Sahil Gandhi of Discover On The 5 Best Ways to Drive Product Growth

In the realm of business, particularly with regard to tech products, growth is the key to success. However, navigating the journey from ideation to expansion presents its own unique set of challenges. How does one devise a strategy to ensure sustained growth of a product in a competitive marketplace? What are the best practices, strategies, and methodologies to accomplish this? In this interview series, we would like to speak to experienced professionals who have successfully driven product growth. As part of this series, we had the distinct pleasure of interviewing Sahil Gandhi.

Sahil Gandhi is a data science leader with nearly a decade of experience building analytics and AI systems that drive measurable impact across finance, manufacturing, and healthcare. His work spans machine learning, causal modeling, AI agents, and RAG-based LLMs with a focus on taking solutions from 0 to 1 and scaling them to enterprise adoption. He also serves on the Advisory Council at Products That Count, one of the world’s largest product communities, and is pursuing executive education at Stanford to further expand his leadership perspective.

Thank you so much for joining us in this interview series! Before diving in, our readers would love to learn more about you. Can you tell us a little about yourself?

I’m a data science professional with nearly a decade of experience applying analytics and AI across industries like finance, healthcare, and manufacturing. Working in such different domains has taught me how to adapt solutions to very different challenges whether that’s improving decision systems, building platforms that make knowledge more accessible, or using AI to streamline operations. What excites me most is turning complex data into tools people can actually use, and seeing the impact those solutions have on the way organizations work and people make decisions.

What led you to this specific career path?

I’ve always been drawn to math and problem-solving, which is what led me to study electrical engineering. During my undergraduate studies, I took an introductory programming course, and that experience opened my eyes to how coding could be used to build solutions and test ideas in ways that felt creative as well as logical. That curiosity about coding and data kept growing, and I soon realized I was more excited by the information those systems produced than by the hardware itself. That realization pushed me toward analytics and eventually into data science, where I’ve been able to combine math, engineering discipline, and programming to build AI and data systems that drive impact across industries.

Can you share the most exciting story that has happened to you since you began at your company?

At Discover, my work in data science focuses on supporting decisions in areas like credit card collections. One of the most memorable moments wasn’t in a project itself, but during a fireside chat with a senior leader. He shared how a member of his own family had struggled with debt, and how hopeless that situation can feel when people are afraid to ask for help.

Even though I don’t interact with customers directly, that conversation gave me a deeper sense of the bigger vision behind our work. It reminded me that at the end of the day, it’s not just about balances or metrics — it’s about giving people tools, empathy, and support to make better decisions. When customers feel understood and treated fairly in those vulnerable moments, it builds trust, and that trust is what ultimately stays with them long after the financial stress has passed.

What are some of the most interesting or exciting projects you are working on now? How do you think that might help people?

One of the most exciting things I’m working on right now is helping shape the transformation following Discover’s acquisition by Capital One this past May. Bringing together two huge organizations with different strengths and a customer base that impacts financial lives at a scale rarely seen in any industry is both complex and energizing. My role has included working closely with executive leadership, sharing insights that guide decisions about how systems, processes, and customer experiences should evolve so we carry forward the best of both worlds while keeping people at the center.

What excites me most is that the choices we make now don’t just streamline operations; they shape how millions of people experience their finances every day. Being part of a transformation of this magnitude is both humbling and energizing — it’s the kind of work that reminds me why I chose this career path.

You’re a successful business leader. What are three traits about yourself that you feel helped fuel your success? Can you share a story or example for each?

When I think about what’s helped me most in my career, it hasn’t been just technical skills or titles, it’s been the mindset I’ve carried into different challenges. Three traits in particular that stand out to me are:

Curiosity and Continuous Learning — I’ve always been driven by the need to dig deeper and keep refining how I learn. At Discover, that meant championing the use of causal frameworks to move beyond just predicting outcomes to understanding why they happen — insights that directly influenced product strategy and decision-making. I also leaned heavily on experimentation design as a discipline to continually test and sharpen our approach. That mindset shows up outside of work too whether I’m diving into new research or simply figuring out how a system works for the sake of it. Curiosity and continuous learning go hand in hand for me: ask deeper questions, and then be willing to experiment and iterate until you reach clarity.

Collaborative Leadership — I’ve learned that collaboration works best when different perspectives are aligned into a clear strategy. On complex projects, I’ve seen people zero in on risks, some chase opportunities, and others focus on execution details. Left unchecked, that diversity can scatter progress. What I’ve found most effective is creating clarity on the direction forward, then applying a principle I value deeply: disagree and commit. Not every voice needs to prevail in the moment, but once we’ve chosen a path, the team unites behind it. That combination of diverse perspectives, trust, and unified execution has consistently led to stronger results.

