This Powerful AI Tool Lets You Scrape Anything You Can Think Of (Insane Use Cases with Apify)

I found an AI-powered scraping platform that changed how I collect web data and build automations. Apify turns public web content into structured data you can feed into AI models, automate workflows, and even power products and websites. I use it dozens of times a day to pull data from Zillow, TikTok, Facebook Ads Library, Google Maps, Amazon, and more. Below I’ll walk through what Apify does, how I use it, practical use cases, integration patterns, best practices, and a few automation blueprints you can implement right away.

Table of Contents

• Why Apify is a game changer for web scraping and automation
• Getting started: console, store, and saved tasks
• Three high-impact use cases you can implement today
• Real estate example: scraping Zillow for actionable deals
• Integrations: how to glue Apify into your stack
• Practical mini-workflows you can implement
• Best practices, legal considerations, and reliability tips
• Costs and promotions
• Examples of outputs and how I transform them
• How teams are already using scraping + LLM workflows
• Multimedia and content suggestions
• Meta description and tags
• Call to action
• FAQ

Why Apify is a game changer for web scraping and automation

At its core Apify is an actor-based scraping and automation platform. Actors are pre-built scrapers and integrations that can crawl websites, collect structured outputs (JSON, CSV), and pump that data into other tools. What makes it powerful is the combination of:

• Pre-built actors for popular sites like Zillow, TikTok, Facebook Ads Library, Google Maps, Amazon, and many niche services
• Scheduleable runs so you can collect fresh data on a repeat cadence
• Storage and run history that keeps results accessible for troubleshooting or chaining into workflows
• Integrations and webhooks with tools like Make (formerly Integromat), Zapier, Slack, Gmail, Google Drive and LLM services
• Developer features to customize scraping logic or build your own actor

Put simply, Apify turns the messy web into structured, actionable data you can use inside an LLM, inside an app, or push to a client automatically.

Getting started: console, store, and saved tasks

Once you log into the Apify console, the fastest path to results is the Apify Store. Think of the store as an app marketplace for scrapers and automation actors. You can search by site or use case—

• Search “TikTok” to find scrapers that extract shop products or trending posts
• Search “Facebook ads” to pull competitors’ ad creatives from the Ads Library
• Search “Zillow” for real estate scrapers that return listings, ZIP-code results, comps, and more

Each actor includes a usage guide that explains required inputs, output fields, and run options. For repeat work, save a configuration as a saved task—then run, schedule, and store outputs without rebuilding inputs each time.

Example: Save a TikTok trends task

I keep saved tasks for the social platforms I use most: TikTok, Instagram, and Facebook. For TikTok I upload a list of competitor usernames, run the actor, and get a JSON that shows recent posts, views, and other metrics. I copy that JSON into ChatGPT and ask it to return the top five performing URLs and a short rationale. In seconds I have a prioritized list of content ideas to recreate or iterate on.

Three high-impact use cases you can implement today

Apify is versatile, but here are three use cases that showcase how scraping plus automation multiplies value.

1. Power products and websites with live scraped data

You can build a public-facing tool or SaaS feature and let Apify run in the background as the data engine. For example, a “best time to post” tool can collect posting times from a list of competitor accounts, analyze when engagement is highest, and email recommendations to a user.

How that typically looks under the hood:

1. A user fills a form on your website and clicks submit.
2. The website sends a webhook to an automation platform like Make or Zapier.
3. The automation triggers an Apify actor that scrapes competitors’ posting times and engagement.
4. The actor returns structured data to the automation workflow.
5. An LLM or rules engine analyzes the data and generates a user-friendly email or PDF.
6. The automation sends the result to the user via email or stores it in Google Drive.

This pattern works for any vertical: social media insights, real estate comps, market price trackers, product availability dashboards, and more.

2. Generate creative briefs from competitors’ ads

Creative brief generation used to be painfully manual. Now you can scrape an entire brand’s Facebook Ads Library, collect all running creatives, and feed the dataset into an AI that produces a multi-page creative analysis. The output can include:

• Key findings and themes across ads
• Timing, durations, and hook types
• Call-to-action breakdowns and landing page patterns
• Suggested creative concepts and scripts

In practice I export the scraped ad dataset and upload it to an AI brief builder like DeepAgent or ask ChatGPT to produce a structured brief. The brief includes per-ad breakdowns and aggregated recommendations that creative teams can execute quickly.

3. Lead generation at scale

Need B2B contacts in a niche? Use a lead-finder actor that scrapes business directories, LinkedIn pages, and company websites. You can filter by job title, location, company size, industry, revenue, and more. Once you have the list:

• Store the CSV or JSON in Google Drive or your CRM
• Use an LLM to craft personalized outreach messages
• Automate follow-ups via Gmail or your outreach platform

I once pulled 25 leads for a targeted niche and paid less than a dime in platform costs for the entire run. The economics on these scrapers make targeted outreach campaigns affordable and fast.

Real estate example: scraping Zillow for actionable deals

Real estate agents and investors can extract massive value by automating ZILLOW searches. A ZIP-code scraper lets you set a minimum and maximum price range, filter by days on market, transaction type (for sale by agent, for sale by owner, sold), and more. The actor returns the raw fields—price, address, broker, days on market, listing URL, and additional property details.

