The First NIDA Business Analytics and Data Sciences Contest/Conferenceวนท 1-2 กนยายน 2559 ณ อาคารนวมนทราธราช สถาบนบณฑตพฒนบรหารศาสตร

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กววฒน สนเจรญ วทม. (NIDA)Head of Marketing Intelligence King, Power International

Analytics in Real Life

ใครจะคดวา Analytics ค าทฟงดเขาใจยาก แตจรงๆแลว อยใกลชดกบเราตลอดทงวน ตงแตตนเชา จนถงตอนทเรานอนหลบ วนเวยนแบบนไปเรอยๆ ทกกจกรรมในชวตประจ าวนของเรา เพยงแคมการจดเกบขอมลทถกตองเหมาะสม กระบวนการวเคราะหเพอน าไปใชประโยชนดานตางๆ สามารถท าไดทนท

นวมนทราธราช 3002 วนท 2 กนยายน 2559 13.30-14.00 น.

Analytics in Real Life

Kawewat Sincharoen

Head of Marketing Intelligence

King Power International

What is analytics?

Analytics is an encompassing and multidimensional

field that uses mathematics, statistics, predictive

modeling and machine-learning techniques to find

meaningful patterns and knowledge in recorded

data.

Descriptive Predictive Prescriptive

Analytics, which use

data aggregation and

data mining to provide

insight into the past and

answer:

“What has happened?”

Analytics, which use

statistical models and

forecasts techniques to

understand the future

and answer:

“What could happen?”

Analytics, which use

optimization and

simulation algorithms to

advice on possible

outcomes and answer:

“What should we do?”

Analytical Landscape

Analytics in Real Life

Check traffic • Driver behavior tracking

• Oil status

• Shopping online• Say hi “Social Network”• Watch movies online• E-Banking

• Catch Pokemon ‘• Egg Incubation

Analytics in Business Perspective

• Customer Relationship Management

• Risk Management

• Fraud Protection

คณไดรบสวนลดรายเดอน 50%เพยงตอสญญาแพคเกจรายเดอนเปนเวลา 12 เดอน สนใจตดตอ 911

Analytics in Business Perspective

• Customer Relationship Management

• Risk Management

• Fraud Protection

บตรเครดตของทานไดรบการอนมตแลว ธนาคารจะจดสงใหภายใน 7 วน ขอบคณทใชบรการธนาคาร ABC

Analytics in Business Perspective

• Customer Relationship Management

• Risk Management

• Fraud Protection

เ พอความปลอดภยในการใชบตรเครดต โดยทางธนาคารจะจดสงบตรใบใหมใหกบทานในวนพรงน ขออภยในความไมสะดวก

Analytics in Real Life

Understanding and influencing the

customer journey throughout the relationship.

Real-time next-best action.

Churn / Lapse Prediction

A complete view of the customer.

Better forecasts, Better planning, Better business results overall.

Marketing optimization.Credit risk.

Operational risk.

Liquidity risk.Social media analytics.

Customer segmentation.

Claims fraud.

Actuarial analysis and ratemaking.

Analytics in Real Life

Understanding and influencing the customer

journey throughout the relationship. Quantify

customer lifetime value, and orchestrate omnichannel

communications that are consistent, contextual and

meaningful.

Predicting and preventing churn. Analyze

structured and unstructured data to gain deeper

customer and service performance insights. Spot

behavioral trends and churn triggers – whether network,

product, service or pricing related – and take pre-

emptive action. And identify operational changes that

could lower your cost to serve while improving service

quality.

Real-time next-best action. Automate and

optimize customer interactions based on up-to-the-

moment, streaming data on account history, product

usage, data plans, network experiences, personal

preferences, sentiment, location and more.

Telecom

Retail

Banking

Insurance

Analytics in Real Life

A complete view of the customer. Create a

single view of each customer – one that includes

preferences, propensities, transaction history and social

media interactions – across brands and merchandise.

The ability to predict customer behavior. Use

predictive analytics to gain insights into the major factors

that influence customer satisfaction, long-term

relationships and sales results.

Omnichannel marketing. Gain a richer, more

meaningful omnichannel customer understanding so you

can put customer intimacy at the heart of your retail

operations.

Better forecasts, Better planning, Better business results overall.Improve every aspect of your business with better

forecasting and replenishment. That means more

sufficient in-stock levels, less wasted inventory and

greater profits.

Telecom

Retail

Banking

Insurance

Analytics in Real LifeMarketing automation. Develop more campaigns

faster – and get superior results.

Marketing optimization. Create the best offers for

individual customers, and get optimal returns on your

marketing investments.

Real-time decision management. Get more

value from your real-time customer interactions.

Social media analytics. Bring context to the

conversations your customers are having about your

brand in social media.

Asset and liability management. Visualize

aggregated market risk across asset classes and

portfolios – on demand, intraday.

Credit risk. Manage counterparty exposures and CVA

to achieve Basel compliance.

Liquidity risk. Optimize capital and funding, perform

FTP and analyze hedging strategies with efficiency and

accuracy.

Operational risk. Manage and value operational

and compliance risk.

payments fraud. Find payments fraud faster by

scoring 100 percent of all transaction types in real time,

for all your lines of business.

Telecom

Retail

Banking

Insurance

Analytics in Real Life

Customer segmentation. Create more granular

customer segments based on demographic,

geographic, attitudinal and behavior data across your

business.

Customer retention. Predict customer lapse, and

create personalized campaigns designed to keep your

most valuable customers from leaving.

Cross-sell and up-sell. Uncover new revenue

opportunities. Predictive analytics enables you to

forecast expected customer behavior and connect the

right offers to the right customers. At the right time

Claims fraud. Detect and prevent both opportunistic

and professional fraud throughout the claims process.

Actuarial analysis and ratemaking. Create

more competitive pricing models by using multivariate

statistical techniques to increase rating granularity.

Claims analytics. Reduce loss ratios and lower loss-

adjustment expenses by apply analytics across the entire

claims process.

Telecom

Retail

Banking

Insurance

The Most Famous Analytical Tools

SVMSupport Vector Machine

Regression Decision Tree Survival Analysis Forecasting Techniques

Neural Network Support Vector Machine Clustering Association

Applying Analytical Tools in Business

• Campaign Response

• High Potential Customer

• Churn Score

• Credit Score

• Fraud Score

• Pre-payment Score

• Profile

• Spending Behaviors

• Payment Behaviors

• Usage Behaviors

• Life-style

Xi

Predictors Predicted

Y

Thank You