Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
Actowiz Metrics Now Live!
logo
Unlock Smarter , Faster Analytics!
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] => 216.73.216.115
                    [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] => 216.73.216.115
                    [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
)
Navratri Mega Sale Price Tracking

Introduction

India's baby-care eCommerce market explodes during festive seasons like Diwali, Dussehra, Independence Day, and New Year sales. Among platforms leading this surge, FirstCry stands out as the largest online marketplace for baby and maternity products.

For diaper brands, these seasons can determine quarterly performance. Prices fluctuate daily, discounts vary by city, and inventory often sells out in hours. Tracking these changes manually is nearly impossible.

Actowiz Solutions, a global leader in e-commerce and price intelligence scraping, partnered with leading diaper manufacturers to monitor FirstCry's pricing, promotions, and availability during festive campaigns.

This case study explores how Actowiz Solutions' FirstCry product data scraping and analysis uncovered actionable insights that helped diaper brands optimize pricing, plan stock, and improve campaign ROI.

Problem Statement

Navratri Mega Sale Price Tracking

Every festive season, FirstCry rolls out aggressive discount campaigns such as:

  • "Diaper Fest Week"
  • "Big Baby Days"
  • "Diwali Flash Deals"
  • "Independence Day Price Drop"

While these promotions boost traffic, diaper brands often lack visibility into:

  • How discounts vary by brand, SKU, or region
  • What competitor brands are offering
  • Which price points generate the most sales
  • When to launch or extend their own campaigns

Without real-time festive discount tracking, brands risk mismatched pricing, lost visibility, and inventory misallocation.

Actowiz Solutions' challenge was clear: Build a scalable, API-driven, FirstCry discount tracking system to analyze festive price movements at a SKU and city level.

Objective

The project's goal was to:

  • extract FirstCry pricing and promotional data for diaper categories during key festive windows.
  • Compare discounts and availability across leading brands (Pampers, Huggies, MamyPoko, SuperBottoms, etc.).
  • Identify regional pricing variations across top Indian cities.
  • Build insights dashboards for decision-making.

Actowiz Solutions Approach

Actowiz Solutions implemented a four-stage approach for this analysis.

Stage 1: Data Collection (Web Scraping & API Integration)

Actowiz Solutions deployed crawlers to continuously scrape FirstCry product listings, collecting:

  • Brand and product name
  • Pack size and price per diaper
  • Original price vs discounted price
  • Discount percentage
  • Stock availability
  • Category ranking (based on popularity)
  • City or pin-code location (where available)

Data was refreshed every 6 hours during the Diwali sale period.

Stage 2: Data Cleaning & Structuring

Collected data was normalized to ensure:

  • Uniform pricing units (₹ per diaper)
  • Unified brand taxonomy
  • Elimination of duplicates and expired offers
Stage 3: Analysis & Benchmarking

Actowiz Solutions analytics team processed the data to identify:

  • Average discount depth per brand
  • Top-selling SKUs by city
  • Timing patterns (flash sales vs long-run promotions)
  • Elasticity between discount depth and stock depletion
Stage 4: Visualization & Reporting

Interactive dashboards were created to monitor:

Sample Data Snapshot

Brand SKU Pack Size Original Price Discounted Price Discount % Availability Region Date
Pampers Active Baby 72 pcs ₹1,199 ₹899 25% In Stock Delhi 27 Oct
Huggies Wonder Pants 56 pcs ₹1,049 ₹819 22% Low Stock Mumbai 27 Oct
MamyPoko Extra Absorb 74 pcs ₹1,149 ₹849 26% In Stock Bengaluru 27 Oct
Supples Premium 60 pcs ₹799 ₹599 25% In Stock Hyderabad 27 Oct
SuperBottoms UNO 2 pcs ₹890 ₹745 16% Out of Stock Pune 27 Oct

This snapshot shows the average festive discount range of 15–30%, with variations by city and availability.

