Banking

It is true that for many clients you have plenty of data - those who actively use your services. For others however there is only a handful of information - those who have registered during a promotion and forgot about you.

In both cases it may be equally difficult to asses client's overall potential as there still may be your competitor eating a "bigger half" of the apple. Two accounts are quite an often case.

All of this makes data analysis vital for customer portfolio management. Product usage, changes in behavior, loyalty, response to marketing messages are all important when evaluating long-term client value.

For financial institutions DataWise can offer several services that start with data but end with serious business conclusions:

Basket analysis
Which financial services are being used together? What should be the up-sell sequence? What is the customer life-stage?

Profile analysis
Which questions should be asked during customer registration process? How to motivate the clients to fill them? How to tie the profile data with product usage information?

Segmentation
How to split your customers along the key dimensions: loyalty, value, profile and product usage patterns. How to do it in such a way, so the results bring insight and knowledge but first of all provide an actionable set of segments.

Communication scenarios
How to map the communication scenarios with segments? Is there a space for automatic profiled offer generation? How to measure and monitor communication effectiveness?

Branch network optimization
Where do you miss point of sales? Where does the unused potential concentrate? Which branches sell relatively little compared to others who operate in similar environment? Where to install VIP services?

Optimizing sales targets
Is it the same thing to sell 100 credit cards in Warsaw and in Radom? How to use external data to establish sales targets that are more complex then just adding 10% to a last year figure? How to find reliable reference points for information coming from the field? How to convince your employees that the rules treat everyone equally?