By Ming-Cheng Ho — 19 Feb 2025

Navigating Incremental vs. Existing Markets in Generative AI: Balancing Product Vision and Practicality

Generative AI has opened new frontiers for indie hackers and startup leaders looking to build transformative products. Whether you are venturing into an emerging, incremental market or refining offerings in an established sector, you need a clear understanding of what you’re building, why it matters, and how it fits user needs. In this post, I’ll share strategic insights from my recent discussions with a fellow product manager. We debated the differences between new “emo robot” experiences versus AI-driven content creation tools, and we examined how indie hackers should balance product vision with commercial viability.

1. Incremental vs. Existing Markets: Finding Your Strategic Fit

Incremental Markets :
An incremental or “blue ocean” market involves creating entirely new user behaviors and experiences. An example is an “emo robot” that fosters emotional interaction with users. Because few existing reference points or incumbent products exist, you have a great deal of freedom to experiment with novel features—like multiple characters, creative dialogue modes, or AI-driven emotional connections. This creative vacuum can be a major advantage: it is easier to capture attention in a fresh space, and users’ curiosity for the unfamiliar can drive early traction.

However, success in an incremental market depends on building a truly core experience that resonates emotionally and practically. Retention and monetization are challenging when your product requires new behaviors from users. If your “emo robot” product feels too abstract, users may engage only for novelty without developing lasting habits. You must craft experiences that provide genuine emotional value—like companionship, humor, or problem-solving—to keep people coming back.

Existing Markets :
In contrast, an existing or “red ocean” market usually has established user expectations and well-known competitors. AI-powered content creation tools, such as automated video or audio editors, belong here. Because creators already have legacy tools and workflows, any new solution must demonstrate tangible advantages—faster production, better quality, innovative features—while lowering switching costs. Your prospective users won’t ditch their current tools unless they see clear benefits and minimal disruption.

This environment emphasizes efficiency gains, measurable outputs, and ease of adoption. AI tools that transform short-form videos for social media or automatically generate podcast soundbites can win if they provide creators with a leap forward in productivity. But because you are fighting for attention in a crowded market, you need compelling proof points (e.g., “30% faster editing,” “20% increase in video engagement”) to motivate users to pay for your solution and keep using it over time.

2. Shaping Product Sense Based on Your Target Market

Just as the markets differ, so does your “product sense”—the lens through which you craft the core offering:

For Incremental Products: Focus on novelty, emotional pull, and user delight. Because your product may spark entirely new habits, you must build an inviting on-ramp. Provide small yet magical moments that intrigue users and reward them for continued engagement. Think beyond mere functionality: how can your AI bring empathy, creativity, or companionship into a user’s daily routine?
For Existing Products: Highlight efficiency, convenience, and ROI. Lower the friction users face when switching from incumbents. Show how your features are distinct enough to justify a transition. Offer data-backed improvements—faster production times, better analytics, or integration with existing workflows—that assure creators this new tool is a worthy replacement.

In both cases, retention hinges on delivering consistent value. An “emo robot” might use playful conversations or mood-tracking features to keep users returning, while a content creation tool might show analytics proving that AI-edited videos earn higher engagement rates.

3. The Indie Hacker’s Dilemma: Product vs. Personal Project

As an indie hacker, it’s easy to conflate building a product with creating a personal “work of art”. You have a vision that energizes you—perhaps an elegant AI-driven idea that pushes boundaries. But to transform a creative idea into a real product, you must validate the commercial potential.

A “Creative Idea” exists to express your creativity or vision—its primary goal is personal fulfillment and artistry. It’s a wonderful pursuit but may not inherently attract or retain paying users.

A “Product” must solve a genuine problem or generate tangible value for others. It needn’t sacrifice innovation or craftsmanship, but it must be anchored in market realities. That means talking to prospective customers early, gauging interest, and iterating based on feedback. The ultimate test is whether people are willing to pay (with money or attention) and keep using your solution.

Striking a Balance: If you’re driven by a bold idea, borrow a page from “Saleskit Driven” thinking. Create prototypes, landing pages, or interactive demos that capture your concept—then test them with real users. Use that feedback to refine, not to water down your vision, but to ensure your final product resonates in the real world.

4. Retention in SaaS: Balancing User Value and Business Needs

Retention is the lifeblood of any SaaS solution, and generative AI products are no exception. Even the most compelling AI service will flounder if users don’t stick around—or if churn rates exceed the pace of new customer acquisition. The retention equation becomes more nuanced depending on whether you’re competing in an existing market or creating an experience for an incremental market. Each setting poses unique retention risks and demands different mitigation strategies.

Retention Risks in Existing Markets

Competitive Pressure and Commodity Features
In crowded, established markets, your product may deliver a feature set similar to competitors—editing templates, collaboration tools, AI automation, etc. If users can find similar functionality elsewhere with fewer friction points, you’re at risk of losing them. Retention therefore hinges on creating clear, compelling reasons for customers to stay, such as robust analytics, personalized support, or seamless integrations that genuinely outperform current alternatives.
Switching Cost vs. Switching Effort
Many users have deep investments in legacy tools—custom plugins, saved projects, or muscle memory from years of usage. A new SaaS must lower the effort it takes to switch, while also providing enough tangible benefits to make switching worthwhile. If your product fails to continuously prove its value—e.g., time saved, improved output quality, or new monetization avenues—customers may revert to familiar tools.
Price-Sensitive Churn
In markets saturated with competing services, pricing often becomes a differentiator. Without a clear unique value proposition (UVP), users can be swayed by a competitor’s discount or free tier. If you can’t prove the ROI of your AI solution, you risk losing paying customers to less expensive alternatives.

