Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Grab Offer Now

Grab Offer Now

GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [continent] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [registered_country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
                (
                    [0] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.58
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.58
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)

 country : United States

 city : Columbus

US

Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

• Home
• E-commerce
• Ecommerce & Marketplace Scraping USA | Real-Time Price & Review Data

Ecommerce & Marketplace Scraping Services in USA – Real-Time Product, Price & Review Insights

Get accurate and scalable e-commerce scraping solutions from Actowiz Solutions. Monitor products, prices, stock availability, promotions, ratings, and reviews across platforms like Amazon, Walmart, Flipkart, eBay, BestBuy, and more. Capture SKU-level insights with 99.9% accuracy — delivered instantly in JSON, CSV, or Excel.

• Product & Pricing Data – Track SKUs, discounts, and price fluctuations in real time.
• Stock & Availability – Monitor inventory levels, delivery SLAs, and seller updates.
• Review & Ratings – Extract customer reviews, star ratings, and seller performance.
• Marketplace Coverage – Amazon, Walmart, Flipkart, BestBuy, eBay & 100+ sites.
• Flexible Output – JSON/CSV/Excel, delivered via API, S3, GCS, Azure, or SFTP.
• Global Reach – USA, UK, UAE, India, Germany, Canada & beyond.

Request a Free Quote

Top Countries:

Create your own

What We Extract

We provide comprehensive SKU-level e-commerce data including:

Product names, SKUs, categories, brand hierarchy

Real-time prices, discounts, coupons, and flash sales

Stock status (in stock, out of stock, backordered)

Seller details (FBA, 3P, brand resellers)

Ratings, reviews, verified purchase tags

Product images, videos, descriptions, attributes

Sponsored listings, banner ads, promotions

Shipping fees, delivery timelines, fulfillment type

Full competitor catalogs across categories

Delivered in Excel, CSV, JSON, API feeds, or integrated dashboards.

Platforms We Cover

We provide comprehensive SKU-level e-commerce data including:

Amazon (US, UK, India, EU, Global)

Walmart (US, Canada, Mexico)

Flipkart (India)

Target

Best Buy

eBay

Snapdeal

Alibaba

Shopee

Lazada

Carrefour (UAE, EU)

Noon (Middle East)

Zalando (EU)

We cover global regions: USA, UK, UAE, India, Germany, Canada, Europe, SEA.

Expanded Use Cases

Price Monitoring & Dynamic Repricing

In e-commerce, price changes decide who wins or loses sales. On Amazon, Walmart, and Flipkart, even a small difference of a few cents can shift the Buy Box. Without automated monitoring, retailers risk being undercut by competitors or missing discount trends. Price intelligence is no longer optional — it is survival. By scraping price and discount data in real time, businesses can implement dynamic pricing rules, protect margins, and stay competitive.

What We Do:

• Track real-time prices across marketplaces and categories.
• Capture discount codes, promotions, and flash sales.
• Monitor Buy Box winners and their pricing strategies.
• Deliver hourly or daily price feeds via API or CSV.
• Enable automated repricing integration with ERP/CRM.

Impact:

• Prevent revenue leakage from overpricing.
• Win the Buy Box consistently.
• Detect undercut competitors instantly.
• Enable data-driven dynamic pricing strategies.

Example:

A global electronics retailer scraped 100K SKUs during Black Friday across Amazon and Best Buy. With real-time repricing automation, they achieved a 22% increase in conversions and captured an additional $3.5M in seasonal revenue.

Read More

Product Catalog Enrichment & Image Sync

Outdated or incomplete catalogs cause lost sales and high return rates. Customers abandon carts if images, descriptions, or attributes are missing. Competitors with better-optimized catalogs gain higher visibility and trust. By scraping competitor catalogs, retailers can enrich their product listings with accurate details, attributes, and visuals — ensuring their feeds remain complete and competitive.

What We Do:

• Extract titles, descriptions, images, and attributes.
• Standardize SKUs across multiple marketplaces.
• Fill missing metadata like color, size, warranty.
• Detect discrepancies in cross-channel listings.
• Provide catalog enrichment APIs for automation.

Impact:

• Improve customer trust with accurate product info.
• Reduce returns caused by incorrect descriptions.
• Enhance marketplace SEO with enriched listings.
• Increase conversion rates by improving catalog quality.

Example:

A footwear brand enriched its listings by scraping Flipkart and Myntra competitor catalogs. Adding missing attributes like shoe width and material reduced returns by 18% and increased conversions by 14%.

