer with a paid ChatGPT plan (Enterprise, Team, Pro, Plus, or Edu), you can get started now!

When I started in #product 15 years ago, everyone used Jira, Confluence, Balsamiq, and later Airtable + Figma. With GenAI, the landscape has evolved, and here is a list of tools I expect every PM to use to stay ahead. ✨ Strategy & Competitor Analysis ✨ I think #Notion did a great job upgrading their capabilities and integrating OpenAI and Anthropic models (not sure what #Coda is doing?), which support drafting and refining strategies using internal (Slack messages, docs) and external data (investor presentations, etc.). I have personally used #Competely, which provides a massive head start and notifies you when competitors release new features and their potential impact on your strategy. 🔎 Customer Research & Discovery 🔎 Platforms such as #Kraftful automate feedback aggregation from various sources. Pushing it further, #Genway creates agents that automatically conduct your interviews, and #NextMinder can simulate research based on provided customer segment details and behavior, allowing you to simulate millions, not just dozens, of users. 🚀 Rapid Prototyping 🚀 Much has been said here, and tools like #Loveable are growing at a rapid pace. However, I’m personally more of a fan of the #Uizard toolkit, which lets you upload screenshots and whiteboard drafts and turn them into mobile and desktop designs automatically (and can also generate functional code). ✏️ Requirements & User Stories✏️ I think every PM has now used ChatGPT to generate requirements or user stories. I’ve personally found more success with #Claude, and investing in building your own GPT, populated with your strategy context, OKRs, and example PRDs and user stories, goes a long way. ✅ Testing & Validation ✅ I started product when we forced PMs to write Gherkin syntax into user stories. #QualGent and #Spur are two great examples on how Agents + MCP will change the way Product Managers will test software before it reaches users. 🤝 Collaboration & Documentation 🤝 I haven’t used them in action yet, but #Quantstruct and #Mem are notes on steroids: they automatically feed into a central knowledge base accessible by the team and help automate documentation. I’m eager to see how far we can push this in the context of technical/API/feature documentation and how we can remove outdated content from it. #GenAI #ProductManagement Shivani Rathi, Emily Gao, Shai Dinnar, Dimitrios Lippe, Bradley Antcliff, Frederic Doppstadt

I was just interrupted during our onsite innovation sprint… “I’m sorry, but I don’t think that’s what our customers want.” We’ve been mapping our innovation roadmap all week, and something fascinating keeps happening: Our social team (who absolutely has a seat at the table) continuously brings a critical perspective: “The conversations on social are focusing elsewhere...” “Our listening tools show this is the actual pain point...” “Here’s what customers are saying in real-time...” Their insights can shift our next steps. And they are backed by data from thousands of real customer conversations flowing through social channels every day, unfiltered and honest. So the most valuable question we kept returning to during our onsite was: → Are we building what WE think matters, or what our CUSTOMERS say matters? Your social team isn’t just executing your social strategy - they’re sitting on insights that should be shaping your entire business strategy. How are you integrating social intelligence into your product roadmap? The answers might surprise you.

Tactic 2 for influencing stakeholders from Jules Walter: Frame your message from their POV (not yours) It’s more effective to speak their language and demonstrate how your proposal will help them reach their goals, not yours. Stakeholders are focused on their own problems and are more receptive to proposals that address what’s already top of mind for them. A few years ago, when I was leading Monetization at Slack, we began to encounter diminishing returns in our product iterations, and we needed to take a bigger swing to re-ignite revenue growth. To do that, I spearheaded a controversial project to experiment with a new approach to free-to-paid conversion. The CEO, Stewart Butterfield, had strong reservations about the project. I knew from his previous statements that he didn’t want the company to be thinking about ways to extract value from users, but rather ways to create value for them. We had scheduled a review with the CEO and a few of his VPs to discuss the proposal. Since he was intensely user-driven, I framed the entire proposal around the benefits it would have for users (the CEO’s POV) rather than emphasizing the revenue impact of the project (our team’s goal). I started the meeting by anchoring the proposal on user-centric insights that we shared in a deck: - “About 10% of purchases of Slack’s paid version happen from users in their first day on Slack.” - “Paid users find more value and retain better. Yet we make it hard for people to discover that Slack has a paid version that’s more helpful.” - “How do we help new teams experience the full version of Slack from the start?” Once we framed the issue with this user-centric lens, the CEO was more open to our proposal and let us try a couple of experiments in this new direction. This user-centric framing also got the cross-functional team more excited and set an aspirational North Star with clear guardrails, which then enabled various teammates to contribute productively to the project. After we tested two iterations of our monetization experiment, we landed on a version that resulted in a significant increase in revenue for Slack (a 20% increase in teams paying for Slack) and we used what we learned to shift Slack’s monetization strategy into a new, more successful direction. Full set of tactics here: https://lnkd.in/gezP2EDw

