May 20, 2026
Updated May 20, 2026
About Author
Kalpesh Zalavadiya
Head of Customer Success
As part of the Office of CEO team, he works across product research, support, QA, and operations—collaborating with the CEO to manage and ship polished, high-quality products.
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Table of contents
What is Voice of Customer research for product builders?
How fast does Rocket.new's Solve produce VoC research?
How is Rocket.new different from standalone VoC tools or AI builders?
What does the Rocket.new free plan include?
Voice of Customer research is how builders know what to build and for whom. This blog breaks down the Rocket.new fast-track method combining Solve for deep research, Intelligence for competitive monitoring, and Build for production-grade apps, all in one platform with compound context that makes every build smarter.
Are You Building the Right Product?
Most founders assume they are. The data says otherwise. Research from Founders Forum shows that 42% of startups fail simply because they misread market demand - building things nobody actually wanted. That's not a skills problem. It's an information problem.
Voice of Customer (VoC) research is the fix. It's the systematic practice of gathering, synthesizing, and acting on real customer signal to guide every product decision.
This blog breaks down the fast-track method built for founders and product teams, and shows exactly how Rocket.new collapses the gap between customer insight and product building.
VoC research for builders is not a one-time survey. It's a continuous intelligence habit that draws from every channel where customers reveal what they actually need - before a single line of code gets written.
Recorded sales and discovery calls - where prospects reveal unmet needs, competitor gaps, and the real reason they started evaluating
Customer support tickets - structured, timestamped, and tied to specific accounts, including the comments left inside tickets that explain the real context
Review platforms - G2, Capterra, App Store reviews - where detailed customer comments and star ratings surface comparative sentiment in unprompted language
Community channels, videos, and social posts - the earliest indicators of brewing dissatisfaction, from comments on product launch posts to threads in Reddit and Slack communities
In-product NPS and surveys - useful for measuring baseline satisfaction, weaker for discovering what customers haven't told you yet
For builders - founders, developers, and product teams shipping products - VoC research ultimately answers the most important question in product building: what should I build, and for whom? The global VoC segment was valued at $1.69 billion in 2024 and is growing at 18.9% CAGR through 2030 (Grand View Research), driven by teams connecting customer insight to build decisions faster than ever before.
Three common reasons founders skip VoC research come up again and again - and none of them hold up when you have the right process.
"It takes too long" - traditional VoC cycles run quarterly, by which point the market has already moved on
"It's expensive" - legacy research setups require dedicated tools, manual tagging, and often an external research function as alternatives to building an in-house process
"I already know my customers" - the most expensive assumption a builder can make, typically formed from a handful of vocal accounts, not a validated pattern
Industry data tells the real story - 65% of B2B product features see less than 20% adoption (Pendo benchmarks), which means teams are consistently shipping things customers never asked for
73% of B2B SaaS product teams now use AI to synthesize customer feedback at least weekly, up from just 19% in 2023, and those teams are 2.4x more likely to exceed revenue targets with 25% lower churn than peers who don't (BuildBetter, 2026)
"The riskiest moment in product is when teams build based on a few loud customer voices instead of validated patterns. VoC platforms must show pattern strength, not just request counts."- Marty Cagan, SVPG (via BuildBetter)
Good VoC research surfaces validated patterns across your full customer base - not just the loudest voices - and that difference is what separates products people love from roadmaps that quietly miss the mark.
Modern VoC research for builders pulls from five distinct source types, each carrying different signal density and a different kind of insight.
| Signal Source | What It Reveals | Signal Type |
|---|---|---|
| Sales and discovery calls | Unmet needs, competitor gaps, buying rationale | Qualitative |
| Customer support tickets | Friction patterns, bug clusters, workflow breakdowns | Structured |
| Review platforms (G2, Capterra, App Store) | Comparative sentiment and comments on competitor weaknesses | Qualitative |
| Community and social channels | Unprompted public feedback, early frustrations | Unstructured |
| In-product NPS and surveys |
Research from Gong (2025) shows the average SaaS company generates 400 to 1,200 hours of recorded customer conversations per month, but product teams typically review less than 3% of it - which means the highest-leverage signal source is also the most consistently ignored one.
Traditional VoC research follows a slow path: gather data in one tool, tag it in a spreadsheet, wait for quarterly synthesis, debate the findings, then finally build something. The time from question to shipped product can run to months.
The Rocket.new fast-track method compresses that cycle. Research, competitive intelligence, and product building happen inside one platform with shared compound context nothing gets re-explained, nothing gets lost between steps.
The research is only as good as the question that starts it, and vague questions produce reports nobody acts on.
