How to Find High-Quality Data for Your Directory: Step-by-Step Guide

When it comes to building a directory, the secret to success isn’t the number of listings you have—it’s the quality of your content. A directory filled with outdated, inaccurate, or irrelevant information will fail to attract users, let alone keep them coming back. On the other hand, a directory with carefully curated, reliable, and enriched data becomes a trusted resource that stands out in any niche.

In this guide, we’ll explore how to lay the foundation for a high-quality directory. You’ll learn:

• Why curating your data beats scraping every time.
• Where to find the best seed data to get started.
• How to efficiently collect, enrich, and organize your data using tools like Airtable, Apify, and Perplexity AI.
• Practical tips for cleaning and standardizing your data to ensure a seamless user experience.

By the end, you’ll have a clear roadmap for creating a directory that users trust, value, and keep returning to. Quality isn’t just the key to a great user experience—it’s the cornerstone of long-term growth and monetization.

How To Add Your Initial Data For You Directory

Scraping vs. Curating: Why Curating Will Make Your Directory Better

When building a directory, many people think the easiest way to populate it with data is to find another directory and scrape their content. While this might sound like a shortcut, I believe it’s not only unethical but also highly ineffective.

Here’s why scraping isn’t the answer: in most cases, the data you scrape will be riddled with inaccuracies or completely outdated. This creates a poor user experience, reduces trust in your directory, and ultimately hurts its potential to grow or generate revenue.

The key to building a successful directory—both for user experience and future monetization—is to focus on quality over quantity. Curating data manually ensures that every listing is accurate, relevant, and valuable to your audience. It may take more time upfront, but the long-term benefits far outweigh the effort. Users trust your site more, and your directory becomes a reliable resource they return to again and again.

Later in this guide, I’ll share some tools and strategies for using scraping techniques ethically and effectively, but if you’re just starting out, my advice is simple: start with the best data you can find, even if it’s less data. The quantity can come later, but quality is what sets your directory apart.

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Where to Find Seed Data

Seed data refers to the first few listings you add to your directory. It’s your foundation—the starting point for building a rich, valuable resource. The best place to start finding this data is where most people are already looking: Google.

A quick search can uncover a variety of sources to kick off your research, including:

• Blogs that feature curated lists or recommendations.
• Other directory sites that focus on your niche.
• Social media platforms like Reddit, where users discuss relevant topics and share insights.

While these sources are great for inspiration, many of them present a common challenge: their data is often unstructured. This means it’s not formatted in a way that makes it easy to add to your directory in a clean, consistent manner —a crucial step for enabling search and filtering features later on.

To overcome this, focus on finding sources that include links to social media accounts for the listings. These links often lead to structured, up-to-date content, which is easier to integrate into your site.

How I Found My First Data Sets For The Running Directory

• Run Clubs: I found that most run clubs have active Instagram accounts. These are excellent sources for seed data because they’re typically:
  • Managed by the club itself, meaning the information is up-to-date.
  • Instagram pages all the same, making it easier to extract details like location, schedules, and images.
• Races: Many race blogs included links to websites and Facebook pages for individual events. While both are useful, I focused on Facebook pages because they often:
  • Contain structured and well-organized data, like event details and photos.
  • Are actively updated by race organizers, ensuring accuracy.

By prioritizing structured and reliable sources like social media pages, you set the stage for a directory filled with accurate and well-formatted listings. Next, we’ll dive into how to efficiently collect this data and add it to your directory.

How To Efficiently Populate Your Database

Once you’ve found reliable sources for your seed data, the next step is adding that data to your database. If you followed my last post, you’ll know that I use Airtable as my database of choice. It’s beginner-friendly, flexible, and ideal for managing structured data.

One of Airtable’s in-built tools I use for this task is the Airtable Web Clipper—a Chrome extension that makes adding data seamless as you browse.

Using the Airtable Web Clipper

The Web Clipper lets you quickly add information from websites directly into your Airtable base without switching tabs. Once configured, you can:

1. Set up your Airtable Web Clipper:
   • Install the Chrome extension and connect it to your Airtable account.
   • Link it to the Airtable base where you’ll store your directory data.
2. Clip data on the go:
   • As you browse sites like blogs, social media, or directories, you can highlight the details you need and add them to your Airtable base with just a click.
3. Save time and stay organized:
   • No more copying and pasting between tabs. The Web Clipper speeds up data collection, making it efficient and straightforward.

How to Use CSS Selectors in the Airtable Web Clipper

Where the Web Clipper becomes a real game-changer is its ability to target specific data on websites that use structured CSS, such as Instagram or Facebook. Here is how it works:

Instead of manually entering information, you can configure the Web Clipper to extract specific data points directly.

For example:

• Run Clubs on Instagram: I used CSS selectors to automatically capture:
  • The club’s name.
  • The Instagram bio or description.
  • Profile images.

By identifying and setting rules for CSS class names, the Web Clipper pulls this information automatically, saving you hours of manual work.

