SOCIAL MEDIA PROJECT Prediction whether the customer is going to adopt the tourism package based on a social media campaign

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SOCIAL MEDIA PROJECT

Prediction whether the customer is going to adopt the tourism package based on a social media campaign.

Business Objective

An aviation company that provides domestic as well as international trips to the customers now wants to apply a targeted approach instead of reaching out to each of the customers. This time they want to do it digitally instead of tele calling. Hence they have collaborated with a social networking platform, so they can learn the digital and social behaviour of the customers and provide the digital advertisement on the user page of the targeted customers who have a high propensity to take up the product. 

Propensity of buying tickets is different for different login devices. Hence, you have to create 2 models separately for Laptop and Mobile. [Anything which is not a laptop can be considered as mobile phone usage.] 

The advertisements on the digital platform are a bit expensive; hence, you need to be very accurate while creating the models. 

 

Variable Description

Variable	Description
UserID	Unique ID of user
Buy_ticket	Buy ticket in next month
Yearly_avg_view_on_travel_page	Average yearly views on any travel related page by user
preferred_device	Through which device user preferred to do login
total_likes_on_outstation_checkin_given	Total number of likes given by a user on out of station checkings in last year
yearly_avg_Outstation_checkins	Average number of out of station check-in done by user
member_in_family	Total number of relationship mentioned by user in the account
preferred_location_type	Preferred type of the location for travelling of user
Yearly_avg_comment_on_travel_page	Average yearly comments on any travel related page by user
total_likes_on_outofstation_checkin_received	Total number of likes received by a user on out of station checkings in last year
week_since_last_outstation_checkin	Number of weeks since last out of station check-in update by user
following_company_page	Weather the customer is following company page (Yes or No)
montly_avg_comment_on_company_page	Average monthly comments on company page by user
working_flag	Weather the customer is working or not
travelling_network_rating	Does user have close friends who also like travelling. 1 is highs and 4 is lowest
Adult_flag	Weather the customer is adult or not
Daily_Avg_mins_spend_on_traveling_page	Average time spend on the company page by user on daily basis

DATASET: Social Media  Data For DBSA.csv

1. Project notes 1

1. Business Problem Understanding and Problem definition
2. Understand and define the problem statement.
3. Get a preliminary understanding of data and perform exploratory data analysis.
4. Discuss the business context.
5. Data cleaning and pre - processing (like outlier treatment, missing value treatment etc.)
6. How to generate insights from EDA?
7. Discuss about any finer nuances that could be used to generate insights.
8. Generate a data report.
9. Exploratory Data analysis and insights driven from it.

2. Project notes 2

1. Model Building and comparison
2. Build various models and check their accuracy.
3. Discussion around what model performance measures could be applied?
4. Discuss about model validation
5. Discuss about model tuning
6. Discuss about how to draw business insights & recommendations.
7. Model Tuning
8. Model Interpretation 3.  PPT 

A PPT which helps explain & communicate the data analysis to be used in the final presentation.

4. A business report 

A business report in pdf format which includes the detailed analysis of project notes 1 and 2 along with business insights and recommendations.