Input Data
Below is the Data we have taken as an input.
1. Activity data of the previous marketing automation campaigns from email, SMS, and Notifiction campaign.
2. Customer data with all the available segments, age, gender, the fund purchased, avg value, city, date and frequency of purchase, etc
Approach Taken to solve the problem
Security
Since the client is a Mutual fund customer, they don't want their customer data to out of their premises hence we have deployed our Models on top of the client's database to ensure the security of the customer data.Project Process
The project was divided into 3 stages.Stage 1
- Data Integration & prep
- Data transfer from client
- Database
- Data Transformation
- Cloud Integration
Stage 2
- Identifying the business use cases
- Building Models.Building business use cases
- Identifying the segments
- Automating the intelligence for delivery
Stage 3
- Ongoing updating of the models
- Additional business use cases
- Monitoring of the performance of the models
- Fine-tuning the models for accuracy
Output
1. Churn Analysys.
2. Recommending the Top Products based on the user profiles.
3. Recommending New launches to the audience based on the probability of investing new funds.
4. Intelligent segmentation of the audience based on their profiles and identifying the best Funds that best fit for each segment.
5. Customized models to attract new customers. .
Results
1. 35% increase in engagement rates.
2. 63% increase in the website traffic from email marketing.
3. 40% increase in selling new funds to existing customers.
4. 22% increase in inquiry to purchasing for new customers.
5. 28% drop in unsubscribe rate