Read More

Customer Review & Sentiment Analytics

Customer reviews are a goldmine of insights — they reveal what customers like, dislike, and expect next. Yet, most businesses struggle to analyze reviews at scale. Scraping reviews from Amazon, Walmart, and Flipkart allows businesses to collect thousands daily, categorize them by sentiment, and uncover patterns. Positive reviews highlight competitive strengths; negative reviews expose weaknesses.

What We Do:

• Scrape reviews and star ratings across platforms.
• Perform AI-driven sentiment analysis (positive, neutral, negative).
• Extract metadata like verified purchase, review frequency.
• Identify recurring complaints or praise.
• Benchmark review scores vs competitors.

Impact:

• Improve product design and quality.
• Reduce returns by addressing recurring issues.
• Protect brand reputation with sentiment tracking.
• Enhance marketing by leveraging real customer language.

Example:

A fashion retailer scraped 200K reviews across Amazon and Zalando. The analysis showed recurring “size too small” complaints. Adjusting size charts reduced return rates by 12% and improved satisfaction scores.

Read More

Promotion & Banner Tracking

Competitors spend heavily on ads, banners, and seasonal campaigns. If you can’t see where and when they promote, you miss the chance to respond effectively. Scraping sponsored listings, banners, and discount promotions allows businesses to benchmark ad spend and optimize their own strategies.

What We Do:

• Extract sponsored products and banner ads.
• Monitor discount badges and limited-time offers.
• Track promotion start/end dates across categories.
• Identify seasonal campaign frequency.
• Deliver visual data dashboards of ad placements.

Impact:

• Benchmark ad visibility vs competitors.
• Optimize timing of your own promotions.
• Improve ROI by avoiding wasted ad spend.
• Detect competitor seasonal campaign strategies.

Example:

A cosmetics brand tracked Flipkart banner ads across 12 competitors during Diwali. By reallocating spend to match peak competitor hours, they improved ad ROI by 20% and boosted seasonal sales.

Read More

Inventory Gap Detection

Stockouts represent lost revenue — but they’re also opportunities. When competitors run out of stock, customers actively look for alternatives. Businesses that detect these gaps quickly can capture market share.

What We Do:

• Track stock status across millions of SKUs.
• Detect out-of-stock, low-stock, and backorder signals.
• Deliver real-time stock alerts to sales teams.
• Benchmark competitor fulfillment reliability.
• Integrate stock signals into promotional campaigns.

Impact:

• Capture competitor’s lost customers.
• Improve own logistics strategy.
• Identify fast-moving SKUs for forecasting.
• Prevent your own stockouts with trend signals.

Example:

A consumer electronics seller scraped Walmart’s TV stock data. When a competitor’s best-selling model went out of stock, they raised ad bids on their alternative SKU, resulting in a 12% sales uplift in 2 weeks.

Read More

MAP & Brand Compliance Monitoring

Unauthorized sellers often undercut brand prices, violating Minimum Advertised Price (MAP) policies. This damages brand reputation, frustrates authorized resellers, and erodes margins. Without systematic monitoring, detecting these violations is almost impossible. Scraping seller listings across Amazon, eBay, and Walmart enables brands to enforce compliance and maintain healthy reseller relationships.

What We Do:

• Monitor all sellers listing your products across marketplaces.
• Detect MAP violations in real time.
• Flag unauthorized sellers and price undercutting.
• Track seller profiles, fulfillment type, and pricing history.
• Provide violation alerts and reporting dashboards.

Impact:

• Protect brand equity from unfair discounting.
• Strengthen relationships with authorized resellers.
• Stop revenue erosion caused by MAP violations.
• Enforce contracts and distribution agreements.

Example:

A premium skincare brand monitored 15K SKUs across Amazon and eBay. Within 60 days, Actowiz flagged 200+ MAP violations and helped them cut unauthorized discounting by 70%, restoring reseller trust.

Read More

New Market & SKU Discovery

Before launching in a new region, brands need to know which products sell well locally, what price ranges customers accept, and who dominates the category. Market entry without competitive intelligence is risky and expensive. Scraping competitor catalogs and SKUs across marketplaces provides clear visibility into local demand and competitor strengths.

What We Do:

• Scrape full category data across regional marketplaces.
• Identify best-selling SKUs in target regions.
• Benchmark competitor pricing strategies.
• Track new product launches and adoption rates.
• Deliver SKU-level insights for launch planning.

Impact:

• Minimize risks during market entry.
• Launch products aligned with regional demand.
• Stay ahead of local competitors.
• Accelerate growth with data-driven strategies.

