1nlpA company that could read the minds of its customers would have ensured its business success forever, but the considerable challenges that companies face in the digital age show that this isn’t easy to achieve. Not only do the demands of customers constantly change, providers can’t adapt their existing processes quickly enough to meet their customers growing needs and expectations. Those who have set themselves the task of building intelligent processes to improve the customer experience often whether know where to start collecting necessary data nor how to process them smartly. New digital technologies are constantly raising the bar for customer experience.

Never before have customers been so fast and well informed and extensively networked as today. Hence, they expect companies to be the same and to be where they are instead of waste time looking for the right offers and information. In other words, they demand their customer experience to be intuitive and seamless. Without saying, only those who align their business with the customer experience through intelligent processes in the front and back office are competitive and future-proof.

This requires the collection and processing of large amounts of different data, which is easier said than done: according to a survey by Accenture and HfS Research, 50 to 90% of a company's data is unstructured and inaccessible to around 80% of the company’s employees. But only by using customer data, together with AI and other complementary technologies, companies can reach a level of maturity that enables them to create a corresponding digital customer experience - from onboarding to customer service.

A "digital first" approach should be pursued and proactive strategies developed to always be one step ahead of customers’ expectations. This requires smooth internal processes that can be implemented, for example, via an intelligent automation platform within the company. Known as "intelligent operation”, such a platform uses complementary AI-based technologies, to make data analyzable and usable, and to incorporate the knowledge gained from this business processes.

An intelligent automation platform can combine different technologies to make processes more effective and efficient, and the following listed technologies show how companies can improve their customer experience through technological support:

  • A so-called entity extraction identifies information objects that are referred to in the text automatically with the help of natural language processing (NLP) and the analysis of context data. NLP encompasses various linguistic methods and modern techniques and algorithms such as artificial intelligence (AI), to capture and process natural language. Entity extraction can help determine the intent of the incoming customer request, enter it into the system, and forward it to the department in question within minutes instead of hours. This relieves customer service, reduces processing times, and offers the customer an overall better service experience.
  • The sentiment analysis also works with NLP algorithms and AI to process large amounts of unstructured data. In this way, companies can find out how customers think about products and services or how they rate the service. This technology enables marketing experts to determine the emotional response of customers in real time via social media and other digital channels and helps to make campaigns more effective, messages more personalized and the customer experience overall better. However, sentiment analysis requires constant monitoring of how the measures implemented are received by the target group and adjustments must be made accordingly.
  • Data extraction uses NLP and machine learning to identify valid information from various data sources, extract it, and translate it into a data record for use in an application. Valid information is information that is useful, relevant, or meaningful for a particular purpose. The self-learning effect makes the technology increasingly intelligent, and with it the business processes it supports. The principle of personalization works in this way: when a customer interacts with a website or app, data is created that - processed by AI-based data extraction - serves as the basis for personalized content and recommendations. When the same customer opens the website or app again, he/she receives relevant content and suggestions based on the customer’s previous actions. This automated familiarization is the basis for a successful customer experience.
  • Cognitive capture goes beyond simple optical character recognition (OCR), rather enables the recording and understanding of documents, no matter via which channel and in which format they arrive: forms, contracts, texts and images from a wide variety of sources can be analyzed for the extraction of entities and moods. This type of unstructured data is a treasure trove for those who understand the core of the challenges and want to quickly identify and respond to emotions in order to improve the overall customer experience.
  • Robotic process automation (RPA) uses robots to automate repetitive, data-driven activities. The resulting ability to integrate diverse data from websites, online portals and applications increases productivity and provides a solid information base for decision-making. Automation frees employees from repetitive tasks so that they can spend more time on more qualitative work, such as customer care and individual problem solving that improves again the customer experience.
  • Advanced Analytics offer consistent transparency of the systems and processes. Since all data is integrated in a single platform, decision-makers receive a holistic and always up-to-date view of the entire company. The ability to analyze data in the context of business processes gives them a deeper understanding of how customers interact with the company. Real-time data and analysis provide the insights needed to quickly adapt to changing customer needs. Businesses can move with their customers instead of wondering where they went.

In a nutshell: if you succeed in becoming a data-driven company and transforming the customer experience, you are well prepared for the future.

By Daniela La Marca