Category-wise packs with monthly refresh; export as CSV, ISON, or Parquet.
Pick cities/countries and fields; we deliver a tailored extract with OA.
Launch instantly with ready-made scrapers tailored for popular platforms. Extract clean, structured data without building from scratch.
Access real-time, structured data through scalable REST APIs. Integrate seamlessly into your workflows for faster insights and automation.
Download sample datasets with product titles, price, stock, and reviews data. Explore Q4-ready insights to test, analyze, and power smarter business strategies.
Playbook to win the digital shelf. Learn how brands & retailers can track prices, monitor stock, boost visibility, and drive conversions with actionable data insights.
We deliver innovative solutions, empowering businesses to grow, adapt, and succeed globally.
Collaborating with industry leaders to provide reliable, scalable, and cutting-edge solutions.
Find clear, concise answers to all your questions about our services, solutions, and business support.
Our talented, dedicated team members bring expertise and innovation to deliver quality work.
Creating working prototypes to validate ideas and accelerate overall business innovation quickly.
Connect to explore services, request demos, or discuss opportunities for business growth.
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] => 216.73.216.24 [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] => 216.73.216.24 [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 )
The association between food delivery apps and QSR chains has benefits and drawbacks. Among the crucial complaints, QSRs have against the food apps are incremental marketing spending needed to take part on a platform and the incapability of measuring investment impacts.
At Actowiz Solutions, we allow QSRs to outline measurable metrics to get positive ROIs for app marketing investments. We also equip QSRs using the tools to track their competitive performances at coarse, zip code- depending levels so that restricted strategies can be modified as required. Here is the example of 1000+ store chain QSRs we have partnered with for optimizing pre-existing investments made with the larger food aggregator apps. With the months engagement with us, they have achieved a 3X increase in sales without giving any extra marketing dollars.
Lets understand the pain points that we have recognized and solved:
Among the fundamental issues, we have realized was that sales werent an effective metric to track marketing performances because its a dawdling metric that doesnt apprehend the problems that help grow or suppress the sales.
Most sales are determined by ranks in the food category and search for the branded keywords. However, a QSR chain cant track those ranks.
In reality, 70%+ of the sales go to the top five restaurants in the category and keywords
By data aggregation across various food app platforms expansively, i.e., in locations, at multiple times a day, we have established the QSR chain ranking in essential categories and for important keywords, recognizing where they over or under-performed related to competition. Because we did that every day- it became a candid metric that helped establish the marketing campaign performance.
We understood it wasnt easy to recognize well-performing stores on food apps as sales rely on different factors like competition, area population, local cuisine preferences, etc.
We have tracked the Ranking of every store with every Zip Code for keywords and made a listing of poor-performing stores. Also, we have scraped attributes like Estimated Time of Arrival (ETAs), Ratings, Delivery Fees, Reviews, etc., for all the poorly-performing stores to recognize the reasons for poor Ranking.
E.g., We comprehended that 356 stores werent on the first page, mainly due to High ETAs and poor ratings. After the intensive initiative, 278 stores started coming on the first page with a 23% increase in sales.
The precise ranking algorithms for food apps are not shared publicly. Therefore the QSR chain wasnt sure which variables of ratings, fees, ETAs, ad spend, or accessibility has contributed relatively to the general Ranking.
Comprehensive data for different zip codes in different timestamps were analyzed to determine which variables contribute most extensively to the Ranking. We have also directed A/B testing – concurrently testing two variables like decreasing ETAs at one store and improving ad spending at another, analyzing which has led to better ranks and sales impacts.
For instance, we have found a QSR chain done well in the main urban centers; however, the competition was doing much better; however, there wasnt any good way of tracking and comparing the competitors performance.
We also tracked the QSR chain with competition for all the metrics and compared performances.
We rapidly realized Ranking began quickly improving because we gained a slight edge in every metric against competitors. For instance, 5 minutes lesser ETA adds to a higher Ranking.
After six months of exercise with the QSR chain, we have improved the average rankings to 11 from 24 for a QSR chain, having them featured on the first page.
Problem:
The QSR chain wasnt clear about which banners to select for investment and needed to rely on food platforms recommendations.
