NLP and conversational analytics focus on customers’ needs, perspectives, and behavior

As a result of digitization, companies from all industries have more data than ever at their disposal. This data includes information about their customers’ needs, perspectives, and behaviors. The challenge is to use modern technologies such as Natural Language Processing (NLP) and conversational analytics, together with artificial intelligence (AI) and machine learning (ML). These technologies help to raise and evaluate this wealth of data to design a customer journey with a consistently positive experience. Companies must make data-based decisions regarding content offerings to identify trends and monitor campaign progress. They can also detect mood swings at an early stage. Conversations with customers are compared with their actual behavior. This comparison helps to derive strategies for the target groups and to see the customer experience from the perspective of the customer.

In the future, marketers could be relieved of decision-making regarding the optimal subject line of an email or even the entire campaign content. Natural Language Processing (NLP) captures natural language and processes it computer-based with rules and algorithms. NLP uses various methods from linguistics and combines them with modern computer science and artificial intelligence (AI). In email marketing, appropriate solutions can propose sentences, words, or phrases. These proposals work particularly well within a certain content paradigm or for a certain target group. This is especially true in relation to economic conversions or human reading and consumption habits. AI holds an almost infinite potential for use in marketing. This includes assessment of customer potential through neural networks and highly intelligent chatbots through natural language processing. Additionally, automated target group and sales analysis through deep learning is possible. But while new insights and tools are constantly emerging in the AI context, their use in practice still lags far behind.

Fortunately, not all industries are “AI-shy.” This is especially true in the B2C...An omnichannel strategy does not consider the channels in isolation. Rather, it analyzes the entire feedback of all digital touchpoints in one context. Insights are gained from interactions across all core channels, including CRM, social media, and chat conversations. Whether during registration, trial subscription, program selection, conclusion of a contract or payment options, these digital touchpoints influence the customer journey. This influence provides all teams involved with a context-related understanding. In this way, strengthening internal company communication contributes to process improvement.