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                                    [ru] => Огайо
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            [validAttributes:protected] => Array
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [validAttributes:protected] => Array
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    [registeredCountry:protected] => GeoIp2\Record\Country Object
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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    [traits:protected] => GeoIp2\Record\Traits Object
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            [validAttributes:protected] => Array
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    [postal:protected] => GeoIp2\Record\Postal Object
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                                    [de] => Ohio
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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
)

Amazon's Prime Day for this year they have shattered records, marking the most monumental Prime Day occurrence in the company's history. Throughout the two-day spectacle, consumers in the United States expended an astonishing $12.7 billion, showcasing a 6.1% surge from the prior year. Amid inflationary pressures and disturbances in the supply chain, Amazon boldly embraced a discounting strategy that presented even more substantial price cuts in contrast to the Prime Day of 2022.

An intriguing facet of Amazon's strategy is its utilization of loyalty-driven incentives. In the weeks leading up to the July 11-12 Prime Day, members of their loyalty program were provided access to "by-invitation-only deals," allowing shoppers to request invitations for specific products they aimed to purchase at discounted rates. On the whole, Amazon's intricate pricing and discount maneuvers during Prime Day were meticulously orchestrated to incite excitement among shoppers, stimulate heightened sales, and preserve a competitive edge within the market.

While Prime Day undoubtedly commands Amazon's spotlight, it's equally captivating to observe how other prominent retailers react to this massive sales event orchestrated by their principal contender. Do they conform by lowering their prices during the event, or do they prefer to assume a more passive role? In addressing these inquiries, we harnessed our exclusive data compilation and analysis platform to scrutinize the pricing and discounts presented by Amazon and its chief rivals across pivotal product categories – encompassing Apparel, Home & Furniture, Consumer Electronics, and Health & Beauty – during the Prime Day extravaganza.

Acknowledging that products on Amazon and other e-commerce platforms often feature reduced prices even on regular days outside of sale events, we delved into the authentic value Prime Day imparts to shoppers. This approach concentrated on the scale of price deductions or supplementary discounts attainable during the sale when juxtaposed with the preceding week. Consequently, our methodology accentuates the bona fide advantages the event extends to shoppers anticipating decreased prices amid the sale period.

Research Methodology

In our study, we closely monitored price fluctuations across a substantial assortment of products available at multiple prominent retailers throughout both the Prime Day event and the preceding week. The specifics of our chosen sample are outlined below:

  • Analysis Period before Prime Day: July 4th to July 10th, 2023
  • Enlisted Categories: Home & Furniture, Apparel, Health & Beauty, Electronics
  • Online Platforms Included: Walmart, Amazon, Overstock, Target, The Home Depot, Ulta Beauty, Wayfair, Sephora
  • Prime Day Analysis Period: July 11th to July 12th, 2023
  • Total SKUs Examined: 110,000+

Fundamental Discoveries

Based on our collected data, it becomes evident that Amazon exhibited the most assertive price cuts within the Consumer Electronics domain during Prime Day. This segment experienced an average price decrease of 10.4%, driven by its widespread appeal and substantial demand.

Fundamental-Discoveries

The sale event witnessed relatively moderate offerings in the Health & Beauty category (6.7%), followed by Apparel (5.9%) and Home & Furniture (4.8%) segments.

In the subsequent sections, we delve into a more detailed analysis of each category. This enables us to understand how price reductions were dispersed among vital subcategories on Amazon and further explore the discounting approaches employed by Amazon's foremost competitors.

Apparel

Confronted with excess inventory, elevated warehousing expenses, and narrowed profit margins in the apparel sector—much akin to the challenges faced by many other retailers—Amazon had already marked an average pre-Prime Day discount of 13.3%. However, during the Prime Day event, Amazon's discounted offers on apparel settled at a more restrained 5.9%, spanning an impressive 33.1% of its product array. In contrast, Target and Walmart opted for a less pronounced competitive stance.

Apparel

Diverging from Prime Day 2022, during which Target actively competed with Amazon through substantial discounts, the retailer's participation in the current event was marked by a meager supplementary discount of 0.8% applied across merely 4.4% of its merchandise within the same category. Similarly, Walmart's pricing strategy reflected a restrained approach, with a modest 1.4% price reduction observed across 8.5% of its product selection during the Prime Day event.

We invite you to peruse our most recent analysis encompassing fashion pricing trends from 2022 to 2023. This examination offers an enhanced understanding of this particular category's intricate pricing dynamics.

