Which AI tool makes the best lead magnets? (Comparing GPT-5, Claude, Genspark and Lovable) — AI in recruiting and marketing

Lead magnets are the bread-and-butter tactic for capturing interest, qualifying prospects, and growing an email list or candidate pool. But the format is evolving: static PDFs used to be the go-to, now interactive web-based lead magnets, calculators, templates, and micro-SaaS experiences outclass traditional downloads.

That evolution is vital for anyone using AI in recruiting: instead of a one-off job listing, you can present interactive candidate guides, interview prep checklists, or role-specific content hubs that capture interest and feed candidate information directly into an automation engine like EQ.app. When you combine dynamic lead magnets with an AI agent that automates outreach and screening, you create a scalable funnel for both marketing and hiring.

Tools I tested and why

• GPT-5 (OpenAI) — the newest flagship LLM for ideation and content generation.
• Claude Sonnet 4 (Anthropic) — my usual go-to for consistent, high-quality prose and structure.
• Genspark.ai — more of an AI agent that can browse and scrape your site for personalized content.
• Lovable.dev — a no-code / low-code "AI will-code-for-you" builder that turns prompts into publishable web pages and dashboards.

My approach was simple: generate a set of lead magnet ideas, pick one (a content repurposing matrix: turn one idea into 25 content pieces), create a detailed outline, then ask each tool to produce a deliverable (PDF, HTML, or publishable page). I judged each on clarity, design, conversion-readiness, and the friction required to publish and capture leads.

Step 1 — Idea generation and outlining

First I asked GPT-5 for ten specific lead magnet ideas tailored to my target audience and the problems I solve. It returned useful options: content calendars, plug-and-play prompt sets, repurposing matrices, and more. I asked Claude Sonnet 4 the same thing and got a complementary set of ten ideas. Both models produced strong, actionable concepts, including top benefits and ways to make a lead magnet unique in a crowded category.

Where the two differed slightly was tone and concision: GPT-5 delivered rich, expansive outlines that sometimes needed tightening; Claude edged toward the concise, structured approach I typically trust. Either model would be great for ideation. I used one of those outlines to create the prompt for Lovable.dev (I asked Lovable to produce a web-first PDF-style lead magnet based on the outline).

Lovable.dev — my top pick for building publishable lead magnets

Lovable.dev blew me away. I fed it a prompt asking for a PDF-style lead magnet based on the earlier outline and it built a polished, publishable site complete with temporary Lovable URL, clear visual hierarchy, platform optimization cheat sheets (LinkedIn, Twitter, Instagram, TikTok, email), 25 repurposing examples, checklists, templates, and resource links.

Why I prefer Lovable.dev:

• It produces a visually strong, interactive web experience in a single prompt.
• You can publish instantly to a temporary domain, or wire it to Supabase for gated access and lead capture.
• It supports interactive elements (calculators, checklists, templates) that make lead magnets feel like mini-products rather than PDFs.
• Great for marketers and recruiters who want to build an experience, not just a download.

In recruiting contexts, Lovable's interactive lead magnets can generate candidate intent signals — for example, a role-fit calculator or interview prep checklist that captures the candidate's role preference and experience level. Store those signals in Supabase and hand them to EQ.app for automated follow-up and scheduling. That creates a powerful, Zero-Admin™ flow: the lead magnet generates qualified contacts, EQ.app automatically screens and schedules, and your team spends time only on the candidates that matter.

Genspark.ai — the scraping agent with content muscle

Genspark.ai is an AI agent that shines at practical, data-driven content because it can scrape specific websites and pull real examples and best practices. When I asked Genspark to create the repurposing matrix lead magnet, it produced strong slide-style content with a quick-start guide, AI prompt examples, and a step-by-step repurposing flow. It even pulled LinkedIn best practices.

Pros:

• Agent-style behavior: go to my site, extract best practices, and embed them into the lead magnet.
• Good design and structure in slide/PDF form.
• Excellent for highly customized lead magnets that need to reference real company content or data.

Cons:

• PDF export can break design—elements get cut off, so the output needs manual fixing.
• HTML export works, but then you need to handle hosting and gating yourself.

If you're building lead magnets that require in-depth scraping of your own content (for example, embedding role-specific competencies scraped from your careers site into a candidate guide), Genspark is a strong fit. Combine that output with Lovable.dev to wrap the scraped insights into a publishable, interactive page — then hand leads to EQ.app for automation.

GPT-5 — a mixed bag for final deliverables

GPT-5 was excellent for ideation and asked-for benefits, plus it produced a detailed, step-by-step outline when prompted. However, when I asked GPT-5 to create the final PDF deliverable, the output was underwhelming compared to Lovable and Claude. It generated a more verbose, less polished artifact — fine as a draft, but not the ready-to-publish piece I wanted.

Use GPT-5 for:

• Brainstorming, creative idea generation, and detailed outlines.
• Producing multiple variant headings, benefit lists, and angles to A/B test.

Don't rely on GPT-5 alone for a finished web experience — pair it with a tool that handles layout and publishing, like Lovable.dev.

