Customer Success Stories
Effective response modeling
SAS and Python Predictions enable the creation of ING’s Proactive Targeting Framework
Which customers will respond best to a given product offering? It remains a central question in any business. The Customer Intelligence Department at ING Belgium relies on response modeling software to provide the answer. In 2006, ING and Python Predictions developed a new tool – the Proactive Targeting Framework. Based on SAS software, it predicts customer behavior in a fast, effective, flexible, and user-friendly manner.
Intelligent actions with customer intelligence
The ING Financial Services group was founded in the Netherlands in 1991. Since then, the company has expanded throughout the world, setting up operations in more than fifty countries. Today, it is the sixth financial player in Europe and among the top fifteen in its sector worldwide.
Rapidly changing environment calls for new modeling
In 2006, the local CI department at ING Belgium decided it was time to refine its response models. In order to gain a competitive advantage in analytics, Martine George and her team defined five cornerstones that would be indispensable in the new targeting mindset:
“A first step was the construction of a data matrix containing more than 300 distinct pieces of information that are available for every client on a monthly basis,” explains Pieter Dyserinck, Senior Customer Intelligence Analyst at ING Belgium. “While these indicators had proven their value in previous targeting projects, we were looking for an expert partner to help us mold this mass of information into a more powerful, flexible, and interpretable solution.”
Efficiently predicting customer behavior
ING teamed up with SAS partner Python Predictions to develop the Proactive Targeting Framework, based on SAS software modules. “Due to the existence of the data matrix, only a limited amount of time was needed for data preparation. Instead, we were able to focus on constructing a battery of predictive models,” recalls Dr Wouter Buckinx, Partner at Python Predictions.
When easy expansion is key
Due to the success of the Proactive Targeting Framework, an expansion is already planned for the near future. Additional response models will be developed on a regular basis. From the creation of variables to the generation of a list of targets, ING’s new Proactive Targeting Framework relies on SAS software. This provides a powerful, performing, user-friendly, and dynamic solution, where it is particularly easy to integrate new models or to adapt and update the current properties. “In short, the new Proactive Targeting Framework will surely help improve the efficiency and success rate of ING’s Customer Intelligence Department,” concludes Martine George.
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Customer response modeling
SAS® Customer Intelligence
SAS® Enterprise Miner
More effective targeting of marketing campaigns
Flexibility - quick and easy expansion of any system with new data and predictive models
Time gain - increased efficiency provides for quick access to correct information
“The SAS software modules are capable of managing large amounts of information and offer the best flexibility. These are the key ingredients we need to develop efficient response models.”
Dr Wouter Buckinx
Partner, Python Predictions
“Our new Proactive Targeting Framework will greatly improve the efficiency and success rate of our Customer Intelligence Department.”
Dr Martine George
Head of Customer Intelligence, ING