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3 Scenarios where Predictive Analytics is a must!
Slide 2Slide 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
Slide 3Slide 3Slide 3 www.edureka.co/advanced-predictive-modelling-in-r
Types of Analytics?
Slide 4Slide 4Slide 4 www.edureka.co/advanced-predictive-modelling-in-r
Types of Analytics
Slide 5Slide 5Slide 5 www.edureka.co/advanced-predictive-modelling-in-r
Next-Generation Analytics
Slide 6Slide 6Slide 6 www.edureka.co/advanced-predictive-modelling-in-r
Source : gartner
Analytics in Future
Slide 7Slide 7Slide 7 www.edureka.co/advanced-predictive-modelling-in-r
What is Predictive Analytics?
Slide 8Slide 8Slide 8 www.edureka.co/advanced-predictive-modelling-in-r
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
Slide 9Slide 9Slide 9 www.edureka.co/advanced-predictive-modelling-in-r
Predictive Analytics Lifecycle
Source: blogs.sas.com
Slide 10Slide 10Slide 10 www.edureka.co/advanced-predictive-modelling-in-r
Advantages Predictive Analytics
Slide 11Slide 11Slide 11 www.edureka.co/advanced-predictive-modelling-in-r
Why Predictive Analytics?
Slide 12Slide 12Slide 12 www.edureka.co/advanced-predictive-modelling-in-r
Only Analytics Is Not Enough!
Predictive analytics is a game-changer — it’s like “Moneyball” for… money.
Slide 13Slide 13Slide 13 www.edureka.co/advanced-predictive-modelling-in-r
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.
Slide 14Slide 14Slide 14 www.edureka.co/advanced-predictive-modelling-in-r
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%
Slide 15Slide 15Slide 15 www.edureka.co/advanced-predictive-modelling-in-r
Major Domains Using Predictive Analytics
Slide 16Slide 16Slide 16 www.edureka.co/advanced-predictive-modelling-in-r
3 Scenarios where Predictive
Analytics is Must
Slide 17Slide 17Slide 17 www.edureka.co/advanced-predictive-modelling-in-r
Churn Prevention and
Customer Lifetime Value
Slide 18Slide 18Slide 18 www.edureka.co/advanced-predictive-modelling-in-r
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
Slide 19Slide 19Slide 19 www.edureka.co/advanced-predictive-modelling-in-r
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:
Slide 20Slide 20Slide 20 www.edureka.co/advanced-predictive-modelling-in-r
Why Churn Prediction
Slide 21Slide 21Slide 21 www.edureka.co/advanced-predictive-modelling-in-r
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
Slide 22Slide 22Slide 22 www.edureka.co/advanced-predictive-modelling-in-r
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 :
Slide 23Slide 23Slide 23 www.edureka.co/advanced-predictive-modelling-in-r
Predictive Model
Churn likelihood and profitability matrix :
Slide 24Slide 24Slide 24 www.edureka.co/advanced-predictive-modelling-in-r
Flow of Churn Analysis
Slide 25Slide 25Slide 25 www.edureka.co/advanced-predictive-modelling-in-r
How It Goes
www.edureka.co/advanced-predictive-modelling-in-r
Slide 27Slide 27Slide 27 www.edureka.co/advanced-predictive-modelling-in-r
Sentiment Analysis
Slide 28Slide 28Slide 28 www.edureka.co/advanced-predictive-modelling-in-r
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
Slide 29Slide 29Slide 29 www.edureka.co/advanced-predictive-modelling-in-r
Sentiment Analysis Flow
Text Input
Tokenization
Stop word filtering
Negation handling
Classification
Sentiment class
Slide 30Slide 30Slide 30 www.edureka.co/advanced-predictive-modelling-in-r
Recommendation
Slide 31Slide 31Slide 31 www.edureka.co/advanced-predictive-modelling-in-rSource: http://fortune.com/tag/predictive-analytics/
E-Commerce using it for recommendation!
Recommendation
Slide 32Slide 32Slide 32 www.edureka.co/advanced-predictive-modelling-in-r
This is how Amazon’s recommendation engine works
Amazon : Case Study
Questions
Slide 33 www.edureka.co/advanced-predictive-modelling-in-r
Slide 34
Your feedback is important to us, be it a compliment, a suggestion or a complaint. It helps us to make
the course better!
Please spare few minutes to take the survey after the webinar.
www.edureka.co/advanced-predictive-modelling-in-r
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3 scenarios where predictive analytics is a must!

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3 scenarios where predictive analytics is a must!

