Science of Customer Satisfaction
More than half of US shoppers abandon a brand following a bad experience [1]. More than half the customers are willing to pay more for a better customer experience and 13% will share with at least 15 people or more if they are unhappy with a product or a service [2]. It is not surprising that industry experts predict that customer experience will be a differentiating factor in coming years, possibly overtaking price and product. Hence, measuring the customer experience is not just a strategic move but a necessity for a business’ existence.
Measuring the Loyalty
An independent research [3] found that two-thirds of experience directors use NPS or Net Promoter Score to measure customer loyalty. An NPS survey asks two questions:
1. How likely are you to recommend our business to a friend or a colleague?
2. Why?
The scoring system then classifies the respondents into three groups:
· Promotors (9–10): are the loyal customers who are enthusiastic about the business and would continue buying from it
· Passives (7–8): are customers who are overall satisfied but likely to switch to competition
· Detractors (0–6): are unhappy customers that are likely to damage the brand by a negative word of mouth
NPS is the difference between the percentage of Promotors and Detractors. This acts as a vital indicator of the customer’s perception of the business, which in turn impacts the growth. according to this research by London School of Economics, an average NPS increase of 7% can translate into a 1% growth in revenue on an average [4].
Decoding the Score
While it is important to know the customer’s impression of your business it is equally important to understand why. In today’s world of omnichannel experience a customer interacts with 5 channels on an average while engaging with a business [5]. Each of these activities generate a tremendous amount of data that can be connected to derive intelligence from the customer’s journey. Using analytics to evaluate the customer touchpoints to realign your business strategies to better serve the customers, drive growth and ensure customer retention is Journey Science.
With the variability of channels and the speed with which customers switch among different divisions of a business, a huge amount of data about customer experience is fragmented and remains unexploited due to siloed operations. Customer journey Analytics is a new breed of data science services that creates an infrastructure to store and organize the raw data, clean it and aggregate it into intelligent insights. The aggregated data helps create a unified view of journey into account all touchpoints of a single customer. It is possible to segment the customers by demography, the nature of transaction and unique circumstances under which they interacted with the business.
The team then narrows down the journeys that are relevant to their analysis to understand the impact of the service channel on the customer NPS Score. A comparative analysis helps the team to localise areas that need more attention.
Similarly, the team can analyze the customer journeys followed by a high NPS score to understand the well performing channels and positive experience. This also creates space for predictive and real-time analysis to identify the nature of customer interaction, the hurdles they face, their needs and the next probable action. This helps businesses to improve their backend to better serve their customers and creates an opportunity for customization.
Journey Science tool creates a decision tree, providing a comprehensive analysis of each slice of the customer demographic. Then they perform statistical analysis to test their hypothesis regarding the customer behavior. The results returned can be used to identify key performance metrics, assumptions regarding customer perceptions and corrective actions that can be taken.
Journeys to Business
A study by Econsultancy found that 63% of financial services organizations ranked customer experience as their №1 priority. [6] Consequently it is vital that businesses not only track the customer perception, but also proactively identify methods to positively influence them, gaining a competitive edge over their counterparts. A well-integrated framework of customer data allows the businesses to link customer expectations and likely behavior, recognize focus groups, prioritize certain activities and strategize their tactical moves.
A transparent cross-functional view provides a view of redundant cost centers and optimize the operations. It allows companies to understand the effectiveness of their marketing techniques and design a program that yields maximum output. A collective view enables a smooth collaboration across different divisions of the organization, reducing the lead times and elevating the customer experience. By creating a Path to Purchase with a high precision has a direct impact on the revenues of the business and facilitates growth.
[2] https://www.slideshare.net/ekolsky/cx-for-executives
[3] https://lumoa.me/blog/net-promoter-score-statistics
[5]https://practicalanalytics.wordpress.com/2015/09/04/customer-journey-analytics-and-data-science/
[6]https://www.pointillist.com/blog/how-to-calculate-nps-using-journey-analytics/
