Financial service marketers know that every interaction with customers and prospects is an opportunity to better match products and services with the customer’s needs and expectations, and to predict the next best purchase option. But instead of putting their hand on the pulse of what their customers really want and need, they’re overwhelming them—blasting multiple products and offers repeatedly within the same channel, drowning customers with an overload of irrelevant information.

The reality is that when more of the same information from a silo is recycled and spread disparately across new and existing channels (i.e. branch, website, call center), it doesn’t matter how many times it’s distributed.

Thinking that this type of strategy is going is going to generate more sales, actually has the opposite effect. In fact, without applying a segment-based approach to refine the data, marketers are almost better off not integrating new channels at all, and letting established channels carry less noise. Banks and credit unions can’t craft an efficient one- size- fits- all brand message for everyone. They have to break away from the old batch-and-blast model and get to segmenting all that data before it hits the streets.

For example, how many customers and prospects repeatedly receive the same irrelevant offers time and time again? What about the Gen-Y customers who are receiving financial information on retirement products, or a customer who has just purchased a home and now is receiving offers to refinance? See—nothing but noise.

So the challenge isn’t about having enough data, but being able to mine a little deeper to effectively find the right information about a prospect or customer to build highly targeted marketing campaigns based on their needs and particular life-cycle. It means breaking down the silos, segmenting and integrating the data throughout the enterprise, and focusing more on the consumer rather that the product.

With Big Data comes a responsibility to your customers. A recent 2013 survey by Cisco Global Retail Banking reported that 46 percent of U.S. consumers feel their bank has enough information to be able to offer personalized products and services. Don’t disappoint them. A successful cross-channel strategy depends on a high level of accurate data to generate analytics. Segment customer data correctly to individually identify customers’ wants, needs, and channel of preference—and eliminate all the noise.