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Actowiz Metrics Now Live!

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Actowiz Metrics Now Live!

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Actowiz Metrics Now Live!

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Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

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Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

Unlock Smarter , Faster Analytics!

Actowiz Metrics Now Live!

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Actowiz Metrics Now Live!

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GeoIp2\Model\City Object
(
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                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                    [iso_code] => US
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                            [ru] => США
                            [zh-CN] => 美国
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            [postal] => Array
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            [registered_country] => Array
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                            [zh-CN] => 美国
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                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
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                            [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
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                    [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
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                            [ru] => США
                            [zh-CN] => 美国
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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        )

    [locales:protected] => Array
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    [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
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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        )

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

            [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
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                    [5] => type
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [ip_address] => 216.73.216.213
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
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            [validAttributes:protected] => Array
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                    [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
                        (
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                            [en] => Columbus
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                )

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

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

            [validAttributes:protected] => Array
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                    [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
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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
)

Introduction

In consumer brands, the digital marketplace presents unprecedented opportunities for customer engagement and market expansion. Within this dynamic landscape, incorporating Digital Shelf Analytics becomes pivotal in a brand's eCommerce strategy. This cutting-edge technology provides crucial insights into a brand's visibility, encompassing organic and paid aspects on various marketplaces. It delves into essential facets such as content quality, pricing strategies, promotional initiatives, and product availability. By emphasizing concepts like Digital Shelf Analytics, ROI business, eCommerce scraping services, retail analytics, and retail data collection, brands can effectively utilize these insights to understand their competitive positioning and elevate their overall market performance.

Despite the challenges many brands face in understanding whether insights from the digital shelf translate into actionable strategies that drive tangible business impact and ROI, there is evidence that effectively leveraging these insights can lead to significant, measurable benefits.

The crucial question remains: Does Digital Shelf Analytics live up to its promises? At Actowiz Solutions, we have collaborated with numerous brands, empowering their eCommerce growth through digital shelf analytics. This article will explore these insights, revealing the concrete and quantifiable results that brands can attain through their investments in digital shelf analytics.

Unlocking the Power of Digital Shelf Key Performance Indicators (KPIs) for Business Impact

Digital Shelf Analytics is a robust system that analyzes key performance indicators (KPIs) related to the digital shelf. This system provides brands with precise recommendations to strengthen these KPIs and monitor improvements over time. The following concisely explains digital shelf KPIs and the impact areas they are expected to influence.

Eliminating Out-of-Stock Situations: Ensuring Seamless Product Availability for Shoppers

Accurate and timely insights into product availability are essential for brands to streamline large-scale replenishment processes, exerting a significant influence on sales and establishing a robust correlation between product availability and revenue. Through the utilization of Digital Shelf Analytics, purchasing and replacement teams can configure notifications to swiftly identify low or out-of-stock items, facilitating prompt corrective action. This capability extends to specific ZIP codes or individual stores. Additionally, product availability plays a pivotal role in determining a brand's Share of Search and search rankings, as online marketplaces prioritize displaying in-stock products among the top results.

Maximizing Digital Shelf Visibility: Unveiling the Significance of Share of Search

In the digital realm, product visibility is paramount – if a product isn't visible, does it exist? With 70% of consumers never venturing beyond the first page of search results on major online marketplaces, a brand's product visibility for relevant search keywords, particularly on the first page, significantly influences awareness metrics. Enter the concept of Share of Search, akin to securing prime shelf space in a physical store. Leveraging digital shelf insights and benchmarking against category leaders, Share of Search ensures that your products garner substantial attention on the digital shelf.

Elevating Content Quality for Enhanced Product Visibility and Sales Impact

In the competitive landscape of a crowded marketplace, creating captivating product descriptions and visuals is like providing your products with a powerful megaphone. Elevating content quality, encompassing product names, titles, descriptions, and images, empowers brands to ascend the search result rankings, resulting in heightened visibility and, consequently, increased sales.

