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GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
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                            [en] => Columbus
                            [es] => Columbus
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                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [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
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                    [iso_code] => US
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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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            [postal] => Array
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            [registered_country] => 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
                        )

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                            [names] => Array
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                                    [de] => Ohio
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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
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.160
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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
                        )

                )

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

            [validAttributes:protected] => Array
                (
                    [0] => code
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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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                    [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
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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
                )

        )

    [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
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

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

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

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

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

        )

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

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

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

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)
Pricing-and-Availability-Trends-of-Top-Retailers-and-Brands-in-South-Africa-in-2023

Despite the temporary setbacks caused by COVID-19, South Africa's eCommerce market is poised for substantial growth in 2023 and beyond. With a projected market size of $7.2 billion and a compound annual growth rate (CAGR) of 12.5% until 2027, retailers have immense potential to capitalize on this expanding market.

To attract and convert online shoppers, retailers must aim to secure the most competitive pricing position among their competitors. Consistently offering competitively priced products is crucial for gaining and maintaining market share. This necessitates tracking and comparing product pricing relative to competitors on an ongoing basis.

For brands, aligning pricing and discounting strategies with market trends is essential for capturing market share. In light of recent global supply chain challenges, maintaining high stock availability rates is crucial for capitalizing on rising consumer demand. As brands develop a cohesive eCommerce strategy, ensuring price parity across all online channels becomes increasingly essential.

In this blog, we have utilized Actowiz Solutions' proprietary data aggregation and analysis platform to analyze the eCommerce performance of leading South African retailers and brands across various critical dimensions.

Research Methodology for Analyzing South Africa's Leading Retailers and Brands

Our research focused on analyzing the performance of prominent South African retailers and brands, including ShopRite, Takealot, Leroy Merlin, and Pick n Pay. Our study covered a vast product range, with over 40,000 SKUs across over 190 categories.

We paid particular attention to critical categories such as Home, Spirits, Bath, and Food, which provided valuable insights into pricing and availability trends within these segments.

To ensure comprehensive findings, our analysis spanned from October 2022 to March 2023, allowing us to capture relevant market dynamics and fluctuations during this timeframe.

We utilized Actowiz Solutions' advanced data aggregation and analysis platform for data collection and analysis. This proprietary tool enabled us to efficiently gather and process large volumes of data, extracting critical insights on pricing strategies, product availability, and market competitiveness.

By leveraging this robust research methodology, we aim to provide valuable and accurate information on the competitive pricing and availability trends of South Africa's leading retailers and brands in 2023.

Reported Key Metrics:

Price Increase Opportunity: This metric identifies situations where a retailer has the potential to increase the price of a product while remaining the lowest-priced option among competitors. Capitalizing on price increase opportunities can directly contribute to margin improvement and profitability.

Price Decrease Opportunity: This metric highlights instances where a retailer should decrease the price of a product by a certain amount to secure the lowest price position among competitors. Implementing price decreases can lead to increased sales and market share.

Action Rate: The action rate is the percentage of identified price improvement opportunities (both price increases and decreases) the retailer acts upon within 15 days of identifying the opportunity. For instance, an action rate of 25% indicates that out of 100 identified price improvement opportunities, the retailer takes action on 25 of them within the specified timeframe. This metric measures the retailer's responsiveness and agility in adjusting prices based on market dynamics.

Competitive Pricing Actions of Retailers

Retailers employ diverse approaches when responding to their competitors' pricing actions, and it is crucial not only to react but also to react swiftly. The chart below showcases the average action rates for the price increase and decrease opportunities, categorized into three timeframes: within 5 days, 6-10 days, and 11-15 days of the opportunity arising.

Among the retailers, Takealot stands out with a robust competitive pricing engine. The retailer seizes over half (51%) of price increase opportunities, enhancing their margins. Additionally, they act on more than a third (36%) of price decrease opportunities, which helps them gain a competitive edge. However, there is room for improvement in acting on these opportunities more promptly. Only 52% of the identified opportunities are acted upon within 5 days, while the remaining are addressed within a maximum of 15 days.