Insights from Festive Season Tracking

Discount Depth & Duration
  • Average discount across diaper brands: 23.5%
  • Premium organic brands like Super Bottoms maintained smaller discounts (10–15%) but high sell-through rates.
  • Budget brands like Supples offered larger discounts (25–30%) to compete in price-sensitive markets.
Regional Price Variations

Using FirstCry price comparison scraping, Actowiz Solutions found:

  • Southern cities (Bengaluru, Chennai, Hyderabad) saw deeper average discounts.
  • Northern metros (Delhi, Chandigarh) showed moderate markdowns but faster stockouts.
  • Western regions (Mumbai, Pune) had high discount diversity, often testing multiple promo levels.
Time-Based Flash Sales
  • 70% of diaper promotions were active between 7 PM – 11 PM, coinciding with high traffic hours.
  • Flash deals (limited 2-hour slots) had higher conversion but faster stock depletion.
Competitor Behavior
  • Actowiz Solutions FirstCry promotion tracking API highlighted how leading brands reacted dynamically:
  • When Pampers reduced its discount from 25% to 20%, Huggies increased its offer from 22% to 28%.
  • MamyPoko ran "Buy 2 Get 1 Free" promotions instead of flat discounts — a tactic that sustained average order value.
Category Elasticity
  • Every 5% discount increase drove an 11–13% volume uplift on average.
  • Price elasticity was highest in mid-range SKUs (₹600–₹900).
  • Super-premium diapers showed steady sales even at lower discounts.

Dashboards & Data Visualization

Actowiz Solutions built a custom dashboard for the client featuring:

  • Daily discount heatmaps across cities
  • Brand vs brand comparison graphs
  • "Top 10 SKUs by Discount Uplift" lists
  • Time-series analysis for each festive week

Sample visualization excerpt:

Chart 1:

Average Discount % by Brand (Diwali 2024)

  • Pampers: 24%
  • Huggies: 26%
  • MamyPoko: 22%
  • Supples: 27%
  • SuperBottoms: 15%

Chart 2:

Discount Elasticity CurveHigher discounts correlated directly with spike in conversions until ~30% threshold; beyond that, sales plateaued.

Impact & Business Outcomes

Metric Before Actowiz After Actowiz
Discount timing accuracy Manual, reactive Data-driven, real-time
Regional visibility Limited Pin-code level
Forecast accuracy ±15% ±4%
Stock-out rate 12% 6%
Campaign ROI +11% +24%

In just two festive seasons, Actowiz Solutions insights improved gross margin control and inventory distribution efficiency across all monitored SKUs.

Lessons Learned

  • Timing beats depth – Launching promotions at the right hour matters more than increasing discount percentages.
  • City-specific strategy – Bengaluru and Hyderabad buyers are more discount-sensitive; Mumbai prefers convenience offers.
  • Brand positioning defines elasticity – Premium brands rely on perception, not markdowns.
  • Inventory planning must sync with flash sales – Predictive analytics can prevent stockouts in high-volume zip codes.
  • Continuous tracking is crucial – Scraping data only once a day misses real-time fluctuations that define conversion spikes.

Technology Stack

Actowiz Solutions utilized:

  • Python-based crawlers with rotating proxies
  • API connectors for structured JSON feeds
  • AI-based discount detection engine
  • Tableau dashboards for visual analytics
  • MySQL + PowerBI integration for client access

Security and compliance were maintained under India's data guidelines and FirstCry's data-access policies.

Challenges & Mitigation

Challenge Solution
Dynamic pricing changes every few hours Automated crawlers every 6 hours with historical logs
Regional redirects in FirstCry listings Pin-code mapping & normalization
Out-of-stock visibility lag Custom availability tracker integrated with API
Seasonal API throttling Load-balanced scraping schedule
Duplicate data noise Data deduplication via SKU hashing

Strategic Recommendations

Based on Actowiz Solutions findings, diaper brands should:

  • Run regional A/B pricing tests during peak hours (e.g., Diwali evenings).
  • Target mid-tier SKUs with optimal 20–25% discounts for maximum uplift.
  • Leverage data scraping dashboards to track competitor changes live.
  • Align ad budgets with regions showing fastest stock movement.
  • Plan inventory at least two weeks ahead of FirstCry's campaign calendar.