Example:

An apparel brand entering UAE scraped Noon and Carrefour fashion categories. They identified 200 trending SKUs in modest wear and footwear. Optimizing their launch strategy reduced market-entry risk and led to 40% faster adoption.

Read More

Competitor Assortment & Category Benchmarking

Retailers often don’t realize how their assortment compares to competitors. Some carry deeper catalogs in key categories, while others expand into new verticals faster. Assortment benchmarking ensures you know where you stand relative to peers and where opportunities lie.

What We Do:

• Scrape competitor category trees and product hierarchies.
• Benchmark assortment size per category.
• Track assortment growth over time.
• Identify assortment gaps in your catalog.
• Provide insights into competitor expansions.

Impact:

• Close assortment gaps faster.
• Improve category competitiveness.
• Anticipate competitor expansion strategies.
• Grow market share in under-served categories.

Example:

A grocery retailer benchmarked its organic food assortment vs competitors. Actowiz data showed competitors carried 35% more SKUs. By expanding their organic catalog, the retailer grew revenue in that category by 18% within 2 months.

Read More

Flash Sale & Deal Tracking

Flash sales and mega discount events like Amazon Lightning Deals or Flipkart Big Billion Days can make or break a retailer’s quarter. Missing these events means competitors grab market share. Real-time flash sale tracking helps businesses stay agile and competitive.

What We Do:

• Monitor flash sales and limited-time deals.
• Capture hourly discounts during mega sales.
• Track coupon codes and voucher usage.
• Provide historical flash sale data for planning.
• Deliver real-time alerts for sudden deal launches.

Impact:

• Prevent loss of customers to competitor discounts.
• Match or beat competitor promotions instantly.
• Optimize promotional budgets during seasonal sales.
• Improve sales forecasting using historical trends.

Example:

A fashion retailer tracked hourly discounts during Flipkart’s Big Billion Days. By dynamically adjusting discounts, they retained 12% more customers and improved campaign ROI.

Read More

Seller Performance & Marketplace Intelligence

Marketplaces are powered by sellers, but not all sellers are equal. Some dominate through fast delivery, some through high ratings, and others via aggressive pricing. Tracking seller performance gives brands competitive intelligence at the seller level.

What We Do:

• Scrape seller ratings, reviews, and performance metrics.
• Track delivery times and fulfillment type (FBA/3P).
• Monitor seller activity across multiple categories.
• Identify high-performing or aggressive competitors.
• Benchmark seller share per category.

Impact:

• Identify key competitors per category.
• Track reseller activity on your products.
• Benchmark delivery and fulfillment performance.
• Strengthen negotiations with marketplaces.

Example:

A consumer electronics brand analyzed seller competition across Amazon India. They discovered a reseller winning Buy Box due to faster delivery (2 days vs their 5 days). By improving logistics, the brand boosted Buy Box wins by 9%.

Read More

Search & Keyword Visibility Tracking

Visibility on marketplaces isn’t only about price — it’s about being discoverable. If your products don’t appear in the first page of Amazon or Flipkart search results, you risk losing customers to competitors. Search scraping helps brands monitor keyword visibility and adjust product listings to climb higher in rankings.

What We Do:

• Scrape keyword rankings for products on Amazon, Flipkart, Walmart, etc.
• Track organic vs sponsored product placements.
• Monitor brand store vs competitor store visibility.
• Benchmark keyword performance across time.
• Provide keyword reports for SEO optimization.

Impact:

• Identify keywords driving competitor traffic.
• Optimize listings for higher rankings.
• Improve sponsored ad efficiency.
• Gain visibility across critical search terms.

Example:

A beauty brand saw slipping keyword ranks for “matte lipstick” on Amazon. With Actowiz data, they optimized product titles and ads, regaining Top 5 ranking in 30 days and boosting sales by 15%.

Read More

Shipping & Delivery Intelligence

Fast and affordable delivery is a key competitive advantage. Many customers choose sellers who can deliver faster — even at a higher price. Monitoring competitor shipping and delivery times provides actionable intelligence to improve your own logistics.

What We Do:

• Track delivery times across regions and categories.
• Monitor shipping costs and free shipping thresholds.
• Detect regional differences in delivery promises.
• Provide fulfillment benchmarking dashboards.
• Integrate shipping data into competitive strategy.

Impact:

• Identify delivery gaps vs competitors.
• Improve logistics partnerships.
• Optimize free shipping offers.
• Win customers with better delivery promises.