Resilience and Adaptability — Resilience is something I’ve had to learn the hard way. I still remember leading a project where the solution we poured months into simply didn’t work once it hit reality. It was humbling, but I was fortunate to have leaders who reminded me that failure isn’t the end, it’s part of the process. I learned to time-box alternatives, gather feedback quickly, and bring a method to the madness so setbacks didn’t spiral. That experience changed how I see challenges: they’re often the beginning of breakthroughs if you approach them with structure and adaptability. In many ways, it’s what taught me the value of failing fast — learning quickly, adjusting, and keeping momentum alive.

Do you have any mentors or experiences that have particularly influenced you?

I’ve been fortunate to learn from both personal and professional mentors. From my mother, I absorbed the value of discipline and consistency — that success often comes not from chasing something new, but from approaching the basics with care and doing them well every day.

From leaders I’ve worked with, I learned that even the most complex challenges should start with clarity: who the solution is for, why it matters, and the simplest way to test if it works. They showed me that the first version doesn’t need to be perfect, what matters is proving impact before putting in deeper investment. That mindset of keeping things simple, focused, and purposeful has shaped how I approach big problems.

Together, those influences shaped not just how I think about challenges, but how I act on them. And it’s something I try to pay forward by mentoring early-career professionals, students, and peers helping them navigate uncertainty with the same balance of guidance and trust that I was given.

What have been the most effective tactics your organization has used to accelerate product growth?

One of the most effective approaches I’ve seen in large-scale transformations is keeping customers at the center. In the Discover–Capital One integration, that means looking at where the two organizations bring different strengths and making sure we preserve the best of both with customer experience as the anchor.

It’s easy in M&A to focus on systems consolidation, but what really matters is how these decisions shape the way tens of millions of people experience their finances every day. That’s why we don’t just jump straight to full rollouts, everything starts with smaller changes, backed by a clear plan to prioritize what matters most. Some things need to move fast because they touch customers directly, while others can happen behind the scenes in phases. That balance is critical: it allows us to learn through pilots and experimentation, but also gives leadership confidence that we’re sequencing the work in a way that minimizes disruption and maximizes impact.

That discipline turns integration from a technical exercise into something much bigger: an opportunity to create a clearer, fairer, and more supportive experience at a scale few industries ever reach.

What do you see as the biggest challenge with respect to scaling a product-led business?

I think one of the hardest parts of scaling a product-led business is that culture doesn’t automatically scale with headcount. In a small team, everyone feels the vision and decisions are naturally aligned. But as you grow, silos form, different groups start chasing their own priorities, and teams can lose visibility into what’s happening upstream or downstream. That makes it harder to keep everyone aligned on the same definition of success.

That’s where another challenge shows up: separating signal from noise. At scale, companies may run thousands of tests a year across different metrics and that’s valuable. The challenge is when those local wins don’t connect back to a broader strategy. For example, one team might optimize for engagement by adding more notifications, while another team is focused on reducing customer friction. Both goals are valid on their own, but without alignment they can work against each other and confuse the customer. What looks like momentum can actually be fragmentation unless the culture anchors everything to customer impact. In my experience, the real work of scaling isn’t just building more, it’s building alignment so experimentation at every level ladders up to a clearer, more supportive customer experience.

What, in your view, is a good litmus test to screen for a skilled and effective growth manager?

In my experience, the most effective growth leaders show two things.

The first signal I look for is whether they can truly bring people together across product, engineering, design, data, and the business. Growth doesn’t happen in a vacuum; it requires understanding the domain, spending time with business teams, and listening closely to customer pain points. I’ve found that the hardest part usually isn’t building the product — it’s making sure people across teams see the value, adopt it, and feel invested enough to give feedback that makes it better. The best growth managers lean into those people skills, because alignment and adoption are what truly unlock scale.

The second quality is analytical depth with strategic breadth. That means being able to dive deep into the details of experiments and metrics, but then zoom back out to connect those details to the bigger strategy. The strongest growth managers understand the complexity of decisions, weigh the trade-offs, and make calls that hold up not just for the next quarter but for the long-term trajectory of the product.

Can you describe a product growth tactic you or your team has used that was more effective than you anticipated? What was the goal, how did you execute, and what was the outcome?

One thing that worked better than I expected was adding really simple feedback loops. Instead of doing big research projects that take weeks, we started sending out short surveys to specific groups of customers just to check what was working and where the friction was. Honestly, I thought people might ignore them, but the response was much stronger than I expected.

I remember one survey where customers kept pointing out how confusing a small step in the digital flow was something we had all gotten used to internally and never really noticed. We fixed it quickly, and the adoption numbers jumped right after. The best part was that customers wrote back saying they appreciated being asked and seeing their input acted on.

For me, it was a reminder that growth doesn’t always come from big launches, sometimes just listening and making small, visible changes builds more trust and momentum than you’d expect.