How to Set It Up

1. Inspect the Website:
   • Use your browser’s developer tools (right-click and select "Inspect") to find the CSS class names for the elements you want to target (e.g., name, description, or images).
2. Configure the Web Clipper:
   • In your Web Clipper settings, add the CSS selectors for each field in your Airtable base (e.g., .username, .profile-bio, or .image-container).
3. Test and Save:
   • Test the configuration to ensure the correct data is being captured.

Tips for CSS Selector Success

• Best for Structured Sites: This method works best on sites with consistent structures, like Instagram and Facebook, where every page uses the same layout.
• Avoid Unstructured Sites: On less consistent websites, this approach can be tricky due to varying layouts.
• Need Help?: If you’re unsure how to find or use CSS selectors, ChatGPT can help:
  • Copy the source code of the page.
  • Ask ChatGPT to identify the selectors for the data you’re targeting (e.g., "What CSS selector extracts Instagram profile names?").

By combining the Airtable Web Clipper with CSS selectors, you’ll drastically speed up your data collection process while maintaining accuracy. In the next section, I’ll show you how to enrich this data to make your directory even more valuable.

How To Enrich Your Data For Your Directory

Once your database is populated with seed data, the next step is enriching it. Depending on the type of directory you’re building, this process can vary, but generally, data enrichment involves:

• Adding more detailed information about each listing.
• Sourcing image assets like logos or banners.
• Including reviews or additional content to make your listings more valuable.

Because the specifics of your data will depend on your directory’s focus, our enrichment workflows might differ. However, I’ll share two incredibly effective methods I use to level up the listings on The Running Directory.

How I Use Apify to Pull Race Images and Logos from Public Facebook Pages

Apify is a scraping tool that retrieves data from a wide range of sources, including Facebook Business Pages, Google My Business, Instagram, and more. Used responsibly, it can save you significant time by automating the process of gathering publicly available data.

Apify works by using "actors" (prebuilt scripts) to scrape specific data. You provide inputs—such as the URLs of the Facebook pages you want to scrape—and the actor retrieves information like images, descriptions, and social stats.

How I Use Apify To Enrich Data on The Running Directory

For The Running Directory, I needed images to make my race listings visually appealing. Manually finding and downloading these images for every listing would have been incredibly time-consuming. Instead, I used the Facebook Page actor from Apify to automate the process.

Here’s how I did it:

1. Select the Scraping Actor:
   • I used Apify’s Facebook Page actor, which is designed to scrape information from public Facebook Business Pages.
2. Input the Data:
   • I provided the actor with the URLs of the race event pages on Facebook.
3. Retrieve the Data:
   • The actor scraped details such as:
     • The page’s follower count.
     • Event descriptions.
     • Most importantly, the Facebook banner image and logo.
4. Store the Data:
   • Once the actor completed its task, I saved the retrieved images and data directly into my Airtable base.

Why I Consider This Approach Fair

• The data I’m accessing is publicly available.
• Using Apify doesn’t provide me with any hidden or private information—it simply automates the retrieval of data anyone could manually view.
• This approach ensures my directory is visually appealing while saving me hours of work.

By leveraging tools like Apify, you can enrich your directory with details that would otherwise take significant effort to compile manually. In the next section, we’ll explore another powerful workflow for enrichment: using Perplexity AI to gather up-to-date and listing-specific details.

How To Use Perplexity AI to Enrich Your Directory Data

When it comes to research and generating additional content for your directory, Perplexity AI is an absolute game changer. Unlike other tools, Perplexity AI combines the conversational ease of a chat model with real-time internet browsing. This means it doesn’t just generate responses—it backs them up with sourced data from the web.

What Is Perplexity AI?

Perplexity AI allows you to ask specific questions and retrieves answers directly from the internet, complete with references. For example, if you want to know what events are part of a specific race series, you can ask Perplexity AI, and it will search for the information, providing accurate results along with links to the sources.

How I Use Perplexity AI for Enrichment

I’ve used Perplexity AI in The Running Directory to:

1. Research Individual Listings:
   • For run clubs, I used Perplexity AI to find additional details like meeting schedules, notable events, or member reviews.
2. Dive Deeper Into Race Series:
   • When a race was part of a larger series, I asked Perplexity AI to identify the other events in the series and their respective details.

This workflow has been invaluable for quickly enriching listings with meaningful and specific content that makes the directory more valuable to users.

Other Use Cases for Perplexity AI

• Finding reviews, links, or detailed descriptions for listings.
• Researching historical or unique details about businesses, events, or clubs.
• Gathering supporting content to make listings more comprehensive.

How to Use Perplexity AI Programmatically

If you find Perplexity AI useful, you can scale your workflow by using its API in tools like make.com. Here’s how:

1. Test Queries First:
   • Before scaling, experiment with Perplexity AI manually to ensure it retrieves the information you need.
2. Set Up an Automated Workflow:
   • Use tools like Make.com to send questions to Perplexity AI’s API programmatically.
   • Example: Ask “What events are part of the Boston Marathon series?” and have the response automatically saved to Airtable.
3. Review and Store Results:
   • Double-check the AI’s answers for accuracy before adding them to your directory.

