Bi mktg presentation - Using Business Intelligence for Marketing and Sales Analysis

Using Business Intelligence for Marketing and Sales Analysis
Vispi Munshi
Founder - ERP India
vmunshi@erp-india.com
http://www.erp-india.com
Proprietary and Confidential © ERP India – Vispi Munshi – erp-india.org 1

Today’s Agenda
- Introduction
- Marketing and Sales Functions
- What is Business Intelligence
- Data Analytics, Dashboards
- Data Mining, Predictive Analytics
- Examples of using BI in Marketing and Sales
- Blueprint of a Marketing Intelligence System
- Measuring Marketing and Sales performance, Scorecard
- Analytics Demo
- Conclusion, Q&A

Ground Rules
- Please turn mobile ringer to SILENT MODE
- If you have to take a call, please leave the room and then start talking
- Questions can be asked any time
- Before asking question, raise your hand
- No talking with each other
- Disagreements allowed, but no disrespect
- Timeframe awareness
- Lets learn from each other and increase our knowledge

Introductions
- Full Name
- Where do you work (Company/Consultant/Student etc)
- Your job designation and responsibilities
- Any BI tool you have already used?
- Expectation from this workshop

What is Customer Relationship Management
CRM is about identifying and acquiring new customers, and
maintaining and enhancing relations with valued customers.
Demand
Creation
Service
Mgmt
Customer
Lead
Generation
Lead
Mgnt
Contracts
Order
Mgnt
Quoting
Opportunity
Mgnt

Key Marketing and Sales functions
- Demand Creation (Marketing Campaigns, Promotions)
- Identify and Acquire customers (Sales Lead management)
- Proposal/Quotation and Order processing
- Order and Contract Management
- Sales Channel Management
- Product and Territory Management
- Pricing
- Loyalty Programs
- Surveys (for feedback)

Identifying and Acquiring Customers
Call Center
Field Staff
Your Web Site
Partners
External
Sources
Suspects
Prospects
Referral
Leads
Repeat
SALE

What is business intelligence?
Business Intelligence is a term generally
used to identify a class of Information
System applications useful for supporting
operational, tactical and strategic decision
making of a organization.
BI deals with producing (and presenting)
Accurate, Relevant and Timely (ART)
INFORMATION from integrated data.
Not Accurate: Users loose faith in system
Not Relevant: Users ignore the system
Not Timely: Users find alternatives to the
system

Benefits
- Sales Optimization
- Cost Reduction, Planning and Budgeting
- Inventory Optimization
- Purchase Optimization
- HR Optimization
- Production / Manufacturing Optimization
- Demand Forecasting
- Market Competitive Analysis and Customer Relationship Optimization
- Supply Chain (Sales and Distribution) Optimization
- Most Important is ART Information to support all levels of Decision Making
- Aim is to replace/reduce Excel based Analysis

BI System Anatomy
BACK-END
Data Collection and
Integration Tools
Forecasting,
Mining
ERP
Ecomm
CRM
Files
….
Data
Mart
PRESENTATION
FRONT-END
Analytics, Visualization,
Dashboards, …
DISTRIBUTION
Alerts, Email, Mobile,
Intranet ….

Backend BI Tools: Used for collection, integration and consolidation
of data from various sources.
Intermediate BI Tools: Allows users to create forecasts and identify
trends (data mining) from the data.
Frontend BI Tools: Provides users with a interactive and intuitive
interface to view the information generated.

Data Analytics (New Age Decision Support Systems)
- Based on multi-dimensional view of data (cubes)
- Pivot Table demo
- Features for drilling in and across data
- Slicing and dicing of data
- Graphics capabilities
- Similar to Excel
- Exception reporting
- Data Analyst would use such tools and create Reports/Analysis/Graphs (objects)
- These objects would be supplied to Executives using Dashboards, Alerts etc.

