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GeoIp2\Model\City Object
(
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                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
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                            [ru] => США
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    [registeredCountry:protected] => GeoIp2\Record\Country Object
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                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
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                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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                    [2] => isInEuropeanUnion
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    [traits:protected] => GeoIp2\Record\Traits Object
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                    [ip_address] => 216.73.216.155
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
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                    [8] => isHostingProvider
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                    [14] => isTorExitNode
                    [15] => mobileCountryCode
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                    [17] => network
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                    [19] => staticIpScore
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    [city:protected] => GeoIp2\Record\City Object
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                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                    [8] => timeZone
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    [postal:protected] => GeoIp2\Record\Postal Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [code] => 43215
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            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
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    [subdivisions:protected] => Array
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            [0] => GeoIp2\Record\Subdivision Object
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                    [record:GeoIp2\Record\AbstractRecord:private] => Array
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                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
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                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
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                    [validAttributes:protected] => Array
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)

 country : United States
 city : Columbus
US
Array
(
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    [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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Report

Zepto Cleaning Aid Product Analysis – Delhi - Fixing Assortment, Promotion, And Margin Leakage Issues

Zepto Cleaning Aid Product Analysis – Delhi uncovering assortment gaps, promotion impact, and strategies to reduce margin leakage.

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Note: You’ll receive it via email shortly after submitting the form.

Introduction

Delhi’s quick commerce ecosystem has rapidly evolved over the past few years, transforming consumer buying behavior in essential categories like household cleaning aids. With ultra-fast delivery promises and high-frequency purchasing patterns, platforms like Zepto have intensified competition across pricing, assortment depth, and promotional campaigns. This comprehensive Zepto cleaning aid product analysis – Delhi by Actowiz Solutions uncovers key trends impacting assortment optimization, discount strategies, and profit margins.

Leveraging advanced Quick Commerce Data Scraping, Actowiz gathered structured datasets from multiple Delhi pin codes covering product listings, SKU variations, pricing shifts, discount intensity, pack sizes, stock availability, and brand positioning. The objective was to analyze market dynamics between 2020 and 2026 and identify margin leakage risks caused by aggressive promotions and inconsistent assortment planning.

The findings reveal that while the cleaning aids category has experienced consistent growth, uncontrolled discounting, overlapping SKUs, and poor promotional alignment have created significant profitability challenges. This report outlines actionable intelligence for brands seeking sustainable growth in Delhi’s competitive quick commerce landscape.

Pricing Intelligence and Competitive Movements

To gain category-wide transparency, Actowiz deployed systems to Extract Zepto cleaning product pricing data across various micro-markets in Delhi. This structured framework, powered by Quick Commerce Data Intelligence, enabled continuous monitoring of base prices, discounted prices, and price fluctuations at SKU level.

Between 2020 and 2026, pricing volatility intensified considerably:

Year Avg. Monthly Price Revisions Avg. Discount Depth SKU Expansion Rate
2020 5 10% 12%
2021 7 14% 18%
2022 10 18% 22%
2023 14 22% 28%
2024 18 25% 35%
2025 22 29% 42%
2026 27 33% 50%

The frequency of price revisions increased more than fivefold. Discount depth rose from an average of 10% in 2020 to 33% in 2026. While expanded SKUs improved customer choice, it also increased internal competition and reduced pricing discipline. Brands without automated monitoring struggled to respond quickly to competitor discount spikes, leading to reactive price drops and shrinking margins.

Promotional Cycles and Offer Benchmarking

Using advanced automation to Scrape cleaning aids prices on Zepto, Actowiz analyzed promotional frequency, flash sale intensity, and coupon integration. This detailed Zepto cleaning aid product analysis - Delhi identified patterns in weekend promotions, festival sales, and limited-time offers.

Year Avg. Monthly Promotions Peak Discount % Revenue Spike During Sale Period
2020 3 18% 8%
2021 4 21% 11%
2022 6 25% 14%
2023 8 28% 18%
2024 11 32% 22%
2025 13 36% 27%
2026 15 40% 32%

Promotional events grew nearly five times between 2020 and 2026. While sales periods drove short-term revenue spikes, prolonged discounting weakened brand equity and trained customers to wait for offers. The data indicates that over-discounting without demand forecasting contributed significantly to margin erosion.