Example:

A US retailer found competitors offered 1-day delivery in NY and CA while their average was 4 days. By upgrading logistics, they halved delivery time and improved repeat purchase rates by 21%.

Read More

Historical Price & Discount Trends

Understanding past pricing behavior is as important as real-time monitoring. Historical data reveals competitor strategies, discount cycles, and seasonal trends. Brands can use this to forecast competitor moves and plan pricing strategies better.

What We Do:

• Collect and store historical price and discount data.
• Provide trend analysis for product categories.
• Track seasonal discounting patterns (Black Friday, Diwali, etc.).
• Benchmark historical average prices vs current rates.
• Deliver historical datasets in CSV/API format.

Impact:

• Forecast competitor discount strategies.
• Optimize pricing for seasonal sales.
• Build historical benchmarks for long-term strategy.
• Improve negotiations with suppliers.

Example:

An electronics retailer analyzed 3 years of historical pricing on laptops across Amazon and Best Buy. Insights revealed consistent 15% discounts in November. By aligning their campaigns, they increased seasonal sales by 28%.

Read More

Cross-Marketplace Product Matching

The same product often appears across multiple marketplaces with different prices, sellers, and descriptions. Without product matching, it’s hard to benchmark across platforms. Automated product matching enables cross-market comparison and unified intelligence.

What We Do:

• Match identical SKUs across Amazon, Walmart, Flipkart, etc.
• Detect price differences for same product across regions.
• Standardize product attributes for comparison.
• Provide matched product datasets for analytics.
• Enable cross-market pricing dashboards.

Impact:

• Detect price discrepancies across channels.
• Improve channel pricing consistency.
• Prevent undercutting across marketplaces.
• Benchmark cross-region product positioning.

Example:

A global mobile brand matched SKUs across Amazon US, Walmart, and Flipkart India. They identified 20% price differences caused by resellers. Adjusting pricing policies improved channel consistency and protected margins.

Read More

New Product Launch Detection

Competitors launch new products almost daily. Missing these signals means delayed response in pricing, promotions, and assortment planning. Scraping new product listings gives brands a first-mover advantage.

What We Do:

• Monitor “new arrivals” sections across marketplaces.
• Detect new SKUs launched by competitors.
• Track launch timing, price positioning, and category placement.
• Provide alerts for competitor product launches.
• Integrate launch detection with market-entry planning.

Impact:

• Respond faster to competitor launches.
• Spot emerging category trends early.
• Adjust assortment strategy proactively.
• Stay ahead in competitive categories.

Example:

A consumer electronics brand tracked “new arrivals” in laptops on Amazon. They detected competitor launches 2 weeks earlier than before. By adjusting pricing, they protected 10% category share during the quarter.

Read More

Competitor Stock Availability Alerts

Stock availability is directly tied to sales performance. When competitors run out of stock, it creates an immediate opportunity for your brand to capture lost demand. On the flip side, frequent competitor restocking signals demand trends. Scraping stock availability across platforms provides brands with actionable alerts for supply chain and marketing optimization.

What We Do:

• Monitor real-time stock levels across SKUs.
• Flag “Out of Stock,” “Low Stock,” and “Backordered” signals.
• Track competitor restocking frequency.
• Provide alerts via API, email, or dashboard.
• Benchmark competitor fulfillment reliability.

Impact:

• Capture market share when competitors run out of stock.
• Forecast demand spikes based on competitor restocks.
• Adjust logistics to maintain your availability edge.
• Prevent overstock or understock situations.

Example:

A fashion retailer tracked competitor stockouts on Flipkart. By launching flash discounts during competitor unavailability, they boosted conversions by 15% in 2 weeks.

Read More

Category & Subcategory Deep Analysis

Competitors don’t just fight at the product level — they dominate entire categories. To compete effectively, brands need visibility into how many SKUs, what price ranges, and which product attributes dominate competitor categories. Category scraping allows benchmarking at a macro level.

What We Do:

• Scrape full category trees from marketplaces.
• Map SKUs, attributes, and price ranges per subcategory.
• Benchmark category growth and SKU turnover.
• Identify white spaces in categories.
• Provide category intelligence dashboards.

Impact:

• Enter new subcategories with confidence.
• Spot assortment gaps to expand faster.
• Track competitor dominance by category.
• Align pricing with category benchmarks.

Example:

A home appliances brand benchmarked Amazon’s kitchen appliances category. They identified gaps in “compact blenders” and launched 5 new SKUs. Within 6 months, they gained 8% category share.