This analysis emphasizes the significance of proactive pricing strategies and timely execution in the highly competitive retail landscape. Retailers can optimize their profitability and maintain a strong market position by swiftly capitalizing on price improvement opportunities.

Competitive-Pricing-Actions-of-Retailers

ShopRite and Pick n Pay exhibit a healthy action rate of 23% for price increase opportunities. However, their performance on price decrease opportunities is relatively lower, with ShopRite at 9% and Pick n Pay at 5%. This indicates a somewhat inconsistent effort in achieving price leadership. ShopRite shows a similar pattern of pricing action velocity as Takealot, although with fewer price improvement actions. In comparison, Pick n Pay demonstrates faster responsiveness, with 64% of price improvement opportunities occurring within 5 days.

On the other hand, Leroy Merlin has a lower action rate, acting on only 9% and 6% of its price increase and decrease opportunities, respectively. However, regarding the velocity of pricing actions, Leroy Merlin surpasses the others, with 90% of its pricing actions executed within 5 days. While this speed is commendable, improving the initial action rates is essential to make the most of this advantage. Therefore, Leroy Merlin has a significant opportunity to enhance its competitive pricing tracking and operational effectiveness.

Overall, these findings highlight the importance of promptly responding to price improvement opportunities and maintaininga consistent and proactive pricing strategies to establish and maintain a competitive edge in the market.

Overall-these-findings-highlight

After analyzing the chart and observing month-on-month variances, it is evident that Takealot has consistently maintained its price leadership position over the past six months. This can be attributed to its consistently aggressive action rates on price improvement opportunities.

When examining the trends across retailers, specific, subtle patterns emerge. Takealot's action rates have slightly declined over time, decreasing its price leadership rates from 14% in November 2022 to 10% in March 2023.

On the other hand, ShopRite experienced an increase in its action rates in early 2023, resulting in an uptick in its price leadership positions. This suggests that their proactive pricing strategies have contributed to gaining a competitive edge.

In contrast, Leroy Merlin has displayed low action rates and minimal price changes. As a result, only around 2% of its products have been priced as the lowest relative to competitors. This indicates a significant opportunity for Leroy Merlin to improve its action rates and implement more competitive pricing strategies.

Overall, these trends highlight the importance of consistent and aggressive pricing actions in maintaining price leadership in the market. It also emphasizes the need for retailers to closely monitor and adjust their pricing strategies to remain competitive and capture market share.

Pricing and Availability of Leading Brands

In this section, we analyze the average discounts, price parity levels, and the stock availability of the top 5 brands, based on the number of SKUs, in four key product categories: Bath, Food, Home, and Spirits.

Bath

Bath

During the last six months, Nivea and Protex have consistently offered significant discounts, with peak discounts observed around the holiday season in December 2022 and January 2023. These brands have proactively provided attractive pricing options to consumers in the Bath category.

Additionally, Nivea and Protex stand out as the brands with the highest proportion of their products carrying discounts, at 10% and 9%, respectively. In contrast, Sanex has been more conservative in the average discounts and the share of discounted products in the Bath category.

While Nivea has been offering attractive discounts, its average stock availability has been relatively low. However, there has been improvement in recent months, with availability increasing from around 70% in October 2022 to approximately 90% in March 2023. Dettol has also faced availability issues but has shown some improvement recently. The other leading brands in this category maintain healthy stock availability levels, with rates above 90%.

Food

Food

Kellogg's and Rhodes emerge as the brands offering the highest discounts in the food category, particularly during the holiday season. They also lead in the share of discounted products, with Kellogg's at 14% and Rhodes at 7%. These brands have proactively provided discounted options for consumers in the Food category.

In the Food category, it is typical for most other leading brands to offer lesser discounts on a smaller proportion of their products, compared to Kellogg's and Rhodes.

Kellogg's offers attractive pricing and demonstrates excellent control over its supply chain operations, maintaining consistent stock availability levels of nearly 100%. Other brands faced challenges towards the end of 2022 but have improved. Nestle, for instance, experienced availability issues with only 70% in October 2022 but managed to increase it to 90% by March 2023.

