How to Build a Profitable Local Directory: A Step-by-Step Guide - Lessons from Katt
I'm participating in the Build the Keyword challenge and trying to stay focused during this short two-week period. My main goal is to avoid past mistakes—pursuing projects without a clear market.
My approach has two parts:
- While technical execution comes easily to me, I need to spend more time on research, getting advice, and learning from experienced people.
- I'm creating a lesson plan to track insights from Katt's videos, as I often forget valuable advice.
I'll document my learnings, experiences, and mistakes as part of this series. I hope to stay consistent and that you find it useful!
Day 1/14
Introduction
Hey everyone, I’m Katt, a no-code maker from Belgium and the founder of Build the Keyword. If you’re looking to create a product that brings in organic traffic on autopilot, you’re in the right place. Today, I’m diving into how I’m building a profitable local directory using keyword research and a structured no-code approach.
The goal? A hands-off business model that leverages SEO to generate passive income.
Why a Local Directory?
Local directories are one of the best ways to generate passive income. I got inspired by a Startups Ideas Podcast episode where they explained how to build a directory website from scratch. Since this aligns perfectly with what we do at Build a Keyword, I decided to give it a shot.
The strategy is simple:
- Find a keyword with decent monthly search volume (30K+ for ad revenue potential).
- Ensure it has low competition (keyword difficulty under 20).
- Build a niche directory around it.
- Rank on Google and monetize through ads or paid listings.
Step 1: Choosing the Right City
I focused on a midsize city (100K–500K residents) because:
- There are enough local businesses to make the directory valuable.
- There’s less competition compared to major cities.
Using ChatGPT, I generated a list of potential cities and chose one close to me—familiarity helps in understanding the local market.
Step 2: Keyword Research
Using Build a Keyword, I conducted smart searches targeting my selected city. My ideal keyword had to meet these criteria:
- Search volume: At least 30K/month for meaningful ad revenue.
- Keyword difficulty: Below 20 to rank without extensive link-building.
- Consistency: Non-seasonal for year-round traffic.
- Non-branded: Avoiding company names that dominate rankings.
- Related keywords: More variations = more traffic potential.
Best Keyword Choice: Restaurants in [City]
It had:
- 27K+ searches/month.
- Many related keywords like brunch, lunch, pizza, Italian restaurants, etc.
- Individual restaurant names with strong search volume.
Step 3: Competitor Analysis
I analyzed the top Google search results for my target keyword:
- TripAdvisor ranks #1 – Expected, but their interface isn’t ideal for everyone.
- A few magazine articles listing only 10 restaurants – I can do better.
- Michelin Guide – Well-established but niche-focused.
- City website – Not SEO-optimized.
- Few individual restaurant websites – Easy to outrank.
No dominant local directory exists, which means there’s room to compete.
Step 4: Domain Name Strategy
While there’s no clear SEO proof that keyword-based domains rank better, they can help. I’ll check if Restaurants[City].com is available to give my site a potential ranking advantage.
Step 5: Understanding User Needs (Using Reddit)
Searching Reddit for my keyword provided valuable insights:
- Users want unique filters like hidden gems, new openings, or best places for a romantic dinner.
- People actively seek recommendations for breakfast, lunch, and local hotspots.
- Trendy vs. budget-friendly options matter to searchers.
I’ll use these insights to make my directory more user-friendly and differentiated from generic lists.
Step 6: Monetization Strategy
A local directory isn’t just about traffic—it needs monetization. Here are my planned revenue streams:
- Google AdSense – Works well if traffic exceeds 30K searches/month.
- Paid Listings – Restaurants can pay for premium visibility.
- Newsletter Sponsorships – A weekly “New Openings” email featuring paid placements.
- Lead Generation – Selling leads to restaurants (reservation services, exclusive deals, etc.).