Read More

E-commerce Ad Intelligence (Sponsored Products, Headline Ads)

Sponsored ads are a major spend for e-commerce brands. Competitors bidding aggressively can dominate visibility. Without scraping ad placements, it’s impossible to benchmark spend and strategy.

What We Do:

• Scrape sponsored product placements across search results.
• Capture headline ads, display ads, and banner campaigns.
• Track ad frequency and share of voice.
• Benchmark organic vs paid visibility.
• Deliver ad placement dashboards.

Impact:

• Optimize your ad spend with competitor benchmarks.
• Identify keywords competitors target aggressively.
• Improve ROI by reallocating ad budgets.
• Increase brand visibility on high-value keywords.

Example:

A consumer electronics brand tracked Amazon sponsored ads in laptops. They discovered competitors dominated “gaming laptop” ads. By reallocating spend, they improved ad ROI by 25%.

Read More

Seasonal Demand Tracking (Black Friday, Diwali, Ramadan, Christmas)

E-commerce sales peak during seasonal events. Competitors launch massive promotions, new SKUs, and bundled deals. Without monitoring seasonal demand, brands miss critical opportunities.

What We Do:

• Track seasonal product launches and promotions.
• Monitor category-level SKU and sales spikes.
• Benchmark seasonal discounting strategies.
• Provide historical seasonal demand datasets.
• Deliver event-based intelligence reports.

Impact:

• Optimize seasonal promotion strategies.
• Identify high-demand products for future cycles.
• Improve stock planning before major events.
• Outperform competitors with early insights.

Example:

A toy retailer scraped Amazon and Walmart during Christmas sales. They identified fastest-moving toys and increased stock before demand peaked, achieving 30% higher sales YOY.

Read More

Coupon & Voucher Code Tracking

Discount codes and vouchers drive purchase decisions, especially in price-sensitive categories. Competitors often use hidden codes to retain customers. Scraping these codes helps brands benchmark promotions.

What We Do:

• Scrape coupon codes across marketplaces.
• Track voucher usage and discount amounts.
• Monitor promo duration and terms.
• Provide competitor coupon benchmarking.
• Deliver structured promo datasets.

Impact:

• Benchmark coupon strategies against competitors.
• Improve discount targeting.
• Prevent over-discounting by analyzing market trends.
• Increase sales with smarter promo campaigns.

Example:

An online grocery retailer scraped coupons across Instacart and Amazon Fresh. By analyzing discount patterns, they optimized their own voucher strategy, leading to a 17% increase in repeat orders.

Read More

Private Label & Reseller Monitoring

Private label products are rapidly gaining traction on marketplaces. Competitors often launch in-house brands at lower prices, undercutting established players. At the same time, unauthorized resellers push products without brand approval, hurting pricing control and customer trust. Monitoring private labels and resellers is essential to safeguard market share.

What We Do:

• Track private label SKUs launched by marketplaces (Amazon Basics, Flipkart SmartBuy, etc.).
• Scrape pricing and positioning of private label vs branded items.
• Monitor unauthorized resellers listing your products.
• Deliver detailed reseller performance dashboards.
• Provide alerts for suspicious product listings.

Impact:

• Protect your brand from reseller undercutting.
• Benchmark against fast-growing private labels.
• Optimize pricing vs marketplace-owned brands.
• Maintain healthy distribution channels.

Example:

A premium electronics brand tracked unauthorized resellers on Amazon India. By detecting early undercutting, they shut down 50+ reseller accounts and protected 12% of margin.

Read More

Product Description & Attribute Benchmarking

Product descriptions, titles, and attributes are critical for SEO and conversion inside marketplaces. Competitors with optimized content gain higher visibility and customer trust. Scraping competitor product metadata helps brands benchmark and improve their own listings.

What We Do:

• Extract competitor product titles, bullet points, and descriptions.
• Benchmark attribute completeness (color, size, material, etc.).
• Detect missing keywords and optimize product listings.
• Provide competitive content benchmarking reports.
• Integrate attribute scraping with catalog enrichment.

Impact:

• Improve search ranking visibility.
• Reduce product return rates with accurate attributes.
• Boost conversions through optimized descriptions.
• Gain edge in SEO-driven marketplace sales.

Example:

A furniture retailer benchmarked competitor product descriptions on Wayfair and Amazon. By adding missing attributes like “assembly required,” they improved customer clarity and reduced return rates by 14%.

Read More

Review Fraud & Fake Seller Detection

Fake reviews and fraudulent sellers are common on marketplaces, often misleading buyers and damaging genuine brands. Tracking these patterns helps businesses protect reputation and ensure fair competition.

