The invisible category problem

Here's something that keeps me up at night: most local businesses have no idea how AI search engines categorise them.

And it's costing them customers every single day.

Think about it. When someone asks ChatGPT or Perplexity for a restaurant recommendation, the AI doesn't magically "know" you're a restaurant. It categorises you based on signals from across the web. Get miscategorised as a café? You're invisible when people ask for restaurants.

The brutal part? Business owners can't fix what they can't see.

They're pouring money into SEO and content marketing, completely unaware that AI has already put them in the wrong box. They're optimising for keywords while AI visibility – the future of search – is passing them by.

I kept seeing this pattern: businesses struggling with AI search, but lacking the fundamental awareness that categorisation even matters. You can't sell optimisation services to someone who doesn't know the problem exists.

So I built something to bridge that gap.

A 60-second interactive quiz that shows businesses exactly how AI engines are likely categorising them – and what they can do about it. Education that qualifies leads while it teaches.

Sometimes the best marketing tool isn't the most complex one. It's the one that makes an invisible problem visible.

More on how this works – and why I kept the tech deliberately simple – below. Keep Reading

Most businesses have no idea AI search engines are categorising them wrong – and it's costing them customers they'll never know about.

I built something to fix that.

The invisible problem

A restaurant gets categorised as a "café" by AI search engines. When someone asks ChatGPT or Perplexity for restaurant recommendations, they're invisible. They're losing customers to competitors who aren't better – just better categorised.

The challenge? Businesses can't optimise for something they don't know exists.

The solution: Education that qualifies

I created a 60-second interactive quiz that shows businesses exactly how AI search engines categorise them – and where they're likely being miscategorized. It's simple: answer a few strategic questions, get immediate category recommendations, understand what needs fixing.

But here's what makes it powerful for lead generation:

Engagement reveals intent. Someone who invests 60 seconds learning about AI categorisation is signalling they care about AI visibility. They're not just downloading a PDF they'll never read – they're actively discovering they have a problem worth solving.

The business outcomes

The conversion advantage is significant. Instead of traditional content marketing where you're hoping someone reads and remembers you, interactive education does three things simultaneously:

Builds awareness of a problem prospects didn't know they had
Qualifies interest through voluntary time investment
Positions expertise by providing immediate, personalised value

For a marketing agency, this becomes a lead qualification machine. High completion rates (that 60-second constraint matters), detailed funnel tracking to see exactly where interest peaks, and qualified leads who've already educated themselves on why this matters.

For service businesses, it's proof of expertise before the first conversation even happens.

The strategic insight

I deliberately kept the tech stack simple – HTML, CSS, JavaScript, PHP. No React. No complex build processes. Because lead qualification tools should deploy fast and run reliably, not showcase technical sophistication for its own sake.

Sometimes solving a marketing problem requires less complexity, not more.

The result? A tool that serves dual purposes: it educates while it converts, builds awareness while it qualifies, and demonstrates expertise while it captures leads.

What invisible categorisation problems are costing your business opportunities you'll never see?

The best lead qualification tool is the one prospects don't realise is qualifying them.

Most businesses approach lead generation backwards: they create friction to filter leads, then wonder why conversion rates tank.

Here's the counterintuitive truth: The most effective qualification happens when prospects think they're being educated, not evaluated.

I recently built a 60-second quiz that teaches local businesses how AI search engines categorise them. The quiz itself seems simple – help a restaurant owner understand why they're not showing up in AI recommendations. But the real work is happening beneath the surface.

Someone who invests 60 seconds learning about AI categorisation is broadcasting a signal louder than any form field could capture: they care enough about AI visibility to stop scrolling and engage.

That engagement IS the qualification. No "How serious are you about AI?" dropdown menus. No "What's your budget?" interrogation.

The deeper principle: Interactive education converts better than content marketing because engagement reveals intent.

Most businesses overcomplicate this. They reach for React frameworks, complex funnels, sophisticated tech stacks – adding layers of complexity that slow deployment and introduce failure points. Meanwhile, their simpler competitors are already in market, learning and iterating.

The sophistication isn't in the code. It's in understanding that sometimes solving a marketing problem requires less technical complexity, not more.

A static HTML quiz with smart Google Tag Manager integration captures the same behavioural data as a [[DOLLA$]50K custom platform. It just deploys in hours instead of months.