Getting the right feedback will transform your job as a PM. More scalability, better user engagement, and growth. But most PMs don’t know how to do it right. Here’s the Feedback Engine I’ve used to ship highly engaging products at unicorns & large organizations: — Right feedback can literally transform your product and company. At Apollo, we launched a contact enrichment feature. Feedback showed users loved its accuracy, but... They needed bulk processing. We shipped it and had a 40% increase in user engagement. Here’s how to get it right: — 𝗦𝘁𝗮𝗴𝗲 𝟭: 𝗖𝗼𝗹𝗹𝗲𝗰𝘁 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 Most PMs get this wrong. They collect feedback randomly with no system or strategy. But remember: your output is only as good as your input. And if your input is messy, it will only lead you astray. Here’s how to collect feedback strategically: → Diversify your sources: customer interviews, support tickets, sales calls, social media & community forums, etc. → Be systematic: track feedback across channels consistently. → Close the loop: confirm your understanding with users to avoid misinterpretation. — 𝗦𝘁𝗮𝗴𝗲 𝟮: 𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 Analyzing feedback is like building the foundation of a skyscraper. If it’s shaky, your decisions will crumble. So don’t rush through it. Dive deep to identify patterns that will guide your actions in the right direction. Here’s how: Aggregate feedback → pull data from all sources into one place. Spot themes → look for recurring pain points, feature requests, or frustrations. Quantify impact → how often does an issue occur? Map risks → classify issues by severity and potential business impact. — 𝗦𝘁𝗮𝗴𝗲 𝟯: 𝗔𝗰𝘁 𝗼𝗻 𝗖𝗵𝗮𝗻𝗴𝗲𝘀 Now comes the exciting part: turning insights into action. Execution here can make or break everything. Do it right, and you’ll ship features users love. Mess it up, and you’ll waste time, effort, and resources. Here’s how to execute effectively: Prioritize ruthlessly → focus on high-impact, low-effort changes first. Assign ownership → make sure every action has a responsible owner. Set validation loops → build mechanisms to test and validate changes. Stay agile → be ready to pivot if feedback reveals new priorities. — 𝗦𝘁𝗮𝗴𝗲 𝟰: 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 What can’t be measured, can’t be improved. If your metrics don’t move, something went wrong. Either the feedback was flawed, or your solution didn’t land. Here’s how to measure: → Set KPIs for success, like user engagement, adoption rates, or risk reduction. → Track metrics post-launch to catch issues early. → Iterate quickly and keep on improving on feedback. — In a nutshell... It creates a cycle that drives growth and reduces risk: → Collect feedback strategically. → Analyze it deeply for actionable insights. → Act on it with precision. → Measure its impact and iterate. — P.S. How do you collect and implement feedback?

What if your biggest growth opportunity isn’t in your sales pipeline, but in your post-sale experience? While most revenue teams obsess over lead volume and top-of-funnel performance, high-performing organizations are reallocating resources toward the one area most overlooked (and most profitable): customer retention. You’re not losing revenue because you can’t acquire customers; it’s because you can’t keep them. Customer experience, loyalty, and client services are no longer “support” functions. They’re strategic growth levers. And the cost of ignoring them is compounding: - Customer acquisition costs (CAC) are rising 60–75% - Churn is erasing pipeline gains before they hit the forecast - Siloed orgs are failing to act on critical post-sale insights Here’s how growth leaders are operationalizing customer-centricity to outpace competitors: ✅ Shift GTM strategy from funnel-filling to journey stewardship. Map the full customer lifecycle, then build cross-functional ownership for every phase beyond the sale. ✅ Hardwire retention into revenue models. Redefine revenue metrics: CLV, NRR, and CSAT become as critical as quota attainment. ✅ Turn customer success into a revenue function. Enable CS teams to identify expansion triggers, churn signals, and feedback loops that inform both product and GTM. ✅ Engineer feedback into daily operations. Surface real-time insights from support, community, and product usage–not quarterly surveys or lagging indicators. The companies doing this right see up to a 25% lift in renewals, 35% higher LTV, and customer referrals that shorten sales cycles by 30–50%. Want to build a revenue engine that scales and sustains? Start by asking: How are we designing for the customer after the contract is signed? Read the full post: https://lnkd.in/dY3Rxsc9 __________ For more on growth and building trust, check out my previous posts. Christine Alemany Join me on my journey, and let's build a more trustworthy world together. #Fintech #Strategy #Growth

