We extract credit card offers, points valuations, flight routing rules, and award charts from MileValue. 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 milevalue.com. All fields typed and schema-versioned.
"card_name": "Chase Sapphire Preferred", "issuer": "Chase", "signup_bonus": 60000, "bonus_currency": "Ultimate Rewards", "min_spend": 4000, "annual_fee": 95
| # | card_name | issuer | network | signup_bonus | bonus_currency | min_spend |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Points Valuations objects from milevalue.com. All fields typed and schema-versioned.
"program_name": "American Airlines AAdvantage", "program_type": "Airline", "value_cents": 1.5, "transfer_partners": "['Bilt', 'Marriott']", "alliance": "Oneworld", "url": "https://milevalue.com/points-valuations"
| # | program_name | program_type | value_cents | previous_value_cents | trend | last_updated |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Travel Articles objects from milevalue.com. All fields typed and schema-versioned.
"article_id": "post-48291", "title": "How to Book Emirates First Class", "author": "Sarah Page", "publish_date": "2025-10-14", "category": "Award Booking", "comment_count": 24
| # | article_id | title | author | publish_date | category | tags |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Award Charts objects from milevalue.com. All fields typed and schema-versioned.
"airline": "Avianca LifeMiles", "region_from": "North America", "region_to": "Europe", "class_of_service": "Business", "points_required": 63000, "fuel_surcharges": false
| # | airline | region_from | region_to | class_of_service | points_required | partner_airlines |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Flight & Hotel Reviews objects from milevalue.com. All fields typed and schema-versioned.
"review_type": "Flight", "property_or_flight": "Qatar Airways Qsuite", "rating": 4.8, "cabin_class": "Business", "pros": "['Privacy doors', 'Dine on demand']", "cons": "['Cabin temperature']"
| # | review_type | property_or_flight | brand | rating | cabin_class | flight_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our MileValue scraper converts unstructured blog content into queryable datasets: extracting credit card offers, points valuations, and award charts while resolving affiliate redirects.
Extract sign-up bonuses, minimum spend requirements, annual fees, and earning multipliers from dedicated card review pages.
Capture cents-per-point valuations for airline miles, hotel points, and transferable bank currencies, tracking changes over time.
Convert text-heavy award booking guides into structured region-to-region pricing tables for economy, business, and first class.
Follow tracking links through multiple redirects to capture the final destination URL and actual offer ID.
Extract full article text, author metadata, publish dates, and categories for content syndication or LLM training.
Parse complex airline routing rules, including stopover policies, open jaws, and maximum permitted mileage.
Monitor top credit card offer pages daily and emit diffs when sign-up bonuses or minimum spend requirements change.
Automatically classify content into airlines, hotels, credit cards, or general travel advice based on tags and NLP.
Extract pros, cons, ratings, and verdicts from detailed flight and hotel review articles.
Brief in. Clean data out.
Provide target categories, specific card issuers, or points programs. We design the extraction schema together.
We configure Scrapy crawlers, NLP parsing rules for unstructured text, and proxy rotation for consistent access.
Schema validation, null-rate checks, and affiliate link resolution testing before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting structured data from a WordPress-based blog requires advanced DOM parsing and link resolution. Here is how we maintain data quality.
Travel blogs often embed critical data like sign-up bonuses and minimum spend requirements within paragraphs. We use custom regex and NLP models to extract these entities into strict JSON schemas.
Credit card links on MileValue route through multiple affiliate networks. Our Playwright instances follow the full redirect chain to capture the final bank URL, ensuring you track the actual offer destination.
WordPress themes update frequently, breaking standard CSS selectors. We rely on underlying DOM structures, semantic HTML tags, and text-pattern matching to ensure uninterrupted extraction.
Credit card sign-up bonuses change without notice. We maintain a hash index of active offers and run daily diffs, alerting your systems immediately when a bonus increases or decreases.
High-traffic blogs use Cloudflare and aggressive caching. We utilise residential proxies and tailored headers to bypass WAF challenges and ensure we scrape the live version of a page, not a stale cache.
Credit card issuers monitor affiliate sites to track competitor sign-up bonuses, annual fees, and marketing positioning.
Award travel search engines ingest points valuations and routing rules to power their internal pricing algorithms.
Marketing agencies track which credit cards are promoted heavily across top travel blogs to estimate affiliate payouts.
Travel portals aggregate flight reviews, hotel guides, and destination advice to enrich their own platforms.
Analysts track the frequency and magnitude of credit card sign-up bonuses to gauge consumer credit demand and bank acquisition budgets.
LLM developers use structured travel guides and award booking tutorials to train travel-specific conversational agents.
"MileValue holds a dense repository of credit card offers and award travel rules, but extracting structured data from blog format content requires precise parsing."
Travel points data is highly volatile. Sign-up bonuses change daily, and award charts devalue without notice. DataFlirt builds pipelines that monitor these changes, resolve affiliate redirects, and deliver clean, structured data so your team can focus on analysis.
Everything supported by our milevalue.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 resolves affiliate redirects and handles JavaScript-heavy page elements.
We maintain pools of residential ISP proxies to bypass aggressive caching and WAF rules, ensuring we scrape live content.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About milevalue.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available blog content, credit card offers, and points valuations is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
We use custom regex patterns and NLP models to identify entities like sign-up bonuses, minimum spend requirements, and points values within standard paragraphs, converting them into strict JSON schemas.
Yes. Our Playwright instances follow the entire redirect chain for credit card application links, capturing the final bank URL and specific offer ID so you know exactly which product is being promoted.
We typically monitor top credit card offer pages daily to detect changes in sign-up bonuses or annual fees, emitting diffs immediately when a change is detected.
Yes. We can traverse the entire site pagination and category archives to extract historical travel guides, award charts, and flight reviews from the beginning of the site's publication.
We utilise residential proxies, realistic browser fingerprints, and cache-busting headers to ensure we bypass WAF challenges and retrieve the most current version of a page.
Our minimum engagement covers daily tracking of the top 500 credit card offer pages and points valuation tables. For full historical blog extraction, we price based on total page volume.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off extraction of historical flight reviews or a continuous feed of credit card sign-up bonuses - we scope, build, and operate the pipeline. Tell us what you need.