Throughout our scrutiny of various apparel subcategories, noteworthy price reductions were evident in Women's Athleisure (8.7%), Men's Swimwear (8%), and Women's Tops (7.6%). Conversely, more conservative markdowns were observed in Men's Athleisure (2.5%), Women's Shoes (3.5%), and Men's Innerwear (4.1%).

Apparel

Pricing determinations within the diverse subcategories were undoubtedly shaped by multiple factors, including inventory levels, consumer demand trends, and the imperative to strike a harmonious equilibrium between competitive propositions and sustaining viable profit margins. This approach was particularly evident as Amazon endeavored to cater to a clientele with a heightened sensitivity to price considerations.

Among the entirety apparel subcategories scrutinized, prominent brands that implemented the most substantial price reductions included Tommy Hilfiger (11.5%), Amazon Essentials (9.4%), Adidas (8.6%), and Calvin Klein (8.6%).

Apparel

Nevertheless, for brands, reducing prices represents merely one facet to allure and convert potential shoppers. Equally crucial is their ability to establish a strong visibility and discoverability within Amazon's search listings. This pivotal aspect exponentially augments their prospects of eliciting more clicks and conversions. In our comprehensive analysis, we meticulously monitored brands' Share of Search across various popular search keywords. The Share of Search signifies the proportion of a brand's products present within the top 20 search results for a given query.

Our amassed data underscores that numerous brands managed to enhance their discoverability substantially during the Prime Day event, while others encountered setbacks in this endeavor. Notably, Gildan in the Men's Innerwear category, Adidas in both Men's and Women's Shoes, Anrabess in Women's Athleisure, and Lululemon in Men's Athleisure, among other instances, significantly improved their Share of Search metrics during the Prime Day period.

Apparel

Conversely, certain brands, including Hanes in Kanu Surf for Men's Swimwear, Men's & Women's Innerwear, Cupshe for Women's Swimwear, and several others, experienced a decline of approximately 10% in their Share of Search during the event. This is likely to have exerted an adverse influence on their sales volumes.

Home & Furniture

The Home & Furniture sector has encountered difficulties stemming from dwindling demand, primarily attributed to inflationary forces prevailing over the past year. Foremost players in this category miscalculated the extent of demand, resulting in an excess inventory accumulation. Consequently, Home & Furniture stands as one of the limited domains where Amazon's contenders are markedly engaged during Prime Day. This strategic involvement aimed to safeguard against the risk of lagging in liquidating their surplus stock.

Home-&-Furniture

Amazon extended supplementary discounts averaging 4.8% across 30.2% of its product range. Wayfair and Overstock followed suit, implementing price cuts of 4.8% and 4.3%, respectively, affecting approximately 44% of their respective inventories. Wayfair's maneuver aligns with its strategy to attract fresh clientele and broaden its market presence, addressing the decline in its consumer base. The prior year they witnessed Wayfair experiencing a notable reduction of 5 million customers from its 1.3 billion total due to weakened demand.

While Target and Walmart did introduce additional discounts, their competitive edge was limited. Meanwhile, Home Depot chose not to engage in the competitive arena during the sales event. These retailers' pricing tactics starkly contrast with the notably restrained pricing strategies observed during Prime Day the previous year.

Our recently conducted pricing analysis within the Home & Furniture category has unveiled further intriguing revelations regarding the pricing dynamics over the past year. Across all the meticulously examined subcategories, noteworthy price reductions were found in Bookcases (8.2%), Rugs (7.8%), Mattresses (6.5%), and Luggage (6.2%).

Home-&-Furniture2

Conversely, Sofas (2.4%), Washer / Dryers (2.4%), and Entertainment Units (2.7%) exhibited comparatively more modest markdowns. These particular items constitute significant purchases, prompting retailers to exercise prudence in applying deep discounts while maintaining profitability.

Among the brands that embraced a more assertive approach and implemented substantial markdowns within this category, notable participants encompassed Zinus (20.2%), Comfee (10.8%), Sauder (9.9%), and Best Choice Products (8.7%).

Home-&-Furniture3

Examining the Share of Search metrics, Rockland emerged at the forefront in the Luggage segment with the most significant gain (21%). Subsequently, Farberware in the Dishwasher category, Olee Sleep in Mattresses, and Homeguave in Mattresses notably elevated their standings in their respective domains, as illustrated in the accompanying image.

Home-&-Furniture4

Brands such as Best Products of Coffee Tables, Black+Decker for Washer/Dryers, Molblly for Mattresses, and Dishwashers come across notable declines in their Share of Search during the event. Given the intense rivalry for prominence during sale occasions, brands that neglect to monitor their Share of Search metrics risk experiencing a decline in their sales performance. This circumstance holds particularly true in categories like Home & Furniture, where brand loyalty tends to be relatively low.

