Transforming Marketing Analytics with Big Data Solutions

RAJIV KUMAR

DATA SCIENTIST

Why to Rethink marketing analytics?29%

of firms are good at turning data in to action

73%

of firms aspire to be data- driven

Source: Forrester’s Global Business Technographics Data and Analytics Survey,2015

Why to Rethink marketing analytics?• Big data means big opportunities

Why to Rethink marketing analytics? – Traditional Solutions

Campaigns

CRM/Profile

Location

Social

ClickStream

Data Marts

ETL/ Stored Procedures

Data Warehouse

Segmentation and Churn Analysis

BI Tools

Marketing Offers

Does not Model

easily in to

RDBMS schema

New data

sources-Mobile,

Apps, network

Logs?

Limited

processing

power

Scaling is

Expensive and

cumbersome.

Manual Work.

Few automated

system feeds

Based on

Sample and

Limited data

Limited

processing

power

Loss in

Fidelity

Why to Rethink marketing analytics? …continued

• Gaining a competitive advantage requires operating in real-time across various customer touch points.

• Big data analytics enables businesses to leverage data driven, insightful, 360 degree view of customer to:• Develop customer profiles based on characteristics of individuals and segments.

• Execute targeted marketing campaigns with real time adjustments to maximize performance.

• Generate Accurate customer life time value scores.

• Big data analytics allows business to analyze customer behavior in real time to:• Identify customer behavior patterns for any anomalies in behavior.

• Fostering brand loyalty through clear understanding about customers.

• Real time tracking of customer journey in marketing funnel.

Why to Rethink marketing analytics? …continued

• Real time and Targeted cross selling and upselling offersReal time offer

management

• Real time Prediction of future behavior of customers to act upon before its too late

Real time Prediction of

future behavior

• Understand customer interaction through Omni channel touch points to generate useful insights

• Which channels primarily maintain brand awareness?

Brand Interaction

Benchmarking Existing

Marketing plans

Marketing investments

Ratio

Purchase Intent behavior

Increased ROI

• Reveal the ideal ratio of marketing investments to maximize sales.

• Mapping customer behavior with purchase to target right individual at right time

• Which channels are the primary drivers of current sales?

• Which channels can deliver incremental sales?

Journey to Advance Marketing Analytics

•Omni channel Customer interaction

•Purchase history

•Social media and web activity

•Customer behavior

Integrate and

Understand

•Customer affinity

•Conversion path

•Customer behavior

•Brand value

•Customer lifecycle

Analyze and Discover

•Customer segmentation

•Marketing channel attribution

•Real time offer management

•Business processes

•Decision making

Act and Optimize

Journey to Advance Marketing Analytics-Big Data Landscape

Hadoop Ecosystem

Journey to Advance Marketing Analytics-High Level Path

Data Ingestion

Customer Profile

Statistical Modeling

Structured Data

Unstructured

Data

Semi Structured

Data

Customer segmentation

Marketing channel attribution

Offer management

Informed business decisions

Improved Business Processes

Cost optimization

ROI

Sample Customer 360 degree profile

Who are you?

Where are you?

What have you

purchased?

What product

you prefer?

Who do you know?

What can you afford?

What is your value

to business?

How/why have you contacted

us?

Continue to enrich profile

Continue to enrich profile

Journey to Advance Marketing Analytics- Solution Architecture

Customer Service Data

Demographic data

Customer interaction

Campaign Data

Sales Force Trouble Ticket data

Billing data

Orders data

Contact data

Contract Data

Product Quall Data

Survey

Social Media

Web Activity

Chat /email

interactions

Voice Call

Recordings

Textual

Correspondence

RDBMS

Semi Structured Data

Unstructured Data

HDFSData lake

Machine

Learning

Data

Ingestion

Data

Access

Data

Validation

Application layer

360 Degree

Customer profile

Real Time/Streaming Data

Real Time/Streaming Data

Reference Deployment Architecture

Ad hoc/on

Demand

Source

Streaming

Source

Batch source

Reference

Data

Spark Stream Processing

Data Pipe Line Long term Data

Warehouse

Advance

Analytics

Operational

Reporting

Data

Discovery

Business

intelligence

Machine

Learning(Spark ML)

Data Sources Data AccessData Processing, Storage & Analytics