Future Applications

Navratri Mega Sale Price Tracking

The same methodology can be extended to:

  • Baby wipes, feeding bottles, apparel, and toys
  • Cross-platform scraping across Amazon, Flipkart, and Nykaa Baby
  • Predictive analytics for upcoming sale seasons
  • Automated alert systems for discount changes beyond thresholds

Actow continues to refine FirstCry data extraction to include:

  • Review sentiment analytics
  • Competitor ad tracking
  • Real-time category share estimation

Conclusion

Festive seasons redefine India’s baby care market — and data decides who wins.

By partnering with Actowiz Solutions, diaper brands gained end-to-end visibility into FirstCry’s festive discounts, stock patterns, and competitor behavior.

Through web scraping, API integration, and analytics, Actowiz Solutions turned raw FirstCry data into actionable insights — improving pricing agility, campaign ROI, and inventory efficiency.

In the words of one client:

“Before Actowiz Solutions, we reacted to discounts. Now, we anticipate them.”

As the eCommerce landscape evolves, data scraping and retail intelligence will remain essential for brands that want to outpace competition during India’s biggest shopping seasons.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape Structure Analyze Visualize

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

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 Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
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.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
Product Image
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!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
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

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 10, 2025

How Scrape SpiritStore.co.uk Discounts & Deals Reveals Shifts in UK Consumer Liquor Demand?

Discover how Scrape SpiritStore.co.uk Discounts & Deals uncovers trends in UK consumer liquor demand, tracking promotions, clearance offers, and buying patterns.

thumb

Tracking FirstCry Discounts During Festive Seasons – A Case Study for Diaper Brands

Actowiz Solutions analyzes FirstCry’s festive discounts to reveal price, demand, and sales trends for diaper brands during India’s top shopping seasons.

thumb

UK Food Aggregator Pricing Scraping Reveals Competitive Pricing Trends Across Deliveroo, Just Eat, and Uber Eats

This research report uses UK Food Aggregator Pricing Scraping to reveal competitive pricing trends across Deliveroo, Just Eat, and Uber Eats

Oct 10, 2025

How Scrape SpiritStore.co.uk Discounts & Deals Reveals Shifts in UK Consumer Liquor Demand?

Discover how Scrape SpiritStore.co.uk Discounts & Deals uncovers trends in UK consumer liquor demand, tracking promotions, clearance offers, and buying patterns.

Oct 10, 2025

Product Variants, Offers & Discount Scraping Reveals 30% Increase in Quick Commerce & Supermarket Promotions

Discover how Product Variants, Offers & Discount Scraping reveals a 30% increase in promotions across quick commerce and supermarket websites for smarter strategies.

Oct 10, 2025

How the Wayfair Ratings and Reviews Aggregate API Can Help Collect Ratings & Reviews in the USA?

Leverage the Wayfair Ratings and Reviews Aggregate API to efficiently collect, analyze, and consolidate customer ratings and reviews across the USA market.

thumb

Tracking FirstCry Discounts During Festive Seasons – A Case Study for Diaper Brands

Actowiz Solutions analyzes FirstCry’s festive discounts to reveal price, demand, and sales trends for diaper brands during India’s top shopping seasons.

thumb

EV Charging Infrastructure Mapping Highlights 35% Growth Opportunities Across European Urban Areas

Explore how EV Charging Infrastructure Mapping uncovers 35% growth opportunities across European cities using ChargePoint and EVgo data for smart planning.

thumb

Government Schemes Data Scraping: Central & State Program Intelligence

See how Actowiz Solutions scraped and organized current Indian government schemes across healthcare, education, agriculture, and business sectors.

thumb

UK Food Aggregator Pricing Scraping Reveals Competitive Pricing Trends Across Deliveroo, Just Eat, and Uber Eats

This research report uses UK Food Aggregator Pricing Scraping to reveal competitive pricing trends across Deliveroo, Just Eat, and Uber Eats

thumb

KEETA Menu Data Extraction Reveals High-Demand Dishes and Peak Hours Across Saudi Arabia

This research report uses KEETA Menu Data Extraction to reveal high-demand dishes and peak ordering hours across Saudi Arabia.

thumb

Price Matching & Availability Analysis for Lidl in the UK Retail Market

Discover key insights in the UK retail market with our Research Report – Price Matching & Availability Analysis for Lidl, tracking pricing trends and stock availability.