Consumer Electronics

Consumer-Electronics

In 2023, the spotlight on Amazon Prime Day was undoubtedly centered around consumer electronics. Amazon orchestrated an average price reduction of 10.4% across 54.5% of its product lineup within this category. In contrast, Target and Walmart took a distinct approach, presenting notably more conservative additional discounts of 1.9% and 2.7%, spanning 10.4% and 19.1% of their assortments, respectively.

Consumer-Electronics2

The consumer electronics sector consistently experiences robust price cuts during Prime Day and similar sales, mainly due to its widespread popularity and substantial demand. Moreover, given the typically narrow profit margins for retailers within this category, consumers often anticipate sale events like Prime Day, where brands adjust their wholesale rates to access a diverse array of appealing deals.

Spanning our analysis of diverse subcategories, Smartwatches (15.4%), Wireless Headphones (15.4%), Earbuds (14.9%), Headphones (12.5%), and Tablets (12.0%) emerged as the subcategories featuring the most pronounced price reductions. Each subcategory enjoys considerable popularity and registers substantial sales volumes during sale events.

Consumer-Electronics3

In contrast, Laptops (2.1%), TVs (3.1%), and Smartphones (7.6%) observed relatively more modest price reductions. The reduced markdowns on smartphones could reflect a sustained demand pattern throughout the year, consequently mitigating the need for substantial discounts during the relatively brief Prime Day period.

Amazon (22%), Tozo (12.5%), Lenovo (10.8%), JBL (8.3%), and Apple (5%) were at the forefront in offering the most substantial price reductions across the entire spectrum of Consumer Electronics. Amazon was committed to enticing deals for its proprietary label products within this category.

Consumer Electronics, a category characterized by brand loyalty among shoppers, still places significant importance on the generic Share of Search keywords. Share of Search for generic terms remains crucial, particularly for products such as earbuds, headphones, and tablets, which are associated with relatively lower price points social. Notably, HP in Laptops, Samsung in Tablets and TVs, and Oneplus in Smartphones made commendable strides in bolstering their visibility on Amazon during the Prime Day event. This initiative transcends merely driving sales, extending to fostering heightened brand awareness among intent-driven shoppers.

Consumer-Electronics4

Sony in the Headphones category, Asus in Laptops, and Insignia in TVs encountered challenges regarding their visibility compared to other brands during the sale event. This outcome is significant for Sony and Asus, given their notable standing as prominent brands within their respective categories.

Health & Beauty

The Health & Beauty category garners significant favor among consumers during Prime Day due to its diverse products, including skincare, cosmetics, and grooming essentials. Given shoppers' inclination to stock up during this sale, brands and retailers are inclined to provide competitive discounts to secure a competitive advantage over their rivals.

Our collected data reveals that Amazon featured an average supplementary discount of 6.7%, extending to slightly over one-third of its product range. Equally substantial, Walmart introduced noteworthy price reductions, with an average markdown of 3.1% applicable to 13.4% of its offerings within the category.

Health-&-Beauty

Curiously, prime contenders in the Health & Beauty realm, Sephora and Ulta Beauty opted out of competitive pricing endeavors during this Prime Day event. This strategic choice likely stems from their confidence in the steadfast loyalty of their customer base. They are unwavering in their belief that Amazon's Prime Day offerings won't sway their devoted clientele with the mere allure of lower prices. Moreover, maintaining steady pricing during Prime Day could be an intentional move to uphold its brand reputation and preserve its premium positioning.

Among the relatively upscale subcategories, like Electric Toothbrushes (10%), Moisturizer (8.3%), Beardcare (7.3%), and Makeup (6.7%), Amazon displayed the most notable price reductions.

Health-&-Beauty-2

On the other hand, essentials such as Toothpaste (3.7%), Shampoos (5.4%), and Conditioners (5.7%) experienced relatively modest price reductions.

Among the prominent brands within this category, Oral-B (10.3%), Philips Sonicare (8.7%), Neutrogena (8.4%), and Colgate (5.6%) emerged as the frontrunners in presenting alluring deals during the sales event.

Health-&-Beauty-3

Regarding substantial advancements in Share of Search metrics for brands, Oral-B took the lead once more in Electric Toothbrushes. Following closely were Neutrogena (Sunscreens) and Somall (Toothpastes), both achieving more than a 10% increase in their Share of Search during the sale event. This was trailed by Tresemme (Shampoos) and Airspun (Make-Up products), showcasing notable strides in boosting their discoverability.

