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  • ML-Driven Cart Abandonment Detection on Zapp UK – Actowiz

Case Study: Actowiz Solutions – ML-Driven Cart Abandonment Triggers from SKU Trends in Zapp UK

Actowiz Solutions uses machine learning to analyze cart abandonment patterns from SKU-level trends on Zapp UK. Discover predictive triggers and behavioral insights.

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Case-Study-Actowiz-Solutions-–-ML-Driven-Cart-Abandonment-Triggers-from-SKU-Trends-in-Zapp-UK

Introduction

Zapp, one of the fastest-growing Q-commerce platforms in the UK, delivers essentials within minutes. But with fierce competition from Getir, GoPuff, and Deliveroo Express, abandoned carts represent lost revenue—and missed insights.

Actowiz Solutions helped a major UK-based consumer goods brand integrate machine learning models and real-time scraping to detect and analyze SKU-level cart abandonment triggers on Zapp. The result: smarter campaign targeting, better pricing, and reduced drop-offs.

Client Objectives

  • Identify what SKUs are most frequently abandoned before checkout on Zapp
  • Understand behavioral triggers behind drop-offs (price, timing, stock)
  • Predict cart abandonment risk based on product type and time-of-day
  • Correlate discount patterns and abandonment likelihood
  • Generate alerts for high-risk product combinations in real time

Challenges Faced

Challenges-Faced
  • 🛒 Zapp doesn’t offer cart data publicly—behavior needed to be reverse-engineered
  • 📉 SKU trends changed hourly with dynamic pricing and availability
  • ⚡ Cart abandonment could spike due to delays, pricing, or stockouts
  • 📦 Identifying multi-SKU interactions (e.g., bundles abandoned) required clustering
  • 🧠 Client lacked predictive modeling for drop-off scenarios

Actowiz’s AI/ML & Data Scraping Strategy

Actowiz’s-AI-Powered-Data-Approach
🔍 1. Scraping User-Facing Signals on Zapp

Actowiz deployed a Zapp scraper capturing:

  • SKU availability, price, and discounts
  • “Low stock” tags, delivery ETA, and cart limits
  • Add-to-cart button status & changes
  • Repeat pattern tracking (e.g., items added repeatedly but never purchased)

Data was extracted across London, Manchester, Birmingham zones every 15–30 minutes.

📊 2. Data Points Extracted
Timestamp City SKU Name Price Stock Status Discount Delivery ETA Add-to-Cart Status
2025-06-15 18:00 London Alpro Almond 1L £2.10 Low Stock 10% 22 mins Enabled
2025-06-15 18:00 London Cadbury Buttons £1.80 In Stock 0% 16 mins Enabled
2025-06-15 18:00 London Dettol Wipes 20ct £2.50 In Stock 5% 26 mins Enabled
🧠 3. Machine Learning Models Deployed
  • Logistic Regression – Classified SKUs by likelihood of abandonment
  • XGBoost Classifier – Scored risk levels based on discount, stock, and timing
  • K-Means Clustering – Grouped abandoned SKUs by behavioral signals
  • Sequence Pattern Mining – Detected repeat abandonment patterns by users

Top Abandonment Triggers Identified

🧾 Key Findings:
Abandonment Trigger Impact Detected
Delivery ETA > 25 mins +38% likelihood of cart drop-off
Discount < 5% 2.3x more likely to be abandoned
Low Stock Tag Increased hesitation on checkout
Multi-SKU Cart (3+ items) Drop-off spike due to perceived complexity
Repeatedly Viewed SKU Abandoned unless offered discount in 24 hrs

Cart Abandonment Heatmap by Time of Day (London)

Time Slot Avg Cart Abandonment Rate
8 AM – 11 AM 18%
12 PM – 3 PM 26%
4 PM – 7 PM 32%
8 PM – 11 PM 21%

🔍 Insight: Evening hours saw highest drop-offs—often due to peak ETA delays or unavailable fast-moving SKUs.

Real-World Example:

The-Client

SKU: Magnum Classic Ice Cream

  • 📍 London SW6
  • Regular Price: £3.50
  • Offered 5% discount → Drop rate: 29%
  • Offered 15% discount → Drop rate: 9%

Actowiz flagged this behavior for the client, prompting strategic discounting only after first drop-off detection.

Actowiz Dashboard Highlights

Feature Description
SKU Drop-Off Risk Scoring Visualize real-time cart abandonment likelihood per product
Time-Based Abandonment Patterns Analyze hourly/day-wise cart abandonment trends
Trigger Alert System Push alerts for high-risk SKU combos
Multi-SKU Cart Drop Analysis Track how cart complexity affects purchase behavior
Promo Recommendation Engine Suggest optimal discount % based on historic abandonment elasticity

Geographic Coverage

Monitored regions across Zapp in the UK:

  • London (SW6, NW1, E14, EC1, SE10)
  • Manchester (M1–M16 zones)
  • Birmingham (B1–B33 regions)
  • Leeds, Bristol, Liverpool – added in Phase 2

Business Impact Delivered

📈 Results after 60 Days of Implementation:
KPI Before Actowiz After Actowiz
Average Cart Abandonment Rate 36% 19%
Time to Detect Drop-Off Pattern Manual (24h+) Real-Time
Discount ROI (after AI-driven targeting) - +31% uplift
SKUs Recovered via Promo Alert - 800+ SKUs
Multi-SKU Cart Conversions 41% 63%

Client Testimonial

“We never had real visibility into Zapp cart behavior. Actowiz gave us the triggers, patterns, and recommendations to turn drop-offs into conversions.”

– E-Commerce Lead, UK FMCG Brand Partnering with Zapp

Next Steps

  • Integrate behavioral email/SMS triggers tied to SKU abandonment
  • Expand insights to Amazon Fresh, GoPuff, and Deliveroo UK
  • Add price elasticity models by category
  • Build competitive benchmarking layer (e.g., Zapp vs Getir)

Conclusion

In a Q-commerce ecosystem where consumers make split-second decisions, understanding why carts are abandoned can unlock substantial revenue.

Actowiz Solutions transformed SKU-level scraping and ML modeling into a high-ROI abandonment prediction tool—helping Zapp’s brand partners reclaim lost sales across the UK.

In a world where milliseconds matter, Actowiz lets brands act at the right moment.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize
Explore Solutions Get a Custom Demo

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.

Ecommerce
Q-Commerce
Travel & OTA
Food Delivery
Real Estate
Social Media
Trusted by Global Leaders – Secured by International Standards

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.
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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
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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
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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

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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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