Marketing Analytics - Measure Effectiveness of Email Campaign for Bank
In our Case Study: Customer Analytics for Telecom Operator to Cross-Sell and Up-Sell we had a look at the Telecom Analytics .. Now let's have a look at how Analytics has changed the communication between the bank and its customers
Banks have a good understanding of customer as the customers part with various data points (SSN #, Tax #, Address, Employee, Salary etc.) at different points of time (Enrolment, Address Change, Mobile Banking etc..)
This information is used for personalized marketing through email (This is the Channel for analysis - multiple outbound channels can also be fed) .
Processes in Marketing Analytics for Personalized Promotions for Banking
The processes involved are as follows
1. Gather Data
2. Analyze Data , Document Discovery and Create Model
3 Execute Campaign
4. Collect Responses
5. Measure the Results (Efficiency)
6. Fine tune / Optimize the model
7. Refresh Model and Segment
Since the necessary data for understanding the customer is already available / collected, the data is segmented to understand different customer segments that are available and their profiles
Each segmented is treated in unique way based on their behavioural patterns
The segments are divided into control and test groups. The customers in the test groups are subjected to the personalized marketing campaign while the control segment customers are part of regular campaigns
The most important step after sending those mailers is to collect responses. This is a key differentiator between a good and bad campaign management
The responses are subjected to Response Segmentation analysis and the results are measured. What are the parameters that are clearly visible in the responders? What are the feature of the non-responders .. this is an area where business needs to play some role rather than IT / Analysts
The Bank's Personalized Campaign has created a 500% increase in response compared to the generic mailer (Refer Figure)
The model is recreated with the understanding from the new findings - this is called Model Recalibration. The model is refreshed in campaign management system and the process continues
The Next Best Action (here the Mailer) is a continuous learning process
+Microsoft Dynamics ERP was used as the CRM for the Bank. Third party software was used for Mail blast and custom code was used for model development \
There are also custom tools/solutions for campaign / personalized promotion. For example, Manthan Systems' TargetOne tool uses data from various touch points like point-of-sale (POS) and store vicinity, during ecommerce transactions, email click-throughs and social media engagements to ensure right conversation is initiated with the right customer at the right time through the right medium
See also:
Payment Card Industry - Crucial for Real-Time Next Best Action (NBA) - Big Data
Customer Analytics, Supply Chain Analytics, Next Best Offer, Next Best Action, Consumer Behavioral Prediction, Social Analytics, Social Media Analytics, Location based Analytics, SoLoMo Analytics, Predictive Modelling, PMML, Statistical Models, Statistical Modelling, Revolutionary R, SAS, SPSS, Demand Forecasting, Product Affinity Analysis, Offer Response Model, Customer Intelligence Modeling, Machine Learning
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