What We Do:

• Scrape review text for suspicious patterns (duplicate wording, burst reviews).
• Detect fake seller accounts with abnormal ratings.
• Monitor unverified purchase tags.
• Deliver fraud detection dashboards.
• Provide competitor fraud intelligence reports.

Impact:

• Protect brand reputation against fake review attacks.
• Identify fraudulent sellers undermining fair pricing.
• Improve trust with customers by promoting authentic reviews.
• Maintain competitive advantage with clean seller monitoring.

Example:

A skincare brand identified 500+ fake reviews targeting its flagship product on Amazon. With Actowiz data, they flagged suspicious sellers and improved brand trust, recovering 9% lost sales.

Read More

Competitive Market Share Estimation (SKU & Pricing Overlap)

Understanding how much share competitors hold within a category is critical for strategy. By scraping SKU overlap, pricing ranges, and reviews, businesses can estimate competitor market share and position themselves more effectively.

What We Do:

• Scrape competitor SKUs across categories.
• Benchmark SKU count vs your own catalog.
• Track pricing overlap and customer reviews.
• Estimate market share using SKU-level analysis.
• Deliver competitor market intelligence reports.

Impact:

• Quantify competitor dominance.
• Identify categories with growth potential.
• Improve positioning in high-competition categories.
• Align investments with market dynamics.

Example:

A consumer electronics retailer benchmarked laptop SKUs across Amazon and Walmart. Insights showed a competitor held 28% more SKUs in mid-range laptops. Expanding assortment helped recover 10% lost share.

Read More

Benefits of E-commerce Scraping with Actowiz

E-commerce is a dynamic ecosystem where prices, promotions, and product assortments change every hour. Businesses that rely on manual monitoring often lag behind competitors who use automated, data-driven strategies. Actowiz empowers you with accurate, structured, and real-time e-commerce data, enabling smarter pricing, faster decisions, and stronger customer experiences. From monitoring millions of SKUs to analyzing customer sentiment at scale, our scraping services provide the intelligence you need to thrive in hyper-competitive marketplaces. Below are the key benefits you gain by leveraging Actowiz for your e-commerce data needs.

360° Price Intelligence

Stay ahead of pricing wars with complete visibility into competitor prices, promotions, and discounts. Our scraping solutions track SKUs across Amazon, Walmart, Flipkart, eBay, and other marketplaces, giving you a unified dashboard of pricing trends. Businesses use this intelligence to implement dynamic pricing and protect margins.

Example: An electronics retailer scraped 50,000 SKUs during Black Friday, enabling them to auto-adjust prices. The result: a 15% boost in conversions within 3 months.

Inventory & Stock Insights

Monitor competitor inventory levels, stockouts, and shipping timelines in real time. This allows businesses to identify supply gaps, optimize replenishment, and reduce lost sales opportunities.

Example: A consumer electronics brand identified competitor stockouts on Amazon in peak season, increased ad bids, and gained a 22% sales lift in 2 weeks.

Review & Sentiment Analytics

Extract and analyze customer reviews, ratings, and complaints to understand buyer sentiment. This data helps improve product quality, enhance service, and refine marketing campaigns.

Example: A fashion brand scraped 200,000 reviews from Amazon and Zalando. Insights into “size too small” complaints allowed them to adjust sizing charts, cutting returns by 12%.

Global Marketplace Coverage

From Amazon USA to Flipkart India and Shopee Singapore, Actowiz covers 100+ marketplaces worldwide. Businesses can benchmark their global catalog, spot international trends, and align regional pricing strategies.

Example: A multinational FMCG company compared basket prices across 7 countries to align promotions globally, improving pricing consistency by 18%.

MAP & Compliance Monitoring

Ensure sellers follow your Minimum Advertised Price (MAP) policies. Our crawlers detect MAP violations instantly, protecting your brand equity and retailer relationships.

Example: A consumer electronics brand reduced MAP violations by 40% in 6 months by automating compliance monitoring across 20 online sellers.

Smarter Marketing & Promotions

Scrape competitor ad placements, promotional banners, and sponsored listings to refine your marketing strategies. Get insights into discounting tactics and seasonal campaigns.

Example: A beauty brand tracked 10,000 promotional listings across Amazon and Walmart, allowing them to launch better-timed campaigns, increasing CTR by 28%.