Harnessing the Influence of Social Proof: The Impact of Ratings and Reviews on Sales Growth

The power of public opinion is significant, as research has shown that a single positive review can result in a 10% boost in sales. Additionally, accumulating multiple favorable reviews can push a product to a 44% higher trajectory. This connection between ratings and sales is unsurprising, as each step up the rating scale can lead to significant revenue growth.

While anticipating a correlation between these key performance indicators (KPIs) and downstream impact metrics like impressions, clicks, and conversions, we delved into this connection through an analysis of real-world data. We precisely monitored digital shelf KPIs for our client and scrutinized the enhancements in these metrics.

It's important to note that not all observed impact areas can be solely attributed to enhancements in digital shelf KPIs. Nevertheless, a strong and clear correlation does exist. The following section presents an in-depth case study that sheds light on the results of this analysis.

From Data to Success: A Complete Example of Digital Shelf Analytics Making a Difference

Join us as we explore the journey of a well-known consumer packaged goods (CPG) brand that specializes in baked food and desserts. Through their experience, we aim to showcase the transformative effects of our Digital Shelf Analytics products suite. In the time period from August ‘22 to July ‘23, the brand actively utilized various critical components of Digital Shelf Analytics used for Amazon. These modules, which include Share of Category, Share of Search, Availability, Reviews, Ratings, and Content Audit, served as essential digital shelf key performance indicators (KPIs), significantly shaping the brand's performance at different stages of the buyer's journey.

The typical buyer's journey unfolds in three distinct stages:

Awareness: Shoppers explore various product options displayed on category and search listing pages, gaining an initial understanding of the available choices.

Consideration: Shoppers narrow their selections, evaluating a few products more closely as they move closer to a purchase decision.

Conversion: In the final stage, the shoppers make their final product choice and complete the purchase.

Now, let's delve into the data to comprehend how digital shelf KPIs played a pivotal role in driving tangible ROI on Amazon for the brand across these stages of the buyer's journey.

Stage 1: Raising Awareness

In the first stage, our aim is to increase the visibility of the product and create brand awareness. To achieve this, we focus on improving the Share of Search and the Share of Category. Our client has seen consistent and incremental improvements in their Share of Search and Share of Category over the analyzed period. This has been possible through the strategic implementation of various tactics such as product sponsorship, content enhancement, price optimization, and promotional initiatives. The chart below illustrates the improvements made by our client within the top 20 ranks of each listing page.

This increased Share of Search and Share of Category directly results in enhanced product discoverability, as highlighted by the notable surge in impressions in the chart below.

Stage 2: Deliberation in Progress

During the consideration stage, shoppers refine their product choices based on factors such as average rating, the number of ratings, price, product title, and images. This emphasizes the critical importance of brands creating meticulously detailed product content and accumulating significant ratings.

The following chart depicts the year-long trend in average ratings and the number of ratings, showcasing a consistent and positive improvement over time.

The improvements in both the number of ratings and the average rating exert a direct and positive influence on product consideration. Consequently, this has resulted in a discernible year-over-year increase in page views, as depicted in the chart below.

These enhancements are likely inclined by the overall improvement of content quality that is given distinctly in the section given below.

Stage 3: Guiding Decisions

As buyers move to the next stage, they reach a crucial point of purchase. Several factors influence this decision, including product availability, content quality, and the quality of reviews that reflect customer sentiment.

Our client utilized our Availability insights efficiently, considerably reducing the possibility of probable out-of-stock scenarios and better replenishment rates. This improvement is highlighted in the chart below. The same chart also demonstrates an improvement in content quality, as measured by the alignment of content on Amazon with the brand's ideal content standards.

Below, you'll discover the year-over-year conversion rate growth for the Amazon brand. This metric is the ultimate gauge of business impact, directly translating into heightened brand revenue.

As revealed by the data, the growth in critical digital shelf KPIs collectively exhibited a robust correlation with impressions, page views, and conversion rates. It's crucial to acknowledge that the impact of each KPI cannot be viewed in isolation, as they often exhibit interdependence. For instance, enhancements in content and availability could elevate Share of Search, while accurate content contributes to more positive customer feedback. Brands should adopt a holistic optimization approach to digital shelf KPIs to generate sustained business impact.