"Why are customers churning after the onboarding flow?" targets a specific drop-off point with clear actions attached
"What job is the 5-person SaaS team actually hiring our product for?" - surfaces the real use case vs. the assumed one
"Which competitor features are our customers mentioning most in support tickets?" connects competitive monitoring directly to product priorities
Keep questions specific to a segment - a question scoped to enterprise accounts produces different, more useful research than one asked about all customers
Separate the discovery question from the validation question first find the problem, then confirm the solution
A sharp question produces research you can act on immediately. A vague one produces a deliverable that sits in a folder.
Rocket.new's Solve is the decision intelligence engine at the center of the fast-track method - give it any business question in plain language and it runs thousands of queries across 150+ sources simultaneously.
Delivers a complete structured analytical deliverable in 60 to 90 minutes work that typically takes a research team days or a strategy firm weeks
Direct verdict at the top - the recommendation comes first, not buried in appendices
Core customer objectives and jobs-to-be-done - what customers are actually trying to accomplish, in their language
Key findings with signal strength tags - every finding is marked High, Medium, or Low confidence, and conflicting signals are called out explicitly rather than smoothed over
Risk matrix and market context - structural risks, regulatory factors, and competitive dynamics that matter for the decision
Execution path with owners and timelines - the output is designed to move straight into action, not sit as a research artifact
Accepts uploaded files - customer interview transcripts, financial models, product briefs, and pitch decks are read structurally, not as flat text
That Solve output doesn't disappear after you read it. It becomes the foundation of every task that follows inside the project, present when a developer opens Build, present when marketing writes a landing page.
Understanding what customers need is one side of the VoC picture. Competitive intelligence tells you how competitors are responding to those same needs and which gaps they're leaving open.
Website signals: every page change, messaging shift, pricing update, and new feature announcement across competitor websites, with before-and-after interpretation
Social media signals: posts, comments on those posts, videos published on YouTube and TikTok, and engagement patterns across LinkedIn, X, Instagram, and Reddit
News and web presence: press coverage, partnership announcements, executive interviews, and media mentions updated over time
Reviews and reputation signals: customer comments and sentiment shifts on G2, Glassdoor, and Capterra; impact tags applied to significant changes
People signals: hiring velocity, key exits, new executive hires, and open role breakdown by department; hiring concentration reveals where competitors are investing before any product announcement confirms it
Performance marketing signals: ad videos and creative content across LinkedIn, Meta, and TikTok; what competitors are paying to push right now
Each day, Rocket.new's Intelligence feature produces a structured brief for every tracked competitor: what changed, what the pattern signals, and what your business should do in response. That brief is updated overnight and waiting before the first meeting of the day.
Here's the architectural difference that sets Rocket.new apart. The research doesn't live in a separate document that gets summarized into a build brief - it's already in the project when you open a Build task.
The Solve output is already present: Customer insights, JTBD, risk matrix, and product direction are inherited by every build task automatically
Competitive intelligence from Intelligence is already there: No re-briefing on what competitors shipped last month
Uploaded files and customer transcripts carry forward: interview quotes, product briefs, and context docs are present in every task without re-uploading
Web apps generated in Next.js: production-grade, with SEO-ready structure, WCAG accessibility compliance, and GDPR coverage built in as the baseline
Mobile apps generated in Flutter: Real design systems, dark and light theming, fluid navigation, and staggered animations from the first generation
Landing pages and websites built from the specific customer problem your research identified: Not from a generic template, from what Solve surfaced about your actual user
Internal tools, customer portals, and compliance systems: The full range of product building for teams running operations alongside customer-facing products
The build starts where the research ended which is how it should work, and which is not how any other AI platform in the market is structured.
One of the most underrated parts of VoC research is treating competitive monitoring as a continuous product input, not a project you run once a year before planning season.
Signal clusters tell the real story: A single pricing page update is noise; that same update alongside new enterprise sales hires, a shift in social messaging, and defensive comments on G2 reviews is a clear strategic signal
Competitor review comments reveal unmet customer needs: When customers post detailed negative comments about a competitor's onboarding in G2 or Capterra, that's a direct signal about what the market wants and isn't getting
Videos reveal messaging priorities: The videos competitors publish on YouTube and short-form videos on TikTok show which customer problems they're prioritizing in their content strategy
Hiring patterns show where competitors are investing next: A cluster of new ML engineering roles or enterprise sales hires is a product signal months before any announcement
Social comments reveal how customers actually feel: Comments on competitor product launch posts are often more honest than anything in a formal survey
Rocket.new's Intelligence feature connects competitive monitoring directly to the same project workspace where product decisions are being made competitive briefs are updated continuously, not just when someone remembers to check.
Rocket.new is the world's first Vibe Solutioning platform the first AI platform where business research and product building happen in the same place, connected through a shared compound context architecture.
Here's what the platform gives builders running VoC research:
Solve turns any customer, market, or competitive question into a structured analytical deliverable.
