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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
                        )

                )

            [continent] => Array
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                    [code] => NA
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                    [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
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                    [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
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                    [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] => 216.73.216.160
                    [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
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                    [2] => names
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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
                (
                    [0] => en
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            [validAttributes:protected] => Array
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                    [1] => geonameId
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                    [3] => isoCode
                    [4] => names
                )

        )

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

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [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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            [validAttributes:protected] => Array
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                    [0] => confidence
                    [1] => geonameId
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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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            [validAttributes:protected] => Array
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                    [2] => isInEuropeanUnion
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                    [4] => names
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                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.160
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
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                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
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                    [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
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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
                        )

                )

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

            [validAttributes:protected] => Array
                (
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                    [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
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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
)

Starbucks Menu And Store Dataset From USA – Prices, Locations & Reviews Data

Access the Starbucks Menu And Store Dataset From USA – a comprehensive dataset featuring prices, locations, and reviews to analyze trends and optimize store and menu strategies.

  • Store Name
  • Menu Item
  • Price
  • Customer Rating

Starbucks Datasets Explained

Starbucks Menu Prices Dataset for the United States and the Starbucks Store and Menu Dataset in the US provide structured data on store locations, menu items, prices, and customer insights, enabling analysis, trend tracking, and data-driven business decisions.

  • Product ID
  • Product Image
  • Product Name
  • Country of Origin
  • Brand
  • Allergens
  • Availability
  • Category
  • Delivery Fee
  • Delivery Options
  • Delivery Time
  • Description
  • Discounts/Offers
  • Expiration Date
  • Ingredients
  • Minimum Order Amount
  • Nutritional Information
  • Order Status
  • Packaging Details
  • Payment Methods
  • Price
  • Promotional Tags
  • Return Policy
  • Reviews
  • SKU (Stock Keeping Unit)
  • Stock Level
  • Store Location
  • Store Name
  • User Ratings
  • Weight/Volume
  • Nutrition
Datasets-Explained
AP_IDAirport NameBrandMenuItemNameMenuItemIDCategorySubCategory_1SubCategory_2SizeLongNamePricePromotional PriceURLBrand_StoreIDAddressCityStateZipCodeCountryPhoneLatitudeLongitudeExtractionDateCaloriesStore NameCurrencydistance_apartFlavor_1Flavor_2Flavor_3
RDURaleigh-Durham International AirportStarbucksSteamed Milk747DrinksHot Chocolate, Lemonade & MoreMilk & SteamersShortSteamed Milk Short3.35N/Ahttps://www.starbucks.com/menu/product/747/hot?storeNumber=68126-30162910406521070 Darrington DrCaryNC27513US+1 919-342-300535.79998-78.8171206/24/2025 02:07:45 AM100Cary Parkway & DarringtonUSD5.7894'category_name': 'Syrups', 'flavours_name': ['Brown Sugar Syrup', 'Caramel Syrup', 'Cinnamon Dolce Syrup', 'Hazelnut Syrup', 'Horchata Syrup', 'Peppermint Syrup', 'Sugar-Free Vanilla Syrup', 'Vanilla Syrup'] 'category_name': 'Sauces', 'flavours_name': ['Dark Caramel Sauce', 'Mocha Sauce', 'White Chocolate Mocha Sauce'] 'category_name': 'Powders', 'flavours_name': ['Cherry Sweet Powder', 'Chocolate Malt Powder', 'Lavender Powder', 'Vanilla Bean Powder']
ATLHartsfield-Jackson Atlanta International AirportStarbucksEthos® Water873068636DrinksBottled BeveragesWater & Sparkling23.7-PackagedEthos® Water 23.7-PackagedN/AN/Ahttps://www.starbucks.com/menu/product/873068636/packaged?storeNumber=17527-1815651137283660 Marketplace BlvdAtlantaGA30344US+1 404-267-006333.65904-84.4994906/25/2025 07:54:41 PMN/ATarget East Point 1546USD4.2276N/AN/AN/A
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Flexible-Data-Delivery

Flexible Data Delivery

Tailored to your Instacart product price scraping needs, we provide flexibility in selecting output formats, storage options, and delivery schedules:

  • Access food datasets in JSON, CSV, and other preferred formats;
  • Retrieve data through SFTP or integrate directly with cloud storage solutions like Google Cloud Storage, AWS S3, and more;
  • Choose one-time, monthly, quarterly, or bi-annually extract food datasets frequencies to suit your requirements.
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Premium Industry Datasets on Demand

Access Actowiz's curated enterprise datasets for precise data insights, sourced by top web data specialists.

