3 scenarios where predictive analytics is a must!

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3 Scenarios where Predictive Analytics is a must!

Slide 2Slide 2 www.edureka.co/advanced-predictive-modelling-in-r
At the end of the session, you will be able to :
✓ Types of Analytics
✓ Why Predictive Analytics?
✓ Domains where predictive analysis is creating magic
✓ 3 Scenarios where Predictive Analytics is Must
• Churn prediction
• Sentiment Analysis
• Recommendation
Agenda
Hands
on

Types of Analytics?

Types of Analytics

Next-Generation Analytics

Source : gartner
Analytics in Future

What is Predictive Analytics?

Predictive analytics is the analysis of data by using statistical algorithms and machine-learning
techniques to identify the likelihood of future outcomes based on historical data.
Predictive Analytics

Predictive Analytics Lifecycle
Source: blogs.sas.com

Advantages Predictive Analytics

Why Predictive Analytics?

Only Analytics Is Not Enough!
Predictive analytics is a game-changer — it’s like “Moneyball” for… money.

Forbes Says
Source: Forbes
The top objective for between two-thirds and three-quarters of executives is to develop the ability
to model and predict behaviours to the point where individual decisions can be
made in real time, based on the analysis at hand.

Predictive Analytics Is A Game-Changer
Source: Forbes
Best Buy determined 7% of its customers were responsible for 43% of its sales. The
company then segmented its customers into several archetypes and redesigned
stores
Olive Garden uses data to forecast staffing needs and food preparation requirements
down to individual menu items and ingredients.
The U.K.’s Royal Shakespeare Co. theatre company then developed a marketing
program that increased regular attendees by more than 70% and its membership by
40%

Major Domains Using Predictive Analytics

3 Scenarios where Predictive
Analytics is Must

Churn Prevention and
Customer Lifetime Value

What Is Churn/Attrition ?
When your customers reduce their usage or completely stop using your products or services
They are leaving your brand and might be shopping with your competitor

1. Reduce
marketing costs -
maximize profits
2. Reduce churn
through predictive
models
3. Segment market
into alike clusters
as per their profits
4. Understand
customers & their
behaviors
5. Adversely
impacts the
profitability of
organization
6. Cost of acquiring
new customer is
much higher than
retaining existing
customer
7. Reduce the loss
of referrals via the
existing customers,
if they churn out
Reasons For Doing Churn Analysis
Most important reasons for doing churn analysis:

Why Churn Prediction

Cost to acquire
a new customer
is 5X higher
than retaining
existing
customer
Top 30% of
existing
customers
comprise 100 –
150 % of your
profitability
10 – 20 %
churn annually
High churn rate
will impact
growth –
Relying on new
customers is
not a
sustainable
strategy
How does it affect business

Identify :
• Which of customers are churning
Evaluate :
• What is the churn rate
Measure:
• What is the financial loss
Monitor :
• How is it trending
What we can do about it
Analyze the following traits :
Market Research :
• Cost is high
• Customer service issue
• Competitor has superior service
Segmentation :
• Divide you customers in categories
• Monitor each segment trend
Predictive modeling :
• Which customers are like to churn
• Which customers are the most profitable
Proactive marketing and retention strategies:
• Use your insights to re-engage your customers
• Create separate strategies for each segments
Action Plan To Combat :

Predictive Model
Churn likelihood and profitability matrix :

Flow of Churn Analysis

How It Goes

Sentiment Analysis

Sentiment Analysis
Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a
writer with respect to some topic or the overall contextual polarity of a document.
The attitude may be his or her judgment or evaluation ,affective state (that is to say, the
emotional state of the author when writing), or the intended emotional.
… Wikipedia

Sentiment Analysis Flow
Text Input
Tokenization
Stop word filtering
Negation handling
Classification
Sentiment class

Recommendation

Slide 31Slide 31 www.edureka.co/advanced-predictive-modelling-in-rSource: http://fortune.com/tag/predictive-analytics/
E-Commerce using it for recommendation!
Recommendation

This is how Amazon’s recommendation engine works
Amazon : Case Study

Questions
Slide 33 www.edureka.co/advanced-predictive-modelling-in-r

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3 scenarios where predictive analytics is a must!

3 scenarios where predictive analytics is a must!

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3 scenarios where predictive analytics is a must!