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216.73.216.35
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AI-Scraped-Insights-for-Q-Commerce-Delivery-Time-Optimization-in-Singapore

Introduction:

Singapore’s high-density geography and digital-first population have made it a prime market for Q-Commerce. Platforms like RedMart, FairPrice, GrabMart, and Pandamart promise ultra-fast grocery deliveries. But as competition intensifies, delivery time is the new battleground.

Actowiz Solutions partnered with a leading last-mile logistics provider in Singapore to use AI-powered web scraping and machine learning models to extract, monitor, and optimize delivery time data across Q-Commerce platforms—by zone, time of day, and SKU type.

Client Objectives

  • Extract real-time delivery time estimates from Q-Commerce platforms across Singapore
  • Analyze how delivery ETAs vary by product type, location, and time
  • Identify delays, peak-hour congestion, and platform-specific fulfillment issues
  • Optimize routing and staffing models for last-mile fleets
  • Benchmark delivery time promises vs. actual performance

Challenges Faced

Challenges-Faced
  • Delivery estimates fluctuate rapidly on platforms like GrabMart and RedMart
  • ETAs varied widely between central and suburban districts
  • Some SKUs (e.g., ice cream, baby food) had stricter delivery windows
  • No historical visibility into ETA accuracy vs. promises
  • No unified data source—every platform had unique logic for time display

Actowiz’s Approach

Actowiz’s-Approach
1. AI-Powered Web Scraping Engine

Actowiz built scrapers that accessed real-time delivery ETA data from:

  • RedMart: Based on product + postal code
  • GrabMart: Dynamic delivery windows based on current fleet load
  • FairPrice Online: Delivery slot availability for next 6 hours
  • Pandamart: ETA directly shown on product detail page

These were scraped every 20–30 minutes for top 500 SKUs across 50+ postal zones.

2. Data Captured
Field Description
Platform GrabMart, RedMart, Pandamart, FairPrice
Product Name SKU being monitored
ETA (mins) Platform-reported estimated delivery time
Postal Code Singapore 6-digit code
Timestamp When the ETA was scraped
Category Frozen, Fresh, Packaged, Beverages, Essentials
3. Sample Dataset (Singapore Postal Zones)
Timestamp Platform Product Postal Code ETA (mins) Category
2025-06-14 10am GrabMart Ben & Jerry’s 239732 26 Frozen
2025-06-14 10am RedMart Ayam Brand Tuna 560143 40 Packaged
2025-06-14 10am Pandamart Dettol Soap 4pk 529538 18 Essentials

Insight: GrabMart consistently offered faster delivery for frozen products within city czones like Orchard and Clarke Quay.

4. AI Models for ETA Optimization

Actowiz used scraped data to train the following models:

  • Regression Models – Forecast delivery times based on product, time of day, and zone
  • Clustering Algorithms – Identify delivery bottlenecks by platform and region
  • Anomaly Detection – Spot outliers in promised vs. actual delivery ETAs
  • Time-Series Forecasting – Predict future delays during rain, lunch hours, or public holidays

Dashboard Features Delivered

Feature Description
ETA Heatmaps Postal code-wise visual of average delivery time by platform
SKU Delivery Benchmarking Compare delivery time for each product across 4 platforms
Peak‑Time Alerts AI‑generated alerts for high‑congestion delivery windows
ETA Accuracy Report Match promised vs. actual delivery over 7‑day cycles
Zone‑Based Routing Suggestions Suggest optimal staffing needs for last‑mile fleets

Platform vs. Platform Comparison

Platform Avg ETA (Central SG) Avg ETA (North-East) Frozen SKU Avg ETA Essentials ETA
GrabMart 24 mins 36 mins 22 mins 25 mins
Pandamart 20 mins 40 mins 30 mins 18 mins
RedMart 45 mins 55 mins 50 mins 42 mins
FairPrice Slot-Based (60–180m) Slot-Based N/A N/A

Results After 60 Days

Logistics Improvements for Client (Fleet Operator):

KPI Before Actowiz After Actowiz
On‑Time Delivery % 71% 91%
Fleet Overhead Cost High ‑22% reduced
Delay Prediction Accuracy 58% 89%
Missed Frozen Delivery Incidents 19/month 3/month
ETA Variability Range Wide (10–60m) Narrowed (15–30m)

Real-World Insights

  • Frozen goods deliveries had the narrowest time margins but biggest variance
  • Rain and lunch-hour traffic increased ETAs by up to 22% in postal codes 58xxxx–61xxxx
  • RedMart’s slot-based delays spiked during major events like Hari Raya and Lunar New Year
  • GrabMart fleet saturation caused surges in ETA across CBD zones during weekday evenings

Testimonial

“Before Actowiz, our teams had no reliable ETA intelligence. Now we can proactively plan deliveries, reroute fleets, and deliver within our promised windows—even in traffic.”

– Operations Head, Singapore Q-Commerce Logistics Partner

Next Steps:

  • Integrate real-time weather APIs to enhance ETA accuracy
  • Expand scraping coverage to Malaysia and Hong Kong Q-commerce platforms
  • Build predictive ETA models for multi-SKU cart orders
  • Offer WhatsApp alerts to customers based on expected delay risks

Conclusion

In Singapore’s tightly timed Q-Commerce race, delivery efficiency is a make-or-break factor. By scraping delivery time data from top platforms and combining it with predictive AI, Actowiz Solutions empowers logistics teams to meet customer expectations with confidence and consistency.

From postal code heatmaps to hourly delay prediction models, this solution transforms data into precision—keeping deliveries on time, every time.

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
Product Image
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 & palniring

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 inights Top-slling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Relail Partner)

"Actow's helped us reduce out of ststack 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

"Actow's helped us reduce out of ststack incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

Actowiz Insights Hub

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