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Marketing data extraction

Ads, reviews and rankings, delivered as clean data.

We collect ads and creatives, platforms, landing pages and reviews from public ad libraries and review sites.

Built around your competitors and markets, delivered on your schedule.

Get a free sample from your own sources within 24 hours and see the data before you commit.

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advertisers.csvsample data
Illustrative sample of scraped advertiser data. Select a brand to see how many ads it runs over time.
brandplatformlive_adsdays_runningstatus
Social384▲ 2
Search270unchanged
Display260▼ 1
Social14new
Display038ended
Illustrative data. Select a brand to see how many ads it runs over time.

Trusted by 500+ companies, startups and individuals.

Rock the Rankings
Iceland Travel
Blue Orange
myrunway
boxtribe
Kore Real Estate Group
42matters
Udemy
nextflat
Crunch
Swell Inc.
Sunday
Wildcat Capital Management
XCStats
Distribusion
catchhotels
QAPA
Product Folks
Client logo
Quotient
Saw.com
Markmi
Client logo
Tensile Capital Management
Car Geeks Collision
ParcelNinja
Packt
Pioneer Interests
Syndigo
Luxury Family Rentals
flowingbee
Moshbit
Velocity by design
Auditi
mxney
What you get

Every field you need from an advertising source.

These are the usual building blocks. We add or drop fields to fit your project, and the free sample shows exactly what comes back.

Ad

What the ad says and shows.

  • ad_id
  • ad_text
  • headline
  • call_to_action
  • format
  • creative_url
  • landing_page_url
  • language
  • ad_variations

Advertiser

Who is advertising. Public business details only.

  • advertiser_name
  • brand
  • page_url
  • website
  • country
  • industry
  • social_links
  • page_category

Reach and spend

How far it goes, where it is published.

  • impressions_range
  • spend_range
  • currency
  • platforms
  • placements
  • audience_country
  • audience_age_range
  • reach_estimate

Timing and status

When it runs, and when it stops.

  • first_seen
  • start_date
  • end_date
  • active
  • days_running
  • live_ads_count
  • status_history

Reviews and rankings

How customers and search engines see a brand.

  • rating
  • review_count
  • review_text
  • review_date
  • search_keyword
  • search_position
  • result_url
  • brand_mentions

Source and history

Where each record came from, and how it changed.

  • first_seen
  • last_seen
  • days_listed
  • listing_status
  • source_urls
  • sources_count
  • last_checked
  • duplicate_of

On requestSocial media posts, brand mentions, promotions and coupon codes, landing page changes and the tracking tags used on sites, where they are public.

Who uses it

How teams put marketing data to work.

Agencies and consultancies

Watch what your clients' competitors advertise, on which platforms and for how long, and report on it without screenshots.

Typical refresh: daily to weekly

Brands and in-house teams

See when competitors launch campaigns, change offers or stop ads, and compare ratings and rankings in your market.

Typical refresh: daily

Ad tech and analytics tools

Feed your product with ad, creative and ranking data from many sources, matched to one record per advertiser.

Typical refresh: daily

Researchers and analysts

Study how advertising, reviews and search rankings change over time, from one consistent history.

Typical refresh: weekly to monthly
Why it is hard

Why marketing data is harder than it looks.

Ads and rankings change daily and are shown differently to everyone. These are the five problems we plan for, and how we handle each.

The problem

Ads come and go quickly.

Campaigns start and stop within days, and ad libraries show what is running now, not what ran last month.

How we handle it

Frequent re-checks store each ad's first and last seen date, so you get launches, stops and run length, not just a snapshot.

The problem

Reach and spend are ranges.

Libraries publish bands such as "1k-5k" or "$100-500", and some publish nothing at all for commercial ads.

How we handle it

We store each range exactly as published, note when a field is not published, and never turn a range into an invented exact figure.

The problem

Results depend on place and device.

Search and review pages differ by country, language, device and time, so one reading rarely matches what a customer sees.

How we handle it

We fix the location, language and device for every run and store them with each row, so rankings stay comparable over time.

The problem

The same brand has many names.

Advertiser pages, brand names, review profiles and store listings rarely match one to one.

How we handle it

We match them by name, website domain and country into one brand record that keeps every source.

The problem

Sites block and change.

Ad libraries and review sites use bot protection and redesign their pages, and scrapers quietly return half the rows.

How we handle it

Every pipeline is monitored with row-count and field checks. When a site changes or blocks us, we fix it. Maintenance is part of the service.

How it works

From your list of competitors to a live data feed.

Tell us what you need

Share the competitors or sites, the platforms and countries, and the fields. A short call or a message is enough.

See a free sample

Within 24 hours of the call, depending on the sources, you get a sample from your own sources. You see the fields, the quality and the refresh rate before you commit.

Pick the schedule

Hourly, daily, weekly or monthly. We scope the price once you have seen the sample.

Receive and rely on it

Data arrives as CSV, JSON, Excel, Google Sheets, Airtable, in your database, through an API or in cloud storage. We monitor it and fix what breaks.

Common questions

Straight answers.

What teams ask before they start.

What marketing and advertising data can you collect?

Public ads from ad libraries, with advertisers, formats, dates, platforms and landing pages, plus reviews, ratings, search rankings and brand mentions. On request we also collect promotions, coupon codes and social media posts. Tell us the fields you need and the free sample shows what is possible.

Can you track new ads and stopped campaigns?

Yes. We re-check your sources on a schedule from hourly to monthly and store every change. You get each ad's first and last seen date, its run length and the number of live ads per brand over time, not just a snapshot. When an ad disappears from a library, we mark it as ended, but we cannot see why it was stopped.

How do you match the same brand across sites?

We match brands by name, website domain and country, and keep every source on one record. Anything we cannot match with confidence is marked, not guessed.

Which sites and countries can you cover?

Public ad libraries, review sites, search results, social media pages and brand websites, in any country and language. If a source is not practical, for example because of a login wall or heavy blocking, we tell you upfront, before you commit to anything.

Is scraping marketing websites legal?

We collect publicly available data only, such as the ads, ratings and rankings any visitor can see. Rules differ by country and by site, a site's terms may restrict automated access, and reviews and posts can include personal details such as reviewer names, which are personal data under laws like GDPR. We flag risky sources and fields before we build. We are not lawyers, so for sensitive uses we recommend checking with your own counsel.

How do I receive the data?

CSV, JSON, Excel, Google Sheets, Airtable, your own database, an API or cloud storage, on a schedule you choose, ready to feed your reports or dashboards.

How much does it cost, and how fast can we start?

Pricing depends on sources, volume and frequency. We scope it after a free discovery call and sample. Most samples are ready within 24 hours of the call, depending on the sources.

Your free marketing data sample, built on your actual sources.

Tell us the competitors, platforms, countries and fields you need. We reply with a plan and a sample.

Prefer to talk first? Book a call with the founder

Lazar Telebak, founder of REData Analytics

Lazar Telebak

Founder, REData Analytics

You work directly with the person who builds your data feed. In 10+ years he has worked with 500+ startups, agencies and companies, from one-time extractions to long-running systems processing tens of millions of records.

Founder profile on LinkedIn ↗