Multi-dimensional Data

Data Analytics Tools in Market
High-end: Business Objects, OBIEE, Microstrategy, …
Open Source: http://en.wikipedia.org/wiki/Business_intelligence_tools

Dashboards and Alerts
- Dashboards are collection of reports/analysis/graphs
- Alerts are specific events that the system finds and sends a email/sms etc to
the executive
- Key Performance Indicators (KPI’s) can be set and linked to alerts
- Linking across objects provides executive with ability to go through the
generated information in a very intuitive manner

Data Mining
- Also known as KDD (Knowledge Discovery in Databases)
- Involves use of large data sets
- Involves uses of Statistical Methods, Database Systems and Artificial Intelligence
- The objective is to discover patterns or knowledge from existing data
- Involves four step process: Data Preparation (classification), Hypothesis (user provided
guidance), Discovery (of knowledge) and Validation (of discovered knowledge against
hypothesis)
- Techniques: Classification, Clustering, Association Rules, Regression
- Predictive Analytics
- High end tools: SPSS, SAS, …
- Open Source: http://en.wikipedia.org/wiki/Data_mining

Data Visualization
- Presents a intuitive graphic representation of the data and generated
knowledge
- The visualization is a embedded feature in most Analytics and Mining tools

Predictive Analytics
- Combines Data Analytics and Statistical techniques to provide a interactive
tool
- encompasses a variety of statistical techniques from modeling, machine
learning, and data mining that analyze current and historical facts to
make predictions about future, or otherwise unknown, events
- Recency, Frequency, Transaction Value, Demographics
- Classification, Clustering, Association Rules, Regression
- http://en.wikipedia.org/wiki/Predictive_analytics

Marketing and Sales Metrics
- Cost per lead generation
- Proposal turnover time
- Lead closure rate
- Lead closure time
- Sales Channel utilization
- Customer Retention/Churn rate
- Campaign Effectiveness

Using BI for Marketing and Sales Examples
- Example 1: Predicting which Customers are likely to switch to
competitors
- Example 2: Predicting which Customers can be cross sold
- Example 3: Predicting lead success probability & providing
recommendations
- Example 4: Focusing Marketing Campaigns

Predicting which Customers are likely to switch to competitors
Past Customer Records
- Transactions
- Demographics
- Buy Behavior
Service Records
Past Switch Records
Current Customer Records
- Transactions
- Demographics
- Buy Behavior
- Service Records
Create Model
(Association Rules,
Clustering
Switch Model
(Decision Tree,
Neural Network)
Prediction
Algorithm
(Classification)
Switch
Predictions
Analytics

Predicting which Customers can be cross sold
Past Customer Records
- Transactions
- Demographics
- Buy Behavior
Service Records
Past Cross Selling
Records
Current Customer Records
- Transactions
- Demographics
- Buy Behavior
- Service Records
Create Model
(Association Rules,
Clustering
Product Cross
Sell
Possibilities
Cross Sell Model
(Decision Tree,
Neural Network)
Prediction
Algorithm
(Classification)
Cross Sell
Predictions
Analytics

Predicting lead success probability & providing recommendations
Past Leads
-Attributes
- Campaign
- Sales Channel
Conversion Results
- Success or Failure
- Reasons
- Process followed
Create Model
( Clustering)
Current
Leads
Conversion
Model (Decision
Tree, Neural
Network)
Prediction
Algorithm
(Classification)
Conversion
Probability
Predictions
&
Recommendations
Analytics

Focusing Marketing Campaigns
Past
Prospects/Leads
Conversions and
Failures
Demographic Data
Create Model
(Association)
Prospect
List Shortlisted
Model (Decision
Tree)
Shortlisting
Prospects
High
Medium
Low

More Ways to use BI
- Customer Profitability Analysis: which customers to value?
- Ecommerce Site User behavior analysis: Make special offers to
convert suspects to prospects and leads, depending on which pages
of the site the suspect has visited
- Call Center Log Analysis: identifying leads using data mining or
predictive analysis
- Customer Retention: identify potential leads, renewal offers
- Customer Relation Extension: identify potential leads based on
service records

Marketing and Sales Intelligence System
BACK-END
Data Collection and
Integration Tools
ERP,
CRM
Sales
Industry
data
….
Forecasting,
Mining
Marketing
Data Mart
PRESENTATION
FRONT-END
Analytics, Visualization,
Dashboards, …
EXTRANET ACCESS
To
PARTNERS (Marketing Portal)
ALERTS by email and mobile
to Sales Force and Partners

Measuring Performance: For each Campaign or Sales Channel
New Customers: 5678, 7%
Acquisition Cost: 2500/-
Lead Closing %: 34%
Renewal %: 77%
Extended Relations: 345, 1.3M
Recovered Relations: 45

Analytics Demo

Q&A
Thank You
vmunshi@erp-india.com
98250 11489

Bi mktg presentation - Using Business Intelligence for Marketing and Sales Analysis

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