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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
                        )

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            [continent] => Array
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                        (
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                            [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
                        )

                )

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

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            [location] => Array
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                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
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            [postal] => Array
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                    [code] => 43215
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            [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
                        )

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            [subdivisions] => Array
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                            [iso_code] => OH
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                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
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                        )

                )

            [traits] => Array
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                    [ip_address] => 216.73.216.155
                    [prefix_len] => 22
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        )

    [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
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                )

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            [validAttributes:protected] => Array
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    [country:protected] => GeoIp2\Record\Country Object
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            [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
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            [validAttributes:protected] => Array
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                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
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        )

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

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

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

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.155
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
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                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
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                    [6] => isAnonymousProxy
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                    [8] => isHostingProvider
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                    [11] => isPublicProxy
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
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                )

        )

    [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
                        )

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            [validAttributes:protected] => Array
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                    [1] => geonameId
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                )

        )

    [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
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                    [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
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                )

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)
 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
)

Introduction

The Malaysian retail landscape has transformed significantly over the past five years, with evolving consumer habits, rapid e-commerce adoption, and shifting price sensitivities reshaping business decisions. Through detailed Malaysia retail market analysis, Actowiz Solutions highlights how brands can decode these shifts using granular, real-time category-level intelligence.

Rising competition, fluctuating economic indicators, and expanded online assortment volumes have made category-level monitoring essential. This report unpacks trends across Grocery, Electronics, Beauty, and Home categories, showing how retailers can react faster, price smarter, and stay aligned with consumer purchasing patterns.

Market Dynamics in Fast-Moving Retail Categories

Real-Time Electronics Price Tracking for Black Friday – 2025 Insights

Understanding how retail categories evolve over time is essential for brands trying to capture market share amid intense digital competition. This analysis leverages insights from a detailed Malaysia category performance report to identify how category demand, shelf price variations, and discount patterns have shifted between 2020 and 2025. During this period, online shopping penetration grew from 58% to 82%, and average basket value rose 26%, driven primarily by lifestyle changes and increased digital literacy.

2020–2025 Category Growth Snapshot
Year Online Retail Growth (%) Avg. Basket Value (MYR) Promotion Participation (%)
2020 12% 98 22%
2021 18% 103 26%
2022 21% 110 30%
2023 26% 118 34%
2024 29% 121 38%
2025 33% 124 41%

Across grocery, consumers shifted heavily toward value-based shopping, with private-label growth rising by 19% since 2020. Electronics saw a 40% rise in demand for mid-range smartphones and home appliances due to hybrid work models. Beauty categories recorded stronger promotional dependency, while Home category products grew steadily due to home improvement trends. These insights underscore the urgency for retailers to adopt automated analytics and real-time category surveillance.

Pricing Trends and Consumer Sensitivities Across Malaysia

The Malaysian retail landscape has become increasingly price-sensitive. With inflation peaking at 3.8% in 2023 and subsequently stabilizing by 2025, price-monitoring and demand forecasting remain critical. In this Malaysia price and demand analysis, Actowiz Solutions identifies how Malaysian shoppers respond to price adjustments and the factors influencing category-level conversions.

Price & Demand Relationship Table (2020–2025)
Category Avg. Price Change Demand Change Promo Elasticity Conversion Lift
Grocery +6% +12% High 8%
Electronics +15% +26% Medium 5%
Beauty +9% +18% Very High 14%
Home +7% +15% Medium 6%

Beauty products showed the highest promotion elasticity, illustrating consumer responsiveness to discount percentages rather than brand loyalty. Electronics witnessed the largest demand surge due to hybrid work adoption. Actowiz Solutions helps businesses decode these trends with real-time pricing datasets, enabling accurate revenue forecasting and optimized promotions.

Digital Transformation in Electronics Retailing

The electronics sector underwent an accelerated transformation due to remote work adoption, growth in smart devices, and evolving consumer expectations for real-time price visibility. Actowiz Solutions uses its Malaysia electronics catalog crawler to extract SKU-level intelligence and monitor product movement across online platforms.

Electronics Category Trends (2020–2025)
Segment Avg. YOY Growth Price Fluctuation Stock Variation Consumer Rating Trend
Smartphones 22% High Medium 4.5 Avg
Laptops 28% Medium High 4.4 Avg
Smart Appliances 18% Medium Low 4.6 Avg
Wearables 31% Low Medium 4.7 Avg

YOY data shows significant growth in laptop and wearable sales as consumers prioritize efficiency and fitness. Brands using automated catalog crawlers gain access to real-time pricing, demand signals, out-of-stock alerts, and competitor movements to guide assortment planning and dynamic repricing.

