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Weekly E-commerce Price Comparison in Amazon India - Trends & Insights-01

Introduction

Navratri marks one of India’s biggest shopping seasons, where online platforms like Amazon, Flipkart, Myntra, Ajio, and Snapdeal roll out mega discounts ranging from 50% to 70%. With millions of buyers rushing to grab deals, businesses must go beyond traditional monitoring methods to keep pace with this competitive ecosystem. Manual tracking is no longer sufficient—this is where Navratri E-Commerce Sale Data Insights make the difference.

Festive sales have grown consistently over the years, with India’s e-commerce festive revenue rising at a CAGR of 23% between 2020 and 2024. Shoppers now expect real-time offers, instant availability, and competitive prices across categories. This makes advanced tools for sale tracking and competitor monitoring critical for both customers and businesses.

At Actowiz Solutions, we enable structured and automated monitoring of festive offers using advanced scraping technologies. Our expertise in Ecommerce Data Scraping provides retailers with actionable insights, helping them forecast demand, adjust pricing strategies, and capture market share during the high-stakes Navratri season.

This blog explores how businesses can decode consumer trends and stay competitive with Navratri E-Commerce Sale Data Insights, while automating tracking across Amazon, Flipkart, Myntra, and other leading e-commerce platforms.

The Growing Power of Navratri Festive Deals

The Indian festive shopping landscape has witnessed exponential growth over the last five years. Navratri, in particular, has become one of the most lucrative sales periods, rivaling even Diwali and New Year campaigns. Platforms such as Amazon, Flipkart, and Myntra attract millions of shoppers daily, driving massive revenue inflows for retailers.

Between 2020 and 2024, the total value of online festive sales in India nearly tripled. In 2020, the market recorded approximately ₹28,000 crore during Navratri, whereas 2024 saw this figure cross ₹72,000 crore. Analysts expect 2025 to hit ₹90,000 crore, driven by rising internet penetration, aggressive offers, and increased adoption of digital wallets.

Year Festive Sale Value (₹ Crore) Avg Discount % Active Shoppers (Million)
2020 28,000 30–50% 120
2021 36,000 35–55% 150
2022 47,000 40–60% 180
2023 56,000 45–65% 220
2024 72,000 50–70% 260
2025* 90,000 (projected) 50–75% 300+

(*Estimated CAGR: ~23%)

While consumers benefit from discounts, businesses face intense competition. Without Web Scraping Navratri Festive Deals 2025, it becomes nearly impossible to identify winning categories or optimal discount ranges. For example, electronics may dominate Flipkart sales, while Myntra focuses heavily on ethnic wear during Navratri. Businesses that lack data-driven strategies risk missing consumer demand shifts.

Retailers also need Navratri E-Commerce Sale Data Insights to monitor emerging trends. In 2024, for example, kurtas and fusion wear saw a 40% higher demand compared to traditional sarees, while consumer electronics achieved record-high flash sale participation.

Another critical element is Real-Time Track Competitor Prices. Research shows that brands adjusting their pricing based on competitor movements increase sales conversions by 25–35%. This proves that competitive tracking is as important as customer engagement.

In summary, the growing importance of Navratri festive sales means businesses cannot afford guesswork. They must leverage structured insights to stay competitive, make smarter pricing decisions, and deliver maximum value to customers.

Real-Time Tracking of Discounts Across Platforms

Real-Time Tracking of Discounts Across Platforms

During Navratri, e-commerce giants launch multiple campaigns across different time slots. Amazon may start with its “Great Indian Festival,” Flipkart counters with “The Big Billion Days,” and Myntra introduces “Big Fashion Festival.” Each campaign has different timelines, discount slabs, and category-specific promotions. Keeping up with all these variations in real time is nearly impossible without automation.

This is why businesses rely on tools to Scrape Amazon And Flipkart Navratri Deals and Offers, allowing them to capture live data on discounts, coupon codes, and category trends. With structured dashboards, businesses can identify which products are gaining traction and which offers are underperforming.

Real-world example: In 2023, Amazon launched midnight smartphone deals offering 30–40% discounts. Within hours, Flipkart countered with 35–45% discounts on similar models. Businesses that monitored these trends manually missed critical opportunities. Automation ensured instant alerts, enabling sellers to adjust campaigns and pricing strategies quickly.

The role of Navratri Mega Sale Price Tracking is particularly important in fashion categories. Myntra, for instance, often launches tiered discounting models—50% off on kurtas, 60% on lehengas, and additional 10% coupons for select banks. Without real-time monitoring, sellers lose out on visibility into consumer choices.

For customers, structured insights from Navratri E-Commerce Sale Data Insights provide direct benefits. Shoppers can set alerts for their desired discount ranges. For instance, a buyer looking for footwear at 60% off can receive an alert the moment such an offer goes live.

