Case studyCAMPAIGN MANAGEMENT INTRODUCTION IN SIBERIA

ABC has a history of completing interesting projects for clients in different regions. Among others, we had a chance to work with leading bank in Ural region in Central Russia. After successful delivery of risk related project in summer 2012, we were later hired to help with CRM/CVM processes targeting Private Individuals (PI) and Small and Medium Enterprises (SME). Our tasks in this 6 months long project consisted of:

1

Customer Segmentation

Identify and describe current customer segments in portfolio, suggest suitable approaches to keeping up relationships with clients in different segments

2

Development of Predictive Model and its Prolongation into Profit Model

For cross-selling and up-selling campaigns for different customer segments, probability of customer default (customers that fail to meet their debt obligations in time) and customer churn (customers closing their account in bank within period of time)

3

General Reviews

Review of current processes and suggest improvements, define reporting framework to compare campaigns.

4

Price Elasticity

Analyze price elasticity for clients that were offered new loans and credit cards.

Prior to our project, CRM process setup in bank was to select a group of active customers that passed simple hard filter and offer them another credit product. Using outputs of our statistical models and customer segmentation, the client now selects only top 20% to 40% of customers with highest probability to accept the offer in each customer segment and targets them, though reaching the same revenue while enjoying higher profit. Saved resources that are not wasted by contacting customers with low probability to accept the offer are used to target customers in other segments. Also, customers are not only assessed for probability to accept an offer but also for probability to default, allowing bank to adjust their interest rate offered accordingly.

Despite the enormous growth of bank’s PI portfolio, one of the issues identified was number of SME customers leaving the bank. Thanks to churn model developed, our client is able to identify 80% of SME customers likely to close their account in only 4 steps and take action accordingly in advance. On top of that, thanks to improved processes and common language used, bank can also compare efficiency of campaigns in time, IT and marketing employees understand each other when talking about data extracts, marketing and risk share information regarding on-going campaigns and limitations, etc.

As an interesting inside: some of the issues we had to face were non-existent data dictionary between departments causing marketing to ask for data field and IT delivering what they believed was asked from them; fairly complicated data structure causing IT to deliver data extracts only with long time-lag; non-standardized reporting making it almost impossible to compare and analyze previous campaigns; call-center infrastructure rebuild on-the-go. Apart from these issues, our consultants had an amazing chance to experience true low-Siberian winter and visit another beautiful region in Russia :)

 

“Estimated economic surplus reaches hundreds of millions Rubbles already in the first year.”

 

Despite all the challenges, we have delivered fully functional campaign management process, enabling our client to financially optimize marketing offers to customers. Estimated economic surplus reaches hundreds of millions of Rubbles already in the first year, meaning ABC has delivered successful project with ROI well over 18. Not a bad result after all!