01 · Prediction
Prediction and targeting
A purchase-probability prediction module by category and gender, plus a send-time optimizer tailored to each customer.
Case study · fashion / children's e-commerce
Personalization and improved shopping experiences at Coccodrillo
For Coccodrillo - an international children's clothing and footwear brand - Persooa personalized every step of the purchasing journey: purchase prediction, 1:1 recommendations by gender and size, RFM campaigns, and a loyalty program on the Synerise platform.
4 → 7,5products in cart with recommendation widgets
+26%increase in cart value
+16,5%increase in transactions from product recommendations
80%+loyalty program sign-ups from offline
Client
Coccodrillo
Focus area
AI Personalization, Recommendations, Marketing Automation, Loyalty
Segment
B2C · e-commerce (children's clothing, international)
Technology
Synerise + Persooa
Starting point
A rich offering without fully personalized journeys
A wide assortment for both genders and many sizes was difficult to match 1:1, while mass campaigns didn't leverage purchase probability or optimal send times.
Difficulty in precisely understanding the customer and their preferences
Offering for both genders and many sizes without 1:1 matching
Mass campaigns instead of targeting by purchase probability
Suboptimal campaign send times
Scattered online and offline data - no 360 view
Need to build customer loyalty and retention
Persooa's solution
Personalizing every step of the purchasing journey
We combined prediction, 1:1 recommendations, and RFM segmentation with a loyalty program and a 360 view - to deliver the right offer at the right time.
02 · 1:1 Personalization
1:1 recommendations
An AI engine matches the offer to purchase and browsing history, split by gender and matched to the size being viewed.
03 · Segmentation
RFM campaigns
Activation of key segments - New Customers, Churn, and Heavy Buyers - with A/B tests and prediction of future purchase timing.
04 · Loyalty & 360
Loyalty program and 360 view
Loyalty program automations and integration with offline stores, plus a 360 customer view updated in real time.
Phased implementation
From a 360 view to loyalty
1
Data and 360 view
Phase I
- Customer analysis across all communication channels
- Demographic, behavioral, and device-technical data
- 360 customer view updated in real time
- Foundation for marketing and operational decisions
2
Prediction and personalization
Phase II
- Purchase probability prediction (category, gender)
- Email campaigns with personalized recommendations
- 1:1 personalization by gender and size being viewed
- Send-time optimizer per customer
3
Segmentation and loyalty
Phase III
- RFM campaigns: New Customers, Churn, Heavy Buyers
- A/B testing of recommendation selection
- Loyalty program automations
- Synerise integration with offline stores (80%+ sign-ups)
Tactics implemented
Personalization and recommendations at every touchpoint
A set of mechanisms that together grew the cart, increased transactions from recommendations, and built customer loyalty.
Prediction · email
Purchase prediction + campaign
The segment of customers with a high purchase probability receives an email campaign with personalized recommendations.
high-prob precise targeting
Timing · send
Send-time optimizer
Analysis of campaign response ensures every customer receives their email at their individually optimal moment.
1:1 optimal timing
Personalization · gender
Recommendations by gender
The AI engine matches the assortment, and for purchases spanning both genders it offers girl / boy tabs.
AI gender-based matching
Personalization · size
Recommendations by size
Similar products match the size being searched for - e.g., you view size 122, you get 122.
size offer matching
Segments · RFM
RFM campaigns
Welcome campaigns with a survey, churn reactivation based on favorite products, and Heavy Buyers campaigns with A/B testing.
RFM New / Churn / Heavy
Loyalty · omnichannel
Loyalty program
Welcome, points information, and activation, with offline integration accounting for 80%+ of sign-ups.
80%+ sign-ups from offline
Results
A bigger cart and more transactions from recommendations
7,5 items
products in the cart when recommendation widgets are present - versus 4 without them - with +26% cart value and +16,5% transactions from product recommendations.
Effects of personalization and recommendations
Products in cart (with widgets vs. 4)7,5
Increase in cart value+26%
Increase in transactions from recommendations+16,5%
Increase in revenue from recommendations+4,11%
Purchase prediction
Segmentation by purchase probability, category, and gender.
1:1 personalization
AI recommendations matched to gender and the size being viewed.
Send-time optimizer
Email at the individually best moment for each customer.
RFM segmentation
New Customers, Churn, and Heavy Buyers with A/B testing.
Loyalty program
Automations and offline integration (80%+ sign-ups).
360 customer view
Data from all channels updated in real time.
We personalize every step of the purchasing journey and turn data into a bigger cart, higher conversion, and lasting loyalty - in the Human + AI model.
- Persooa · Revenue Growth Agent
Frequently asked questions
FAQ - personalization and recommendations at Coccodrillo
What results did personalization bring at Coccodrillo?
With recommendation widgets present, the number of products in the cart rose from 4 to 7,5, cart value by +26%, and transactions from product recommendations by +16,5% (with a +4,11% increase in revenue involving them). The personalized journey also boosted conversion and customer satisfaction.
What did the 1:1 personalization involve?
We matched AI-engine-based recommendations to purchase and browsing history, split by gender (girl / boy tabs for customers shopping for both) and matched to the size being viewed - if a customer is browsing size 122, they receive suggestions in that size.
How were prediction and RFM analysis used?
The prediction module identified the segment of customers with a high purchase probability, to whom we directed an email campaign with recommendations and a send-time optimizer. RFM analysis fed campaigns for the New Customers, Churn, and Heavy Buyers segments (with A/B testing and prediction of future purchase timing).
How was customer loyalty built?
We implemented loyalty program automations - from invitations and welcome campaigns, through points-balance information, to activation campaigns. The Synerise integration with offline stores, which account for over 80% of program sign-ups, enabled consistent cross-channel communication.
What technology was used?
The Synerise platform combined with Persooa's framework and components - with full personalization, campaign automation, real-time analysis through dashboards, and A/B testing, which made it possible to achieve the goals set at the start of the collaboration.
What does Persooa do?
Persooa implements and activates AI in e-commerce - mainly on the Synerise platform - with an emphasis on a fast start and the first measurable results within 90 days. We combine strategy, data, and execution in the Human + AI model: personalization, marketing automation, recommendations, and AI agents that translate into revenue growth.
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