Business strategy today is all about integrating some new insights and forging a comprehensive plan for success. According to a study by McKinsey, companies which use customer analytics extensively are more likely to generate above-average profits. Not stopping there, they also outperform less analytically oriented peers, staying in the lead across the entire customer lifecycle and enjoy much superior customer loyalty. How exactly is analytics helping enterprises?
Much of the credit for this success is being attributed to how responsive businesses today are to customer needs and about their focus on establishing systems and guidelines relevant to the customers. Analytics provide insights into customer preferences to companies, which tailor their content and messages to stay relevant to customers and await a timely opportunity to make offers suited to their customers’ wishes. They use their insights to drive better and more relevant and valuable interactions turning even new customers into loyal ones, so they come back for more, again. They also retain the unshaken loyalty of long-standing customers through these measures.
Important ways in which enterprises stay relevant to customers include the following:
The time to establish relevance is when the customer shows interest in your product, and not at any other time. Your sales plans, targets, and metrics have no relevance to a customer. Pitch your product when a customer wants something like it, and sit back to watch the deal getting struck.
Use analytics to understand the mapping of a customer’s decision journey, understand the opportunities and areas of friction with customer interests.
Extrapolation: Extrapolate the insights offered by analytics to cover your demographic of customers at a high level of granularity, using a broad range of attributes like behavior, demographics, location, age or even the customer’s stage in the buying journey. Use them to craft personalized messages which talk to them about what they are looking for only, down to a color or size.
Use data to define customer segments using broad criteria and dive down deeper to make your message personalized and relevant to each group by its characteristics and attributes. These could be thank you notes, feedback requests, new offerings of similar products offering them a special discount or other personalized incentives.
Businesses need to train and orient their employees to provide personalized experience to the customers, whether in providing a service or responding to an inquiry. They need to be willing to learn and be flexible in carrying their learning from one customer interaction to another, to revise their approach.
Understanding customer intent:
Successful enterprises learn to spot positive signals of customer intent or negative signals of their refusal to be engage, using their behavior. This ability to spot a customer’s intentions and read them right qualifies an insurer for success. Insurers today are taking advantage of data from third parties, which provide a deeper insight into customer health needs, lifestyle choices and risk-taking behavior, like recreational activities, travel choices or even weight, to decide how to tailor a policy to suit a customer’s particular needs. Data today can help businesses anticipate intent, by using predictive analysis based on previous or related purchases made by other customers which led them to purchase a specific next product, encouraging upsell initiatives and offers.
Rewarding customers for volunteering data:
Customers today tend to reveal data willingly and without any incentivization. Businesses are happy to offer freebies and rewards to customers who are willing to share data which reveals their priorities, habits and tastes.
Upsell or Cross-sell flagged customers:
Brands treat high value customers differently. Customers who call in are treated to a wide variety of options and choices as the calling agents offer them relevant products and services, or even an upgrade.
Most businesses are seeing a tremendous value and multiplied return on investment with taking such a relevant approach. They need to recognize that real insights from analytics will not be possible without collecting detailed, relevant and useful information about customers which can be converted into real time business intelligence. It’s also extremely critical to the success of the approach to have all customer-facing agents, representatives, managers and others to subscribe to the same attitude and approach when dealing with the customers.
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