Consumer journey analysis led to efficient marketing implementation. A journey represents a path of steps and interaction between consumer and service units at each touchpoint. Dissatisfaction in the touchpoint, causes a negative effect to retain a customer. Previous studies always constructed the journey maps relied on the narrative approach. According to use Google, consumers always face massive websites to access, which is a pain point in the journey. Improving consumer buying, led to the research aims: identifying consumer needs, and reducing SEO pain-point using content relevance indexing. The data (social media posts from the Thai beauty communities in the year 2020) is analyzed and has found that there are two need types: curative and preventive. The study can segment the 150 websites into four groups which reduce the search space. Moreover, the significant words from the wrapping technique can use to create keywords in the homepage introduction that are matching the products to consumer needs.

For companies to retain customers and ensure effective management-level resolution, they need to anticipate customer churn and determine the root cause of complaints. To achieve this, analyzing personalized complaints from the customer's perspective is crucial. This research advocates for a multidisciplinary approach that combines language behavior, relevance feature extraction, feature weighting, and sentiment analysis to extract the underlying problem in real time. Applying this approach to the CFPB database sample yielded an accuracy rate of 82% and a system validity of 75%, which can help improve customer service and protect consumers in the financial and other service industries. By addressing individual customer issues that cause dissatisfaction, businesses can enhance customer satisfaction and retention levels. Thus, by analyzing complaints from a personalized standpoint, companies can identify the root cause of the problem, improve their services, and establish stronger customer relationships.

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For companies to retain customers and ensure effective management-level resolution, they need to anticipate customer churn and determine the root cause of complaints. To achieve this, analyzing personalized complaints from the customer's perspective is crucial. This research advocates for a multidisciplinary approach that combines language behavior, relevance feature extraction, feature weighting, and sentiment analysis to extract the underlying problem in real time. Applying this approach to the CFPB database sample yielded an accuracy rate of 82% and a system validity of 75%, which can help improve customer service and protect consumers in the nancial and other service industries. By addressing individual customer issues that cause dissatisfaction, businesses can enhance customer satisfaction and retention levels. Thus, by analyzing complaints from a personalized standpoint, companies can identify the root cause of the problem, improve their services, and establish stronger customer relationships.