P r e d i c t i n g i P h o n e X b u y e r s - WKU

Predicting iPhone X buyers Abdulaziz ALDEHAIM & Faisal Chowdhury Objective: Predicting iPhone X Buyers Data Description We had to nd the iPhone adoption of the customers based on their given data whether they were Early Adopter, Innovator, Early Majority or Late Majority. Using this dataset we used Rapidminer to build a model and then use the model to build a decision tree to nd the appropriate adoption for each customers. Research Background Modeling & Evaluation Conclusion We used our two datasets in Rapidminer to predict iPhone X buyers. We set our label as iPhone_Adoption. There are four types of buyer: Early Adopter Innovator Early Majority Late Majority We had two excel les that include details about the customers. For example, Gender, Age, Website Activity, and Bought Apps, etc. We had 10 attributes and 473 Customers. Most of the customers are early adopters which means that they get the phone as soon as its available. The second highest is late majority which means that they will adopt the new iPhone X after majority of the people already have. To the late majority special offers can be given before hand to make them be a early adopter.

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Transcript of P r e d i c t i n g i P h o n e X b u y e r s - WKU

Page 1: P r e d i c t i n g i P h o n e X b u y e r s - WKU

P re d i c t i n g i Ph o n e X b u ye r s A b d u l a z i z A L D E H A I M

& F a i s a l C h o w d h u r y

O b j e c t i v e : P r e d i c t i n gi P h o n e X B u y e r s

D a t a D e s c r i p t i o n

W e h a d t o � n d t h e i P h o n ea d o p t i o n o f t h e c u s t o m e r sb a s e d o n t h e i r g i v e n d a t aw h e t h e r t h e y w e r e E a r l yA d o p t e r , I n n o v a t o r , E a r l y M a j o r i t y o r L a t e M a j o r i t y .

U s i n g t h i s d a t a s e t w e u s e dR a p i d m i n e r t o b u i l d a m o d e la n d t h e n u s e t h e m o d e l t ob u i l d a d e c i s i o n t r e e t o � n dt h e a p p r o p r i a t e a d o p t i o n f o re a c h c u s t o m e r s .

Re s e a r c h B a c k g r o u n d

M o d e l i n g & E v a l u a t i o n

C o n c l u s i o n

W e u s e d o u r t w o d a t a s e t s i nR a p i d m i n e r t o p r e d i c t i P h o n e Xb u y e r s .

W e s e t o u r l a b e l a si P h o n e _ A d o p t i o n .

T h e r e a r e f o u r t y p e s o f b u y e r :

E a r l y A d o p t e r I n n o v a t o r

E a r l y M a j o r i t y L a t e M a j o r i t y

W e h a d t w o e x c e l � l e s t h a ti n c l u d e d e t a i l s a b o u t t h ec u s t o m e r s . F o r e x a m p l e ,G e n d e r , A g e , W e b s i t eA c t i v i t y , a n d B o u g h t A p p s ,e t c .

W e h a d 1 0 a t t r i b u t e s a n d 4 7 3C u s t o m e r s .

M o s t o f t h e c u s t o m e r s a r e e a r l ya d o p t e r s w h i c h m e a n s t h a t t h e yg e t t h e p h o n e a s s o o n a s i t sa v a i l a b l e .

T h e s e c o n d h i g h e s t i s l a t em a j o r i t y w h i c h m e a n s t h a t t h e yw i l l a d o p t t h e n e w i P h o n e X a f t e rm a j o r i t y o f t h e p e o p l e a l r e a d yh a v e .

To t h e l a t e m a j o r i t y s p e c i a lo f f e r s c a n b e g i v e n b e f o r e h a n dt o m a k e t h e m b e a e a r l y a d o p t e r .