The business side also benefits from Real-Time AI Dynamic Pricing. By integrating AI-driven scrapers, retailers can automatically update product pricing to remain competitive. A report by RedSeer Consulting indicates that brands using dynamic pricing during festive sales experience up to 40% higher conversion rates compared to those relying on fixed pricing models.

Ultimately, real-time tracking across Amazon, Flipkart, Myntra, and other platforms ensures businesses remain proactive instead of reactive. Whether it’s for sellers wanting to maintain competitiveness or shoppers eager to grab the best deals, real-time insights are a must-have in 2025.

Stay ahead this Navratri—use real-time tracking of discounts across Amazon, Flipkart & Myntra to unlock 50–70% savings instantly!
Contact Us Today!

Flash Sales and Limited-Time Offers

Flash sales are the heartbeat of festive campaigns. They generate urgency, drive massive spikes in traffic, and create FOMO (Fear of Missing Out) among customers. But they also present a challenge—offers often last only a few minutes, and monitoring them manually is practically impossible.

This is where Scraping Navratri 2025 Flash Sales & Festival Discounts becomes invaluable. Automated tools continuously monitor e-commerce sites, capturing data about flash sale launches, discount percentages, and stock availability. Both consumers and businesses benefit from instant notifications.

For example, Myntra launched a lehenga flash sale in 2024 at 65% off at 7:00 PM. Within 15 minutes, the stock was sold out. Customers using automated tools could act instantly, while businesses captured the data for future demand analysis.

The relationship between discounts and stock movement is particularly revealing. Research shows that products discounted at 65% sell out 2x faster than those at 50%. This insight helps businesses plan their inventory and promotions more effectively.

Discount % Avg. Sell-out Time (Fashion) Avg. Sell-out Time (Electronics)
40% 6–8 hours 2–3 hours
50% 3–4 hours 1–2 hours
60% 1–2 hours 45–60 minutes
65%+ <1 hour 20–30 minutes

The use of Real-Time Navratri Sale Price Tracking via Web Scraping also builds predictive intelligence. For instance, in 2023, footwear categories with flash discounts consistently sold faster than accessories. Businesses could then allocate higher ad spend to categories with quicker sell-out rates.

Equally important is capturing festive season price intelligence. Beyond consumer benefits, structured flash sale data enables sellers to forecast future campaigns, ensuring they don’t understock or overprice products.

In summary, flash sales are no longer just about quick discounts—they are about unlocking insights into consumer urgency and price sensitivity. With structured monitoring, businesses can not only participate in flash sales but also dominate them.

Competitive Benchmarking Across E-Commerce Sites

Competition is fierce during Navratri, and customers often compare products across multiple e-commerce sites before purchasing. In fact, a Deloitte India survey revealed that 72% of online shoppers check at least two platforms before making a purchase decision. This makes competitive benchmarking across platforms critical.

By Scraping Navratri 2025 flash sales across eCommerce sites, businesses can capture cross-platform pricing and discount variations. For instance, while Amazon may offer 55% off on kurtas, Myntra might push discounts to 60%, and Ajio may offer additional bank-linked cashback. Businesses with access to structured data can fine-tune their promotions accordingly.

One popular use case is Amazon vs Flipkart Navratri sale price comparison. Electronics such as smartphones often see head-to-head battles, with price differences as low as 2–3%. Brands and retailers tracking both platforms can adjust prices instantly to retain competitiveness.

Customers also benefit from such benchmarking. Instead of manually switching between apps, scraping tools consolidate insights into one place, helping users grab the best deal.

Retailers leverage Web Scraping Services to integrate benchmarking into their dynamic pricing models. For example, if Amazon cuts laptop prices by 20% in a flash sale, Flipkart sellers can match or slightly undercut prices within minutes.

Cross-platform benchmarking also reveals consumer behavior trends. Data from 2020–2024 shows that:

  • Amazon dominates electronics.
  • Flipkart leads in budget smartphones and appliances.
  • Myntra captures fashion and footwear markets.
  • Ajio sees growth in western wear and casual categories.

By aligning with these insights, businesses gain a strategic edge. With Navratri E-Commerce Sale Data Insights fueling cross-platform comparisons, retailers can ensure competitive parity while enhancing customer satisfaction.

Structured Data Extraction for Deeper Insights

Tracking discounts is just the first step—making sense of the data is where the real value lies. Without structured datasets, insights remain fragmented.

The ability to scrape Navratri 2025 offers from Myntra, Ajio & Snapdeal ensures businesses can extract product names, categories, prices (original vs discounted), availability, and even user reviews. This structured format allows for trend analysis across multiple years.

