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216.73.216.35
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Case-Study-Actowiz-Solutions-–-Price-Clustering-&-Discount-Mapping-on-GoPuff-Using-AI-Algorithms-(UK)

Introduction

In the UK’s ultra-fast delivery space, GoPuff has emerged as a major player, offering essentials, groceries, and convenience items within minutes. But behind GoPuff’s success lies a complex and dynamic pricing engine—with frequent price changes, regional discounting, and hyper-targeted offers.

Actowiz Solutions partnered with top FMCG brands to decode GoPuff’s pricing logic through AI-powered price clustering, discount mapping, and pattern recognition—uncovering the hidden algorithms shaping retail decisions in the UK’s quick commerce space.

Client Objectives

  • Track SKU pricing across UK cities like London, Manchester, and Birmingham
  • Identify price clusters by product category and region
  • Map discount patterns over time (flash sales, weekend deals, etc.)
  • Benchmark GoPuff's pricing against local and retail market standards
  • Provide actionable insights to plan promotions, pricing strategies, and product launches

Key Challenges

The-Client
  • Price changes occurred frequently, sometimes hourly, making manual tracking impractical
  • Regional pricing created city-level differences across SKUs
  • Flash discounts lacked warning or duration details
  • SKU naming conventions varied, requiring normalization for clustering
  • Brands lacked tools to group similar pricing patterns

Actowiz’s Data Collection & AI Modeling Approach

The-Client
GoPuff Scraping Infrastructure

Actowiz built real-time web scrapers to extract:

  • SKU Name & Brand
  • Original Price & Offer Price
  • Discount %
  • Category & Subcategory
  • Product ID
  • Region (Postcode-based or city-tagged)
  • Timestamp of each scrape

Sample Data Structure (London Zone)

Timestamp Product Name Price Discount Category Region
2025-06-15 12pm Red Bull 250ml £1.65 15% Beverages London SE1
2025-06-15 12pm Pepsi Max 500ml £1.10 0% Beverages London E1
2025-06-15 12pm Coca-Cola 330ml x4 £2.99 25% Beverages London SW6

AI Models Used

  • K-Means Clustering – Grouped SKUs into clusters based on price similarity by region
  • DBSCAN – Identified irregular pricing behavior and outliers
  • Time-Series Discount Detection – Tracked weekly/monthly price dip patterns
  • Discount Elasticity Modeling – Analyzed customer interest spikes vs. discount levels
  • Price Anomaly Detection – Alerted for steep, unscheduled price changes

Pricing Clusters Identified

Top Pricing Clusters in London:
Cluster Avg Price Range Categories Dominant Zone Sample
A £0.99–£1.50 Snacks, Soft Drinks SE1, NW1
B £2.00–£3.50 Household, Hygiene E1, SW6
C £5.00+ Alcohol, Baby Care, FMCG W1, EC3

Insight: Snacks and beverages maintained stable pricing, while clusters C (premium SKUs) showed highest volatility.

Discount Pattern Mapping

Weekly Discount Patterns (Birmingham Example):
  • Monday–Tuesday: Minimal offers, mostly full-price
  • Wednesday–Thursday: Category-specific discounts (e.g., personal care)
  • Friday–Sunday: Surge in promotions across beverages, frozen foods, essentials

Top Flash Discount Trends:

SKU Discount Spike Days Peak Discount (%) Duration
Red Bull 4-Pack Friday, Sunday 25% 6–12 hours
Doritos Nacho 150g Saturday 18% 4 hours
Andrex Tissue Sunday 30% 8 hours

Actowiz Dashboard Features

Feature Description
Real-Time Price Cluster Heatmap Visual map of average pricing tiers across regions
Discount Calendar Visualizes day-wise discount activity across product categories
Elasticity Curve Generator Shows impact of discount % on price engagement rates
Flash Sale Detection Alerts for sudden discounts in targeted categories
SKU Benchmarking Tool Compare GoPuff SKU vs. Sainsbury’s, Tesco, Amazon UK

Geographic Zones Covered

The-Client
  • London (SE1, SW6, E1, W1, NW1, EC3)
  • Manchester (M1–M20 postal clusters)
  • Birmingham (B1–B33 regions)
  • Bristol, Liverpool, Leeds
  • 1200+ regional SKUs monitored daily

Impact for FMCG Clients

Results After 45 Days:
KPI Before Actowiz After Actowiz
SKU Pricing Visibility Manual checks 24/7 automated
Discount Planning Accuracy ~45% 88%
Campaign ROI (targeted by cluster) - +29% uplift
Flash Discount Awareness Time >12 hrs late Real-time alert
Price Outlier Response Time 2–3 days <1 hour

Use Case Examples

  • Beverage Brand: Adjusted weekend promotions in sync with GoPuff's flash deals in Manchester
  • Household Product Supplier: Used Actowiz price clustering to launch region-specific bundle offers in London
  • Snack Brand: Detected inconsistent pricing across GoPuff’s zones and aligned with competitor positioning

Client Testimonial

“Actowiz gave us pricing clarity on GoPuff that we never had. Their AI models help us plan offers smartly—by location, by category, and even by day.”

– Senior Pricing Manager, UK-based FMCG Brand

Next Steps

  • Extend model to include Amazon Fresh UK and Ocado Express
  • Predict next discount cycle triggers using historical clustering
  • Add basket-level analytics by scraping cart behavior
  • Offer Slack/Teams alerts for category-specific price shifts

Conclusion

GoPuff’s pricing engine is dynamic, regional, and strategically unpredictable—but not for brands using Actowiz Solutions. With AI clustering, discount mapping, and near-a real-time tracking, FMCG companies can finally respond with data—not guesswork.

This case proves how AI + scraping delivers actionable competitive intelligence in today’s digital grocery battlefield—across the UK, one postcode at a 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

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