Offers, Discounts & Consumer Decisions in the Beauty Sector

The beauty industry remains one of the most competitive and marketing-driven categories in Malaysia. With an increasing preference for premium skincare, natural formulations, and K-beauty trends, the need for Beauty discount & offer scraping has surged.

Beauty Market Highlights (2020–2025)
Metric 2020 2025 Growth
Avg. Discount 14% 22% +57%
Online SKU Count 5,200 8,900 +71%
Loyalty Program Usage 31% 46% +48%
Promotion-led Conversions 36% 52% +44%

Promotions drive more than half of category conversions, illustrating a heavy dependency on price to influence purchasing behavior. Retailers using real-time offer scraping can customize their promotional calendars, optimize discount depth, and react quickly to competitor strategies.

Evolving Consumer Needs in the Home Category

The Home category has seen consistent growth as Malaysians focus on comfort, functionality, and DIY improvements. Using the Malaysia home category product crawler, Actowiz Solutions tracks price changes, top-selling SKUs, product availability, and competitor listings.

Home Category Stats (2020–2025)
Sub-Category Growth Rate Avg. Price Demand Shift Promo Impact
Kitchen Appliances +19% Moderate High Strong
Home Décor +14% Low Medium Medium
Storage & Organization +28% Moderate Very High High
Cleaning Supplies +17% Low Medium Low

The increased focus on home organization led to sharp demand spikes in storage items, while affordable kitchen appliances gained traction due to meal-prepping trends. Retailers can leverage these insights for assortment strategy and seasonal demand forecasting.

Leveraging Data for Strategic Retail Growth

Today's retail success relies heavily on data-driven decisions rooted in real-time Data Intelligence. With over 40% of Malaysian consumers shifting their buying patterns since 2020, businesses need scalable systems for monitoring price changes, product launches, promotions, customer sentiment, and competitor strategies.

Key Data Intelligence Metrics (2020–2025)
Indicator 2020 2025 Change
Real-Time Data Use 18% 57% +217%
Automated Pricing Tools 23% 48% +109%
Competitive Intelligence Adoption 35% 62% +77%

Retailers equipped with automated intelligence frameworks enjoy faster decision-making, improved margins, and more accurate customer targeting. Actowiz Solutions helps businesses deploy these systems seamlessly.

Actowiz Solutions delivers industry-leading retail analytics powered by real-time Price Monitoring capabilities, enabling companies to react instantly to competitive changes. Our advanced scrapers, automated dashboards, and structured datasets help brands unlock insights from Malaysia retail market analysis, ensuring smarter pricing strategies, optimized assortment decisions, and improved revenue performance.

Conclusion

As Malaysian retail continues evolving, brands must rely on data-driven insights to navigate complex category behaviors and shifting customer preferences. Using Actowiz Solutions’ enterprise-grade Web Crawling service and scalable Web Data Mining systems, businesses can stay ahead of competitors through real-time analytics, pricing intelligence, and market forecasting.

Contact Actowiz Solutions today to transform your retail analytics with precise, automated, and actionable intelligence!

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:

Fintech / Digital Payments

Result

Accurate daily voucher &

cashback visibility across platforms

★★★★★

“Actowiz Solutions helped us automate daily voucher and cashback data collection across PhonePe, Paytm, Flipkart, and Hubble. The API-driven delivery significantly improved offer accuracy and operational efficiency.”

Product Manager, Fintech Platform (India)

✓ Daily voucher & cashback tracking via Push & Pull APIs

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.
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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

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Shopsy Discount Intelligence- Extracting Offer Data for Competitive Benchmarking

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How Hyperlocal Healthcare Pricing Intelligence Using 1mg Data Solves Medication Cost Challenges for Patients

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Feb 20, 2026

Amazon USA Price Scraping API 2026: Buy Box Reclaiming New York Retailers

Track Amazon USA prices and Buy Box shifts in 2026. Help New York retailers reclaim Buy Box share using real-time price scraping API by Actowiz Solutions.

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Shopsy Discount Intelligence- Extracting Offer Data for Competitive Benchmarking

Shopsy Discount Intelligence - Extracting offer data to track competitors, benchmark promotions, and optimize pricing strategies effectively.

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Costco Walmart Grocery Pricing Scraping – Geo-Based Real-Time Houston

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Apartments.com Inventory Scraping Houston 2026 – Lead Generation for Real Estate

Houston apartment inventory scraping from Apartments.com for 2026. Generate verified rental leads with structured data and real-time insights by Actowiz Solutions.

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Swiggy Instamart Snack & Drink Sales Analysis: Trends, Consumer Behavior, and Growth Opportunities

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US Coffee Shop Industry Data Scraping - Market Trends, Pricing Intelligence, and Competitive Landscape Analysis

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Zepto Cleaning Aid Product Analysis – Delhi - Fixing Assortment, Promotion, And Margin Leakage Issues

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