AI Personalizationby skyware

An experience tailored
to every single customer, automatically

AI Personalization Platform

Real-time data analysis and a machine-learning recommendation engine cover everything from customer segmentation and content recommendations to multichannel sending and real-time analytics.

Overview

Overview

AI Personalization Platform Overview

AI Personalization Platform with CLOUVI (AI CX chatbot)

Customer behavior and purchase data are analyzed in real time to automate recommendations, segmentation and hyper-personalized messages, and the CLOUVI AI CX chatbot extends it into customer service.

A closed loop from data collection through personalized execution to performance analysis.

Real-time data analysis · AI recommendations
Customer segmentation and hyper-personalized message automation
Integration with the CLOUVI AI CX chatbot
Use case: NiceAI, the NICE CLAUP online mall shopping assistant

Features

Four functions, from segmentation to analytics

Customer segmentation, personalized recommendations, multichannel sending automation and real-time analytics in one.

Smart customer segmentation

Real-time behavior and purchase history analysis
Multidimensional segmentation (age, gender, region, interests and more)
Automatic target group creation and management
Target group optimization per campaign

Personalized content recommendations

AI-based product and content recommendations per customer
Improvement by learning click and purchase patterns
Applied across channels (web, app, email, messages)
Recommendations updated in real time

Multichannel message automation

Unified sending across SMS, email, app push, RCS and more
Scenario-based automatic message triggers
Delivery performance analysis and retargeting
Timing and channel optimization

Real-time analytics and reporting

Performance and KPI dashboard per campaign
Real-time monitoring of customer behavior and conversion
AI recommendation performance analysis
ROI-based marketing strategy suggestions

Eight things that change after adoption

Higher conversion and loyalty, lower churn and operating load.

Higher conversion

Offers and recommendations optimized per customer maximize purchases and service use

Lower churn

Experiences matched to interests and behavior keep customers from leaving

Stronger loyalty

Consistent, personalized communication sustains long-term relationships

Greater operating efficiency

Automated marketing and sending processes save people and time

Large-scale real-time processing

A distributed architecture that handles millions of records without delay

APIs for every channel

A unified API across SMS, email, app push, RCS and more

Customer-specific UI/UX

Dashboards, reports and sending screens designed for your brand and industry

High-precision AI targeting

Machine-learning segmentation and personalized recommendations maximize conversion

Five steps to adoption

From assessment to operations, paced to how ready your data is.

STEP 01

Consultation

We review your goals and current marketing and data environment together.

STEP 02

Data assessment

We check member, product, purchase and search data and define what can be used.

STEP 03

Model and integration build

We train the recommendation model and connect it to your mall and message channels.

STEP 04

Validation and launch

We confirm recommendation quality and KPIs, then open the service.

STEP 05

Operations and improvement

Models and campaigns keep improving based on operational data.

Architecture

AI Personalization Architecture

Generative AI and machine-learning datasets run on one platform, learning customer behavior history and turning it into hyper-personalized recommendations.

Users

WEB / APPChatbot AIApp Push

AI Commerce Service Platform

Generative AI Dataset

ML model training · deploymentConversation handling · query analysisContent generation (text · images)Monitoring · feedback

AI Machine-Learning Dataset

ML model training · deploymentRecommendation algorithms · real-time personalizationStatistics · predictive analyticsVector data · data mining

Source dataData design · classificationData cleansingBig data analysis

Machine Learning Framework · TensorFlow

MembersProductsPurchasesSearches

Administrators

Monitoring · analytics

Data Security

Data modelingData encryptionAccess control

AI commerce service platform, generative AI dataset · machine-learning dataset · TensorFlow

① Collect behavior history

IndividualSearch historyPurchase historyCart · recently viewedWishlistSiteTrending searchesRecommended products · reviewsProduct rankings

② AI pattern learning

Individual · mall AI pattern analysis+ AI modeling dataset= Matching datasetSignals consideredGender · age · country · locationPurchase activity · interestsWeather · weekday · sentiment data

③ Hyper-personalized recommendations

Recommendations by customer typeBanner optimizationRecommendation messagesHigher conversion

Collect behavior history → AI pattern learning → hyper-personalized recommendations

From data to recommendations

The AI Personalization Platform connects users (web/app, chatbot AI, app push) with administrators (monitoring and analytics).