They werent given a clear view about which position has made a banner visible, and at what ranks among the flags the promo was visible.
We have combined data for different banners populated in every zip code and found Ranking and at which position a QSR chain was noticeable.
The QSR chain capitalized on 630 zip code-based banners having guaranteed visibility; however, our assessment directed that the banners were visible in only 301 zip codes. After choosing suitable banners for promotions, we improved visibility at 533 zip codes to improve the budget.
We are now using a similar strategy to refine offers, discounts, coupons, and promotions.
Usually, increasing the marketing spend gives a temporary boost to sales; however, the question of the QSR chain was how we could determine long-term impacts, i.e., ranking keywords and targeted zip codes.
We have created an easy widget for all marketing campaigns that shows the Ranking for keywords for particular zip codes before a campaign, during a campaign, and after a campaign, clearly founding the midterm effect of the movement. This continuous monitoring permitted QSR to quickly hinge on the strategy for national holidays etc., and work accordingly.
Though a QSR chain might track sales coming through a food app channel, they had no way to know incremental organic volumes done by marketing efforts.
One missing aspect was how much extra sales might be attributed to QSR ranking improvement.
By compounding sales data and aggregated insights, we have established a QSR chain and how much sales they might expect from a ranking increase. We also understand which changed aspects led to the percentage of change increases.
A sales increase of 3x in six months was just the beginning, and the journey of impulsive marketing competence using channel and competitive data has just started.
Actowiz Solutions has been dealing with worldwide QSR chains, assisting them in driving growth on aggregators platforms by helping them to observe key metrics, recommend action, identify improvement areas, and determine interventions impact. Actowiz Solutions strategy removes the dependency on food apps to get accurate data. We combine websites and food app data to analyze and justify marketing spending to drive the growth of 10-15%.
Contact us if you need to know how your brand can influence Actowiz Solutions data insights with better sales. You can also reach us for mobile app scraping and web scraping services requirements.
✨ "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"
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.
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
Real Estate
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×
Organic Grocery / FMCG
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
Quick Commerce
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
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
Beverage / D2C
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
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
Real results from real businesses using Actowiz Solutions
In Stock₹524
Price Drop + 12 minin 6 hrs across Lel.6
Price Drop −12 thr
Improved inventoryvisibility & planning
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
"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"
✔ Scraped Data, SKU availability, delivery time
With hourly price monitoring, we aligned promotions with competitors, drove 17%
Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place
Discover how Scraping Consumer Preferences on Dan Murphy’s Australia reveals 5-year trends (2020–2025) across 50,000+ vodka and whiskey listings for data-driven insights.
Discover how Web Scraping Whole Foods Promotions and Discounts Data helps retailers optimize pricing strategies and gain competitive insights in grocery markets.
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.
Scrape USA E-Commerce Platforms for Inventory Monitoring to uncover 5-year stock trends, product availability, and supply chain efficiency insights.
Discover how Scraping APIs for Grocery Store Price Matching helps track and compare prices across Walmart, Kroger, Aldi, and Target for 10,000+ products efficiently.
Learn how to Scrape The Whisky Exchange UK Discount Data to monitor 95% of real-time whiskey deals, track price changes, and maximize savings efficiently.
Discover how AI-Powered Real Estate Data Extraction from NoBroker tracks property trends, pricing, and market dynamics for data-driven investment decisions.
Discover how Automated Data Extraction from Sainsbury’s for Stock Monitoring enhanced product availability, reduced stockouts, and optimized supply chain efficiency.
Score big this Navratri 2025! Discover the top 5 brands offering the biggest clothing discounts and grab stylish festive outfits at unbeatable prices.
Discover the top 10 most ordered grocery items during Navratri 2025. Explore popular festive essentials for fasting, cooking, and celebrations.
Explore how Scraping Online Liquor Stores for Competitor Price Intelligence helps monitor competitor pricing, optimize margins, and gain actionable market insights.
This research report explores real-time price monitoring of Amazon and Walmart using web scraping techniques to analyze trends, pricing strategies, and market dynamics.
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.
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.
Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations