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RESEARCH
ANALYSIS
TRENDS

NLP and conversational analytics focus on

customers' needs, perspectives, and behavior

As a result of digitization, companies from all industries But while new insights and tools are constantly
have more data than ever at their disposal: about their emerging in the AI context, their use in practice still
customers' needs, perspectives, and behaviors. The lags far behind.
challenge is to use modern technologies such as
Natural Language Processing (NLP) and Fortunately, not all industries are “AI-shy”, especially
conversational analytics, together with artificial not in the B2C sector, but B2B industry, like brand
intelligence (AI) and machine learning (ML), to raise manufacturers since companies in these industries
and evaluate this wealth of data in order to design a want to build first a solid database before dealing with
customer journey with a consistently positive further trend topics. Here too, the focus is on
experience, i.e. make data-based decisions regarding automating the very own marketing processes,
its content offerings, identify trends, monitor the improving existing data quality, and breaking down data
progress of campaigns or detect mood swings at an silos. Anyone who is in a dynamic and highly
early stage. Conversations with customers are competitive market not only has to meet customer
compared with their actual behavior to derive strategies expectations, but create added value in a highly
for the target groups and to see the customer competitive environment, too. NLP and AI-supported
experience from the perspective of the customer. analysis technologies can e.g. interpret sentences and
reveal the emotional reaction of customers as well as
In the future, marketers could be relieved of decision- discrepancies and tensions in unstructured customer
making regarding the optimal subject line of an email or feedback.
even the entire campaign content. Natural Language
Processing (NLP) captures natural language and An omnichannel strategy does not consider the
processes it computer-based with rules and algorithms. channels in isolation, but rather analyses the entire
NLP uses various methods from linguistics and feedback of all digital touchpoints in one context. The
combines them with modern computer science and insights are gained from the interactions across all core
artificial intelligence (AI). In email marketing, channels, including CRM, social media, and chat
appropriate solutions can propose sentences, words or conversations. Whether during the registration, trial
phrases that work particularly well within a certain subscription, program selection, conclusion of a
content paradigm or for a certain target group: e.g. in contract or the payment options, the influence of the
relation to economic conversions or human reading and individual digital touchpoints along the customer
consumption habits. AI holds an almost infinite potential journey provides all teams involved with a context-
for use in marketing: assessment of customer potential related understanding. In this way, strengthening
through neural networks, highly intelligent chatbots internal company communication contributes as well to
through natural language processing, or automated process improvement.◊
target group and sales analysis through deep learning.
By Daniela La Marca
May 2020: Natural language processing & conversational analytics: data quality beyond reproach 22