Generative AI dataset

ML training set · conversation and query analysis · content generation (text/images) · monitoring and feedback

AI machine-learning dataset

Training set · real-time personalized recommendation algorithms · statistical and predictive analytics · vector data · data mining

Data pipeline

Source data → design/classification → cleansing → big data analysis · machine-learning framework (TensorFlow)

Security

Data modeling · data encryption · access control

AI ready for commerce

How the recommendation engine and generative AI are used across mall operations.

Personalized support from AI analysis of customer preferences

Agents get the best guidance, related product information and suggested personalized answers.

Inventory support through sales and demand forecasting

Sales, inventory and customer data plus demand patterns feed precise demand forecasts.

Understands the question and completes the task

Even complex tasks such as order cancellation, option changes and reservation management are handled in real time.

Discounts on frequently viewed items

Individual discounts on items customers keep viewing but not buying raise conversion.

Automatic marketing copy for each product

Product details, display and promotion copy written in a few clicks from product data and images.

AI-assisted coding and review

Natural-language questions are answered with awareness of project structure and code context, with drafts and security-vulnerability guidance.

AI personal shopping

CLOUVI · AI Shopping Assistant

An AI personal shopping: say what you are looking for or what it is for, and it picks the right products from the mall and recommends them in conversation.

Overview

CLOUVI Overview

An AI CX chatbot connected to the AI Personalization Platform’s recommendation engine

CLOUVI is an AI CX chatbot that brings the AI Personalization Platform’s recommendation engine into conversation. It finds products that match the customer’s question and adjusts its recommendations as the conversation unfolds.

Segments, recommendation scenarios, chatbot and agent handoff, and expected results are managed in one console.

Conversational product recommendations
Recommendation engine and mall integration
Chatbot and agent handoff

Total revenue$128,430+12.4% vs last period

Active subscriptions8,642+5.7% vs last period

Churn rate2.3%-1.2% vs last period

Rec. conversion9.2%+1.8%p vs last period

Conversion rateRec. click rate

3%2%1%0%

● Conversion rate2.46%previous

● Rec. conversion2.87%↑ 12.6%

Oct 1Oct 8Oct 15Oct 22Oct 29

Customer segments

8,642Total customers

Active42%
At risk28%
Churned15%
New15%

Recommended actionsReview ▾

Action	Priority	Impact	Updated
High	Re-engage at-risk customers	High	2h ago
High	Optimize checkout flow	High	5h ago
Medium	Refresh personalization model	Medium	1d ago
Medium	Review pricing strategy	Medium	2d ago
Medium	Improve onboarding	Medium	3d ago

12 actions total

💬 Customer support↩

Hi! I am your CLOUVI support assistant. How can I help you today?

Here are some actions I can help you with:

Re-engage at-risk customersOptimize checkout flow

How can I help you today?

Watch CLOUVI in action

See the flow from a single question to a recommended product.

CLOUVI in action

Features

How the conversation goes

Ask in words instead of a search box, and CLOUVI answers with products from the mall.

Product discovery

“Recommend a bag I can carry to work”

Say what you need and what it is for, and matching products from the mall appear as cards.

Gift recommendations

“What would make a good gift for my parents?”

It understands the gift occasion and suggests products that are good to give.

Order and delivery questions

“Can I change the option on my order?”

Connected to the AI Personalization Platform’s actionable AI chatbot, it can handle tasks such as cancellations and option changes.

Continuing the conversation

“Show me something a bit lighter”

It picks up the earlier conversation, narrows the conditions and recommends again.

What conversational shopping changes

Higher conversion

Personalized offers and recommendations carry customers through to purchase.

Less churn

Finding the right product by conversation means fewer customers wander off.

Lower CS load

The chatbot answers repetitive product and order questions first.

Stronger loyalty

Consistent, personalized service builds lasting relationships.

How It Works

Four steps from question to product

Understand the conversation, find products, and show the ones that fit the customer.

