As banks, thrifts, and other financialinstitutions seek ways to better understand their customers’ andmembers’ needs, they must sift through enormous amounts of data.Each customer inquiry and transaction creates data, includingcustomer account postings, lead generation, campaign management,market segmentation, social media inputs, and customer relationshipmanagement results.
All of this data is typically too much to digest and too costly toanalyze with traditional reporting tools without the use ofanalytics to sift through the noise to come to meaningfulconclusions. As part of these initiatives, institutions are tryingto strike the right balance between costs and benefits, knowingthat discovering customer wants and needs can be an arduousprocess. Increasingly, financial institutions are using powerfulanalytics systems to provide such insight and build more meaningful(and profitable) relationships with customers.
These analytics tools can vary from simple reports, to businessintelligence tools and dashboards, to high-powered customer,predictive, and profitability analytics tools and processes. Andwhile some experts consider only the latter to be considered bonafide analytics tools, many business intelligence solutions nowoffer some level of predictive capabilities, adding value to manyinstitutions.
These solutions help to identify purchasing motivators and loyaltydrivers that may be unknown by the customers themselves. Analyticssystems can help identify which channels customers use most, whichnew products and services that are likely to be of interest tocustomers, and which customers are likely to attrite. With suchinformation, financial institutions can reach out to deepen (orsave) a valued relationship.
Financial institutions are increasingly realizing that analytics,in its many forms, offers significant opportunities to betterunderstand customer wants, needs, and behaviors and increasecustomer satisfaction, all while offering outstanding value and animpressive return on investment to help the bottom line.
