Fast is out. Relevance is in. Before even writing a line of code, entrepreneurs need to have a level of assurance that a market even exists for what they envision. The facts are brutally honest here: 42% of all ventures still fail because there is simply no market need for what they are creating.
In this article, I will break down a modern and data-driven approach to pre-overhead market evaluation in technology. Utilising case studies and successful approaches in 2023 for a startup, this written piece will examine market size and how to estimate demand factors. I will include frameworks and proposed key metrics for you to implement concrete approaches to engaging with first adopters and prototyping without coding in no-code development. Examples will span from testing in Perplexity AI to OpenAI changes in market evaluation for enterprises.
Founders & MarTech Strategists, this is a roadmap that will help you translate your gut instincts into insights and eventually into evidence even before your first engineering sprint.
Market sizing and segmentation
Niche validation begins with a quantitative assessment of the market opportunity. In a broad sense, TAM (Total Addressable Market) is the total revenue if you captured 100% of the market. SAM (Substantial Available Market) is the share of TAM that is realistically achievable given the scale and geography of your product. And, SOM (Serviceable Obtainable Market) is the realistic share you can capture in the short term (usually within 6-18 months) given your resources. For instance, in 2009 Uber defined its TAM as the entire taxi/limousine industry in its launch city but initially targeted the much smaller SAM (luxury private transportation services). So the company proved its appeal locally before expanding its SAM and capturing a larger TAM. Similarly, Airbnb’s TAM was focused on the global lodging market, while its initial SAM was the short-term rental niche in a few cities.
To rigorously estimate market size, both top-down and bottom-up methods are used. The top-down approach begins with industry reports and extensive market statistics; the bottom-up method builds estimates based on real data (e.g., target segment size, pricing, expected conversion). The bottom-up method is generally more reliable because it “combines multiple data sources” and relies on specific assumptions. For example, you might estimate SOM as follows: “If SAM is $200 million, and our sales funnel can attract 2,000 customers at $10,000 each this year, then SOM ≈ $20 million (10% of SAM).” It is crucial to document all assumptions with data (reports, surveys, pilot project results).
B2B vs. B2C differences: B2B markets often have narrower segments (by industry, company size, and geography) but higher revenue per customer. B2C markets are broad but require mass appeal or aggregation of many small purchases. In either case, define your niche clearly. For B2B, segment by vertical and firmographics; for B2C, segment by consumer demographics and psychographics. Then compute SAM by focusing on a specific use case or customer subset you can reach first. In practice, investors expect to see startup founders identify a realistic SOM – what fraction of the initial segment they can win in 1-2 years. For instance, a B2B software startup might target the IT departments of 100,000 companies (TAM), then focus initially on 10,000 companies in North America (SAM), and plan to onboard 200 of them (SOM) in the first year, with revenue projections to match. Always cite external market data or pilot results for each step.
Actionable recommendations: Use industry reports, public documents, government data, and competitor metrics to assess TAM/SAM. Perform bottom-up calculations based on realistic assumptions about user growth and pricing. Avoid vague assumptions like “all my clients.” Prepare a conservative TAM/SAM/SOM slide to clarify scope and growth plan.
Demand test for signals and interest
When you have a hypothesis regarding a niche, validate demand thrоugh no-code and/or low-cost tests. Examples of this are search volume, online chatter, landing page opt-ins, pre-оrders, and a small advertisement run. To illustrate, you can simply check how much search volume there is for your space on Google Trends. In addition, you can browse niche communities like Reddit/Quora and find out if users are ranting about your respective space. If not enough chatter is occurring, that is your first warning flag.
A common tactic is a ‘fake door’ landing page: create a simple landing page or website with a description of your product and a single call to action (e.g., ‘Sign up for the waiting list’ or ‘Get early access’). Tools such as Carrd, Unbounce, or Webflow allow you to do this in a few hours. Run small paid campaigns (Facebook, Google Ads, IG, TG, LinkedIn) or drive organic traffic to this page. Then measure the conversion rate: if only a small percentage (<5–10%) of interested visitors sign up, this indicates weak demand. Conversely, a high conversion or registration rate indicates that people are interested in the concept. (A rule of thumb in the industry is that a registration rate of more than 10% is promising for a well-targeted niche.)
