Web Scraping Services in Mexico

Mexico's federal data protection law applies to private parties, with INAI as the supervisory authority. Reform discussion has been ongoing, which is a reason to scope conservatively rather than to wait.

Our position is the same as in every market: we do not collect or resell personal data. No CURP, no individual RFC, no personal identifiers, no reviewer names or profiles or histories.

What that means in scope

• Product, price and availability data from public pages sits outside the personal data question.
• Seller identity is captured as a business characteristic where displayed, and we distinguish business RFC from individual RFC.
• B2B contact data only where a lawful basis exists for your intended use, which we ask about before scoping.
• No credentialed access, no account creation, no client credentials.

We provide a written methodology document and a DPA before signature. We will not certify an engagement as LFPDPPP-compliant, because compliance depends on your purpose and basis rather than only on collection method.

Two features shape a useful Mexican dataset, and merging either into a headline price destroys it.

Instalments are a pricing mechanic

• Interest-free instalment plans are prominent on higher-value items and frequently what shoppers compare.
• Two listings at the same price differ if one offers twelve interest-free months and the other three with interest.
• Terms differ by seller on the same product, so the offer set matters.

We capture count, amount and interest-free status as separate fields and do not compute an effective price. Whether terms matter depends on your buyer, and that judgement is yours — the same position as in Brazil and Turkey.

Store-level pricing on formal retail

Formal retail here shows genuine price variation by store and region, so a national figure averages markets that behave differently. We put a store identifier on every record where the retailer publishes store-level pricing, and we design the store set with you rather than maximising it.

Cost scales with stores times SKUs times frequency, so store design is the main lever. We sample one store per price zone to remove redundancy, weight by revenue-relevant regions, and add a rotating low-frequency sweep to confirm the dense sample still represents the wider estate.