Scrape Consumer Electronics D2c: Festival Price Trend Analysis

By Author: Actowiz Solutions
Total Articles: 186
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Introduction
Scrape Consumer Electronics D2C: Festival Price Trend Analysis is a case study by Actowiz Solutions that shows how large-scale price intelligence helps brands plan and win festival sales.
The festival season in India marks a surge in online consumer spending, especially across electronics categories. During Diwali and Independence Day, marketplaces such as Amazon, Flipkart, Croma, Vijay Sales, and Reliance Digital launch aggressive promotional campaigns featuring flash deals, cashback offers, and bundled discounts.
However, predicting when and where prices will drop — and which SKUs will trend — can be challenging for D2C (Direct-to-Consumer) brands competing alongside major retailers.
To solve this, Actowiz Solutions, a leading web scraping and data intelligence company, deployed a large-scale data collection and analytics solution to monitor festival pricing patterns across major marketplaces. The goal was to give brands accurate, daily insights into pricing behavior, helping them plan marketing budgets, time promotions, and forecast demand.
Project Objective
The client ...
... — a top consumer electronics D2C brand — wanted to:
Track Diwali and Independence Day price patterns across marketplaces.
Identify peak discount windows for phones, wearables, and accessories.
Analyze competitor pricing strategies and promotional patterns.
Create an actionable price-intelligence dashboard for internal teams.
Use historical price data to forecast demand and schedule campaigns effectively.
The overarching goal was simple: maximize ROI from seasonal promotions by aligning campaigns with real-time market data.
Scope & Dataset Size
Actowiz Solutions set up a daily crawling system covering:
1.2 Lakh SKUs across categories: smartphones, smartwatches, earbuds, chargers, and accessories.
5 Major Platforms: Amazon India, Flipkart, Reliance Digital, Croma, and Vijay Sales.
Duration: 45 days leading up to Diwali and 20 days before Independence Day.
Data Points Captured: Product name, brand, SKU ID, MRP vs. sale price, discount percentage, stock availability, rating and review count, delivery speed, and regional price variations.
This dataset helped identify patterns between festival events and consumer buying behavior.
Key Challenges
1. Dynamic Pricing Fluctuations
Marketplace prices changed hourly, especially during flash sales. Capturing accurate moment-in-time data was critical.
2. High SKU Volume
Tracking over 1.2 lakh SKUs daily across multiple platforms required distributed crawling infrastructure.
3. Inconsistent Data Structures
Different marketplaces used varying HTML structures and APIs, complicating normalization.
4. Stock Volatility
Products frequently went out of stock during peak hours, making it difficult to track true pricing trends.
5. Historical Comparison
To identify genuine discounts, historical MRP and sale-price archives were required since many discounts were recycled from earlier months.
Actowiz Solutions Approach
1. Real-Time Data Collection Infrastructure
Actowiz deployed dedicated cloud servers to crawl and refresh pricing data every 4 hours during peak festival periods. The system detected sudden price drops, deal expirations, and platform-specific offers.
2. Data Normalization & Enrichment
AI-powered parsers standardized product titles to match SKUs across sites. Enrichment layers added brand mapping, model identification, and category segmentation.
3. Historical Data Benchmarking
Price archives from the previous quarter served as a baseline to identify genuine discounts.

Smartphone Price Drop Analysis – Galaxy S23 128GB
MRP: ₹74,999
July Average Price: ₹44,499
Diwali Offer Price: ₹41,499
True Price Drop: 6.7%

4. Competitor Intelligence Dashboard
An interactive Power BI dashboard enabled SKU-level visualization, real-time monitoring, and historical price trend tracking.
5. Predictive Analytics
Machine learning models forecasted expected discount intensity based on past data and marketplace behavior.
Sample Data Example

Samsung Galaxy S23 128GB – Price & Availability Snapshot (October)
15 Oct – Amazon
MRP: ₹74,999
Sale Price: ₹64,999
Discount: 13.3%
Stock: In Stock
Rating: 4.6