Category Expansion and Consumer Demand Shifts

The Delhi Cleaning Aids Market Analysis Using Zepto Data reveals substantial growth driven by hygiene awareness, nuclear families, and working professionals opting for quick commerce convenience. Categories such as disinfectants, multi-surface cleaners, and toilet cleaners saw steady growth post-2020.

Year Category Growth Rate Avg. Orders/Month New Brand Launches
2020 9% 10,500 12
2021 12% 15,800 20
2022 16% 21,200 27
2023 19% 27,900 34
2024 22% 35,000 42
2025 24% 43,500 49
2026 27% 52,000 57

Rapid brand entries intensified competition. However, duplication in pack sizes and overlapping price tiers resulted in assortment clutter. Without proper rationalization, brands risked cannibalizing their own SKUs and increasing operational complexity.

Price Segmentation and Margin Risk Analysis

Through Zepto cleaning aid product price distribution analysis, SKUs were segmented into three primary tiers: budget, mid-range, and premium.

Year Budget (%) Mid-Range (%) Premium (%)
2020 50 35 15
2021 47 37 16
2022 44 39 17
2023 42 41 17
2024 39 43 18
2025 37 44 19
2026 34 46 20

Mid-range SKUs dominated by 2026. However, frequent discounting blurred tier differentiation, forcing premium SKUs into mid-range pricing territory. Brands offering excessive bundled discounts experienced 8–12% average margin compression. Maintaining strategic tier differentiation is critical for sustainable profitability.

Assortment Depth and Listing Efficiency

By implementing automation to Scrape cleaning aid product listings on Zepto, Actowiz evaluated listing accuracy, image quality, description consistency, and stock availability.

Year Avg. Out-of-Stock Rate Duplicate Listings Content Accuracy
2020 13% 7% 88%
2021 15% 9% 90%
2022 17% 11% 92%
2023 18% 13% 94%
2024 16% 12% 96%
2025 14% 9% 97%
2026 12% 7% 98%

Out-of-stock rates peaked in 2023 due to demand surges but improved with better inventory forecasting. Duplicate listings contributed to customer confusion and pricing inconsistencies, increasing margin leakage risks.

Automation, Infrastructure, and Real-Time Monitoring

With advanced Zepto Quick Commerce Data Scraping, Actowiz implemented scalable data pipelines delivering daily and near real-time insights.

Year Data Refresh Cycle Data Accuracy Reporting Speed
2020 Weekly 84% 5 Days
2021 Bi-Weekly 87% 4 Days
2022 Daily 90% 3 Days
2023 Daily 93% 2 Days
2024 Near Real-Time 95% 1 Day
2025 Near Real-Time 97% <24 Hours
2026 Real-Time 98% Instant

Improved reporting cycles reduced reaction time to competitor promotions by over 40%. Real-time dashboards enabled proactive assortment rationalization and dynamic price optimization.

Actowiz Solutions delivers structured Zepto Datasets customized for SKU-level analysis, category segmentation, and promotional benchmarking. Our deep expertise in Zepto cleaning aid product analysis - Delhi ensures precise monitoring of assortment depth, pricing trends, and discount intensity.

Key Differentiators:

  • Advanced scraping infrastructure ensuring high accuracy
  • Pin code-level competitive intelligence
  • Customizable dashboards and reporting tools
  • Continuous monitoring and adaptive parsing systems
  • Dedicated analytics support for actionable insights

Our solutions empower brands to transition from reactive discounting to predictive pricing strategies.

Conclusion

Delhi’s cleaning aids category within quick commerce presents strong growth potential but also significant risks from uncontrolled promotions and assortment overlap. By integrating advanced Web Crawling service capabilities with structured Web Data Mining, Actowiz Solutions provided actionable intelligence to identify pricing gaps, reduce margin leakage, and optimize SKU portfolios.

Brands leveraging automated quick commerce intelligence can maintain pricing discipline, enhance assortment planning, and sustain profitability in an increasingly competitive environment.

Partner with Actowiz Solutions today to unlock real-time quick commerce insights and build a smarter, data-driven competitive strategy for long-term success.

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Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

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

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

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

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