Effect on eCommerce Sales

Following the integration of digital shelf analytics, the outcomes were self-evident. Sales consistently surpassed the previous year's records month after month. As depicted in the chart below, the meticulous application of Actowiz Solutions' recommendations resulted in a noteworthy 8.5% year-over-year increase in sales, leaving a lasting imprint on the brand's eCommerce success.

Digital Shelf Analytics is a powerful tool that can help brands achieve unparalleled online success, from increasing product visibility to boosting conversion rates. While it's not yet possible to create a direct connection between sales revenue and Digital Shelf Analytics, there is a clear correlation that should not be ignored. By using digital shelf KPIs, brands can optimize their eCommerce performance across all stages of the buyer journey. Therefore, it's crucial for brands to work with the suitable partner and leverage digital shelf insights to perfect eCommerce tactics and strategies.

However, the eCommerce arena is constantly changing, and you can learn so much about how every digital shelf KPI affects brand performance online.

If you want to see your brand succeed in eCommerce, contact us today to learn more about how Digital Shelf Analytics can help you drive higher sales and market share. You can also reach us for all your mobile app scraping, instant data scraper and web scraping service requirements.

GeoIp2\Model\City Object
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            [traits] => Array
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    [continent:protected] => GeoIp2\Record\Continent Object
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                            [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
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    [country:protected] => GeoIp2\Record\Country Object
        (
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                    [iso_code] => US
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                        (
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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    [locales:protected] => Array
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
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            [validAttributes:protected] => Array
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        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [iso_code] => US
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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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    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [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

+1 ▼

Select Service Web Scraping Real-Time API Access Data Dashboards Datasets Review & Sentiment Analysis Price Monitoring Custom Solution

Select Industry E-Commerce Quick Commerce Food Delivery Travel & OTA Grocery & Retail Real Estate Others

Target Country Web Scraping Services Mobile App Scraping Web and App Scraping API Datasets Dashboard

A$лвR$C$CHF¥Kčkr€£HK$FtRp₪₹kr¥₩Mex$RMkrNZ$₱złleikrS$฿₺$R Budget Range $500 - $1,000 - Starter Budget (POC/Single Site) $1,000 - $2,500 - Basic Plan (Small Business Needs) $2,500 - $5,000 - Growth Phase (Multi-site/Data Volume Projects) $5,000 - $10,000 - Business-Scale (Automation/API Integrations) $10,000 - $25,000 - Enterprise Projects (Real-Time Systems, Global Data) $25,000 - $50,000 - Enterprise+ (Custom Dashboards, Ongoing Support) $50,000+ - Strategic Partnership (End-to-End Data Ops)

Additional Trust Elements

✨ "1000+ Projects Delivered Globally"

⭐ "Rated 4.9/5 on Google & G2"

🔒 "Your data is secure with us. NDA available."

💬 "Average Response Time: Under 12 hours"

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize

Explore Solutions Get a Custom Demo

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.

Ecommerce

Q-Commerce

Travel & OTA

Food Delivery

Real Estate

Social Media

Trusted by Global Leaders – Secured by International Standards

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 Galido

Co-Founder / Head of Product at Upright Data Inc.

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.”

Iulen Ibanez

CEO / Datacy.es

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!”

Febbin Chacko

-Fin, Small Business Owner

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

Request Demo Access

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

All

Blog

Case Studies

Infographics

Report

Jan 05, 2026

Hotel & Flights Combined Price Index in Europe - Travel Budget Uncertainty with Integrated Cost Data and Market Statistics

Hotel & Flights Combined Price Index in Europe helps reduce travel budget uncertainty with integrated cost data, market statistics, and actionable pricing insights.

Reducing Hotel Booking Costs Across Multiple Cities Using Trip.com API-Driven Hotel Chain Price Intelligence

Case study shows how Trip.com API-Driven Hotel Chain Price Intelligence enables multi-city hotels to monitor real-time prices, optimize rates, and reduce booking costs.

