We extract credit card offers, points valuations, airline reviews, and loyalty programme data from The Points Guy. 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 Credit Card Offers objects from thepointsguy.com. All fields typed and schema-versioned.
"card_name": "Chase Sapphire Preferred", "issuer": "Chase", "annual_fee": 95, "intro_bonus": "60,000 points", "bonus_spend_req": 4000, "bonus_timeframe": "3 months", "regular_apr": "21.49% to 28.49% Variable", "foreign_transaction_fee": "None"
| # | card_name | issuer | network | annual_fee | intro_bonus | bonus_spend_req |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Points Valuations objects from thepointsguy.com. All fields typed and schema-versioned.
"programme_name": "Chase Ultimate Rewards", "programme_type": "Credit Card", "valuation_cents": 2.05, "prior_valuation_cents": 2.0, "trend": "up", "last_updated": "2023-10-01"
| # | programme_name | programme_type | valuation_cents | prior_valuation_cents | trend | last_updated |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Airline & Hotel Reviews objects from thepointsguy.com. All fields typed and schema-versioned.
"airline_hotel_name": "Emirates", "cabin_class": "First Class", "route_location": "JFK to DXB", "rating_score": 9.2, "pros_list": "['Shower spa', 'Dom Perignon']", "author": "Zach Honig"
| # | review_title | author | publish_date | airline_hotel_name | route_location | cabin_class |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flight Deals objects from thepointsguy.com. All fields typed and schema-versioned.
"deal_title": "Fly to Paris for $350 round trip", "origin_airports": "['JFK', 'EWR']", "destination_airports": "['CDG', 'ORY']", "airline": "Air France", "price": 350, "cabin": "Economy"
| # | deal_title | origin_airports | destination_airports | airline | price | cabin |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Editorial Articles objects from thepointsguy.com. All fields typed and schema-versioned.
"article_id": "tpg-98421", "title": "Maximizing British Airways Avios", "category": "Loyalty Programmes", "author": "Benji Stawski", "publish_date": "2023-09-15", "tags": "['Oneworld', 'Avios']"
| # | article_id | title | category | tags | author | publish_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles dynamic content on The Points Guy, resolving complex affiliate redirects, tracking changing credit card offers, and extracting structured loyalty programme valuations.
Extract sign-up bonuses, annual fees, spend multipliers, and introductory APR periods directly from comparison tables and review pages.
Capture cents-per-point values and historical trend analysis for every airline, hotel, and credit card loyalty programme.
Unroll complex redirect chains to identify the final advertiser destination URLs for credit card applications and travel bookings.
Extract rating scores, cabin classes, pros and cons lists, and bottom-line summaries from detailed travel reviews.
Monitor origin and destination airports, prices, airlines, and alliance data from published flight deal alerts.
Structure transfer partner lists, elite status tier requirements, and point expiration policies from comprehensive guide articles.
Capture article metadata including publication dates, update timestamps, author names, and category tags.
Execute Playwright sessions to hydrate dynamic calculators, interactive tables, and client-side rendered offer details.
Run daily or weekly pipelines to catch offer changes, valuation updates, and new article publications immediately.
Brief in. Clean data out.
Provide target categories, article tags, or specific credit card issuer pages. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, network interceptors for affiliate links, and proxy rotation.
Schema validation, null-rate checks, and redirect resolution testing before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel sites deploy sophisticated affiliate networks and dynamic content loading. Here is how we extract clean data.
Credit card application links are routed through multiple affiliate networks. Our network interception layer follows the redirect chain to capture the final destination URL, ensuring you know exactly which offer is being promoted.
Editorial sites use varying templates for reviews, news, and guides. We deploy resilient CSS and XPath selector chains that adapt to different page layouts, ensuring consistent data extraction regardless of the article format.
Points valuation calculators and dynamic offer tables require client-side execution. We use Playwright to render the full DOM, capturing data that headless HTTP clients miss entirely.
We maintain a hash index of last-seen values for credit card offers and points valuations. Subsequent runs only push diffs, reducing downstream processing load and providing a clean changelog.
Certain flight deals and credit card offers are geo-restricted. We route requests through region-specific residential proxies to ensure we capture the exact content presented to target demographics.
Credit card issuers track competitor sign-up bonuses, annual fee changes, and spend category multipliers to optimise their own products.
Affiliate networks audit link placements, redirect chains, and promotional terms across major publishers to ensure compliance.
Flight search engines integrate points valuations to show users the true cash value of booking with miles versus currency.
Personal finance applications power their wallet optimisation engines using structured data on card perks and bonus categories.
Analysts track historical trends in points valuations and loyalty programme devaluations to assess market health.
Publishers identify high-traffic travel topics and review formats to inform their own editorial calendars.
"The Points Guy holds the industry standard for points valuations and credit card offer history, but accessing this data programmatically requires complex redirect resolution and continuous monitoring."
Credit card offers and flight deals change daily. Relying on manual data entry leads to stale information and broken affiliate links. DataFlirt automates the extraction of dynamic tables, resolves redirect chains, and delivers structured JSON directly to your warehouse, ensuring your downstream applications always reflect the latest market conditions.
Everything supported by our thepointsguy.com 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 and deduplication. Playwright handles JavaScript rendering and interactive elements. Combined via scrapy-playwright middleware.
Custom network interception layer captures HTTP 301 and 302 redirects, logging the entire chain to extract the final affiliate destination URL.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About thepointsguy.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from editorial sites is generally permissible under applicable law. DataFlirt targets only public, non-authenticated articles, reviews, and offer tables. We do not extract personal data or circumvent authentication walls.
We use network interception during the browser session to capture the full redirect chain. This allows us to extract the final destination URL of the credit card application or travel booking, bypassing intermediary tracking domains.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series record for points valuations, allowing you to track devaluation trends historically.
Pipelines can be configured to run daily or weekly. For critical offer tracking, daily runs ensure you capture limited-time sign-up bonuses as soon as they are published.
Yes. We can deliver full editorial content as clean HTML or structured markdown, stripping out advertisements and navigation boilerplate.
Our packages start at defined category tracking, such as all credit card reviews or points valuations, with weekly delivery. We price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 100 articles or credit card offers as part of the scoping process, so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a historical archive of points valuations or a continuous feed of credit card offers, we scope, build, and operate the pipeline. Tell us what you need.