In B2B niches, you can use lead magnets and/or gated content (white papers and webinars targeted to your crowd). The number of firms that come to download it and/or demand more information can provide some feedback. Even a concept video demo on a site like LinkedIn’s Product Hunt community and measuring engagement metrics can provide valuable feedback. “Pre-orders” and/or pilots are very compelling. If you can secure hard commitments and even secure payments and build while others sit out, you’ve demonstrated you are willing to spend. “Demand” can also be demonstrated through “inbound interest”, emails and/or direct messages or requests from people not contacted in a sales pitch regarding your product. These can provide a more compelling validation.
(Note: A successful crowdfunding or pre-order campaign can serve as proof of concept, but ensure to use 2023-specific examples or data if citing campaigns.)
Actionable Recommendations: Gather information like search volume and social buzz to estimate trends. Develop a quick landing page or explainer video. Launch a small ad spend (budget ~$100-$500) to send traffic. Monitor impressions versus clicks versus opt-ins. Perform a round of paid testing to validate interest in your product even before building. One can look to value propositions and pricing points through A/B tests while testing interest.
Customer discovery and early-adopter interviews
Quantitative feedback has to be supplemented with user-level intuition. Just talk to your users directly (lean startup development strategy). The procedure includes doing 10 to 30 in-depth user interviews as a prelude to launching a startup. In B2B development, startup owners often end up conducting meetings with a number of people. In fact, according to a study conducted by Lenny Rachitsky, an avg. of 30 meetings are required to convince startup owners that their idea is ready. In a B2B development setup, this count can reach as many as 75. In a B2C consumer-based product development setup, this can range between 10 to 15 meetings.
Use all these interviews for identifying and understanding problems that are associated with your clients. The type of questions posed in this step are open-ended and include “Tell me about a situation you recently had to deal with [a problem],” “How are you currently addressing this concern,” and “What is not liked about present choices?”
The trick here is to identify people talking about emotive language that suggests a “pain point” when describing a frustrating experience related to switching to a “better” choice. Furthermore, one of the concerns is when interviewees have problems articulating a specific problem and are evasive when stating how they spend time/money on it.
- B2B interviews: Use your connections in your LinkedIn network and/or industry for direct contact with actual decision-makers. Start with a well-defined target customer persona – for example, “SBM IT manager in a 100-500 person company” and arrange a well-structured call. Be transparent that you are doing some market intelligence and not peddling a sales pitch. As cited in Rachitsky’s study, direct interest in your startup is a key factor for product-market fit in B2B. In addition to that, observe how your audience reacts to your pitch. Do they lean in with interest, or shut you down due to skepticism?
- B2C interviews: In cases where in-person interview requests are impractical, consumer-to-consumer market ideas can benefit from more structured methods like consumer surveys and user testing. In consumer market ideas, direct feedback from actual market users or even friends-of-friends can provide valuable information regarding market behavior. Incentivize your social media fans to share feedback.
The point is to improve your personas and your value proposition. The first round of interviews is when you’re going to find unexpected opportunities and pivot points. So 40% of B2B startups end up pivoting after their first round of interviews, according to Rachitsky. Take all your interviews and distill information that you can implement. Perhaps your users want a more simplified workflow or fear your onboarding.
Actionable recommendations: Target a minimum of 10-30 structured calls. Repeat a scripted dialogue to make it feasible to compare your findings and identify two critical elements: pain and Pull. Don’t hesitate to inquire if they will actually pay for your solution. Use CRM and/or survey software to manage your findings and continually refine until your feedback begins to echo similar truths. That is how you’ll know you are onto a good thing.