Grocery Price Movement Tracker – Walmart, Instacart & Target

Real-time grocery price changes across Walmart, Instacart and Target. Track top SKU drops, increases and hourly volatility with Actowiz Solutions.

City-Wise Demand & Delivery Time Analysis for NIC Ice Cream - Solving Last-Mile Challenges in Quick Commerce

City-Wise Demand & Delivery Time Analysis for NIC Ice Cream reveals how data improves stock planning, delivery speed, and customer satisfaction across markets.

Jan 05, 2026

Hotel & Flights Combined Price Index in Europe - Travel Budget Uncertainty with Integrated Cost Data and Market Statistics

Hotel & Flights Combined Price Index in Europe helps reduce travel budget uncertainty with integrated cost data, market statistics, and actionable pricing insights.

Jan 05, 2026

CMC vs Competitors - Ready-to-Cook Pricing Trends on Blinkit & Swiggy Instamart

CMC vs Competitors – Analyze ready-to-cook pricing trends on Blinkit and Swiggy Instamart to track market positioning, discounts, and consumer preferences.

Jan 04, 2026

Naturals & NIC Ice Cream Price Tracking - Blinkit vs Swiggy Instamart - Which Platform Offers Better Deals?

Track Naturals & NIC Ice Cream Price Tracking - Blinkit vs Swiggy Instamart to compare real-time prices, offers, and savings across platforms.

Read More

Reducing Hotel Booking Costs Across Multiple Cities Using Trip.com API-Driven Hotel Chain Price Intelligence

Case study shows how Trip.com API-Driven Hotel Chain Price Intelligence enables multi-city hotels to monitor real-time prices, optimize rates, and reduce booking costs.

Enhancing Quick Commerce Efficiency with Stock-Out & Dark-Store Availability Monitoring for CMC Products

Discover how Stock-Out & Dark-Store Availability Monitoring for CMC Products improves quick commerce efficiency by reducing fulfillment gaps, delays, and lost sales.

Scaling Price Monitoring for a Shopify Aggregator

See how Actowiz Solutions helped a Shopify aggregator scale price monitoring across 500+ stores, driving a 22% revenue increase via automated data scraping.

Read More

Grocery Price Movement Tracker – Walmart, Instacart & Target

Real-time grocery price changes across Walmart, Instacart and Target. Track top SKU drops, increases and hourly volatility with Actowiz Solutions.

Enhancing Deep Learning Models With Image Scraping

Enhance deep learning performance with large-scale image scraping. Build diverse, high-quality training datasets to improve AI accuracy, object detection, and model generalization.

Dark Store Location Optimization - Data-Driven Strategy Explained

Uncover how data-driven strategies optimize dark store locations, boosting quick commerce efficiency, reducing costs, and improving delivery speed.

Read More

City-Wise Demand & Delivery Time Analysis for NIC Ice Cream - Solving Last-Mile Challenges in Quick Commerce

City-Wise Demand & Delivery Time Analysis for NIC Ice Cream reveals how data improves stock planning, delivery speed, and customer satisfaction across markets.

City-Wise Demand & Delivery Intelligence for CMC – Solving Supply Gaps and Last-Mile Delays in Quick Commerce

City-Wise Demand & Delivery Intelligence for CMC reveals how data solves supply gaps and last-mile delays, improving speed, availability, and customer satisfaction.

Brand-Wise Hourly Rental Car Price Datasets Reveal Competitive Behavior Across Hertz, Avis, Budget, Sixt, and Enterprise

Explore how brand-wise hourly rental car price datasets uncover competitive pricing behavior, demand trends, and strategy shifts across Hertz, Avis, Budget, Sixt, and Enterprise.

Read More

Our perks are irreplaceable

Time Zone Flexibility

Benefit from the ease of collaboration with Actowiz Solutions, as our team is aligned with your preferred time zone, ensuring smooth communication and timely delivery.

Clear Communication

Our team focuses on clear, transparent communication to ensure that every project is aligned with your goals and that you’re always informed of progress.

Uncompromising Quality

Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations

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