Industries We Serve

E-commerce scraping isn’t just for online retailers. Businesses across multiple industries rely on Actowiz for actionable insights. From FMCG brands and manufacturers to ad-tech companies and financial analysts, we deliver accurate datasets that fuel smarter strategies and measurable growth.

Retailers & E-commerce Brands

Retailers use our services to benchmark prices, monitor promotions, and optimize product listings across channels.

Mini Example: A global retailer scraped Amazon and Walmart SKUs to maintain consistent pricing, boosting customer trust and conversion rates.

FMCG & Consumer Goods

Track basket pricing, stock availability, and customer sentiment to stay competitive in fast-moving markets.

Mini Example: A beverage company monitored supermarket marketplaces across Europe to optimize regional promotions, increasing sales by 14%.

Market Research & Consulting

Consultancies use our structured datasets for competitor benchmarking, category analysis, and client strategy building.

Mini Example: A market research firm scraped 1M+ SKUs across 8 countries to deliver an FMCG pricing benchmark study.

Price Comparison & Affiliate Sites

Fuel affiliate platforms with real-time price and availability data to attract traffic and improve monetization.

Mini Example: A price comparison portal updated listings every 4 hours using Actowiz, increasing click-throughs by 21%.

Manufacturers & Suppliers

Monitor how resellers present, price, and review your products across multiple marketplaces.

Mini Example: A home appliance manufacturer reduced MAP violations by 30% by automating scraping of 200 reseller sites.

Ad-Tech & Analytics

Get insights into ad spend, promotions, and keyword performance across marketplaces to improve targeting.

Mini Example: An ad-tech company scraped 50,000 sponsored product listings, refining bid strategies for their clients.

Geo Coverage

Actowiz covers 100+ e-commerce marketplaces worldwide, ensuring you capture localized trends and competitive dynamics. Whether you’re expanding into a new region or optimizing an existing one, our data helps you act with confidence.

Regions Covered:

• USA, Canada, UK, Germany, France, Italy
• UAE, Saudi Arabia, Qatar
• India, Singapore, Japan, Australia
• Brazil, Mexico, South Africa

Platforms Covered: Amazon, Walmart, eBay, Flipkart, Shopee, Noon, Carrefour, Zalando, Lazada, BestBuy & more.

GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [continent] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [registered_country] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
                (
                    [0] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.58
                    [prefix_len] => 22
                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.58
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)

 country : United States

 city : Columbus

US

Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

Start Your Project

+1 ▼

Select Service Web Scraping Real-Time API Access Data Dashboards Datasets Review & Sentiment Analysis Price Monitoring Custom Solution

Select Industry E-Commerce Quick Commerce Food Delivery Travel & OTA Grocery & Retail Real Estate Others

Target Country Web Scraping Services Mobile App Scraping Web and App Scraping API Datasets Dashboard

A$лвR$C$CHF¥Kčkr€£HK$FtRp₪₹kr¥₩Mex$RMkrNZ$₱złleikrS$฿₺$R Budget Range $500 - $1,000 - Starter Budget (POC/Single Site) $1,000 - $2,500 - Basic Plan (Small Business Needs) $2,500 - $5,000 - Growth Phase (Multi-site/Data Volume Projects) $5,000 - $10,000 - Business-Scale (Automation/API Integrations) $10,000 - $25,000 - Enterprise Projects (Real-Time Systems, Global Data) $25,000 - $50,000 - Enterprise+ (Custom Dashboards, Ongoing Support) $50,000+ - Strategic Partnership (End-to-End Data Ops)

Additional Trust Elements

✨ "1000+ Projects Delivered Globally"

⭐ "Rated 4.9/5 on Google & G2"

🔒 "Your data is secure with us. NDA available."

💬 "Average Response Time: Under 12 hours"

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize

Explore Solutions Get a Custom Demo

Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

Find Insights Use AI to connect data points and uncover market changes. Meanwhile.

Move Forward Predict demand, price shifts, and future opportunities across geographies.

Ecommerce

Q-Commerce

Travel & OTA

Food Delivery

Real Estate

Social Media

Trusted by Global Leaders – Secured by International Standards

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★

'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"

Thomas Galido

Co-Founder / Head of Product at Upright Data Inc.

2 min

★★★★★

“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”

Iulen Ibanez

CEO / Datacy.es

1 min

★★★★★

“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”

Febbin Chacko

-Fin, Small Business Owner

1 min

See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

Price Drop + 12 min
in 6 hrs across Lel.6

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.

