Guiding the Sales effort: Predictive Insights & AnalyticsMarketing Insights for a Top 10 Canadian Bank
Following a decline in branch and call center traffic and a lack of capability to address the migration of customers to digital channels, this bank, like many large companies, wanted to strengthen its ability to generate high quality insights to guide sales efforts and to generate a high volume of proactive marketing contacts
The effort vastly improved the ability to drive top line results through upskilled talent, higher quality leads, more cost effective campaigns and generate better customer insight
Challenge
One of the largest banks in Canada with over 450 branches and 2 million customers. The Client provides retail products such as savings & checking accounts, brokerage accounts, retirement savings account, mortgages, personal loans, and credit cards. Its commercial business provides cash management, financing, trust and group retirement products.
Following a decline in branch and call center traffic and a lack of capability to address the migration of customers to digital channels, this bank, like many large companies, wanted to strengthen its ability to generate high quality insights to guide sales efforts and to generate a high volume of proactive marketing contacts using predictive analytics capabilities for cross-sell/up-sell, retention and acquisitions. At the start of the project, the bank’s:
- Analytic capacity was insufficient to meet requirements due to limited capacity of analytic platforms and processes, combined with a high volume of ad hoc requests.
- Predictive analytics were based on a very limited set of client data housed across various databases.
- Analytics were based on traditional statistical analysis, and did not leverage recent technology advances such as data discovery techniques.
- Analytics team were inundated with simple requests and did not have the capacity and skill sets to perform analytics requests.
Solution
Our experts collaborated with the client to:
- Transform their analytics capability in terms of people, process and technology across the Bank.
- Rapidly develop a Client Analytic Record (CAR) from over 5 data sources to act as the foundation for future analytics initiatives.
- Enable the integration of data previously not available, including AML, credit bureaus, transactional client data and 3rd party data sources.
- Deploy more sophisticated analytics techniques such as transactional parsing and collaborative filtering to enhance current analytics approach.
- Scale existing model development efforts and rapidly integrate the models into in-market campaigns.
- Develop an analytics measurement framework that separates campaigns from model impacts.
- Train client resources by delivering 4 training sessions and providing personal shadow pairing.
- Validate over 30 business assumptions to inform key strategic decisions such as effective product bundles for different customer segments and the impact of cultural and political change on customers.
Results
The bank was able to drive top line results through upskilled talent, higher quality leads, more cost effective campaigns and generate better customer insight by:
- Bringing more sophisticated data science techniques to the bank vs. relying traditional SAS approaches.
- Evolving the simple analytics datamart with 400 variables to a next generation customer analytical record with more than 3000 variables.
- Enabling the bank to develop 5-6 predictive models per month instead of per year.
- Increasing the direct marketing campaigns response rate by 50% across multiple channels.
- Reducing balance at risk by over $28M within 3 months of the campaign (32% above control group) through an innovative soft attrition model.
- Adding upsell and cross-sell balance of over $7M within 3 months of the campaign (32% above control group).
- Leveraging transactional parsing techniques to proactively identify customers who are most likely to attrite to competitors.
- Upskilled current client resources with a 4.8 overall satisfaction rate and a 4.7 applicable to my work rate.
- Creating a solid link between the marketing strategy team and business intelligence teams.