Guest lecture | SZABIST -Data Mining
-
Upload
muzafer-ahmed-malik -
Category
Presentations & Public Speaking
-
view
127 -
download
1
Transcript of Guest lecture | SZABIST -Data Mining
![Page 1: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/1.jpg)
Leveraging Data Mining for Customer LoyaltySZABIST 105 Campus – Nov 06,
2015
![Page 2: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/2.jpg)
BBA & MBA Class Project Management Customer Loyalty Programs
Venture Partners
![Page 3: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/3.jpg)
Muller & Phipps Pakistan Pvt. Ltd. | www.mulphico.pk
About Presenters
Born in KHI, 19th Dec 1984Born in KHI, 22nd Sep 1979
Hina Ghufran MasoodNational Manager Customer Service
Muzafer Ahmed MalikManager Service & Quality
MBA in Marketing, 2013
Project Lead, Customer Loyalty ProgramsAvid reader, Music n’ film lover, Football FanPeople person
MBA in MIS, 2001
Chair Person, Customer Loyalty Programs
Avid reader, Music Listener, Coffee Lover
Likes interacting with indifferent people
![Page 4: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/4.jpg)
![Page 5: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/5.jpg)
What is Customer Loyalty?
![Page 6: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/6.jpg)
Customer Loyalty Is….
A result of consistently positive
emotional experience, physical
attribute-based satisfaction and
perceived value of an experience, which
includes the product or services.
Muller & Phipps Pakistan Pvt. Ltd. | www.mulphico.pk
![Page 7: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/7.jpg)
Howto
DriveCustomer
Loyalty
![Page 8: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/8.jpg)
Introducing
Approach
![Page 9: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/9.jpg)
Net Promoter Approach - Mechanics
Muller & Phipps Pakistan Pvt. Ltd. | www.mulphico.pk
How NPA Works?
“Based on your recent experience with <touch point>, on a scale from 0 to 10, how likely is it that you would recommend M&P to a friend or colleague?"
Promoter QuestionPromoter Rating
Very likely
Very unlikely
109876543210
Detractors
Promoters
Passives
loyal, enthusiastic customers staying longer, spending more and making referrals
satisfied but unenthusiastic customers being more vulnerable to competitor offerings
complaining often with higher defection rate, spending less, spreading negative news Net Promoter
Score
% Promoters
% Detractors
minus
=
Net Promoter Score
Note: passives are ignored for the NPS calculation
![Page 10: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/10.jpg)
Introduction to Net Promoter Approach
Muller & Phipps Pakistan Pvt. Ltd. | www.mulphico.pk
![Page 11: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/11.jpg)
Net Promoter Approach –Process flow
Muller & Phipps Pakistan Pvt. Ltd. | www.mulphico.pk
First call is made to customer (either from business itself or from an outsourced client) to obtain rating on a scale of 0-10
The rating is between 0 – 8; i.e. Detractor or Passive
Second call is made from a designated representative from organization to enquire reason for dissatisfaction or what went wrong.
![Page 12: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/12.jpg)
Winning Customer Loyalty – Data Mining
Muller & Phipps Pakistan Pvt. Ltd. | www.mulphico.pk
What to do with the available data and how to utilize it fully?
Findings from 2nd call gives customer insight and reason for dissatisfaction, known as Quick Wins
Quick Wins are action items which enables a business to correct what went wrong in the first place
By providing timely appropriate solution you win customer & their Loyalty
by applying
![Page 13: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/13.jpg)
Implementation Examples
Muller & Phipps Pakistan Pvt. Ltd. | www.mulphico.pk
![Page 14: Guest lecture | SZABIST -Data Mining](https://reader035.fdocuments.net/reader035/viewer/2022081514/58f00e381a28abc12a8b463d/html5/thumbnails/14.jpg)
Implementation Examples
Muller & Phipps Pakistan Pvt. Ltd. | www.mulphico.pk
Thank you