As an analyst, I was intrigued to read an article about Instacart's innovative "Ask Instacart" feature integrating chatbots and chatgpt, allowing customers to create and refine shopping lists by asking questions like, 'What is a healthy lunch option for my kids?' Ask Instacart then provides potential options based on user's past buying habits and provides recipes and a shopping list once users have selected the option they want to try! This tool not only provides a personalized shopping experience but also offers a gold mine of customer insights that can inform various aspects of a business strategy. Here's what I inferred as an analyst : 1️⃣ Customer Preferences Uncovered: By analyzing the questions and options selected, we can understand what products, recipes, and meal ideas resonate with different customer segments, enabling better product assortment and personalized marketing. 2️⃣ Personalization Opportunities: The tool leverages past buying habits to make recommendations, presenting opportunities to tailor the shopping experience based on individual preferences. 3️⃣ Trend Identification: Tracking the types of questions and preferences expressed through the tool can help identify emerging trends in areas like healthy eating, dietary restrictions, or cuisine preferences, allowing businesses to stay ahead of the curve. 4️⃣ Shopping List Insights: Analyzing the generated shopping lists can reveal common item combinations, complementary products, and opportunities for bundle deals or cross-selling recommendations. 5️⃣ Recipe and Meal Planning: The tool's integration with recipes and meal planning provides valuable insights into customers' cooking habits, preferred ingredients, and meal types, informing content creation and potential partnerships. The "Ask Instacart" tool is a prime example of how innovative technologies can not only enhance the customer experience but also generate valuable data-driven insights that can drive strategic business decisions. A great way to extract meaningful insights from such data sources and translate them into actionable strategies that create value for customers and businesses alike. Article to refer : https://lnkd.in/gAW4A2db #DataAnalytics #CustomerInsights #Innovation #ECommerce #GroceryRetail

The secret to company success is deep-customer understanding. And no one did it better than Gillette. How? By literally living with their customers and seeing how they use Gillette products. When Gillette wanted to expand to India, they realized that Indians didn't shave the same way as Americans. To understand Indian customers better, one of Gillette's executives, Chip Bergh, asked his team to go to India and live with the customers there. They wanted to observe how people shaved and how it fit into their lives. This concept is called ethnographic market research. One scientist from the UK thought they simply could talk to Indian men living nearby, but Chip said it wouldn't be enough. They needed to see and experience things firsthand. In India, the team discovered that many people in India didn't have access to a big sink with hot running water like in the West. They used a small cup of cold water to shave. This made shaving with regular razors difficult because the small hairs clogged the blades. So, they innovated a razor called the Gillette Guard: it had a single blade with a safety comb to prevent cuts and was easy to rinse. Perfect for Indian customers. This way, they could make razors that people needed and loved. The lesson: The key to unlocking consumer experience lies in understanding the consumer’s needs in-depth. #consumerresearch #customersatisfaction #startups #entrepreneurship

I think about Jeff Bezos's "start with the press release and work backward" approach. Here is a future headline I would like to see: "Surveys are no longer the primary tool for gathering insights." To get there, surveys will have had to evolve into precision instruments used strategically to fill gaps in data. Let's call this the "Adaptive Survey." With adaptive surveys, organizations can target key moments in the customer or employee journey where existing data falls short. Instead of overwhelming consumers and employees with endless, and meaningless, questions, surveys step in only when context is missing or deeper understanding is required. Imagine leveraging your operational data to identify a drop in engagement and deploying an adaptive survey to better understand and pinpoint the "why" behind it. Or, using transactional data to detect unusual purchasing behavior and triggering a quick, personalized survey to uncover motivations. Here's how I hope adaptive surveys will reshape insight/VoC strategies: Targeted Deployment: Adaptive surveys appear at critical decision points or after unique behaviors, ensuring relevance and avoiding redundancy. Data-First Insights: Existing operational, transactional, and behavioral data provide the foundation for understanding experiences. Surveys now act as supplements, not the main course of the meal. Contextual Relevance: Real-time customization ensures questions are tailored to the gaps identified by existing data, enhancing both response quality and user experience. Strategic Focus: Surveys are used to validate hypotheses, explore unexpected behaviors, or uncover latent needs...not to rehash what’s already known. Surveys don't have to be the blunt instrument they are today. They can be a surgical tool for extracting insights that existing data can’t reach. What are your thoughts? #surveys #customerexperience #ai #adaptiveAI #customerfeedback #innovation #technology

What if we reimagined the Double Diamond through the lens of Jobs-to-be-Done? 🤔 Product Management is about mastering various methodologies and knowing when to apply them. No single framework fits all scenarios - the key is understanding how different approaches can complement each other to drive better outcomes. I have been learning and practicing the art and science of Innovation through the concepts of JTBD, Human Centered Design, Design Thinking, Customer Driven Innovation, Continuous Discovery, Product Discovery, Lean, etc., I've found these methodologies aren't just related, they're deeply interconnected pieces of the same puzzle. I took the classic double diamond design thinking framework and applied JTBD to it and here is how it looks in my view. While the double diamond model divides the journey into Problem → Solution spaces, the evolved version speaks the language of jobs and outcomes 💎Left Diamond: Transformed from problem-finding to "Jobs & Outcomes" - focusing on understanding what customers are trying to achieve in their contexts. 🌉The Bridge: "Opportunity Statements" replace "Problem Definition" - shifting from fixing issues to unlocking potential. Opportunity Statements are what Tony Ulwick calls "Hidden Growth Opportunities". These statements guide our innovation direction. 💎Right Diamond: Maintains the Design/Develop and Iterate/Deliver phases, but shifts validation focus to measuring how effectively we enable customers to achieve their desired outcomes. This framework moves beyond problem-solution thinking to create value through deep understanding of customer progress and success metrics in the form of jobs and outcomes. Have you integrated different innovation frameworks in your work? What have you learned? Would love to hear your experiences! #innovation #JTBD #designthinking #productdiscovery