Today’s business strategy is about integrating new knowledge and developing a comprehensive plan for success. According to a McKinsey study, companies that use customer analytics extensively are more likely to generate above-average profits. Without stopping there, they also outperform their less analytics-oriented peers, stay in the lead throughout the customer lifecycle, and enjoy far superior customer loyalty. How exactly does analytics help businesses?
Much of the credit for this success is attributed to companies’ responsiveness to customer needs and their focus on establishing customer-relevant systems and guidelines. Analytics provide information about customer preferences to companies, who tailor their content and messages to remain relevant to customers and wait for a timely opportunity to make offers that are tailored to the wishes of their customers. They use their insights to drive better, more relevant and valuable interactions, turning even new customers into loyal ones, so they keep coming back for more, again. They also preserve the unwavering loyalty of former customers through these measures.
Important ways that companies remain relevant to customers include the following:
Chance: The time to establish relevance is when the customer shows interest in your product and not at any other time. Your sales plans, goals, and metrics are irrelevant to a customer. Present your product when a customer wants something similar and sit back to watch the deal close.
Personalization: Use analytics to understand a customer’s decision journey mapping, understanding opportunities and areas of friction with customer interests.
Extrapolation: Extrapolate the information provided by analytics to cover your customer demographics with a high level of granularity, using a wide range of attributes such as behavior, demographics, location, age, or even the customer’s stage in the purchase process. Use them to create personalized messages that speak only about what they are looking for, down to a color or size.
Segmentation: Use data to define customer segments using broad criteria and drill down to make your message personalized and relevant to each group by its characteristics and attributes. These could be thank you notes, requests for comments, new offers for similar products that offer you a special discount, or other personalized incentives.
Employee orientation: Companies need to train and guide their employees to provide a personalized experience to customers, whether it is providing a service or responding to an inquiry. They must be willing to learn and be flexible in taking their learning from one customer interaction to another, to revise their approach.
Understand the customer’s intent: Successful companies learn to detect positive signals of customer intention or negative signals of their refusal to engage, using their behavior. This ability to detect a customer’s intentions and read them correctly qualifies an insurer for success. Today, insurers leverage third-party data, which provides a deeper insight into customer health needs, lifestyle choices, and risky behavior, such as recreational activities, travel options, or even weight, to decide how to adapt a policy to the client’s needs. particular needs. Current data can help companies anticipate intent, using predictive analytics based on previous or related purchases made by other customers that led them to purchase a specific next product, fostering upsell offers and initiatives.
Reward clients for their volunteer data: Today’s customers tend to disclose data voluntarily and without any incentive. Companies are happy to offer gifts and rewards to customers who are willing to share data that reveals their priorities, habits, and tastes.
Customers marked with upsell or cross-sell: Brands treat high-value customers differently. Calling customers receive a wide variety of options and choices, as calling agents offer relevant products and services, or even an upgrade.
Most companies are realizing tremendous value and a multiplied return on investment by taking such a relevant approach. They must recognize that it will not be possible to obtain real information from analytics without collecting detailed, relevant and useful information about customers that can be converted into real-time business intelligence. It is also extremely critical to the success of the approach that all agents, representatives, managers, and others who deal with the customer subscribe to the same attitude and approach when dealing with customers.
