By Ramya Nirmal
Ramya Nirmal, CEO
Over the years, I’ve seen countless startups pour months of effort into building products that look great on paper, but fail to deliver value where it matters most. Having spent years hands-on in B2B product development, I’ve come to believe that success doesn’t start with code. It starts with clarity. Reducing product development risk
isn’t just about cutting costs—it’s about validating every assumption before you scale.
When we built our own products like RubiCube, what truly worked for us wasn’t just a process; it was a mindset. It was about learning faster than we built, creating value before scaling, and constantly asking: are we solving a real problem, or just building features?
These are the lean product management strategies I live by. An applied approach with MVP development services
that helps B2B startups accelerate time-to-market, reduce risk, and stay anchored in value.
(i) Deconstruct the “Buyer” vs. “User” Problem
One of the biggest lessons I’ve learned is that the buyer and the user are rarely the same person, and they care about very different things.
For a buyer, it’s about ROI, scalability, and long-term value. They ask: What’s my return on investment? Will this scale as I grow? Is the cost justified over time?
But for a user, it’s about experience. They think: Is this easy to use? How steep is the learning curve? Can I get my work done quickly without frustration?
I’ve seen cases where the buyer happily signs the contract; but if the end-user doesn’t actually use the application, the renewal never happens. So, I started thinking about product design from a place of empathy: how do we ensure the user wants to use this product every single day?
At CI Global, we visualize both journeys separately: the decision-maker’s and the end-user’s. Then we bring them together through iterative design. Because when the user experiences real, consistent value, the buyer automatically stays with you.
(ii) Prioritize the Single “Aha!” Moment
In my experience, every successful product can be defined by one “Aha!” moment: the instant where the user realizes this product just made my life easier.
Many teams fall into the trap of thinking “more features = more value.” But that’s not how it works. The question should always be: what is the one problem we’re solving?
Take inventory management, for instance. Businesses often rely on gut-driven decisions: downloading reports, manually reviewing stock, and guessing reorder points. We asked ourselves: can we make this process scientific and predictive?
So, in RubiCube, for instance, we used AI and historical sales data to predict inventory requirements. Instead of waiting for stock-outs, the system could automatically place purchase orders when stock dipped below a threshold. That’s the true “Aha!” moment. It transforms reactive decision-making into proactive intelligence.
Even in manufacturing, say, during the Diwali season in the textile industry, demand forecasting becomes crucial. You can’t afford to overproduce or underproduce. Our solution allows manufacturers to plan raw materials, labour, and production based on data-driven insights rather than assumptions. It’s not about adding more screens or dashboards. It’s about solving real, long-standing problems with precision.
(iii) Manual MVP to Simulate Product Value
Build small, validating early on. Before we even start coding, we create a process MVP. A simulation that tests whether our assumptions hold up in the real world.
Sometimes, it’s as simple as building a wireframe in a spreadsheet to test calculations. Other times, it’s running a mini proof-of-concept with customers using dummy data. The goal is to simulate the value, not the feature.
When we were developing inventory automation, we didn’t jump straight into development. We first replicated the reordering logic on spreadsheets to check if the prediction model made sense. This helped us fine-tune the parameters and validate the approach before investing months of engineering effort.
It’s like practising before the real exam: by building that prototype or “mini POC,” you quickly see if your value hypothesis holds. Then, when you go into full development, you’re building with confidence, not assumptions.
(iv) Instrument for Measurable Learning (Not Vanity)
Not all metrics matter. What truly counts is learning, not vanity.
It’s easy to get distracted by numbers (downloads, sign-ups, demo requests) but those don’t tell you if users actually find value. I’ve learned to look deeper:
- Are users consistently active after onboarding?
- Are they repeating the same actions (a sign of habit formation)?
- What features do they return to most often? (form versus function)
For me, success means seeing sustained usage. You can have 1,000 users who sign up, but if only 200 use your product every week, that’s your real base. Learning from that engagement is what helps us iterate meaningfully.
In every MVP we build, we set up instrument tracking not to impress ourselves with big numbers, but to understand what’s really working. If a feature isn’t being used, it’s a signal to simplify, refocus, or pivot.
(v) Design for Trust and Security (B2B Imperative)
Finally, and most importantly, trust. In B2B, it’s not optional; it’s foundational.
From day one, every product we build goes through rigorous penetration testing, vulnerability assessments, and compliance validation. This isn’t just about ISO certifications; it’s about earning our customer’s confidence.
We ensure data encryption, transparent data handling, and compliance with standards like GDPR. Our philosophy is clear: the customer owns the data, we only own the application. That clarity builds long-term relationships.
Even at the MVP stage, security must be part of design, not an afterthought. Because no matter how innovative your product is, if customers can’t trust it, it won’t scale.
The Bigger Picture
Looking back, my journey from zero to MVP has been less about coding and more about learning. The lean playbook isn’t about moving fast and breaking things. It’s about moving smart and building trust.
As we continue to innovate with partners like IBM, where we’re now implementing AI-driven conversational assistants through WatsonX Agent Chatbot, these principles remain constant. Whether it’s inventory automation, predictive manufacturing, or AI chat experiences, the foundation is the same: empathy, measurable value, and trust.
The future I envision for B2B startups is one where MVPs are not “minimum” in capability, but maximum in learning and purpose. That’s how we turn ideas into products that endure.
Our B2B product validation consulting approach helps startups de-risk innovation and build products customers actually use. Looking for the right startup product development process to bring your idea to life? Let’s talk.