Understand the question

Understand

The item, purpose, situation and budget are read from what the customer says. Missing conditions are clarified with follow-up questions.

“Do you have a light padded jacket for winter?”

Match product data

Match

Products matching the conditions are found in the mall’s (SCOS) name, category, option and price data.

Item: padded jacket · condition: lightweight · season: winter

Personalize

Recommend

The AI Personalization Platform’s recommendation engine applies the customer’s purchase and view history and taste tags to order the results for that customer.

Purchase history, preferred brands and price range applied

Link to details

Connect

Tapping a product card in the conversation opens the detail page while the conversation continues, and hands off to an agent when needed.

Product card → detail page → conversation continues

Architecture

CLOUVI Architecture

Mall product and customer data and the recommendation engine connect to the chatbot, with scenarios and performance managed in the console.

Customers

Web · app chat windowQuestions · preferences

Conversation

CLOUVI AI CX

Conversation · Intent

Intent analysisTaste-tag extractionDialogue management

AI Personalization Engine

SegmentsRecommendation scenariosSimilar products · outfits

Mall data integration, products · customers · orders

Results

Execution

Product cardsChatbot · agent handoff

Console

Scenario managementPerformance analytics

CLOUVI service layout, conversation · recommendation engine · mall data · console

Connected to your mall and the recommendation engine

It runs on the mall data you already have, linked to Skyware’s AI Personalization Platform.

Mall product data

Product data from the mall you run, such as SCOS, is used as is.

Learn more →

AI Personalization Platform

Customer segmentation, personalized recommendations and the similar-customer engine make recommendations more accurate.

Learn more →

Your existing web and app

It attaches as a widget that opens from a button at the bottom right anywhere on the site.

Before and after

Marketing that was the same for everyone becomes tailored to each customer.

Before

After

The same message and products for every customer

Recommendations per customerBehavior data shows each customer different products and content.

Campaign audiences pulled by hand

Automated segmentationSmart segmentation selects campaign audiences automatically.

Campaign results analyzed separately afterwards

Real-time reportingSee sends and responses in real time and adjust immediately.

Recommendation rules tuned by hand

Recommendations that learnThe machine-learning model keeps improving recommendations from data.

We stay with you after launch

The build is not the end. From stable operations to improvements, Skyware stays on.

Stable operations

We keep watching the service after launch and respond to failures and warning signs first.

Dedicated support

The people who delivered the project keep handling operations questions and requests.

Continuous improvement

We keep enhancing features based on operational data and feedback from the field.

Considering AI personalization?

We will design recommendation and sending scenarios around your data and channels.

An experience tailoredto every single customer, automatically

AI Personalization Platform Overview

Four functions, from segmentation to analytics

Smart customer segmentation

Personalized content recommendations

Multichannel message automation

Real-time analytics and reporting

Eight things that change after adoption

Higher conversion

Lower churn

Stronger loyalty

Greater operating efficiency

Large-scale real-time processing

APIs for every channel

Customer-specific UI/UX

High-precision AI targeting

Recommendations from similar customers

Purchase history

Deep-learning model

Similar-customer matching

Five steps to adoption

Consultation

Data assessment

Model and integration build

Validation and launch

Operations and improvement

AI Personalization Architecture

From data to recommendations

Generative AI dataset

AI machine-learning dataset

Data pipeline

Security

AI ready for commerce

Personalized support from AI analysis of customer preferences

Inventory support through sales and demand forecasting

Understands the question and completes the task

Discounts on frequently viewed items

Automatic marketing copy for each product

AI-assisted coding and review

CLOUVI · AI Shopping Assistant

CLOUVI Overview

Watch CLOUVI in action

How the conversation goes

What conversational shopping changes

Higher conversion

Less churn

Lower CS load

Stronger loyalty

Four steps from question to product

Understand the question

Match product data

Personalize

Link to details

CLOUVI Architecture

Connected to your mall and the recommendation engine

Mall product data

AI Personalization Platform

Your existing web and app

Before and after

We stay with you after launch

Stable operations

Dedicated support

Continuous improvement

Considering AI personalization?

An experience tailored
to every single customer, automatically