We extract forum discussions, Qantas and Velocity points strategies, credit card offers, and flight reviews from Australian Frequent Flyer. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Forum Threads objects from australianfrequentflyer.com.au. All fields typed and schema-versioned.
"thread_id": "104921", "title": "Qantas Classic Reward availability patterns 2026", "subforum": "Qantas Frequent Flyer", "author_username": "PointsHacker99", "post_count": 342, "view_count": 45102, "is_sticky": false, "is_locked": false
| # | thread_id | title | subforum | author_username | post_count | view_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Forum Posts objects from australianfrequentflyer.com.au. All fields typed and schema-versioned.
"post_id": "2491034", "thread_id": "104921", "author_username": "QF_Flyer", "content_text": "Just saw a massive drop of First Class seats on QF1 to LHR for October.", "likes_count": 14, "quotes_count": 0, "post_position": 42, "has_attachments": false
| # | post_id | thread_id | author_username | content_text | content_html | quotes_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for User Profiles objects from australianfrequentflyer.com.au. All fields typed and schema-versioned.
"username": "QF_Flyer", "join_date": "2015-04-12", "message_count": 4192, "reaction_score": 8941, "trophy_points": 145, "frequent_flyer_status": "Qantas Platinum", "location": "Sydney, NSW"
| # | username | join_date | message_count | reaction_score | trophy_points | frequent_flyer_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Credit Card Offers objects from australianfrequentflyer.com.au. All fields typed and schema-versioned.
"card_name": "Qantas Premier Platinum", "bank": "Citi", "bonus_points": 80000, "point_program": "Qantas Frequent Flyer", "minimum_spend": 3000, "annual_fee": 349, "offer_expiry": "2026-12-31"
| # | card_name | bank | bonus_points | point_program | minimum_spend | annual_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flight Reviews objects from australianfrequentflyer.com.au. All fields typed and schema-versioned.
"airline": "Singapore Airlines", "flight_route": "SYD-SIN", "cabin_class": "Business", "aircraft_type": "A380", "rating": 9.5, "author": "SuiteDreamer", "date_flown": "2026-02-14"
| # | review_id | airline | flight_route | cabin_class | aircraft_type | author |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles every layer of the AFF platform: deep forum pagination, nested quotes, credit card offer tracking, and XenForo anti-bot circumvention.
Title, views, replies, and subforum mapping extracted across active and archived boards.
Clean text extraction with nested quotes stripped or mapped independently to preserve context.
Post counts, reaction scores, loyalty tier status, and join dates mapped to every post.
Sign-up bonuses, minimum spend requirements, and annual fees extracted from financial subforums.
Parsing user reports of classic reward drops and availability trends across major alliances.
Extracting Qantas, Velocity, and international carrier reviews to feed sentiment models.
Deep stateful crawling of 100+ page megathreads without missing or duplicating posts.
Residential proxies and Playwright sessions handle bot challenges natively.
Only pull new posts in active threads, reducing compute and downstream processing load.
Brief in. Clean data out.
Provide subforums, thread lists, or keyword sets. We design the extraction schema together.
We configure XenForo parsers, proxy rotation, and Cloudflare circumvention.
Schema validation, nested quote parsing checks, and null-rate monitoring before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Forum scraping requires handling deep pagination, nested quotes, and aggressive anti-bot layers. Here is how we maintain data integrity.
AFF uses Cloudflare to block automated traffic. We use Playwright with AU-based residential IPs to solve JS challenges natively, maintaining valid session cookies for sustained extraction.
Megathreads span hundreds of pages. Our crawler maintains state across paginated boundaries, ensuring every post is captured in chronological order without duplication.
Forum posts heavily utilise nested quotes. We parse the XenForo DOM to separate the original author's text from quoted replies, providing clean text for NLP pipelines.
Instead of re-scraping entire threads, we track the last-seen post ID per thread and only extract new replies, delivering a clean changelog.
We enforce strict rate limits and request delays to respect the origin server's capacity, preventing IP bans and ensuring stable long-term extraction.
Airlines and analysts track public opinion on loyalty programme changes, routing updates, and customer service quality.
Financial institutions monitor competitor sign-up bonus offers, churn strategies, and consumer reception to new card products.
Analysts calculate real-world cent-per-point values based on user reports of successful reward seat redemptions and upgrades.
Tourism boards identify emerging popular routes, seasonal demand shifts, and reward seat availability patterns.
ML teams train NLP models on Australian travel vernacular, airline codes, and loyalty programme terminology.
Hospitality teams track user reports of lounge overcrowding, food quality changes, and entry requirement enforcement.
"Australian Frequent Flyer holds the most dense, unfiltered dataset on Australian airline loyalty, reward seats, and credit card churn."
Extracting forum data requires more than simple HTTP GET requests. XenForo's structure, deeply nested quotes, and Cloudflare protection demand stateful crawling and intelligent parsing. DataFlirt manages the proxy rotation and pagination logic so you receive clean, structured text ready for NLP analysis.
Everything supported by our australianfrequentflyer.com.au scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and Cloudflare challenges.
We maintain pools of residential ISP proxies across AU regions. Rotation happens per-session to maintain XenForo authentication states and bypass rate limits.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About australianfrequentflyer.com.au scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available, non-authenticated forum data is generally permissible. DataFlirt targets only public threads and profiles. We do not extract private messages or circumvent paid membership walls.
We use AU-based residential ISP proxies and full Playwright browser sessions to solve JavaScript challenges natively, maintaining valid session cookies for the duration of the crawl.
Yes. Our parsers traverse the XenForo DOM to isolate the original author's text from quoted replies, ensuring your NLP pipelines receive clean, contextual text.
No. We strictly avoid extracting private conversations or any data requiring user-specific authentication.
We configure incremental pipelines to poll active threads hourly or daily, extracting only new posts since the last run to provide near real-time updates.
Yes. We can configure keyword alerts and targeted extraction rules for specific financial subforums to monitor new sign-up bonuses and minimum spend requirements.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full historical forum dump or a continuous feed of credit card offers — we scope, build, and operate the pipeline. Tell us what you need.