Any question in plain language: No templates, no forms, no survey design required
Research runs across 150+ sources simultaneously: In 60 to 90 minutes, not days
Output covers the full picture: Customer objectives, findings with confidence levels, competitive landscape, risk matrix, and execution path
Export as PDF or generate a full presentation deck: The output is ready to act on, present to a team, or hand to an investor
Every Solve output stays in the project and becomes the foundation of every build and marketing task that follows.
Intelligence monitors every public platform a competitor operates on and delivers daily briefs that connect signals into strategy.
Six signal categories tracked: Website, social media, news, reviews, people, and performance marketing
Daily briefs updated automatically: What changed, what the pattern signals, and what your business should do
Executive activity feed: Every post, video, and comment from named executives tracked by platform and impact level
Serves four functions from one source: Sales intelligence, marketing intelligence, product intelligence, and strategic intelligence, all from the same competitive monitoring setup
Delivers where your team works: Briefs arrive in the tools your team already uses, so there's one less platform to manage
Context and Projects form the shared memory architecture that makes Rocket.new a platform rather than a set of separate tools.
Add files and background once: Every task that follows inherits everything automatically
Cross-task context - reference any previous task in a new one and Rocket picks up exactly where the thinking left off
Works with Notion, Google Docs, and Google Sheets existing team knowledge flows in without re-uploading and stays current as the source updates
Inline comments on tasks: Team members leave comments directly inside the workspace; context and feedback stay in one place
Every task makes the next one smarter: The PRD from Solve is present when the developer opens Build; the competitive brief is present when marketing writes the landing page
Build generates production-grade products from the research foundation you've already built inside the project.
Web apps in Next.js: Full design systems, intentional typography, real visual hierarchy, production-quality from the first generation
Mobile apps in Flutter: IOS and Android from a single codebase, dark and light theming, fluid navigation, and staggered animations
Conversion-focused landing pages and websites: Built from project context so the hero speaks to the specific customer problem your research identified
Internal tools, customer portals, and compliance systems: The full range of business infrastructure, not just customer-facing products
25+ integrations authenticate once and flow into every build: Stripe, Google Analytics, Supabase, Notion, Linear, Airtable, Mailchimp, Mixpanel, and more
Staging and production environments: Full version history, one-click rollback, built-in analytics tracking visitors, conversions, and Core Web Vitals
Credits are the unit of usage across every Rocket.new capability - understanding how credits work helps teams plan research and build cycles without surprises.
Credits work across every capability: Solve research sessions, Build generation tasks, and Intelligence competitor setups all draw from the same credit pool
Free plan credits: The free plan includes starter credits to try Solve, Build, and Intelligence before committing to a paid plan
Paid plans add credits per month: Higher credit limits for teams running more research and generation tasks
Per-seat credit allocation: Team plans let admins allocate credits per seat, so each team member works within their own budget
Estimate credit usage before building: Teams can estimate how many credits a build task or Solve session will use before committing
Credits for generation tasks cover the full build cycle: First generation, iterations, redesigns, and image generation all draw credits from the same pool
Credits updated monthly: Plans refresh credits on a monthly cycle, with options to top up mid-cycle if a large project needs extra capacity
AI builders like Lovable, Bolt, and v0 are capable at generating code - but they share one structural gap: they build what you tell them to build, starting from zero each session, with no pre-build intelligence and no persistent memory across team members or tasks.
The cons of relying on separate tools become clear quickly: customer research lives in one app, competitive monitoring in another, and building in a third - with manual handoffs between every step and no shared context to connect them.
| Capability | Traditional VoC Tools | AI Builders (Bolt / Lovable / v0) | Rocket.new |
|---|---|---|---|
| Deep customer research | Yes | No | Yes (Solve) |
| Competitive monitoring | Limited | No | Yes (Intelligence) |
| Persistent project context | No | No | Yes (Context) |
| Builds from research context | No |
The difference is the architecture. Other tools give you pieces. Rocket.new gives you one system where those pieces connect and compound and where the thinking before the build is treated as seriously as the build itself.
The most expensive mistake in product building is not slow execution. It's precise execution aimed at the wrong target. Voice of Customer research is how builders know where to aim.
Voice of Customer Research for builders: the Rocket.new fast-track method turns what used to take months research, synthesis, competitive analysis, build - into a single continuous workflow inside one platform. Other tools make the build faster.
Rocket.new makes the whole cycle smarter, by starting from what customers actually need and keeping that context alive through every step of the product building process.
| Baseline satisfaction, structured data points |
| Quantitative |
| No |
| Yes (Build) |
| Daily competitive brief | No | No | Yes (Intelligence) |
| Free plan available | Some | Some | Yes |
| Credits for generation | N/A | Per-month | Flexible plans |