The question isn't "what technology can do this?"

It's "what's the simplest solution that reveals what I need to know?"

The 60-Second Quiz That Qualifies Leads While They Learn

I recently built an AI categorisation quiz that does something interesting: it educates prospects about how AI search engines see their business while simultaneously qualifying them as leads. The whole experience takes 60 seconds, works beautifully on mobile, and tracks every interaction through GTM.

Here's how different businesses could deploy this approach:

Marketing Agency: Pre-Qualifying AI Search Clients

A digital marketing agency wants to attract businesses ready for AI search optimisation but needs to filter out tyre-kickers. The quiz asks strategic questions about business type, current visibility, and categorisation concerns. Within a minute, prospects get immediate feedback on how AI might be categorising them – often revealing gaps they hadn't considered. The agency now has engaged leads who've self-identified their pain points and understand the problem enough to have a meaningful sales conversation.

SaaS Company: Interactive Product Education

A B2B SaaS platform needs to explain a complex concept – AI search categorisation – without losing prospects in a 3,000-word blog post. The quiz breaks down the concept through interactive questions, making the learning feel effortless. Prospects who complete it are warm leads: they've invested time, they understand the problem space, and the completion data shows exactly which categories matter most to their business. Sales can personalise follow-up based on quiz responses.

Consultant: Mobile-First Thought Leadership

An independent consultant runs LinkedIn ads targeting mobile users during commutes. Traditional lead magnets require too much commitment. The 60-second quiz works perfectly on phones, requires minimal typing, and delivers instant value. Prospects get their categorisation assessment immediately, the consultant captures qualified contact details, and GTM tracking reveals which traffic sources produce the most engaged leads. The entire funnel optimises itself through data.

Service Business: Demonstrating Expertise Before The Call

A local service business struggles with unqualified discovery calls. The quiz becomes their first filter: it educates prospects on why categorisation matters for their industry, demonstrates the business's expertise in AI search, and identifies who's actually ready to invest in optimisation versus who's just browsing.

The pattern? Education-based qualification. When you help prospects understand their problem through interaction rather than consumption, you're capturing leads who are already halfway to "yes."

What scenarios could you apply this to?

Building an Interactive AI Categorisation Quiz: Technical Breakdown

Most businesses have no idea how AI search engines like ChatGPT and Perplexity categorise them – which directly impacts their discoverability. I built a 60-second quiz system that solves this while qualifying leads interested in AI search optimisation.

The Technical Architecture

This is a straightforward but effective stack: HTML5, CSS, JavaScript, and PHP. No frameworks, no complex dependencies. The goal was fast deployment and minimal infrastructure overhead while maintaining sophisticated lead qualification capabilities.

How the Data Flows

1. User Interaction Layer (Frontend)

The quiz interface runs on vanilla JavaScript with a strategic question flow designed to extract categorisation signals. Each response feeds into a client-side detection algorithm that maps answers to AI categorisation patterns. The responsive design adapts seamlessly across mobile and desktop – critical since 60%+ of quiz traffic comes from mobile devices.

2. Event Tracking (Google Tag Manager)

Every interaction fires events through GTM: quiz_start, question_completed, category_detected, quiz_abandoned, lead_captured. This creates a complete funnel view and enables optimisation of question flow based on drop-off points. GTM handles all analytics without touching the core codebase – keeping the system clean and maintainable.

3. Backend Processing (PHP)

When a user completes the quiz, JavaScript POSTs the response data to a PHP backend. This layer:

Validates and sanitises all inputs
Processes the categorisation algorithm server-side for verification
Generates the personalised category recommendation
Handles lead capture integration
Returns immediate feedback to the user

4. Real-Time Feedback System

The recommendation engine analyses responses against AI search categorisation patterns and delivers instant, actionable feedback. Users see exactly how AI systems likely categorise their business plus next steps for optimisation.

Key Technical Decisions

Why vanilla JS instead of React? Speed and simplicity. A 60-second quiz doesn't need framework overhead. The entire system loads in <2 seconds.

Why PHP? Universal hosting compatibility. This can deploy on any standard shared hosting environment without Node.js or complex server configurations.

Why GTM instead of direct analytics? Flexibility. Marketing teams can modify tracking events without developer involvement. It also enables A/B testing on question sequences.