16 Oct – Flipkart
MRP: ₹74,999
Sale Price: ₹62,499
Discount: 16.7%
Stock: In Stock
Rating: 4.5

17 Oct – Croma
MRP: ₹74,999
Sale Price: ₹67,999
Discount: 9.3%
Stock: Out of Stock
Rating: 4.7

19 Oct – Reliance Digital
MRP: ₹74,999
Sale Price: ₹61,999
Discount: 17.3%
Stock: In Stock
Rating: 4.6

20 Oct – Amazon
MRP: ₹74,999
Sale Price: ₹69,999
Discount: 6.7%
Stock: In Stock
Rating: 4.6

Key Insights & Findings
1. Peak Discount Days
Diwali 2024 saw the highest discounts between 17th–19th October.
Independence Day discounts peaked between 12th–14th August.
Accessories and wearables saw steeper markdowns than smartphones.
2. Price Elasticity by Category

Smartphones
Avg. Price Drop: 9–12%
Highest Drop Platform: Flipkart

Smartwatches
Avg. Price Drop: 14–18%
Highest Drop Platform: Amazon

TWS Earbuds
Avg. Price Drop: 22–25%
Highest Drop Platform: Croma

Chargers
Avg. Price Drop: 8–10%
Highest Drop Platform: Reliance Digital

3. Stock & Restock Patterns
Stockouts correlated with influencer promotions and card offers. Alerts enabled rapid restocking coordination.
4. Competitor Timing Strategy
BoAt and Noise launched early teasers, while Apple held offers until the last three days—revealing a tiered promotion approach.
5. Regional Price Differences
Pricing varied up to 4% between metro and Tier-2 cities due to logistics costs and warehouse distribution.
Key Solutions Delivered
1. Unified Pricing Dashboard
Real-time BI dashboard with product trajectories, platform comparisons, and automated summary reports.
2. Automated Alerts
Triggered alerts for best price windows, price restorations, and high-demand SKUs.
3. Predictive Pricing Model
Regression models forecasted discount depths, restock probabilities, and platform aggressiveness.
4. Campaign Optimization
Marketing campaigns aligned with predicted discount peaks, improving ad ROI.
Results

Conversion Rate
Before: 8.5%
After Actowiz: 11.3%
Improvement: +33%

Campaign ROI
Before: 2.8x
After Actowiz: 3.7x
Improvement: +32%

Waste Reduction
Before: –
After Actowiz: 27% less
Improvement: –

Forecast Accuracy
Before: 68%
After Actowiz: 91%
Improvement: +23%

Use Case: Seasonal Price & Demand Forecasting
This project demonstrates how D2C electronics brands can use Actowiz Solutions' scraping and analytics to manage seasonal volatility.
Use Case Summary:
Platforms: Amazon, Flipkart, Croma, Reliance Digital, Vijay Sales
Frequency: 4-hour interval crawling
Volume: 1.2 lakh SKUs
Deliverable: BI dashboard with alerts
Result: +33% conversions, +32% ROI
Why Festival Data Matters for D2C Brands
Festive shopping in India contributes 30–40% of annual sales for electronics brands. Marketplaces adjust prices dynamically, and manual observation can lead to missed opportunities.
By leveraging Actowiz Solutions' scraping and analytics, D2C brands can:
Identify true discount windows.
Benchmark competitor pricing.
Align ad bursts with demand.
Optimize inventory and timing.
Future Outlook
Actowiz is expanding this model globally to support:
Black Friday & Cyber Monday (US/UK)
Singles' Day (China)
White Friday (UAE)
Boxing Day (Australia/Canada)
Each event presents a chance to combine cultural insight with real-time price tracking.
Conclusion
The Consumer Electronics D2C Festival Price Trend Analysis project shows how Actowiz Solutions turns data into strategic advantage. With predictive analytics, automated dashboards, and historical benchmarking, brands can plan smarter, react faster, and sell better.
By integrating Actowiz’s platform, the client achieved measurable sales growth, improved demand forecasting, and maximized festive ROI — setting a new benchmark for D2C data intelligence in India.

Learn More >> https://www.actowizsolutions.com/consumer-electronics-dtoc-festival-price-trends.php

Originally published at https://www.actowizsolutions.com