Conclusion
I’ve validated the city, keyword, competition, and potential monetization—which means we’re ready to build! Next up: picking a no-code tool and setting up the site structure. Stay tuned for the next steps, and if you’re in the Build a Keyword challenge, let’s get building! 🚀
Day 2/14
Building a Local Directory for Restaurants: Research, Strategy & Next Steps
Objective
The goal of this project is to build a local restaurant directory centered around a high-volume, low-competition keyword. The ultimate aim is to monetize the site with display ads, capitalizing on passive income potential.
Keyword Research & Selection
Criteria for Choosing a Keyword:
- 30,000+ monthly searches (actual chosen keyword has 27k)
- Keyword difficulty below 20 (making it feasible to rank in Google’s top 10)
- Not seasonal, not branded
- Has many related keywords to expand ranking opportunities
- Focused on a specific local city for lower competition
Chosen Keyword:
"Restaurant [City]" – slightly lower search volume than hoped, but with many strong related keywords, including:
- Synonyms: "Restos [City]"
- Restaurant types: Sushi, Italian, Indian, etc.
- Meal-specific terms: Lunch, brunch, coffee, breakfast
- Location-based searches: "Restaurant near train station," "Restaurant near Old Market"
- Descriptive searches: "Best restaurants in [City]," "Most cozy restaurants in [City]," "New restaurants in [City]"
Competitor Analysis
A deep dive into the current Google search results found that while there are some big players (TripAdvisor, TheFork, TableBooker), there are also weak spots:
✅ Some ranking results are not optimized for the keyword (e.g., individual restaurant websites, local tourism sites).
✅ No competitor has the exact keyword in the domain name – an opportunity for branding & trust-building.
✅ Google prioritizes local results over large directories, which plays in favor of a well-structured local site.
Domain Name Selection
- Preference for a .be domain (since the directory is for Belgium)
- Considering domain options that include the primary keyword for trust and clickability
- Avoiding hyphens or outdated-sounding names to keep it modern and appealing
Competitor Analysis: Structure & Weaknesses
Analyzing competitor sites revealed common filters & structure:
- TripAdvisor & Michelin Guides:
- Filters for cuisine, meal type, price, rating, awards, and accessibility
- Missing trend-based categories (e.g., "Most trendy restaurants")
- Lacking content-rich listings (mostly reviews, few detailed descriptions)
- Google Maps:
- Provides basic filters (price, rating, hours) but lacks deeper categorization
- Has valuable user-uploaded images and reviews
- Weakness: No curated lists, awards, or unique content
Opportunity to Stand Out:
🔹 Curated, AI-enhanced descriptions summarizing restaurant reviews in a structured way (e.g., ambiance, service, food quality).
🔹 Unique filter options like “Trendy,” “Cozy,” “Best for Groups,” “Newly Opened.”
🔹 More engaging content formats (e.g., award-style rankings, neighborhood-based suggestions).
Facebook & Reddit Research: What People Actually Search For
To differentiate from competitors, the creator analyzed real user discussions in local Facebook groups and Reddit threads to understand what people actively ask about restaurants.
Commonly Requested Features & Filters:
✅ Best restaurants for big groups (30+ people)
✅ Trendy & cozy restaurant recommendations
✅ Vegetarian & vegan-friendly places (beyond just having one veggie dish)
✅ Food sharing / tapas-style dining options (big trend in Belgium)
✅ Restaurants with playgrounds (important for parents)
✅ Best budget-friendly restaurants for students
✅ Best takeaway & delivery options
✅ Hidden gems & lesser-known spots
Conclusion:
💡 This research helps refine the directory’s structure & filter system, ensuring it includes the features people actively look for.
Next Steps: Scraping & Data Collection
- Primary Data Source: Google Maps
- Enhancing Data with Manual Research:
- Adding unique categories & awards based on real user discussions
- Structuring AI-generated summaries to make listings more valuable
- Ensuring comprehensive coverage by comparing restaurant counts across different directories
Final Thoughts & Upcoming Work
This research phase lays the groundwork for a structured, high-value local directory that goes beyond what existing directories offer. The next step? Implementing a scraper to collect and organize restaurant data.
👀 Stay tuned for the next update! The first-time use of a scraper will be an experiment—let’s see how it works out! 🚀