✔ Scraped Data: Price Insights Top-selling SKUs

Request Demo Access

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

Actowiz Insights Hub

Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place

All

Blog

Case Studies

Infographics

Report

Oct 18, 2025

Mapping Product Taxonomy for E-Commerce Marketplaces – Optimize 15+ Product Categories Across Amazon, Walmart, and Target

Discover how Mapping Product Taxonomy helps optimize 15+ product categories across Amazon, Walmart, and Target, ensuring better marketplace insights.

Maximizing Revenue with Price Intelligence - Scraping Liquor Discount Data from Drizly and Total Wine USA

Discover how Scraping Liquor Discount Data from Drizly and Total Wine USA helps businesses maximize revenue with actionable price intelligence insights.

Festive Price Surge Tracker: Amazon Fresh vs BigBasket vs JioMart in India

Track how prices of sweets, snacks, and groceries surged across Amazon Fresh, BigBasket, and JioMart during Diwali & Navratri in India with Actowiz festive price insights.

Real-Time Market Insights with Instacart Price and Availability Scraping for Price and Stock Analysis

This research report explores real-time market insights using Instacart price and availability scraping for product pricing and stock analysis in the USA.

Oct 18, 2025

Mapping Product Taxonomy for E-Commerce Marketplaces – Optimize 15+ Product Categories Across Amazon, Walmart, and Target

Discover how Mapping Product Taxonomy helps optimize 15+ product categories across Amazon, Walmart, and Target, ensuring better marketplace insights.

Oct 17, 2025

Building Historical Real Estate Price Datasets to Forecast Housing Trends – 15% Year-on-Year Price Variation Analysis

Build and analyze Historical Real Estate Price Datasets to forecast housing trends, track decade-long price fluctuations, and make data-driven investment decisions.

Oct 17, 2025

How Travel Agencies in Italy Use Trenitalia Data Scraping for Route Optimization to Enhance Customer Experience?

Discover how Italian travel agencies use Trenitalia Data Scraping for Route Optimization to improve scheduling, efficiency, and enhance the overall customer experience.

Read More

Maximizing Revenue with Price Intelligence - Scraping Liquor Discount Data from Drizly and Total Wine USA

Discover how Scraping Liquor Discount Data from Drizly and Total Wine USA helps businesses maximize revenue with actionable price intelligence insights.

Optimizing Competitive Pricing Strategies in Digital Grocery Platforms Using SKU-Level Price Intelligence

This case study explores how SKU-level price intelligence helps digital grocery platforms optimize competitive pricing, boost conversions, and increase revenue.

Scrape Diwali Real Estate Discounts: How Actowiz Solutions Analyzed 50,000+ Property Listings Across India

Actowiz Solutions scraped 50,000+ listings to scrape Diwali real estate discounts, compare festive property prices, and deliver data-driven developer insights.

Read More

Festive Price Surge Tracker: Amazon Fresh vs BigBasket vs JioMart in India

Track how prices of sweets, snacks, and groceries surged across Amazon Fresh, BigBasket, and JioMart during Diwali & Navratri in India with Actowiz festive price insights.

Top 5 Brands Offering Deepest Discounts on Clothes This Navratri

Score big this Navratri 2025! Discover the top 5 brands offering the biggest clothing discounts and grab stylish festive outfits at unbeatable prices.

Top 10 Most Ordered Grocery Items During Navratri 2025

Discover the top 10 most ordered grocery items during Navratri 2025. Explore popular festive essentials for fasting, cooking, and celebrations.

Read More

Real-Time Market Insights with Instacart Price and Availability Scraping for Price and Stock Analysis

This research report explores real-time market insights using Instacart price and availability scraping for product pricing and stock analysis in the USA.

U.S. EV Adoption and Infrastructure Analysis Leveraging EV Charging Station Data Scraping (Tesla, Rivian, ChargePoint)

This research report analyzes U.S. EV adoption and infrastructure trends using EV charging station data scraping from Tesla, Rivian, and ChargePoint.

Tracking Liquor Trends on Dan Murphy’s & BWS in Australia - Insights from Data Scraping & Sales Statistics

Tracking Liquor Trends on Dan Murphy’s & BWS in Australia - Insights from Data Scraping & Sales Statistics, revealing market patterns.

Read More

Our perks are irreplaceable

Time Zone Flexibility

Benefit from the ease of collaboration with Actowiz Solutions, as our team is aligned with your preferred time zone, ensuring smooth communication and timely delivery.

Clear Communication

Our team focuses on clear, transparent communication to ensure that every project is aligned with your goals and that you’re always informed of progress.

Uncompromising Quality

Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations

Our Affiliations