For example, analyzing Navratri sales data from 2020 to 2024 revealed:

  • Sarees were the top-selling category in 2020–2021.
  • Kurtas overtook sarees in 2022.
  • Footwear demand surged in 2023.
  • Fusion wear became dominant in 2024.

Such long-term visibility helps businesses predict 2025 trends and prepare stock accordingly.

Additionally, integration with Extract Amazon Website Data allows businesses to compare across categories. For example, tracking how electronics vs. fashion performed during Navratri gives businesses a broader view of consumer demand shifts.

Structured insights are also vital for marketing. Retailers can identify high-demand categories and push targeted campaigns to maximize conversions. For instance, if footwear has the fastest sell-out rates, businesses can increase ad budgets specifically for that category.

With Navratri E-Commerce Sale Data Insights, businesses move from reactive discount hunting to proactive festive strategies. They can optimize stock, refine campaigns, and even predict future consumer patterns.

Unlock festive trends with structured data extraction—analyze Navratri discounts, track categories, and make smarter, insight-driven e-commerce decisions!
Contact Us Today!

Beyond Fashion – Expanding E-Commerce Insights

Beyond Fashion – Expanding E-Commerce Insights

While fashion and electronics dominate Navratri sales, other categories such as cosmetics, skincare, and lifestyle products are seeing exponential growth. Urban consumers, especially Gen Z and millennials, are increasingly spending on personal care during festivals.

This is why businesses must expand beyond core categories. By scraping Nykaa Website Data, businesses can uncover discounts on beauty, skincare, and cosmetics. In 2024, Nykaa saw a 35% YoY increase in festive season sales, making it one of the fastest-growing platforms.

Scraping beyond core platforms also reveals cross-selling opportunities. For example, a customer buying a festive lehenga might also search for complementary cosmetics. Businesses analyzing bundled shopping behaviors can create targeted combo offers.

Regional preferences are another dimension. Ethnic wear dominates in North and West India, while fusion and casual categories are more popular in South India. Similarly, beauty and lifestyle categories show higher demand in Tier-1 cities. Businesses using Navratri E-Commerce Sale Data Insights can adjust inventory distribution accordingly.

Another overlooked opportunity lies in smaller platforms like Ajio and Snapdeal, which attract budget-conscious consumers. By integrating festive season price intelligence across these platforms, retailers capture additional market share.

In conclusion, Navratri is no longer confined to fashion and electronics—it’s a holistic e-commerce ecosystem. Businesses that expand their scraping strategies across multiple categories and platforms unlock maximum value during the festive surge.

How Actowiz Solutions Can Help?

At Actowiz Solutions, we provide end-to-end e-commerce scraping solutions tailored for festive campaigns. Whether it’s Web Scraping Navratri Festive Deals 2025, cross-platform benchmarking, or flash sale tracking, we deliver structured insights that empower businesses to make data-driven decisions.

Our offerings include:

  • Real-time monitoring across Amazon, Flipkart, Myntra, Ajio, Snapdeal, and Nykaa.
  • Automated competitor tracking and price benchmarking.
  • Historical data extraction to forecast festive demand.
  • API integration for seamless business intelligence reporting.

With our expertise, retailers can move beyond manual tracking and embrace predictive intelligence. From identifying winning categories to optimizing dynamic pricing strategies, Actowiz ensures businesses stay competitive during high-demand seasons.

By leveraging Navratri E-Commerce Sale Data Insights, we help businesses maximize revenue, minimize risks, and unlock growth opportunities during the most crucial shopping period of the year.

Conclusion

Navratri 2025 promises to be the biggest festive sale season yet, with discounts soaring up to 70% across Amazon, Flipkart, and Myntra. But in a marketplace this competitive, manual tracking and guesswork won’t cut it. Businesses need structured, real-time intelligence to adapt and win.

From monitoring flash sales to benchmarking prices across platforms, Navratri E-Commerce Sale Data Insights empower retailers to anticipate consumer demand, adjust campaigns, and stay ahead of competitors. Shoppers benefit by grabbing the best offers instantly, while businesses benefit by making informed, profit-driven decisions.

Actowiz Solutions specializes in festive season scraping strategies, offering tools to monitor, analyze, and automate sales tracking across multiple platforms. With structured insights and advanced automation, we ensure businesses extract maximum value from every Navratri sale.

Ready to transform your festive sales strategy? Partner with Actowiz Solutions today and harness the power of real-time e-commerce intelligence for Navratri 2025! You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!

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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
                        )

                )

            [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] => 216.73.216.160
                    [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

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

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Co-Founder / Head of Product at Upright Data Inc.
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Iulen Ibanez
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Febbin Chacko
-Fin, Small Business Owner
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1 min

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

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

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

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & 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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