Possible products and automations:

• A neighborhood alert service that emails buyers when a property fits their criteria
• An investor dashboard showing properties on market longer than six months
• An agent prospecting tool that finds FSBO listings or expired listings for outreach

Having this data as structured output is far more useful than manually scanning Zillow. You can feed results into an LLM to generate outreach templates, or into a CRM to automate follow-ups.

Integrations: how to glue Apify into your stack

Where Apify really shines is not just scraping but how easily it integrates with your existing tools:

• Make (Integromat) or Zapier to orchestrate workflows and conditional logic
• Google Drive for storing CSVs, JSON, and PDFs
• Gmail to automate messaging
• Slack to send real-time alerts
• LLMs like ChatGPT for transforming raw output into insights, briefs, or content

Typical flow: an automation sends a webhook to Apify, Apify runs an actor and returns results, Make processes the JSON (filter, map, aggregate), then forwards the result to ChatGPT to generate human-readable content, and finally the automation delivers it via email or stores it in a shared drive.

Scheduling and storage

Saved tasks and run history let you schedule scrapes. Once scheduled, you can have fresh datasets pushed to Google Drive or your database. Storage makes it easy to backtest or analyze changes over time, which is invaluable for trend detection and longitudinal analysis.

Practical mini-workflows you can implement

Here are short, reproducible workflows you can build in hours.

TikTok trend scanner

1. Saved task: upload competitor usernames to the TikTok actor.
2. Schedule daily runs.
3. Webhook results to Make.
4. In Make, pass the JSON to ChatGPT with the prompt: please find the top five URLs from this data set and rank by views.
5. Send the top five as an email or Slack message to your content team.

Automated ad creative brief

1. Run a Facebook Ads Library scraper on a competitor account.
2. Download the full dataset as JSON.
3. Upload JSON to an AI brief generator or call ChatGPT with a structured prompt to produce a PDF creative brief.
4. Store the final PDF in Google Drive and notify the creative team via Slack.

Lead capture and drip outreach

1. Set up a lead-finder actor with filters for title, location, and industry.
2. Run and save results to Google Drive or your CRM.
3. Use an LLM to generate personalized outreach messages based on company and title data.
4. Automate email sending with Gmail or an ESP and schedule follow-ups.

Best practices, legal considerations, and reliability tips

Scraping can be powerful, but it comes with responsibilities and technical constraints.

• Respect terms of service—some sites disallow scraping. Always read the target site’s terms and consider contacting the owner for permission if usage is heavy.
• Rate limits and throttling—don’t overwhelm target servers. Use polite scraping settings and built-in actor options to mimic human traffic patterns when necessary.
• Data privacy—avoid collecting sensitive personal data or using scraped data in ways that violate privacy regulations like GDPR or CCPA.
• Plan for change—sites change markup frequently. Monitor actor run failures and set up alerts when scrapers break.
• Store raw outputs so you can reprocess if scraping logic needs adjustment.

Costs and promotions

Apify offers a free tier that’s great for experimenting. Paid plans add concurrency, longer run times, and more storage. If you’re evaluating paid plans, a promo code can reduce initial costs. I recommend starting with a free account, building a few saved tasks, and scheduling one or two recurring runs to validate your product or automation idea before committing to a paid plan.

Examples of outputs and how I transform them

Typical outputs are JSON or CSV. I usually:

• Send JSON into ChatGPT and ask for a concise summary, top-N list, or an actionable brief.
• Use Make to convert JSON into a CSV and store it in Google Drive for downstream tools.
• Send key fields to a database and trigger further automations like email sequences.

For example, a TikTok dataset returned view counts, post URLs, captions, and post dates. I asked the LLM to identify the top five posts by views and provide a one-line reasoning for each. Within seconds I had a prioritized content plan to test.

How teams are already using scraping + LLM workflows

Marketing teams use the pattern to generate content briefs and A/B test hypotheses. Product teams use scraped competitor feature lists to inform roadmap decisions. Sales teams use lead scrapers to populate CRMs and run targeted outreach. Real estate investors use property scrapers to find off-market or stale listings to flip or contact directly. The common theme is repeatable, scheduled data collection feeding automated analysis and action.

Multimedia and content suggestions

When publishing a guide or product page that describes these workflows, consider including:

• A flowchart image showing the webhook → Apify actor → Make → LLM → deliver path. (Alt text: Flowchart showing scraping data flow from Apify to Make to an LLM and output delivery.)
• Screenshots of an actor configuration, saved task list, and stored JSON output. (Alt text: Screenshot of Apify Store actor configuration and saved tasks.)
• An example PDF creative brief generated from scraped ads. (Alt text: Example multi-page creative brief produced by AI from scraped ad data.)

Call to action

If you want to experiment, create a free Apify account and search the Apify Store for actors that match your top three use cases. Start with a saved task, schedule one run per day, and route the output into an LLM to generate actionable summaries. Try building one small automation end-to-end—scrape, transform, deliver—and you’ll see how quickly scraping can become the engine behind content, leads, and product features.

FAQ