Prototyping and MVP testing (No-code and manual MVPs)
So, evidence of demand and pain points established. The easiest path is to now develop something that proves build-measure-learn. This can simply be an MVP but not exactly the final product. Just enough to provide feedback and even gain some revenue.
No-code MVPs: New no-code development tools like Bubble, Webflow, Airtable, and Zapier enable teams to develop a full-fledged app or website in a quick and efficient manner. In this regard, according to a Toptal product guide, “A no-code MVP is a first version of a product developed through development methodologies that are independent of coding expertise. An MVP provides a quicker time to market and lower financial outlay and enables businesses to validate their assumptions about their ideas.” In this scenario, you can develop a no-code form to gather pre-orders for your product and develop a prototype app that shows your workflows to your target users. The bottom line is to distill your product to its bare essence (i.e., 1-3 key features) and validate user interest.
Concierge or manual MVP: Conversely (or simultaneously), you could pursue a “concierge” MVP where you personally provide the service in the background. As a rule, this is a good strategy for complex business-to-business offerings. To illustrate this point, note that “the founders of compliance startup Vanta manually assembled and provided SOC 2 readiness assessments to prospective clients for six months. The founders examined clients’ existing security docs and spotted issues in spreadsheet comparisons and even made follow-up calls to share findings.” By doing this manual MVP (i.e., doing it themselves), one can gauge interest in a solution that costs essentially zero to build: “the founders of finance startup Ramp prepared ‘savings reports’ for early adopters after users submitted actual expense info, highlighting thousands in waste. It proved that people will find your MVP valuable enough to encourage you to automate it.”
Proof-of-Concept demonstrations: A third approach is to build a clickable demo or wizard-of-oz prototype. Use tools like Figma or InVision to mock up interfaces, or record a demo video. Present it to customers to gauge reaction. Remember Rachitsky’s advice: the four signs of traction are when (1) people start paying (beyond your friends) for the early offering, (2) they continue using even a crude prototype, (3) they express strong pain or excitement, or (4) you get cold inbound requests.
In all instances, one seeks not perfection but learning. Monitor user behavior. Perform a small pilots’ release to a cooperating customer that is happy to provide feedback. In B2C consumer products, you can simply launch a landing page and observe, if people will commit. In B2B SaaS businesses, you can try demoing your no-code app to a few potential clients. Actionable suggestions: The easiest path to value is often the best one. If coding is not occurring quickly and affordably enough, code manually first. There may even be a benefit to pre-selling your MVP through payment requests and contract requests. Analytics can provide a quick determination of whether people are actually engaging. Get feedback quickly and invest in building if positive, and vice versa.
Pull metrics and validation criteria
In order to know if your niche is validated, establish specific success metrics in advance. Useful signals include:
- Willingness to pay: Several customers (ideally outside your immediate network) actually sign up, deposit, or sign contracts for the MVP. Even one paying third party indicates real demand.
- Engagement/Usage: Users consistently use the MVP or prototype (even if it contains bugs). Repeated use or repeated logins indicate that the solution fits their workflow.
- Emotional feedback: Respondents express strong “pain” or enthusiasm for your solution, such as, “I’ve needed this forever!” or “Finally, someone solved this problem!” Open frustration with current alternatives is a good sign.
- Incoming interest: You’re starting to receive unsolicited signups, inquiries, or requests from a broader range of consumers, not just your contacts. Cold signups (either viral or word-of-mouth) indicate organic traffic.
It’s critical to quantify results wherever possible. For example, when testing a B2C e-commerce idea, track how many website visitors convert to a waitlist or pre-order. If you ran ads, consider the cost of acquisition and the registration rate. For B2B, calculate the number of demo requests received and how many of them convert to pilot access agreements. Set benchmarks (e.g., “If >5% of respondents sign up for a waitlist or schedule >3 demos, consider it valid”).
