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GeoIp2\Model\City Object
(
    [city:protected] => GeoIp2\Record\City Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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            [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
                        )

                )

        )

    [location:protected] => GeoIp2\Record\Location Object
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            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

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

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

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

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
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                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
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                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                            [0] => en
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                    [record:GeoIp2\Record\AbstractRecord:private] => Array
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                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
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                                    [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
                                )

                        )

                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

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

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
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                            [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:protected] => GeoIp2\Record\Country Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
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                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

        )

    [locales:protected] => Array
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            [0] => en
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

        )

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

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

            [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
                        )

                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
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            [validAttributes:protected] => Array
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                    [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
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [ip_address] => 216.73.216.110
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
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        )

    [raw:protected] => Array
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                    [names] => Array
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                            [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
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                    [geoname_id] => 6255149
                    [names] => 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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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
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                            [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
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                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

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

            [registered_country] => Array
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                    [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] => 216.73.216.110
                    [prefix_len] => 22
                )

        )

)
 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 Southeast Asian eCommerce space, led by platforms like Lazada, offers fertile ground for American grocery startups eyeing market expansion. This Lazada App & Grocery Delivery Dataset Case Study for American Startups reveals how data from the Lazada ecosystem can inform pricing strategies, trend forecasting, competitor benchmarking, and consumer demand insights.

Using the Lazada grocery App dataset, startups can decode patterns across SKUs, promotions, and customer feedback. Combined with Lazada Product Data Scraper and Lazada Data Scraping API, real-time access to product, pricing, and review data is possible—critical for entering price-sensitive and fast-moving grocery markets.

Why the Lazada Grocery App Dataset Matters for U.S. Startups?

The Lazada grocery App dataset provides unparalleled visibility into Southeast Asian grocery purchasing behavior. For American startups, it offers the following:

  • Competitive pricing benchmarks across SKUs
  • Category-wise volume trends
  • Promotions and discount behavior tracking
  • Consumer review and satisfaction analytics
Table 1: Grocery SKU Listings and Pricing Trends (2020-2025)
Year Avg. SKU Count Avg. Price (USD) Promotions Frequency
2020 8,000 $2.50 15%
2021 10,500 $2.70 18%
2022 13,200 $2.65 22%
2023 15,900 $2.80 25%
2024 17,400 $2.90 28%
2025 18,600 $3.05 30%

Outcome: Increased visibility into inflation impact, SKU availability, and promotional tactics on Lazada from 2020 to 2025.

Extracting Lazada App Product Data for Pricing & Trend Analysis

Through Lazada app product data scraping, U.S. startups can perform region-specific price tracking. Price benchmarking and stockout frequency enable decision-makers to time market entry.

Table 2: Top 5 Trending Grocery Categories in 2025 (Lazada)
Category Avg. Monthly Sales Price Fluctuation %
Packaged Snacks 24,000 6%
Instant Foods 19,500 4%
Cooking Oils 15,200 3%
Rice & Grains 13,800 5%
Beverages 12,100 7%

Outcome: Startups gain insight into fast-selling categories, enabling smarter inventory and import planning.

Benefits of Lazada Grocery Data Scraping for Startups

The benefits of Lazada grocery data scraping for startups go beyond pricing. Startups can identify brand visibility, customer loyalty indicators, and unmet demand signals.

Table 3: Review Sentiment Analysis by Brand (2024-2025)
Brand Avg. Rating Positive Sentiment % Customer Retention Indicator
Brand A 4.5 82% High
Brand B 3.8 68% Medium
Brand C 4.2 76% High
Brand D 3.5 60% Low

Outcome: Positive sentiment and reviews correlate with higher retention and brand loyalty.

Lazada Analytics for Startup Market Research

With Lazada analytics for startup market research, startups can layer product metadata with region-wise sales velocity, reviews, and frequency of deals.

Table 4: Regional Grocery Demand Index (2025)
Region Product Volume Index Top-Selling SKU
Manila 125 Instant Noodles
Jakarta 140 Packaged Snacks
Bangkok 115 Cooking Oil
Kuala Lumpur 110 Beverages
Ho Chi Minh 130 Rice & Grains

Outcome: Enables market entry planning by understanding local demand hotspots.

Real-Time Grocery Product Tracking and Innovation Mapping

Grocery product trend tracking for startup innovation is essential for identifying niche market gaps. Real-time tracking with Lazada Data Scraping API uncovers:

  • Product drop frequency
  • Fast restock signals
  • Seasonal pricing
Table 5: Monthly Trend Volatility for New Grocery SKUs (2025)
Month New SKUs Added Price Volatility %
Jan 1,250 5.5%
Mar 1,370 6.1%
May 1,450 7.0%
Jul 1,510 8.2%
Sep 1,320 6.0%
Nov 1,480 7.5%

Outcome: Timing product launches and understanding seasonal inventory shifts.

Using Lazada Data for U.S. Startup Competitive Analysis

With Lazada data for U.S. startups, teams can conduct competitor audits, price undercutting, and discover white-label opportunities. Combining this with scraping Lazada for competitive grocery product intelligence helps:

  • Track discount cycles
  • Map consumer preferences
  • Segment value vs premium customers
Table 6: Flash Sale Performance Across Grocery Categories (Q2 2025)
Category Avg. Discount % Sales Spike %
Snacks 22% 45%
Staples 18% 30%
Beverages 25% 50%
Frozen Foods 20% 42%
Dairy 15% 28%

Outcome: Sharpening pricing and promotional strategies for new entrants.

Ready to launch smarter with Lazada data?
Contact Us Today!

Conclusion

The Lazada grocery App dataset is a goldmine for U.S. startups seeking to disrupt the Southeast Asian grocery market. With Actowiz’s expertise in Travel & Tourism Datasets, Price Optimization, and Price Intelligence, entrepreneurs gain a critical edge in strategy, product development, and customer acquisition. From real-time pricing data from Lazada for startup analytics to OTA-level competitor tracking, our solutions convert raw data into actionable insights.

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

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Real results from real businesses using Actowiz Solutions

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Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
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“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
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Iulen Ibanez
CEO / Datacy.es
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1 min
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Febbin Chacko
-Fin, Small Business Owner
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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 & palniring

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 inights Top-slling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Relail Partner)

"Actow's helped us reduce out of ststack 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

"Actow's helped us reduce out of ststack incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

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