Health-&-Beauty-4

Interestingly, well-known brands such as Crest (Toothpastes), e.l.f (Make-Up), Philips Sonicare (Electric Toothbrushes), and Sheamoisture (Beardcare) displayed unexpectedly diminished prominence among the upper echelons of search results for pertinent subcategories.

Staying Ahead During Sale Events

In this Prime Day spectacle, Amazon harnessed its extensive reach to deliver robust discounts across pivotal product categories, as certain rival retailers chose to observe the proceedings passively. Others adopted a tactical approach, directing their modest price reductions toward a limited selection of items.

At Actowiz Solutions, we recognize the paramount significance of competitive pricing insights in endowing retailers and brands with a distinct competitive advantage, particularly during pivotal junctures like Prime Day. For retailers, the capacity to meticulously monitor competitor prices with precision, at scale, and promptly is indispensable for crafting and executing impactful pricing strategies, ensuring they remain ahead of the curve.

To delve further into these capabilities, don't hesitate to connect with us today! You can also reach us for all your mobile app scraping, web scraping, or instant data scraper service requirements.

GeoIp2\Model\City Object
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                    [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
                    [1] => geonameId
                    [2] => names
                )

        )

    [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
                )

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

        )

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

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

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

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [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] => 216.73.216.211
                    [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
)

Start Your Project

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Additional Trust Elements

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💬 "Average Response Time: Under 12 hours"

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
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1 min
★★★★★
“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
1 min

See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

Price Drop + 12 min
in 6 hrs across Lel.6

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.

✔ Scraped Data: Price Insights Top-selling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

Actowiz Insights Hub

Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place

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Oct 03, 2025

London Property Market Trends 2025 - Average Price £664,700, Asking Prices Down –1.5% (Rightmove & Zoopla Data)

Explore London Property Market Trends 2025: Avg price £664,700, asking prices down –1.5%. Key insights from Rightmove & Zoopla data.

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Competitor Review Analysis for Retail Conversion - How Retailers Boosted Conversion Rates

Competitor Review Analysis for Retail Conversion, showing how retailers leveraged insights from competitor reviews to boost conversion rates.

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Grocery Pricing Data Intelligence in USA - Comparing Weekly and Daily Insights

Explore this research report on Grocery Pricing Data Intelligence in USA, comparing weekly and daily insights to track trends, optimize pricing, and drive decisions.

Oct 03, 2025

London Property Market Trends 2025 - Average Price £664,700, Asking Prices Down –1.5% (Rightmove & Zoopla Data)

Explore London Property Market Trends 2025: Avg price £664,700, asking prices down –1.5%. Key insights from Rightmove & Zoopla data.

Oct 02, 2025

Hyperlocal Retail Secrets Using Quick Commerce Data - Unlocking Market Insights for Faster Decisions

Discover how Hyperlocal Retail Secrets Using Quick Commerce Data help businesses gain actionable insights, optimize operations, and make faster, smarter decisions.

Oct 01, 2025

Tracking Discount Patterns on Best Buy Using Data Scraping – 10–20% Seasonal Discount Trends in the USA

Explore Tracking Discount Patterns on Best Buy Using Data Scraping – uncover 10–20% seasonal discount trends in the USA with detailed insights from 2020–2025.

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Competitor Review Analysis for Retail Conversion - How Retailers Boosted Conversion Rates

Competitor Review Analysis for Retail Conversion, showing how retailers leveraged insights from competitor reviews to boost conversion rates.

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Real-Time Booking.com Hotel Room Pricing Data Scraping for Optimized Hotel Room Pricing in the USA

real-time Booking.com hotel room pricing data scraping in the USA, helping hotels optimize pricing strategies for better revenue.

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Scrape Zillow and Rightmove Property Data Insights for Predictive Analytics

Discover how Actowiz Solutions used Scrape Zillow and Rightmove Property Data Insights to deliver predictive analytics, market trends, and smarter decisions.

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Grocery Pricing Data Intelligence in USA - Comparing Weekly and Daily Insights

Explore this research report on Grocery Pricing Data Intelligence in USA, comparing weekly and daily insights to track trends, optimize pricing, and drive decisions.

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Leveraging Quick Commerce Price Intelligence - Key Findings from0 Zepto Data Analysis

A research report leveraging Quick Commerce Price Intelligence, analyzing Zepto data to uncover pricing trends, competitive insights, and market opportunities.

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Ride-Hailing Competition in NYC - Uber, Lyft & Yellow Cab Pricing Analysis

Ride-Hailing Price Comparison in NYC - An in-depth analysis of Uber, Lyft, and Yellow Cab fares, highlighting cost trends and competitive insights.