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SOCIAL MEDIA PROJECT Prediction whether the customer is going to adopt the tourism package based on a social media campaign
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
- Business Problem Understanding and Problem definition
- Understand and define the problem statement.
- Get a preliminary understanding of data and perform exploratory data analysis.
- Discuss the business context.
- Data cleaning and pre - processing (like outlier treatment, missing value treatment etc.)
- How to generate insights from EDA?
- Discuss about any finer nuances that could be used to generate insights.
- Generate a data report.
- Exploratory Data analysis and insights driven from it.
2. Project notes 2
- Model Building and comparison
- Build various models and check their accuracy.
- Discussion around what model performance measures could be applied?
- Discuss about model validation
- Discuss about model tuning
- Discuss about how to draw business insights & recommendations.
- Model Tuning
- 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.
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