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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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                        (
                            [de] => Nordamerika
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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
                        )

                )

            [country] => Array
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                    [iso_code] => US
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                        (
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                            [ru] => США
                            [zh-CN] => 美国
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            [location] => Array
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                    [longitude] => -83.0061
                    [metro_code] => 535
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            [postal] => Array
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                    [code] => 43215
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            [registered_country] => Array
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                    [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
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                    [0] => Array
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                            [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
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                    [ip_address] => 216.73.216.150
                    [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
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            [validAttributes:protected] => Array
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                    [0] => code
                    [1] => geonameId
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        )

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

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

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
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            [validAttributes:protected] => Array
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                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.150
                    [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
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                    [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
)

Introduction

Quick commerce has transformed how consumers access ready-to-cook and frozen food products, making delivery speed and availability as important as product quality. For brands like CMC, which operate in a high-frequency purchase category, understanding regional demand patterns and last-mile efficiency is critical. City-Wise Demand & Delivery Intelligence for CMC empowers decision-makers with insights into where demand is rising, where fulfillment is falling short, and how delivery performance directly impacts customer satisfaction and repeat purchases.

As quick commerce platforms expand into Tier-1 and Tier-2 cities, operational complexity grows. Delivery delays, stockouts, and inconsistent service levels can quickly erode brand trust. With real-time intelligence, brands can align inventory planning, dark store placement, and delivery capacity with actual city-level demand. By combining advanced data extraction with analytics, organizations gain the clarity needed to eliminate supply gaps and build a resilient, customer-first quick commerce strategy.

Understanding Speed Gaps Across Cities

Q-commerce Delivery time intelligence

Delivery time is one of the most critical KPIs in quick commerce. Through Q-commerce Delivery time intelligence, brands can benchmark performance across cities and uncover hidden inefficiencies in last-mile operations. From 2020 to 2026, delivery times improved significantly in metros but remained inconsistent in emerging markets due to infrastructure gaps and limited dark store coverage.

Table 1: Average Delivery Time by City Tier (Minutes)
Year Metro Cities Tier-1 Cities Tier-2 Cities
2020 34 40 48
2021 32 38 46
2022 29 35 43
2023 27 33 40
2024 25 31 37
2025 23 29 34
2026 21 27 31

Analysis:The data highlights a narrowing gap in metros and Tier-1 cities, but Tier-2 markets still face delays of nearly 10 minutes more on average. This impacts customer satisfaction for time-sensitive food products and indicates the need for micro-fulfillment centers and smarter route optimization in high-growth regions.

Monitoring Delivery Promises in Real Time

Real-time delivery ETA monitoring via scraping

Customer trust in quick commerce depends heavily on whether delivery promises are kept. With Real-time delivery ETA monitoring via scraping, brands can continuously track whether platforms meet their stated delivery windows across cities. Between 2020 and 2026, the percentage of orders delivered within promised ETAs improved significantly in metros but lagged in Tier-2 cities.

Table 2: On-Time Delivery Rate (% of Orders)
Year Metro Cities Tier-1 Cities Tier-2 Cities
2020 72% 68% 60%
2021 75% 70% 62%
2022 80% 75% 67%
2023 84% 79% 72%
2024 88% 83% 77%
2025 91% 87% 82%
2026 94% 90% 86%

Analysis:While improvements are evident across all city tiers, the persistent gap in Tier-2 cities suggests structural challenges such as rider availability and distance from fulfillment hubs. Real-time ETA monitoring helps brands identify platform-level performance issues and take corrective action through better partner coordination.

Mapping Regional Fulfillment Patterns

Extract Q-Commerce City-Wise Delivery Time

Understanding delivery performance at a city level enables brands to tailor fulfillment strategies based on local realities. Using Extract Q-Commerce City-Wise Delivery Time, CMC can identify cities where delays are frequent and correlate them with order volume, infrastructure, and rider density.

Table 3: Average Delivery Time by Selected Cities (Minutes)
City 2020 2023 2026
Mumbai 30 24 20
Delhi 32 26 22
Bengaluru 34 27 23
Pune 38 31 26
Jaipur 42 35 29
Indore 45 38 32

Analysis:Metro cities show near-optimal delivery performance by 2026, while Tier-2 cities such as Indore and Jaipur still lag by over 10 minutes. This disparity indicates opportunities for expanding dark stores and reallocating delivery resources to high-demand emerging markets.