  • 2. Slide 2Slide 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
  • 3. Slide 3Slide 3Slide 3 www.edureka.co/advanced-predictive-modelling-in-r Types of Analytics?
  • 4. Slide 4Slide 4Slide 4 www.edureka.co/advanced-predictive-modelling-in-r Types of Analytics
  • 5. Slide 5Slide 5Slide 5 www.edureka.co/advanced-predictive-modelling-in-r Next-Generation Analytics
  • 6. Slide 6Slide 6Slide 6 www.edureka.co/advanced-predictive-modelling-in-r Source : gartner Analytics in Future
  • 7. Slide 7Slide 7Slide 7 www.edureka.co/advanced-predictive-modelling-in-r What is Predictive Analytics?
  • 8. Slide 8Slide 8Slide 8 www.edureka.co/advanced-predictive-modelling-in-r 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
  • 9. Slide 9Slide 9Slide 9 www.edureka.co/advanced-predictive-modelling-in-r Predictive Analytics Lifecycle Source: blogs.sas.com
  • 10. Slide 10Slide 10Slide 10 www.edureka.co/advanced-predictive-modelling-in-r Advantages Predictive Analytics
  • 11. Slide 11Slide 11Slide 11 www.edureka.co/advanced-predictive-modelling-in-r Why Predictive Analytics?
  • 12. Slide 12Slide 12Slide 12 www.edureka.co/advanced-predictive-modelling-in-r Only Analytics Is Not Enough! Predictive analytics is a game-changer — it’s like “Moneyball” for… money.
  • 13. Slide 13Slide 13Slide 13 www.edureka.co/advanced-predictive-modelling-in-r 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.
  • 14. Slide 14Slide 14Slide 14 www.edureka.co/advanced-predictive-modelling-in-r 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%
  • 15. Slide 15Slide 15Slide 15 www.edureka.co/advanced-predictive-modelling-in-r Major Domains Using Predictive Analytics
  • 16. Slide 16Slide 16Slide 16 www.edureka.co/advanced-predictive-modelling-in-r 3 Scenarios where Predictive Analytics is Must
  • 17. Slide 17Slide 17Slide 17 www.edureka.co/advanced-predictive-modelling-in-r Churn Prevention and Customer Lifetime Value
  • 18. Slide 18Slide 18Slide 18 www.edureka.co/advanced-predictive-modelling-in-r 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
  • 19. Slide 19Slide 19Slide 19 www.edureka.co/advanced-predictive-modelling-in-r 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:
  • 20. Slide 20Slide 20Slide 20 www.edureka.co/advanced-predictive-modelling-in-r Why Churn Prediction
  • 21. Slide 21Slide 21Slide 21 www.edureka.co/advanced-predictive-modelling-in-r 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
  • 22. Slide 22Slide 22Slide 22 www.edureka.co/advanced-predictive-modelling-in-r 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 :
  • 23. Slide 23Slide 23Slide 23 www.edureka.co/advanced-predictive-modelling-in-r Predictive Model Churn likelihood and profitability matrix :
  • 24. Slide 24Slide 24Slide 24 www.edureka.co/advanced-predictive-modelling-in-r Flow of Churn Analysis
  • 25. Slide 25Slide 25Slide 25 www.edureka.co/advanced-predictive-modelling-in-r How It Goes
  • 27. Slide 27Slide 27Slide 27 www.edureka.co/advanced-predictive-modelling-in-r Sentiment Analysis
  • 28. Slide 28Slide 28Slide 28 www.edureka.co/advanced-predictive-modelling-in-r 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
  • 29. Slide 29Slide 29Slide 29 www.edureka.co/advanced-predictive-modelling-in-r Sentiment Analysis Flow Text Input Tokenization Stop word filtering Negation handling Classification Sentiment class
  • 30. Slide 30Slide 30Slide 30 www.edureka.co/advanced-predictive-modelling-in-r Recommendation
  • 31. Slide 31Slide 31Slide 31 www.edureka.co/advanced-predictive-modelling-in-rSource: http://fortune.com/tag/predictive-analytics/ E-Commerce using it for recommendation! Recommendation
  • 32. Slide 32Slide 32Slide 32 www.edureka.co/advanced-predictive-modelling-in-r This is how Amazon’s recommendation engine works Amazon : Case Study
  • 34. Slide 34 Your feedback is important to us, be it a compliment, a suggestion or a complaint. It helps us to make the course better! Please spare few minutes to take the survey after the webinar. www.edureka.co/advanced-predictive-modelling-in-r Survey