New technologies continue to shape our world, where mobility, constant innovation and disruption have become the new normal. Technology has lowered the barrier for new competitors and fueled increased customer demands and expectations, which continues to grow and evolve at unprecedented rates.
Banks, once perceived as full service, trusted advisors, are often viewed as transaction processors and nuisances on the road to achieving a customers desires. No longer can a bank compare itself only to its direct competitors or changes within its specific market or vertical. Technology has enabled new entrants to build new business models that capitalize on, and with their expertise address specific customer needs. Processes that cause friction in the customer journey are quickly being identified for technical evolution by Fintechs eager to seize the opportunity and attract unhappy customers away from slow to respond banks.
Understanding customers needs, preferences and propensity to churn is of paramount importance given the exponentially high cost of acquiring a new customer versus retaining an existing one. Several empirical studies and models have proven that churn remains one of the biggest destructors of enterprise value. The good news is the volume, variety, and velocity of data along with Big Data technology, allows banks to harness data for new customer insights to improve experiences, operations, and offerings.
It all starts with obtaining a holistic 360 degree view of the customer. Eliminating data silos and federating data to identify inter-organizational customer insights based on customer profile, products, transactions and interactions gives banks a clearer picture of who their customers are, and what each customer needs. Assimilated data fed into a Big Data platform for refinement delivers powerful insights including Agile digital personas, churn propensity scores, and marketing campaign effectiveness metrics.
Analyzing recent interactions and transactions reveals channel preference, spending patterns, and change in frequency of usage to signal possible churn. Further analysis of key variables helps identify the potential value of each customer so proactive measures can be taken to engage or retain those individuals. Conversely, this analysis can also identify unprofitable customers so banks can determine the best course of action for increased profitability.
Simultaneously, improving marketing effectiveness is also key to customer retention. Its no longer about product selection, rates, and location. Increased ease of switching institutions doesnt offer the security it once did. The key to preventing customer loss is being able to convey that you know who you are talking to and that you understand their desires. Customers are tired of being treated as a massive group or a largely segmented target demographic. Technology has created customer expectations that a company should only offer relevant and personalized content. Take for example Amazon or Netflixs recommendation engines. These companies used customer data and applied data science and machine learning to shape the customer experience through contextually relevant suggestions the customers may not have thought of their own.
Examples of poor experiences and misaligned and frequent product offers are rampant in the hungry banking industry. Investing the time, resources, and effort into technology that can help banks understand their customers better and communicate with them more effectively will repay big dividends through retained customers, increased share of wallet, and improved customer experience. Banks have to stop thinking like banks and start acting like forward thinking, tech-enabled, customer-obsessed organizations that provide the best, most relevant experiences possible.