Thursday, 23 May 2013

How to Measure Effectiveness of a Campaign using Marketing analytics (Banking)

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

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