Big data and customer analytics have and continue to be hot topics in retail banking. According to Bob Meara, senior analyst with Celent’s Banking practice, “62% of financial institutions in a recent Celent survey strongly believe that customer analytics offers significant competitive advantages and 53% strongly feel they need a granular, holistic and forward-looking view of customers to be competitive.”
But while banks and credit unions understand that there’s a need for customer analytics, questions still remain on what big data financial institutions need to generate said analytics, and where can they get it. In a recent predictions piece, James Plath, digital lead for the financial services industry at Gartner Consulting, touched on a viable source: “Banks own – arguably – the richest data set in existence on any person: transactions.”
Transaction data—data from consumers withdrawing and depositing at ATMs; data from customers making purchases at point-of-sale (POS) terminals; data from home buyers starting mortgage applications on their mobile banking apps and then completing them online once they get home—is chock full of rich customer engagement and customer experience intelligence. The problem lies in somehow getting access to it, and then making sense of all the information. Per a Capgemini report, when asked to select up to three “key impediments to Big Data success”, organizations’ responses included:
- Too many silos and lack of “pooled” data (57%)
- The time required to analyze large data sets (44%)
- Unstructured content in big data is too difficult to interpret (33%)
Fortunately, new customer analytics tools are becoming available—innovative applications that are able to show how customers engage with a bank’s ATM, POS, mobile, internet and branch service channels. By combining correlated consumer transaction data with other third party feeds, such as regional demographics and locations of competitor ATMs, these customer analytics applications can display information in interactive dashboards and actionable reports. So rather than spending days searching for and piecing together data from disparate internal silos and external service providers, channel managers and operations support teams can access the analytics they need to understand consumers’ experience within a few clicks.
With real-time access to transaction data and analytics the potential results for banks are significant. They gain the ability to react in seconds (rather than hours) to consumer related transaction issues. They can improve service channel availability and optimize their service offerings through easy analysis of consumer usage patterns. Currently a leading Middle Eastern bank is leveraging the rich consumer intelligence gathered from their ATM transactions to build data-driven marketing campaigns targeting off-us consumers in efforts to convert these users into new, higher-margin, on-us customers.
“Banks have a great deal of work ahead of them to deliver a high-quality, low friction, and engaging customer experience across all delivery channels, while concurrently lowering the cost to serve,” says Celent’s Mr. Meara in his report, Retail Banking Channel Systems in North America: The Quest for Omnichannel Continues. “Doing so is not optional…”
In 2015, I foresee many financial institutions adopting new analytics tools that will give them access to, and the ability to make use of, the transaction data flowing through their banking service channels. These customer-focused banking analytics applications will unlock the “Big Data” banks’ chief data officers, line of business managers and data analysts need to make more profitable data-driven decisions and ultimately enhance customer engagement.”
To explore how your organization can Drive Banking Engagement with Customer Analytics, join INETCO for a 45-minute webinar featuring Celent Banking Practice Senior Analyst, Bob Meara, on Wednesday, February 11. Learn how to tap into your existing transaction data and access the rich customer analytics you need to drive banking engagement, adopt data-driven banking strategies, and speed up your profitability reporting cycles.
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