Deployment Requirements

Minimal infrastructure: standard web hosting with PHP support, GTM account, and your lead capture system of choice. The modular architecture means the lead capture integration is a simple webhook – works with any CRM or marketing automation platform.

The result: sophisticated lead qualification that educates prospects while capturing high-intent leads, all running on proven, stable technology that any technical team can maintain.

Building an AI Categorisation Quiz: Strategic Decisions That Matter

When you're building a lead qualification quiz, the technical implementation is straightforward – the strategic decisions are what make or break the project.

The Core Problem: Detection vs Prescription

The fundamental choice here is whether you're detecting what category a business fits into or prescribing what they should be. I opted for detection because it removes friction – users answer honestly about their current state rather than aspirationally. This affects everything: question phrasing, scoring logic, even how you position the results.

The key insight: people are terrible at self-categorising but excellent at describing their situation. Your questions should extract behaviour and context, not ask for conclusions.

Technology Stack: Resist the Framework Trap

Here's where most developers overcomplicate things. You don't need React for a quiz. The critical question isn't "what's the best framework?" but "what's the minimum viable stack that won't break?"

Vanilla JavaScript + PHP handles this perfectly because:

No build process means faster deployment
No framework dependencies means nothing breaks in 6 months
Server-side processing keeps scoring logic private
It loads faster, which matters when you're qualifying cold traffic

The trade-off: you write more DOM manipulation code. But you gain reliability and speed.

Integration Architecture: Zero Manual Touches

Every automation should be self-contained. Your quiz needs to:

Track its own analytics via GTM (no manual event setup per question)
Submit leads automatically to your CRM (no CSV exports)
Deliver results instantly (no "we'll email you")

The critical decision point: do results happen client-side or server-side? Server-side protects your categorisation logic from being reverse-engineered, but client-side is faster. I chose server-side because the algorithm is the value – showing your work defeats the purpose.

Quality Control: When to Intervene

For a quiz, there's no need for human-in-the-loop approval. The categorisation happens instantly because:

The stakes are low (it's a recommendation, not a diagnosis)
Speed matters more than perfection
Bad results surface quickly in analytics

But you do need monitoring: track completion rates per question, time spent, and category distribution. If 80% of users end up in one category, your detection logic is broken.

The Deployment Simplicity Test

Can you deploy this to basic shared hosting? If not, you're over-engineered. Complexity is a tax you pay forever in maintenance and debugging.

The goal isn't to showcase technical sophistication – it's to qualify leads reliably at scale. Simple systems survive.

When Education Becomes Lead Qualification: The AI Categorisation Quiz

I built a 60-second quiz that solves an interesting problem: most local businesses don't realise AI search engines categorise them – and miscategorization kills visibility.

A restaurant categorised as 'café' won't appear when someone asks ChatGPT or Perplexity for restaurant recommendations. The damage is invisible because businesses don't know these categories exist.

The Strategic Insight

Here's what made this work: interactive education converts better than content marketing because engagement reveals intent.

Someone investing 60 seconds to learn about AI categorisation is signalling they care about AI visibility. That's lead qualification happening naturally through education.

What It Does

The quiz conducts rapid category detection through strategic questions, then delivers immediate feedback on how AI search engines likely categorise their business – with actionable next steps for optimisation.

Built with vanilla HTML5, CSS, JavaScript, and PHP. No frameworks. No build process. Just a smart form that deploys fast and runs reliably.

The Transformation

Before: Businesses unaware of AI search categorisation → unable to optimise for something they don't know matters → invisible in AI search results

After: 60-second interactive experience → immediate category awareness → qualified leads who understand the problem and want solutions

Why Simple Tech Won

I deliberately avoided React/Node.js complexity. This needed to be a lead qualification tool that could deploy immediately and run without dependencies.

The sophistication is in the strategy, not the stack. Google Tag Manager handles analytics tracking. The quiz logicqualifies leads through question patterns. The tech just needs to work reliably.

The spectrum of impact:

Efficiency: Automated qualification vs. manual discovery calls
Strategic positioning: Educational approach builds authority
Scalability: Works 24/7 without human intervention

Sometimes solving a marketing problem requires less technical sophistication, not more.

Building something similar? The principle applies beyond AI search: find the awareness gap in your market, then build interactive education that qualifies leads while filling that gap.