Ensuring Product Availability at Speed

Scrape CMC Product on Q-Commerce

Delivery speed alone does not guarantee success—availability at the point of order is equally important. By using Scrape CMC Product on Q-Commerce, brands can track SKU presence, stockouts, and assortment depth across platforms and cities. From 2020 to 2026, CMC expanded its online SKU footprint significantly, but stock consistency varied widely by region.

Table 4: Average SKU Availability Rate (%)
Year Metro Cities Tier-1 Cities Tier-2 Cities
2020 85% 78% 65%
2021 88% 81% 68%
2022 90% 85% 72%
2023 92% 88% 76%
2024 94% 91% 80%
2025 96% 93% 84%
2026 97% 95% 88%

Analysis:Although availability has improved across all regions, Tier-2 cities still face frequent stockouts—contributing to missed sales opportunities. This reinforces the need for demand-driven replenishment models powered by real-time data.

Measuring End-to-End Service Quality

Q-commerce delivery performance intelligence

Delivery performance goes beyond speed—it includes reliability, order accuracy, and customer experience. With Q-commerce delivery performance intelligence, brands can track holistic service metrics across platforms and regions.

Table 5: Customer Satisfaction Score (Out of 5)
Year Metro Cities Tier-1 Cities Tier-2 Cities
2020 3.8 3.6 3.3
2021 4.0 3.8 3.5
2022 4.2 4.0 3.7
2023 4.4 4.2 3.9
2024 4.6 4.4 4.1
2025 4.7 4.5 4.3
2026 4.8 4.6 4.5

Analysis:Rising satisfaction scores show that improvements in delivery speed and availability directly enhance customer experience. However, the slower progress in Tier-2 cities highlights the importance of targeted operational investments in emerging markets.

Driving Consistency at Scale

Quick Commerce Delivery Time Performance

Scaling quick commerce operations requires standardized performance benchmarks. Quick Commerce Delivery Time Performance provides a framework for evaluating whether service levels remain consistent as coverage expands.

Table 6: Orders Delivered Within 30 Minutes (%)
Year Metro Cities Tier-1 Cities Tier-2 Cities
2020 65% 58% 45%
2021 68% 61% 48%
2022 72% 66% 52%
2023 78% 71% 58%
2024 83% 76% 64%
2025 88% 81% 70%
2026 92% 86% 76%

Analysis:The steady improvement across all tiers demonstrates how data-driven delivery management can elevate performance. Yet, the remaining gap in Tier-2 cities signals untapped potential for logistics innovation and deeper platform collaboration.

Why Choose Actowiz Solutions?

Actowiz Solutions empowers brands with Quick Commerce Data Intelligence that transforms operational complexity into competitive advantage. Through City-Wise Demand & Delivery Intelligence for CMC, we help organizations uncover delivery bottlenecks, identify supply gaps, and align fulfillment strategies with real market demand. Our advanced analytics, automated data pipelines, and city-level insights enable brands to improve service consistency, enhance customer satisfaction, and accelerate growth across all quick commerce channels.

Conclusion

In a world where speed defines success, data-driven delivery strategies are no longer optional—they are essential. City-Wise Demand & Delivery Intelligence for CMC equips brands with the visibility needed to eliminate supply gaps, reduce last-mile delays, and build stronger customer trust in quick commerce environments. By combining Web Crawling service and Web Data Mining, organizations can unlock real-time insights that transform fragmented operations into seamless delivery experiences.

Partner with Actowiz Solutions today to turn your quick commerce data into actionable intelligence and build faster, smarter, and more reliable delivery networks across every city.

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.
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

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Feb 09, 2026

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How Scraping Spices Product Data From Ecommerce Improves Demand Forecasting And Inventory Planning?

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How Web Scraping Instacart Product Availability by Zip Code Helps Retailers Optimize Inventory

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Glovo Quick Commerce Price Monitoring in Barcelona

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Optimizing Customer Loyalty with Grab Rewards Data Scraping - Points, Tiers, and Rewards Analysis

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Tracking Grab Gift Card Demand and Usage with Web Scraping Grab Gift Card Data

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UAE E-Commerce & Quick Commerce SKU Data Analysis - Price, Stock & Demand Insights

UAE E-Commerce & Quick Commerce SKU Data Analysis delivers insights on pricing, availability, trends, and performance to optimize catalogs and growth.

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City-Wise SKU Demand and Pricing Trends - E-Commerce & Q-Commerce multi-Platforms, insights to compare demand, pricing, and growth patterns across cities

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