Things to Keep in Mind

• While Perplexity AI is incredibly powerful, it’s not perfect. There’s always a risk of retrieving inaccurate or incomplete information.
• Always verify the AI’s results before publishing them to maintain the credibility of your directory.

By incorporating Perplexity AI into your enrichment process, you can significantly enhance the depth and quality of your listings without spending hours researching manually. In the next section, we’ll move on to cleaning and standardizing your directory data for better usability and SEO.

How To Clean Your Data

Now that we’ve covered how to find your seed data and enrich it, your database is likely starting to grow. But with growth comes a common problem: inconsistent formatting.

For example, when I worked on The Running Directory, I noticed race distances were entered in all sorts of formats—“5km,” “5K,” “Five kilometers,” and so on. This inconsistency can create issues for key features like searching, filtering, and even SEO. It also impacts the overall professionalism of your directory.

Another aspect of cleaning data is creating custom tags to highlight specific attributes of your listings, such as “Beginner-Friendly,” “Trail Run,” or “Marathon.” These tags make your directory easier to browse and more user-friendly.

This process of standardizing, formatting, and organizing your database is what I call data cleaning. It’s just as important as finding and enriching your data because it:

• Improves your SEO by ensuring data is well-structured and easy for search engines to index.
• Enhances search and filtering on your site for better usability.
• Makes your directory look polished and professional.

How to Clean Data in Airtable Using Automations and OpenAI

One of the reasons I love Airtable is that it’s more than just a database—it’s a powerful tool for automation and customization. For data cleaning, I use Airtable Automations paired with OpenAI’s GPT models to streamline the process.

What Are Airtable Automations?

Airtable Automations is a built-in tool that allows you to automate workflows directly within Airtable, similar to Make or Zapier. One of its most powerful features is the Scripting Action, which lets you write custom JavaScript to process your data. You can even make API calls to third-party services like OpenAI.

How I Use OpenAI for Data Cleaning

Here’s my step-by-step workflow for cleaning data in Airtable:

1. Write a Prompt in OpenAI

• Start by crafting a prompt in OpenAI’s playground that specifies how you want your data to be formatted.
• For example, to standardize race distances, your prompt might look like this:
• "Format the following race distance into 'X km' format: {current_value}."

2. Set Up an Airtable Automation

• Create an automation in Airtable that triggers whenever a new record is added or updated.
• Use the Scripting Action to pull the record’s current values (e.g., the race distance).

3. Make an API Call to OpenAI

• Use JavaScript in the Scripting Action to send the current values to OpenAI’s API.
• Include your prompt along with the data, and let OpenAI process and return the cleaned result.

4. Parse and Store the Results

• After receiving the response from OpenAI, parse the cleaned value and update the relevant field in Airtable.
• For example, replace “Five kilometers” with “5 km” in the distance field.

Example Use Cases for Data Cleaning

• Standardizing Formats: Convert inconsistent data into a uniform structure (e.g., race distances, phone numbers, or addresses).
• Generating Tags: Use OpenAI to analyze descriptions and assign relevant tags like “Trail Run” or “Beginner-Friendly.”
• Fixing Common Errors: Correct capitalization, remove unnecessary punctuation, or reformat dates.

This method combines the flexibility of Airtable with the intelligence of OpenAI, allowing you to clean large amounts of data quickly and accurately. While it may require some initial setup, the time saved—and the improvement in data quality—is well worth it.

And that's it - let's recap some key points.

Building a successful directory isn’t about having the most listings—it’s about offering the highest-quality content. From curating your initial data to enriching and cleaning it, focusing on accuracy, relevance, and usability will set your directory apart. This guide has shown you how to lay the groundwork for a reliable and valuable resource, step by step.

Here are the key takeaways:

1. Quality Over Quantity:
   Starting with a smaller dataset of accurate and curated information is far more effective than relying on scraping, which often leads to outdated or inaccurate content.
2. Finding Seed Data:
   Use reliable sources like Google, blogs, and social media to uncover well-structured, up-to-date content that forms the foundation of your directory.
3. Leveraging Tools to Save Time:
   • Airtable Web Clipper: Simplifies the process of collecting and organizing data directly into your database while browsing.
   • Apify: Automates the retrieval of public data, like images and descriptions, to enrich your listings.
   • Perplexity AI: Provides up-to-date, listing-specific details to make your content more comprehensive and valuable.
4. Data Cleaning and Standardization:
   Cleaning and formatting your data consistently ensures better search functionality, improved user experience, and enhanced SEO. Tools like Airtable Automations and OpenAI can streamline this process efficiently.

A directory that prioritizes quality content creates trust and loyalty among its users, establishing itself as a go-to resource in its niche. By implementing these strategies, you’re not just building a directory—you’re creating a platform that users will rely on and recommend. Now, it’s time to put these steps into action and bring your vision to life!