We extract plugin specifications, bundle inclusions, flash sale pricing, Waves Update Plan tiers, and hardware compatibility from waves.com. Delivered as clean JSON, CSV, or Parquet.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Plugins objects from waves.com. All fields typed and schema-versioned.
"plugin_id": "PLG-SSL-G", "name": "SSL G-Master Buss Compressor", "category": "Dynamics", "format_vst": true, "apple_silicon_native": true, "regular_price": 299.0, "sale_price": 35.99
| # | plugin_id | name | category | developer | format_vst | format_au |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Bundles objects from waves.com. All fields typed and schema-versioned.
"bundle_id": "BND-MERCURY", "name": "Mercury", "plugin_count": 195, "included_plugins": "['SSL G-Master', 'CLA-2A', 'H-Delay']", "regular_price": 7599.0, "sale_price": 1999.0
| # | bundle_id | name | plugin_count | included_plugins | regular_price | sale_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & WUP objects from waves.com. All fields typed and schema-versioned.
"product_id": "PLG-CLA-2A", "product_type": "plugin", "base_price": 249.0, "current_price": 29.99, "discount_pct": 88, "wup_renewal_1yr": 12.0, "wup_max_cap": 240.0
| # | product_id | product_type | base_price | current_price | discount_pct | coupon_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Compatibility objects from waves.com. All fields typed and schema-versioned.
"product_id": "PLG-CLA-2A", "mac_os_min": "10.15", "win_os_min": "10", "supported_daws": "['Pro Tools', 'Logic Pro', 'Ableton Live', 'Cubase']", "ram_requirements": "8 GB", "ilok_required": false
| # | product_id | mac_os_min | mac_os_max | win_os_min | win_os_max | supported_daws |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hardware objects from waves.com. All fields typed and schema-versioned.
"hardware_id": "HW-SGS-EXTREME", "model_name": "SoundGrid Extreme Server-C", "category": "DSP Servers", "io_count": 0, "sample_rate": "96 kHz", "network_protocol": "SoundGrid", "price": 2490.0, "stock_status": "In Stock"
| # | hardware_id | model_name | category | io_count | preamps | sample_rate |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the dynamic nature of waves.com: flash sales, complex bundle hierarchies, Waves Update Plan calculations, and hardware specifications.
Extract VST, AU, and AAX format availability, Apple Silicon native status, and detailed audio processing specifications per plugin.
Capture base price, sale price, active coupon codes, and discount percentages. Waves changes prices frequently; we track every update.
Map individual plugins to their parent bundles (Horizon, Mercury, Diamond) to analyse inclusion overlap and upgrade value.
Extract renewal costs, upgrade tier caps, and included support features for maintaining plugin licenses.
Extract I/O counts, sample rates, and network protocols for DSP servers, eMotion LV1 consoles, and audio interfaces.
Track minimum OS requirements, supported DAWs, CPU constraints, and RAM recommendations for every software product.
Group plugins by artist collaborations including Chris Lord-Alge, Manny Marroquin, Greg Wells, and Tony Maserati.
Extract listed factory presets and artist-designed signal chains associated with specific plugins.
Track the calculated cost to upgrade from lower tiers to comprehensive bundles based on current promotional pricing.
Brief in. Clean data out.
Provide categories, bundle targets, or specific hardware models. We design the extraction schema together.
We configure Playwright crawlers to handle dynamic pricing widgets and proxy rotation for waves.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on agreed cadence.
Waves operates a high-frequency promotional model. Here is how our infrastructure captures accurate data without missing flash sales.
Waves product pages use JavaScript to render current sale prices, coupon applications, and WUP calculators. We run full Playwright browser sessions to hydrate these widgets and capture the actual price shown to users.
Because Waves changes promotional pricing almost daily, standard weekly crawls miss critical data. We configure high-frequency polling on target SKUs to capture flash sales and coupon stacking opportunities as they go live.
The Mercury bundle contains smaller bundles which contain individual plugins. Our extraction logic recursively unpacks these hierarchies to map exact plugin inclusions and calculate per-plugin value metrics.
We utilise ISP-grade residential proxies with realistic browser fingerprints to bypass rate limits and ensure uninterrupted access to the complete catalogue during major sales events like Black Friday.
We maintain a hash index of last-seen prices and specifications. Subsequent runs only push diffs, reducing downstream processing load and providing a clean changelog of Waves promotional behaviour.
Audio plugin developers track Waves flash sales and bundle discounts to inform their own promotional calendars and pricing strategies.
Industry analysts evaluate bundle structures, WUP renewal caps, and product release velocity to understand audio software market trends.
Audio production blogs and review sites maintain accurate pricing and sale alerts for their audiences using our automated data feeds.
Marketplaces calculate accurate license transfer values based on current retail prices and outstanding WUP renewal costs.
Hardware manufacturers compare SoundGrid server specifications, I/O capacities, and pricing against native processing solutions.
Music retailers feed their internal databases with accurate plugin specifications, OS requirements, and DAW compatibility matrices.
"Waves operates the most aggressive dynamic pricing model in the audio software industry. Tracking their flash sales and bundle upgrades requires continuous, high-frequency extraction."
Audio software pricing is highly volatile, and Waves sets the standard for constant flash sales, coupon stacking, and complex upgrade paths. DataFlirt manages the proxy rotation, session handling, and JavaScript execution required to track this volatility reliably. Your engineers get clean, normalised pricing and specification data without maintaining fragile scrapers.
Everything supported by our waves.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. Playwright handles JavaScript rendering, cookie sessions, and interaction flows for dynamic pricing widgets.
We maintain pools of residential ISP proxies. Rotation happens per-request to ensure uninterrupted access during major promotional events.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About waves.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from waves.com is generally permissible. DataFlirt targets only public, non-authenticated product, pricing, and specification data. We do not extract personal data or circumvent authentication walls.
We configure high-frequency polling pipelines that run at hourly or custom intervals to capture short-lived promotional pricing, ensuring your database reflects current retail reality.
Yes. Our extraction logic recursively unpacks all bundle hierarchies, mapping every individual plugin included in Mercury, Horizon, Diamond, and other collections.
Yes. We extract the base WUP renewal costs and maximum caps associated with each plugin and bundle.
Depending on your SLA, we can deliver complete catalogue updates daily, or track specific high-value SKUs at sub-hourly intervals.
Yes. We provide a sample run of up to 50 plugins or bundles 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 plugin catalogue dump or a continuous price-monitoring feed for flash sales — we scope, build, and operate the pipeline. Tell us what you need.