Industry example cases
1. Lean Validation in Practice: Perplexity AI
Prior to its success as a hot new startup of 2023, Perplexity AI still had to develop its idea through manually crafting responses as a small in-house research team. Founded by Aravind Srinivas, it did not debut its first product until late 2022 and took early 2023 to determine if users actually wanted to interact with its conversational search engine more than Google. The startup obtained its first users through Reddit and Discord servers and manually observed user behavior without extensive infrastructure until reaching over 10 million monthly users in late 2023.
2. Pivot Insight: OpenAI’s ChatGPT Enterprise
The release of OpenAI’s ChatGPT Enterprise in 2023 was made possible through a swift shift in OpenAI’s strategy from consumer virality to business validation. OpenAI gathered information from business users in 2023 about how they had developed “pro”-level versions of ChatGPT. OpenAI developed a B2B strategy and released its enterprise-level AI in response to demands for SOC 2 compliance and administrative features for its user base. The shift from a consumer product to a SaaS offering made OpenAI cater to clients like PwC and Canva.
3. Failure Warning: Convoy
Seattle-based Convoy, a logistics unicorn that had investments from Jeff Bezos and Bill Gates, shut down in October 2023. Although Convoy raised more than $900 million in funds, its demise can be attributed to a lack of market demand and a shortfall in adjusting its business model to accommodate a reduction in freight volumes. The demise of Convoy proves that without product-market fit in a scaled business model, one burns through cash.
Recommendations
Be data-driven and humble: treat your initial idea as a hypothesis. Test it thoroughly and accept everything the data reveals. Document all assumptions (market size, conversion rates, etc.) with sources or experiments.
Iterate quickly: Use no-code tools and manual methods to learn quickly. If something isn’t working (e.g., low ad conversion, disengaged respondents), iterate on your concept or target segment instead of building a full-fledged product right away.
Segment for focus: Even in global tech markets, start with a narrow focus. Focus on one geographic region or customer segment to keep testing manageable. Validate the concept locally or in a small vertical segment before scaling. Then systematically expand your SAM/SOM (as Uber did, working city by city).
Combine qualitative and quantitative metrics: Combine what the numbers show (signups, search volume) with what customers are saying. Both matter. For example, high website traffic but poor interviews means people are interested but unconvinced—you may need to tweak your messaging or features.
Keep a modest budget: Use free/low-cost methods (self-created landing pages, interviews in coworking spaces, spreadsheets). Every dollar saved on premature development can be invested in deeper validation (e.g., more user testing or a better prototype).
Define clear yes/no criteria: Before testing, decide what success will look like (e.g., “100 signups in 2 weeks” or “3 paid pilot customers”). If you meet these criteria, move forward; if not, reevaluate the idea or change direction.
Final thoughts: Test before you build, or risk building blindly
In 2023, the startup landscape has clearly demonstrated that speed without validation is simply acceleration toward the wrong goal. Whether it’s a two-person startup or one aiming for the global SaaS market, the difference between breakthrough success and quiet failure often comes down to disciplined market validation. Founders who test early, evaluate real-world signals, and maintain the flexibility to pivot their ideas, for example, Perplexity AI or OpenAI’s enterprise approach, are the ones who turn ideas into driving forces.
The modern tech ecosystem rewards evidence-based conviction. You don’t need a massive product to prove value; you need proof that the product matters to real users. This means quantifying demand (TAM/SAM), paying close attention to users, conducting lean experiments, and treating every “no” as a fact, not a failure. Validation is no longer a checkbox before raising funding – it’s the foundation for everything that follows: positioning, pricing, messaging, and the roadmap.
As a martech specialist, I see this as a cultural shift in startup building. Great founders now think like growth strategists from the start: they prototype stories, test audiences, and iterate messaging as thoroughly as they do product features. The goal is not perfection, but clarity.
If there’s one principle you can remember, let it be this: proven ideas form faster than code. Before you build anything, test the market until you can confidently say not only that people need what you’re developing, but that they’re already expecting it. This is how sustainable tech companies are born.