Retention Risks in Incremental (New) Markets

Habit Formation and Novelty Fade
When building an entirely new product category—like an “emo robot” that offers emotional companionship—your first challenge is convincing users to adopt an unfamiliar behavior in the first place. Even if you succeed initially, the novelty can wear off if there isn’t lasting, meaningful engagement. You risk high early drop-off if the core experience doesn’t seamlessly integrate into users’ lives.
Undefined Expectations and Value Metrics
In a new market, your users may not have established expectations or benchmarks to measure the product’s value. This can be both liberating and risky. While you have more freedom to define your own metrics, if you fail to educate users about the product’s benefits—or if users struggle to perceive ongoing value—retention will suffer. You need to make the intangible tangible; for instance, measure mood improvement, skill growth, or time saved through the new behavior.
Scaling Too Early
Rapid expansion in an untested market can spell disaster if you haven’t nailed down the core user experience. Onboarding thousands of new users into a novel concept that still needs iterative refinement may cause poor user satisfaction, eventually driving churn. Controlled rollouts, beta programs, and user feedback loops are essential to stabilize retention before you scale.

Balancing User Value and Business Needs

Across both existing and incremental markets, retention demands a careful blend of delivering continued value and aligning that value with business objectives:

Ongoing Feature Evolution: For existing markets, push frequent performance enhancements or advanced features so you’re not outpaced by competitors. In new markets, refine your core experience based on early usage metrics to maintain excitement and relevance.
Personalized Engagement: Offer tailored support or specialized workflows. In existing markets, this might look like custom integrations with a customer’s tech stack. In new markets, it can involve gradually revealing new capabilities as users become comfortable, ensuring they feel guided and “heard.”
Transparent Metrics & Feedback Loops: Show users how their experience or outcomes improve over time. Whether it’s a “time saved” dashboard for AI video editing or a “mood-tracking” score for an emo robot, visible progress fosters trust and encourages ongoing use.
Sustainable Monetization: Your pricing model must reflect the tangible impact you create. Existing markets typically use tiered subscriptions or usage-based pricing aligned with industry norms. New markets might need more flexible or even experimental pricing—like pilot programs or community-driven membership fees—until value is fully established.

Overall, retention is about staying relevant, solving genuine problems (or consistently delivering emotional connection in the case of a novel product), and evolving with your users. By understanding the distinct retention risks in established vs. incremental markets—and by intentionally balancing user value with your business goals—you’ll build a SaaS offering that keeps customers engaged for the long haul.

5. What Makes a Good Generative AI Product Today?

As we look at the fast-evolving generative AI landscape, a few strategic assumptions can guide indie hackers toward building something with lasting impact:

Domain-Specific Solutions: Generic AI models are becoming widespread. Products that excel in a niche—legal documents, healthcare advice, or specialized industry media—have higher chances of standing out and delivering real value.
Human-in-the-Loop Enhancements: Fully automated outputs are often not enough. Creators, editors, and professionals want control, customization, and interpretability. Offering intuitive ways to refine AI outputs will likely differentiate you from purely “one-click” solutions.
Seamless Integrations: Existing workflows rarely vanish overnight. Building APIs or plugins for popular platforms (e.g., Adobe Premiere, Final Cut Pro, Notion) can lower switching costs and increase adoption among professionals.
Emotional, Conversational Interfaces: Products that forge an emotional bond—like the “emo robot” concept—could thrive if they remain practical and engaging. Being “emotionally aware” or “personally tailored” can drive a unique value proposition.
Scalable Personalization: Many generative AI tools are so broad that users feel lost. The best new solutions understand each user’s style, context, or environment, delivering outputs that feel tailor-made without requiring extensive manual setup.

Final Thoughts

Choosing between an incremental market—where you create an entirely new user behavior—and an existing market—where you optimize or redefine established workflows—depends on your strengths, passions, and resources. As an indie hacker, you carry both the artistic spark of a creator and the practical demands of a business builder. Aim to synthesize these two mindsets: build with imagination, but ground every experiment in real-world feedback and a solid path to monetization.

Remember the product value formula:

Value=(New Experience) - (Old Experience) - (Switching Cost)

For new experiences, your main mission is proving that they are truly better (or more unique) than any existing approach. For established markets, your biggest hurdle is reducing friction and beating well-known benchmarks. Whichever path you choose, keep your sights on retention. Deliver consistent value, and customers will come for your creativity but stay for the results.

Embrace the challenge: build with vision, refine with data, and keep your end users’ needs at the heart of every decision. That’s how you turn your work of art into a viable product—and how you, as an indie hacker, can create something both inspirational and profitable in today’s fast-moving AI landscape.