Banks need emotion recognition software to increase customer loyalty,As the U.S. retail managing an account showcase exhibits a warming rivalry for the greatest offer of wallet, most banks see client encounter (CX) as their upper hand developing the quantity of steadfast clients. Despite the fact that CX experts have for quite some time been utilizing various estimation frameworks and managing an account programming answers for increment client unwaveringness, they appear to disregard one fundamental part: feeling based statistical surveying.

How about we see why breaking down clients' feelings is an unquestionable requirement for banks endeavoring to give magnificent client encounter.

What customers say is NOT what they mean

As expressed by Gerald Zaltman, an educator from Harvard Business School, 95% of obtaining choices occur in the intuitive. In any case, later clients start to defend these supposed gut-level responses. That is the reason, when shoppers endeavor to clarify what they require from a bank, their sound contemplations impact reactions. Subsequently, the greater part of clients regularly say just sensible needs, for example, comfort of branches, loan fees, accomplice programs, and so forth along these lines discarding genuine wants drove by feelings.

Deep emotions increase customer loyalty

However, the most successful world’s brands across various industries swiftly realized the power of emotions and brought to perfection the art of connecting with customers at the emotional level. These brands captured customers’ hearts and minds by revealing their fundamental and thereby often unspoken emotional motives, such as the need to stand out from the crowd or to feel a sense of belonging, freedom, etc.

Why studying emotions is essential for banks

While the world known brands put much exertion into investigating the inward intentions and feelings that characterize client conduct, most bank still would like to build client steadfastness with scarcely detectable means, for example, offering somewhat higher funds rates. This approach is bound to disappointment from the earliest starting point, as Millennials, the biggest era in American history, express no sentiments of client devotion and figure their banks can't offer anything not quite the same as different banks. Accordingly, rather than concentrating on here and now objectives to build the measure of stores, banks ought to go for setting up enduring associations with clients. As ably noted by Duena Blowstrom, sentiments can pay off obviously better than numbers.
Setting up an enthusiastic association with clients, a bank can turn into an accomplice for clients as opposed to just remain a place to keep their cash. In spite of the fact that a financial records, CD or Visa themselves may not bring out an indistinguishable passionate impact from, say, a couple of tennis shoes, it doesn't mean banks should disregard clients' feelings by any means. To make further associations with clients, banks ought not simply offer an assortment of dependability programs. Or maybe, they should endeavor to wind up unwaveringness brands themselves like Apple or Nike do.
On the off chance that banks think little of the estimation of feelings, they hazard getting mutilated bits of knowledge about clients' needs and needs and therefore may pick a wrong advertising and deals system. The outcomes of such lack of caution are various: from low profit for advertising and deals ventures to poor client experience and clients' beat to another bank. All things considered, there's an opportunity to maintain a strategic distance from these results with the assistance of innovation.

How to recognize and analyze customers’ emotions

With our rich experience in banking software consulting, we’ve worked out a number of tips to carry out an in-depth analysis of customers’ emotions.
To define which emotions trigger purchase behavior, the first step is gathering data about a particular customer segment (e.g., the Millennial generation, the most profitable group of customers). Depending on budget, a bank can focus on conducting retrospective CX surveys (e.g., NPS, CSAT or CES) or measure emotions in real-time. In the latter case, banks can choose among a wide variety of emotion recognition technologies, such as text, voice or image analysis software.
Text analysis software uses natural language processing to identify whether a statement is generally positive or negative according to the language style as well as keywords and their valence index. Banks can use this software to analyze customers’ sentiments in their text reviews about products and the quality of their services. Voice analysis software uses recorded or live customers’ speech to uncover tone and word content. Image analysis software detects facial emotions within a photo or video. To identify customers’ expressions, image analysis software establishes relationships between points on the face and compares them with database files. Voice and image analysis software can be of great help in a branch providing real-time ‘emotion data’ for customer service representatives.
Once a bank finished with the first step, it’s time to systematize and analyze ‘emotion data’. Using data analysis software, based on statistical analysis techniques, such as multivariate regression and structural equation modeling, a bank can determine which emotional motivators correspond to a chosen focus group and which of these emotions create the most value for the bank.
After choosing ‘the most valuable emotions’, a bank should then anchor on it by creating consistent customer communications focused on this particular emotional need. At this final stage, every point of contact from content to customer service should reinforce customers’ emotional perception of the bank. A bank that manages to link itself with customers’ emotional motivators will communicate with customers more effectively thereby increasing their experience and loyalty.

Emotions are a universal language to connect with your customers

To achieve meaningful CX results, banks should use solutions for big data analytics and image recognition software to carry out an in-depth analysis of customers’ emotions and adopt the results in their CX strategy. Taking into account customers’ emotional needs will help banks to better engage with their customers, create deeper communications and build brand loyalty.

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