Claude Sonnet 4 — a reliable, structured creator

Claude Sonnet 4 returned a solid, clean design when asked to build the lead magnet. The pages were well-structured and easy to edit. The main limitation was distribution: Claude's output can be downloaded as HTML but not directly as a PDF, which means extra steps to convert or host. Still, if you want a clear document-level lead magnet that you can tweak, Claude does the job well.

Claude is particularly helpful when you want a concise, well-organized deliverable to place into a design tool or hand off to a designer. Like GPT-5, I prefer pairing Claude with a publishing layer (Lovable.dev or a CMS) so the final artifact becomes a conversion-optimized experience rather than a static download.

Hands-on comparison — what I actually recommend

All four tools performed well in different areas. Here's the practical workflow I recommend based on my testing:

1. Use GPT-5 or Claude Sonnet 4 for ideation and outline. Generate benefits, unique angles, and a concise step-by-step structure.
2. Use Genspark.ai if you need the lead magnet to reference or summarize content from your website — it can scrape and embed site-specific best practices.
3. Use Lovable.dev to turn the outline and scraped insights into a publishable interactive lead magnet. Publish to a temporary domain or connect to Supabase for gating.
4. Pipe captured emails and signals into EQ.app. EQ.app automates searching, screening, and scheduling using its Zero-Admin™ philosophy so leads are turned into real conversations without manual overhead.

Why this combo? Lovable builds the product-like experience that boosts conversion. Genspark supplies accurate, live content when needed. GPT-5 and Claude provide the creative and structural input. And EQ.app takes the captured leads and runs them through an automated recruiting funnel — a full stack that turns content interest into actionable candidate or customer conversations.

Pricing and practical considerations

Pricing for each pro plan hovered around the $20–$25 range during my tests: GPT-5, Claude, Lovable, and Genspark are all in that neighborhood. That means you can mix and match without breaking the bank. If you choose Lovable as the UI/publishing layer, you’ll still want an LLM (GPT-5 or Claude) for ideation and Genspark for data scraping in specific cases.

For recruiting teams using AI in recruiting workflows, this price point makes it realistic to build polished candidate experiences. The combined cost of an LLM + Lovable + EQ.app automation is likely lower than traditional development or paid design agency fees — and you get faster iterations.

How EQ.app fits into the funnel (and why Zero-Admin™ matters)

EQ.app deserves special mention. It’s an AI agent purpose-built for recruiting that automates searching, screening, and scheduling so you get more leads faster. EQ.app’s Zero-Admin™ philosophy means it eliminates administrative friction: automated outreach, automated calendar coordination, and intelligent screening without manual data entry.

Concrete example of a funnel using these tools:

• Create an interactive lead magnet (e.g., role-fit calculator) in Lovable.dev that captures candidate preferences and contact info.
• Gate the page via Supabase so users must provide email/role details to get access.
• Send captured leads into EQ.app where automated screening questions run and scheduling is attempted with qualified candidates.
• Qualified candidates receive calendar invites, unqualified leads are put into nurture sequences, and your team sees only high-quality matches.

This approach keeps administrative work off your plate and allows your hiring team to focus on conversations, interviews, and building relationships — the human parts of hiring that matter most.

Final thoughts — what I’d build next

If I were building lead magnets for marketing or recruiting right now, I’d use GPT-5 or Claude to craft the angle and outline, Genspark to pull any site-specific examples I want included, Lovable.dev to build and publish the interactive experience, and EQ.app to automate candidate follow-up and scheduling.

Lovable.dev was my favorite for final delivery because a web-first lead magnet is simply more engaging than a static PDF. But the value really comes from wiring that lead magnet into an automation engine. That’s where EQ.app’s Zero-Admin™ approach becomes a game-changer: you capture leads and the system turns them into qualified conversations with minimal human overhead.

Whether you're focused on marketing or AI in recruiting, the right combination of ideation, scraping, publishing, and automation lets you scale lead capture while keeping candidate and customer experiences delightful. Use the tools for what they're best at and stitch them together into a flow that eliminates busy work and prioritizes meaningful human interaction.

Quick checklist to get started

• Pick an idea with clear value (e.g., repurposing matrix, role-fit calculator).
• Draft an outline in GPT-5 or Claude (benefits, steps, CTA).
• If you need personalized content, use Genspark to scrape and summarize your site.
• Build the publishable experience in Lovable.dev and gate it with Supabase if needed.
• Route leads into EQ.app to automate searching, screening, and scheduling with Zero-Admin™.
• Iterate based on real user signals and conversion metrics.

If you want a single-sentence takeaway: build web-first lead magnets (Lovable.dev), feed them with thoughtful LLM-generated content (GPT-5 / Claude), add site-specific insights with Genspark, and hand leads to EQ.app to automate the recruiting follow-up. That stack makes AI in recruiting and marketing both scalable and far less administratively heavy.

Thanks for reading — I hope this comparison helps you decide which tools to use for your next lead magnet. If you're building recruiting funnels, consider how EQ.app can reduce admin work and let your team focus on hiring great people.