Problem Statement

Landing pages are critical for businesses to convert visitors into customers, yet their performance is often suboptimal.

Key Challenges:

• According to Unbounce, the average landing page conversion rate is only 4.02%, with top-performing pages reaching 9.7% and bottom performers as low as 1.5%.

• A/B testing, a common optimization method, is time-consuming, costly, and often ineffective, with 90% of tests failing to yield significant improvements.

• Businesses lack cost-effective ways to pre-test landing pages before launch, relying on guesswork or limited real-user data.

Product Opportunity

According to Marketing Industry Report 2025 (GlobeNewswire), the global AI in marketing market, valued at $35.54 billion in 2025 and projected to reach $106.54 billion by 2029 with a CAGR of 31.6%, underscores a massive growth opportunity. This creates a prime chance to disrupt the market with a pre-launch simulation tool, competing with tools like Hotjar and Crazy Egg.

Solution

I plan to build LandingLens using AI to simulate thousands of user journeys from uploaded Figma designs, URLs, or HTML files. It will track behaviors like scrolling, clicks, and drop-offs, and provide simple insights like conversion scores, UX tips, and heatmaps to help startups and marketers optimize landing pages before launch, saving time and improving results.

Hypothesis

As Product Manager for LandingLens, after outlining the problem, opportunity, and solution blueprint, my next focus is validating the idea through structured user research. This step ensures we're building something users truly need, minimizing risks before prototyping.

User Hypotheses:

60% of free-tier users will return for multiple simulations within a month, driven by the value of personalized recommendations tailored to their industry (e.g., e-commerce or SaaS).

Insight Actionability Hypothesis

80% of users will implement at least one UX recommendation (e.g., CTA repositioning or copy edits) from the platform, resulting in measurable improvements in engagement metrics like scroll depth.

Satisfaction Hypothesis

After using LandingLens, users will rate their satisfaction (CSAT score) at 85% or higher, citing the predictive conversion scores and visual analytics as key factors over tools like Hotjar.

Cost Savings Hypothesis

Startups and small businesses will report a 40% reduction in optimization costs by relying on pre-launch simulations instead of paid A/B testing services.

Retention Hypothesis

Goal

Metric

User Adoption

# of Active users per month

Conversion Impact

% change in Conversion Rate

Revenue

Avg. Recurring Revenue

Customer Satisfaction

CSAT score from feedback surveys

Assumptions

• Users have easy access to Figma designs, URLs, or HTML exports for uploads.

• AI models can accurately simulate user behavior using training data from real interactions.

• Businesses, especially startups and marketers, are open to adopting AI-driven tools over traditional A/B testing.

• Industry benchmarks (e.g., Unbounce's 4.02% average conversion rate) remain relevant for comparisons.

Discovery

Target Audience:

Tech-savvy professionals aged 25-45 in e-commerce, SaaS, digital marketing, or creative services.

Key segments include:

• Marketers/Growth Hackers: Focused on ROI from campaigns.

• Small Business Owners: Budget-constrained, needing affordable optimization.

• Product Managers/UX Designers: Overseeing launches and user-friendly designs.

• Startup Founders: Seeking quick insights for customer acquisition.

These users are motivated by boosting conversions (20%+ improvement), saving time/resources, simplifying data-driven decisions, and staying competitive. Pain points like low conversions, A/B test failures, and lack of pre-launch data make them ideal for validation.

Sampling for User Interviews:

I'll use purposive sampling to recruit 10-15 participants who match the target audience, ensuring diversity (e.g., 40% marketers, 30% small business owners, 30% UX designers/product managers). Recruitment via LinkedIn, Reddit (e.g., r/marketing, r/startups), or industry Slack groups, targeting those with 1+ year experience in landing page optimization.
Criteria: Must have faced A/B testing challenges or low conversion issues. Interviews will be 30-45 minutes, virtual, with incentives like $10 gift cards.

Interview Questions

Following the Mom Test—focusing on users' past experiences and facts, not pitching the idea—here's a sample set of questions to pinpoint pain points, needs, and motivations -

These questions avoid bias, revealing real behaviors and validating assumptions. Insights will refine the product vision, leading to prototype development in Q4 2025. This user-centered approach ensures LandingLens solves genuine problems effectively.