Efficiency Meets Expertise
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Save time; our team expertly extracts data for analysis, aligning with strategic business goals cost-effectively.

Tailored Data Solutions for Your Enterprise
Tailored Data Solutions for Your Enterprise

Receive tailored industry datasets; our flexible methods align with unique business needs for optimal decisions.

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Commitment to Ethical Data Practices

Actowiz leads Ethical Web Data Collection, upholding GDPR and CCPA, setting standards for responsible data practices./p>

Pricing Overview

Standard-Pricing

Standard Pricing

  • Standardized Data Offerings with readily accessible datasets.
  • Consistent Data Framework that ensures clarity and consistency.
  • Top-tier Data Integrity from the most intricate data channels.

Flexible Delivery Options:

  • Monthly Updates
  • Quarterly Deliveries
  • One-off Purchases
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Custom Pricing

  • Tailored Data Retrieval precisely aligned with your business needs.
  • Adaptable Data Framework crafted to fit your unique needs.
  • Scalable & Dynamic Offerings to ensure flexibility and scalability.
  • Streamlined Communication ensures smooth and instant communication.

Varied Delivery Options:

  • Daily Updates
  • Weekly Snapshots
  • Monthly Insights
  • Quarterly Reports
  • Customized Frequencies to Suit You
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Inclusive Benefits Across All Plans:

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  • Expert Data Extraction
  • Regulatory Assurance
  • Personalized Support
  • Broad Data Coverage

Why Choose Actowiz Solutions’ Datasets?

Assessing-Your-Data-Requirements

Assessing Your Data Requirements:

Our first step is to delve into your company's specifics and business goals, ensuring we align perfectly with your data aspirations.

Crafting-Tailored-Data-Solutions

Crafting Tailored Data Solutions

Leveraging our robust in-house web scraping tools, we design a bespoke strategy tailored to your data extraction needs.

Sample-Data-Preview

Sample Data Preview

Experience firsthand with a sample of our company data. Gauge its quality and familiarize yourself with our seamless data delivery mechanism.

Steadfast-Data-Streamlining

Steadfast Data Streamlining

Once aligned, we initiate regular data dispatches based on the frequency and specifications we've mutually agreed upon.

Frequently Asked Questions

The Starbucks Menu And Store Dataset From USA provides detailed insights into store locations, menu items, prices, and customer reviews. The Prices, Locations & Reviews Dataset helps businesses analyze trends, optimize operations, and improve customer experience. The Starbucks USA Store & Menu Dataset also supports market research and strategic decision-making across the United States.
The Starbucks USA dataset offers structured information on store locations, menu items, and pricing. Using the Starbucks USA locations dataset, businesses can track market trends, compare store performance, and optimize inventory. The Starbucks Store Finder USA Data allows quick access to store-specific information for data-driven decision-making and operational efficiency.
The Starbucks Menu Prices Dataset for the United States provides menu items, categories, prices, and nutritional information. It complements the Starbucks Store and Menu Dataset in the US by including store locations, ratings, and reviews. Together, these datasets allow analysis of trends, pricing strategies, and customer preferences across Starbucks locations in the U.S.
Yes, the Starbucks Store Finder USA Data helps identify store locations, operating hours, and delivery options. Combined with the Starbucks USA locations dataset, it allows businesses to optimize supply chains, monitor performance, and analyze customer behavior. Using the Starbucks Menu And Store Dataset From USA, companies can make informed operational and marketing decisions.
The Starbucks Store and Menu Dataset in the US provides detailed information on menu items, prices, store locations, and reviews. Along with the Starbucks Menu Prices Dataset for the United States, it allows businesses to track Prices, Locations & Reviews Dataset, analyze consumer trends, optimize inventory, and implement competitive strategies across Starbucks stores nationwide.

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

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