We extract credit card offers, reward valuations, Aeroplan guides, and loyalty programme updates from Milesopedia. 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 milesopedia.com. All fields typed and schema-versioned.
"card_id": "amex-cobalt", "card_name": "American Express Cobalt Card", "issuer": "American Express", "network": "Amex", "annual_fee": 155.88, "welcome_bonus_points": 15000, "bonus_valuation_cad": 150.0, "minimum_spend": 750.0, "spend_timeframe_days": 30
| # | card_id | card_name | issuer | network | annual_fee | welcome_bonus_points |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Earning Rates objects from milesopedia.com. All fields typed and schema-versioned.
"card_id": "amex-cobalt", "category": "Groceries and Dining", "multiplier": 5.0, "currency": "MR Points", "base_rate": 1.0, "cap_amount": 30000.0, "cap_period": "Annually", "effective_return_pct": 5.0
| # | card_id | category | multiplier | currency | base_rate | cap_amount |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Insurance Coverage objects from milesopedia.com. All fields typed and schema-versioned.
"card_id": "td-aeroplan-visa-infinite", "insurance_type": "Travel Medical", "coverage_amount": 2000000.0, "duration_days": 21, "age_limit": 64, "out_of_province": true, "trip_cancellation": 1500.0, "rental_car_collision": true
| # | card_id | insurance_type | coverage_amount | eligible_persons | duration_days | age_limit |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Travel Reviews objects from milesopedia.com. All fields typed and schema-versioned.
"url": "https://milesopedia.com/en/reviews/flights/air-canada-signature-class/", "title": "Review: Air Canada Signature Class", "author": "Jean-Maximilien Voisine", "date_published": "2023-11-14", "category": "Flight Review", "rating": 4.5, "pros": "['Lie-flat seats', 'Maple Leaf Lounge access']", "cons": "['Inconsistent Wi-Fi']"
| # | url | title | author | date_published | category | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Loyalty Programmes objects from milesopedia.com. All fields typed and schema-versioned.
"programme_name": "Aeroplan", "points_value_cents": 2.0, "transfer_partners": "['Marriott Bonvoy', 'Amex MR']", "transfer_ratio": "1:1", "expiry_policy": "18 months of inactivity", "elite_tiers": "['25K', '35K', '50K', '75K', 'Super Elite']", "alliance": "Star Alliance"
| # | programme_name | points_value_cents | transfer_partners | transfer_ratio | expiry_policy | elite_tiers |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Milesopedia scraper handles every layer of the platform: credit card offers, earning multipliers, insurance tables, and bilingual content normalisation.
Extract annual fees, welcome bonuses, minimum spend requirements, and standard interest rates across all listed Canadian credit cards.
Capture category-specific point multipliers (e.g., 5x on groceries) including annual spending caps and base rates.
Parse complex insurance coverage tables into structured JSON, capturing coverage limits, age restrictions, and eligible trip durations.
Track Milesopedia's internal point valuations (e.g., Aeroplan points in CAD cents) as they update over time.
Map French and English URLs to the same entity record, ensuring no duplicate cards or guides in your final dataset.
Trace outgoing application links through redirect chains to capture the final issuer destination URL.
Extract details from airport lounge reviews and hotel guides, including access requirements and elite status benefits.
Run daily pipelines to detect when a welcome bonus increases or decreases, emitting only the changed records.
Maintain a time-series database of past welcome offers to analyse seasonal trends in credit card marketing.
Brief in. Clean data out.
Provide target categories, such as credit cards, Aeroplan guides, or flight reviews. We design the extraction schema together.
We configure Scrapy crawlers, handle bilingual route mapping, and build table parsers for Milesopedia.
Schema validation, null-rate checks, and duplicate entity detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting financial data requires precision. Here is how we ensure your credit card dataset is accurate and up-to-date.
Milesopedia publishes in both French and English. We map alternate language URLs via hreflang tags to a single primary entity ID, preventing your database from filling with duplicate credit card offers.
Insurance benefits and earning rates are often stored in complex HTML tables with merged cells. Our parsers flatten these structures into standard key-value pairs that load cleanly into SQL databases.
Credit card welcome bonuses change frequently. We maintain a hash index of last-seen values per card. Subsequent runs only push diffs, allowing you to trigger downstream alerts when an offer improves.
Application buttons use internal redirect URLs. We follow these HTTP 301/302 redirects to capture the final destination URL on the issuer's domain.
If Milesopedia redesigns their credit card template, our observability stack flags the resulting null-rate spikes immediately, allowing our engineers to update selectors before your downstream processes fail.
Financial institutions monitor competing credit card offers, welcome bonuses, and earning rates to adjust their own product positioning.
Personal finance apps ingest structured card data to recommend the optimal credit card to their users based on spending habits.
Travel agencies and corporate travel managers track point valuations and transfer ratios to optimise reward redemptions.
Financial news aggregators monitor new travel reviews and loyalty programme updates for curation.
Consulting firms analyse historical welcome bonus trends to understand customer acquisition costs in the Canadian credit card market.
LLM developers use structured financial product data and travel reviews to train specialised personal finance assistants.
"Milesopedia holds the most structured, up-to-date catalogue of Canadian credit card offers and loyalty valuations available on the public web."
Extracting accurate financial data requires parsing complex tables, resolving affiliate redirects, and mapping bilingual URLs. DataFlirt manages this pipeline end-to-end, delivering normalised data directly to your infrastructure so you can focus on analysis.
Everything supported by our milesopedia.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, deduplication, and retry logic, ensuring complete coverage of the Milesopedia sitemap.
Custom middleware maps hreflang tags to merge bilingual content, ensuring your database contains one authoritative record per credit card.
Pipelines run on AWS ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About milesopedia.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated credit card offers, reviews, and guides. We do not extract personal data or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
Milesopedia publishes in both French and English. We use hreflang tags and URL structure to map alternate language pages to a single entity ID. You can choose to receive data in English, French, or both.
We typically configure Milesopedia pipelines to run daily. This ensures you capture welcome bonus changes and limited-time offers within 24 hours of publication.
Yes. Milesopedia uses complex tables for insurance benefits and earning rates. We build custom parsers to flatten these tables into structured key-value pairs suitable for relational databases.
We begin tracking historical changes from the day your pipeline is commissioned. Every pipeline run produces timestamped snapshots, allowing you to build a time-series database of welcome offers.
Our smallest packages start at a defined set of target pages with weekly delivery. For continuous daily updates across the entire catalogue, we price based on compute volume. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 50 credit cards or guides as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of Canadian credit cards or a continuous feed of loyalty programme updates, we scope, build, and operate the pipeline. Tell us what you need.