Home

Home

The Home category exhibits the highest variance in discount ranges among its leading brands compared to the other categories analyzed in this report. Brands like LocknLock and Legend offer discounts ranging from 25% to 35% on more than a third of their respective product ranges. These brands have been proactive in providing significant discounts to attract consumers in the Home category.

Conversely, ADDIS and Prestige have offered smaller discounts in the range of 0% to 5% on a limited selection of their products (less than 5%).

Maintaining a consistent brand perception among consumers in categories such as Home is crucial for boosting brand value and fostering loyalty. A significant disparity in prices for a brand's products across multiple eCommerce websites can negatively impact how consumers perceive the brand.

In this context, LocknLock stands out with an average price disparity of only 10%, compared to other brands like Eetrite, Prestige, and ADDIS, which exhibit around 30% or more variances. Interestingly, the brands that offer higher discounts also tend to have lower pricing disparities. This suggests a well-thought-out, data-driven approach to eCommerce pricing and discounting, which values sales conversion and brand reputation.

By strategically managing pricing and discounting, these brands can optimize sales conversion rates while maintaining consistent brand perception, enhancing their overall competitiveness in the market.

By-strategically-managing-pricing

Prestige and Eetrite have encountered challenges in their supply chain operations, with Prestige experiencing a low stock availability of 55% in December 2022. In contrast, Legend had vital stock availability towards the end of 2022 but has seen a gradual decline in 2023 so far. On the other hand, LocknLock and ADDIS demonstrate healthy stock availability levels of 95% and above.

Spirits

Spirits

During the Christmas season, the average discounts offered by leading Spirits brands reached their peak. Brands such as Tanqueray, Jameson, and Glenlivet offered discounts of up to 30% during this period. These brands actively promoted attractive pricing options to entice consumers in the Spirits category.

Subsequently, the discounts offered by most Spirits brands have fluctuated within the range of 5% to 20% since the peak Christmas period. Most leading brands, except Smirnoff, have around 20% of their products discounted.

Similar to the Home category, brand perception is also crucial in the Spirits category. However, we observe a consistent pricing disparity among the leading brands, ranging between 18% and 25%. Brands aiming to establish a "premium" perception among consumers, such as Glenlivet and Tanqueray, may benefit from ensuring better pricing parity across their eCommerce channels.

Maintaining a cohesive pricing strategy and minimizing price discrepancies can enhance these brands' perceived value and premium positioning in the Spirits market.

Maintaining-a-cohesive-pricing-strategy

During the Christmas season, a few Spirits brands experienced a decline in stock availability, likely due to increased demand. For instance, Jameson's availability dropped below 80% during this period. However, it has since improved and currently maintains an availability level of above 90%. Similarly, Johnnie Walker has made significant progress in-stock availability, increasing from 80% in October 2022 to 95% or higher in March 2023.

Suppose you are interested in gaining more in-depth insights into South Africa's eCommerce landscape and similar analyses for other retailers and brands in the region. In that case, we invite you to contact us today. Our team can provide comprehensive details and further information based on your requirements.

For services such as web scraping, mobile app scraping, or instant data scraper, feel free to reach out to Actowiz Solutions. We specialize in providing these solutions to meet your specific needs. Contact us today to discuss how we can assist you with your data scraping requirements.

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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                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
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                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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            [country] => Array
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [location] => Array
                (
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                    [longitude] => -83.0061
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            [postal] => Array
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            [registered_country] => Array
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                    [geoname_id] => 6252001
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                            [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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                    [0] => Array
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                            [iso_code] => OH
                            [names] => Array
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                                    [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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                    [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
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
                (
                    [0] => code
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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
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                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

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

            [validAttributes:protected] => Array
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                    [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
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                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

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

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

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

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

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

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

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

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

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

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

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

        )

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

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

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

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

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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

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Smarter product targeting

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“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

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“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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Co-Founder / Head of Product at Upright Data Inc.
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Febbin Chacko
-Fin, Small Business Owner
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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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