Thank you for all of that. Here is the main question of our interview. Based on your experience, what are your “5 Best Ways to Drive Product Growth”? If you can, please share a story or an example for each.

Growth isn’t about chasing every opportunity, it’s about knowing which levers to pull and when. From my experience, five levers have consistently made the difference.

1 . Lead with experimentation, not assumptions — Growth comes from testing, not guessing. I’ve seen “obvious” ideas underperform and small tweaks outperform big bets. Running disciplined experiments shifts decisions away from HiPPOs (highest paid person’s opinions) and builds credibility because growth is grounded in evidence, not opinion. Sometimes it’s the smallest test like tweaking messaging or reducing a single step in a flow that outperforms big, resource-heavy launches.

2 . Simplify to Amplify — Customers don’t always need more features, what they value most is a smoother journey with fewer steps. In one project, stripping a digital flow down to the essentials made it faster and easier for customers to complete, which drove adoption more effectively than adding new options ever could. Growth often comes from removing friction, not piling on complexity. Simplicity is what makes products feel intuitive, and intuitive products scale without needing heavy explanation or training.

3 . Segment to stay relevant and cross-sell naturally — One-size-fits-all rarely drives long-term growth. By segmenting customers based on their needs and life stages, you can surface the right product at the right time. When done well, cross-sell feels like personalization, because customers see clear value in what’s being offered. Segmentation also keeps teams focused, ensuring resources are directed where they make the biggest impact.

4 . The right metrics, not more metrics — Growth isn’t about tracking every possible number, it’s about choosing the few signals that really matter and sticking to them. I’ve found frameworks like HEART (Happiness, Engagement, Adoption, Retention, Task success) or AARRR (Acquisition, Activation, Retention, Referral, Revenue) useful starting points, but the real value comes from aligning teams on a simple set of metrics: one that measures change, and another that acts as a guardrail. For example, you might track activation as the signal of improvement, while keeping retention as the guardrail to make sure short-term gains don’t erode long-term trust. Fewer metrics, chosen well, create clarity and confidence both for teams and for customers.

5 . Actions speak louder than features — The real test of product growth isn’t how many features you ship but whether customers behave differently because of them. The most useful question I’ve learned to ask is: what will this change for the customer’s day-to-day? Sometimes it’s about designing the product so that using it once makes people more likely to use it again like a budgeting tool that sends a simple weekly progress update prompting customers to log back in and adjust their plan. When products are built to reinforce positive behaviors, adoption happens naturally and the value compounds over time.

What I’ve found is that these principles not only drive growth in the moment but also create the foundation for products to keep scaling long after the first wins.

What is the number one mistake you see product marketers make that may actually be hurting their growth outcomes?

One mistake I see often is going too broad too quickly. Early in my career, I worked on a product where the team kept adding features to attract different segments. It looked good on a roadmap, but in practice no customer group felt we were solving their problem deeply. Adoption lagged, and even explaining the product became harder than it should have been.

Things changed when we narrowed the focus to one segment with one clear pain point. At first it felt risky, almost like we were walking away from opportunity, but that clarity made the product click. Customers started using it more consistently, recommending it to others, and only then did it make sense to expand.

That experience stuck with me. The fastest way to scale isn’t trying to be everything to everyone; it’s solving one problem so well that people can’t ignore you. As Steve Jobs once said, “Focus is about saying no.” That discipline doesn’t just sharpen priorities for customers, it also gives teams a clear story to rally around and the credibility to expand once you’ve proven you can win in one space.

It has been said that our mistakes can sometimes be our greatest teachers. Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?

When I was starting out on product teams, I relied too much on jargon and visuals to make my case. In one meeting, I brought in slide after slide packed with charts, acronyms, and detailed breakdowns. I thought I was showing how thorough I could be, but by the end one of the senior leaders laughed and said, “That’s the most wonderful presentation I’ve seen in a while but can you just tell us what we’re supposed to do with it?” The room cracked up, and I did too, though at the time it felt pretty embarrassing.

What I took away from that moment was simple: expertise only matters if people can understand and apply it. Since then, I’ve focused a lot more on clarity and storytelling, and on meeting people where they are instead of hiding behind complexity. It’s made me not just a better communicator, but a better collaborator.

We are very blessed that very prominent leaders read this column. Is there a person in the world or in the US with whom you would love to have a private breakfast or lunch, and why? He or she might just see this if we tag them :-)

I’d pick Ronny Kohavi. He changed the way product teams across the industry think about experimentation, and his work has been a reference point many of us have relied on. His leadership at companies like Microsoft, Airbnb shows the impact of doing this at scale. Sitting down with him would be a chance to talk about how to build a culture where evidence, leadership, and product strategy are aligned because that balance between rigor and vision is what ultimately makes experimentation a driver of lasting growth.

Thank you so much for this. This was very inspirational, and we wish you only continued success!