By Haveesha Ryali |
November 12, 2018
Imagine this scenario – Two customers dial into a bank’s call center. One of them is looking to explore alternate payment options and the other wants to know their credit statement for the month. You would expect the interactive voice response (IVR) options for both customers to be different. However, they are both presented with the same, frustrating automated responses.
This challenge occurs often because the technology fails to recognize the context or behavior that led to each customer’s call. Therefore, their experience was generic and not personalized to a specific need.
Today, advanced analytics combined with digital technology has the power to provide deep customer insights in the financial world. This can create a compelling value proposition provided banks and financial institutions embrace these insights to analyze behavioral trends. To break it down – in this age of advanced analytics, data will become a differentiating factor. Data enables banks to better understand their customers, edge out competition and push the right products at the right time.
However, just analyzing historical data to derive insights may not be enough to predict future customer behavior. To truly predict the future, behavioral analytics needs to be leveraged to understand customers intimately.
Behavioral analytics is the decoding of customer behavior based on their interactions with the organization across platforms and choice patterns. These platforms could be social media, ecommerce sites, online reviews, mobile applications and more. When banks utilize this data and come up with insights into every customer’s decision-making process, they can predict their customers’ unmet needs and design personalized interventions, or nudges. These personalized nudges towards certain choices can generate loyalty in customers and push them to make the right decisions.
Look what Merrill Lynch does. The bank was aware that retirement was the last thing on their younger customers’ minds. Which is understandable, because most young people in the US are working towards paying off their student debt or saving up for family and real-estate. However, saving up for retirement early helps in getting better returns at the time of retirement. Merrill Lynch worked on putting up an aging algorithm on their website – which allows a user to upload their photo and watch it age 20, 30 or 40 years. This seemed like an odd thing for the bank to do, but customers who used the program started saving for their retirement. Merrill Lynch ended up getting the desired result from the digital program.
While Merrill Lynch is just one example, financial services organizations should aim to use the power of behavioral analytics to enhance customer experience regularly. For instance, behavioral analytics can be used to predict customer patterns and raise a flag when suspicious activity is detected. Banks can also use behavioral analytics to sell a set of financial services depending on what a customer wants at a particular time. Programs can also be designed to specifically target customers that are known to have high CLTV and high lapse rates. By equipping themselves with the right tools, banks can ensure they don’t lose out on customers.
So, the next time a customer dials into your call center, wouldn’t it be great to directly address their problems? After all, a personalized response leads to happy customers.
How can OSG help on the journey towards customer satisfaction?
At OSG, we use cognitive and behavioral analytics to understand what matters most to our clients. Cognitive analytics are leveraged to look at historical data and decision making. Behavioral analytics are used to go beyond the “who” and “what”, to understand the “how” and “why” to predict future buying patterns. When combined together, we enable you to design and deliver superior experiences by nudging specific customer segments. This builds up loyalty, leading to higher customer engagement and improved customer experience.
Through behavioral analytics, OSG helped a leading global health insurer segment their customers and understand their lifetime value to predict future customer engagement. By leveraging our powerful behavioral analytics, OSG analyzed the client’s customer data to create segments and improve customer life time value. A predictive scoring model for segments was created to drive a marketing strategy for each segment. Through this approach, OSG helped increase customer engagement and profitability for the client.
To learn more about how you can get started on your behavioral analytics journey, write to firstname.lastname@example.org.