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The most important AI technologies, that are relevant for analyzing customer feedback, fall in the area of natural language processing (NLP) and machinelearning. The situation when B2B CX was very distant from B2C CX has been rapidly changing. Both groups of technologies can be utilized to make analytics more actionable.
Whether you work in B2B or B2C, CX is the sum of all thoughts, feelings, experiences and reactions the customer is left with. CXM (Customer Experience Management) focuses on using strategic methods for influencing the customer experience positively. CX is the customers’ experience of the product or service itself.
The most important AI technologies relevant for analyzing customer feedback fall in the area of natural language processing (NLP) and machinelearning. But machinelearning technologies can also help you to move from diagnostic to predictive analytics: if I fix this issue in my customer experience, how much will my churn decrease?
Add in the fact some B2B, and certainly B2C companies, are still struggling with data management. Real-time lead scoring Using AI and machinelearning, a CDP can identify leads are most likely to convert, those who need more nurturing and those who are likely to churn. They are also cautious about sharing their data.
The most important AI technologies relevant for analyzing customer feedback fall in the area of natural language processing (NLP) and machinelearning. But machinelearning technologies can also help you to move from diagnostic to predictive analytics: if I fix this issue in my customer experience, how much will my churn decrease?
He specializes in customer success, customer experience, SaaS start-ups, B2B & B2C marketing strategy, and e-commerce. Peter Lavers – B2C and B2B Customer Experience & Customer Management Influencer. Currently, he is serving as the Director of Customer Success at Kustomer and an Advisor at The Success League.
Unlike their scripted predecessors, these autonomous agents use natural language processing (NLP) and machinelearning to simulate human-like interactions while solving customer queries effectively.
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