What Comes After Paywall Optimization? Lessons from Flo's Product Team

Every successful subscription app eventually runs into the same challenge.

The obvious opportunities become smaller. Pricing has already been optimized, onboarding has gone through dozens of iterations, and the paywall has been tested from every angle. Growth doesn't stop, but it becomes harder to find.

That's when the conversation shifts from "How do we convert more users?" to "How do we create more value?"

In the latest episode of Reteno Podcast, Oleg Lesov sat down with Olha Kashpur, Senior Product Manager at Flo, to talk about exactly that transition. As part of Flo's Subscription Value team, Olha works on identifying new ways to expand what the product offers by solving adjacent user problems that strengthen the subscription over time.

The conversation covered everything from product expansion and experimentation to AI, behavioral psychology, and why some of the best product ideas look surprisingly simple in hindsight. More importantly, it showed how mature product teams think differently about growth once the obvious wins are gone.

Looking beyond the paywall

When Olha joined Flo, she expected to work on what most subscription businesses associate with monetization: onboarding flows, pricing strategies, paywalls, and conversion optimization.

Instead, she joined a team with a much broader mission.

Subscription Value isn't focused on selling the existing product more effectively. Its purpose is to understand what additional value users might be willing to pay for, even if that value doesn't exist yet.

As Olha explains, her job starts long before pricing enters the conversation.

That mindset fundamentally changes how product growth is approached. Instead of asking how to monetize existing features, the team begins by exploring unmet needs and adjacent use cases. Pricing becomes the final step, not the starting point.

For mature subscription businesses, this shift is increasingly important. Once acquisition and activation reach a certain level of maturity, sustainable growth depends less on optimizing existing journeys and more on expanding the reasons users stay subscribed.

The simplest ideas are often the hardest to see

One of Olha's favorite examples is Flo for Partners, a product extension designed to help partners better understand women's health.

On paper, the idea feels almost obvious. If Flo helps women better understand their bodies, why not help their partners understand them too?

Yet that's exactly why it stands out.

That's an important reminder for product teams. Great expansion opportunities rarely come from trying to invent something completely new. More often, they emerge from looking at existing customer problems from a different perspective.

Rather than asking, "What feature should we build next?" successful teams ask, "Whose problem are we not solving yet?"

Sometimes the answer opens an entirely new audience.

Growth starts with hypotheses, not development

Expanding a product is exciting. Building the wrong thing is expensive. That's why experimentation plays such a central role in Olha's work.

Before investing engineering resources, the team validates whether users actually care about a potential solution. In some cases, they use lightweight concepts or fake-door experiments. In others, they test messaging, positioning, or willingness to pay before a product even exists.

The objective isn't to prove ideas right. It's to reduce uncertainty.

That distinction came up several times throughout the conversation. Experiments aren't treated as isolated growth hacks or A/B tests—they're part of a broader decision-making process. Every hypothesis is supported by research, qualitative interviews, market signals, and data that help the team understand not only what users do, but why they do it.

Not every initiative succeeds.

Olha openly shared that some expansion ideas—such as experiments around mental health services or supplements—didn't generate the expected results. But those outcomes weren't viewed as failures. They became evidence that helped the team better understand user expectations, market timing, and product fit.

For subscription products, that's a valuable lesson. Product expansion isn't about constantly shipping new features. It's about building confidence before committing to them.

Analytics explain behavior. Users explain motivation.

One theme that surfaced repeatedly during the discussion was the relationship between quantitative and qualitative research.

Analytics can show where users drop off, which offers convert better, or how pricing affects subscription rates. But numbers rarely explain the motivation behind those behaviors.

That's why user research remains a core part of product discovery at Flo.

Understanding what users are trying to accomplish, what frustrates them, and how they perceive value often reveals opportunities that wouldn't be visible in dashboards alone. It also prevents teams from optimizing metrics that don't necessarily improve the customer experience.

For Olha, product management isn't about choosing between intuition and data. It's about continuously combining evidence from multiple sources before making decisions.

That approach becomes increasingly valuable as products mature. The larger the customer base, the easier it is to optimize for averages—and the easier it is to overlook the nuances that create meaningful competitive advantages.

AI won't replace product managers. It will remove the work around product management.

It's difficult to have a conversation about product today without talking about AI. Yet one of the most interesting parts of the discussion was how pragmatic Olha's perspective was.

Rather than treating AI as a product strategy, she described it as a tool that helps product teams move faster and make better-informed decisions.

Research that once took days can now be completed in hours. Competitive analysis, idea generation, documentation, and early prototyping have become significantly more efficient. AI doesn't eliminate the need for product thinking—it gives teams more time to focus on it.

That distinction matters because many companies are still approaching AI from the wrong angle. Instead of asking which roles AI can replace, mature product organizations are asking a different question: Which bottlenecks can AI remove?

For product managers, the biggest gains often come from eliminating repetitive operational work. That creates more room for customer research, strategic thinking, and experimentation—the activities that ultimately shape better products.

As AI capabilities continue to evolve, this balance will become even more important. Teams that simply automate existing processes may become more efficient, but teams that use AI to improve how they discover, validate, and prioritize opportunities will build a much stronger competitive advantage.

Experimentation becomes more valuable as products mature

Early-stage startups often experiment because they don't know what works.

Mature products experiment because the market keeps changing.

That distinction became clear throughout the conversation. At Flo's scale, experimentation isn't limited to optimizing onboarding screens or testing different subscription offers. It's part of how the company evaluates entirely new directions for the product.

Every hypothesis starts with a question. Is this a problem users actually want solved? Is it valuable enough to justify development? Does it strengthen the subscription experience or simply add another feature?

The answers rarely come from one source. Product teams combine market research, qualitative interviews, behavioral data, competitive analysis, and small validation experiments before deciding where to invest.

This approach also changes how unsuccessful experiments are perceived. Instead of treating them as wasted effort, they become an important source of learning.

Several of the initiatives Olha discussed didn't deliver the expected results. Some ideas generated little interest, while others proved difficult to position or simply didn't match what users were looking for at that particular moment. But each experiment narrowed the team's uncertainty and improved future decision-making.

That's one of the biggest advantages of mature experimentation frameworks. Their goal isn't to maximize the number of successful ideas. It's to minimize the cost of discovering which ideas deserve to succeed.

Subscription businesses grow when they solve bigger problems

Throughout the conversation, one idea kept resurfacing in different forms.

The strongest subscription products don't continue growing because they constantly improve their paywalls. They grow because they continuously expand the value users receive after subscribing.

That often means moving beyond the original use case.

Sometimes it's an entirely new product. Sometimes it's an adjacent service. Sometimes it's a better understanding of a customer segment that has been there all along but never fully addressed.

Flo for Partners is one example. New health services are another. AI-powered capabilities may become the next.

What connects these initiatives isn't technology or monetization. It's a deeper understanding of user problems.

That perspective also changes how teams think about retention. Instead of viewing retention as a CRM metric or a lifecycle responsibility, it becomes the natural outcome of building a product that continues solving meaningful problems over time.

For app businesses, this is becoming increasingly relevant. Acquisition is more expensive than ever, competition continues to grow, and users are becoming more selective about recurring subscriptions. In that environment, long-term growth depends less on finding new ways to persuade people to subscribe and more on giving them compelling reasons to remain subscribed.

Building products that evolve with their users

One of the biggest takeaways from this conversation is that product management becomes more strategic as products mature.

Early growth often comes from executing well—launching features, optimizing funnels, and improving conversion. Later growth depends on asking better questions.

What problems haven't we solved yet?

Which customer segments are underserved?

What assumptions should we challenge?

How can AI help us learn faster rather than simply work faster?

These questions don't produce immediate answers, but they create the conditions for sustainable growth.

Listening to Olha describe Flo's approach, it becomes clear that successful subscription businesses aren't built around individual experiments or isolated features. They're built around continuous discovery. Product expansion, customer research, experimentation, AI, and pricing all become parts of the same system, helping teams understand users more deeply and make better decisions over time.

For product managers, marketers, and growth teams, that's perhaps the most valuable lesson from the conversation.

The next stage of growth won't come from squeezing another percentage point out of a paywall.

It will come from discovering new ways to create value for the people who have already chosen your product.