24/06/2016
Discover, analyze, and combine customer experiences and successfully reflect them into strategy
Purpose of the text analysis
Recognize relevance, assess the situation and act purposefully
The solution uses the Natural Language Processing (NLP) to „understand” facts, sentiments and their context.
The barriers of otherwise isolated data silos can be overcome and joint analysis of structured and unstructured information (text flow) enabled.
The relevant information will be detected, extracted, and semantically enriched with company-specific metadata. Purpose: creation of customer or product-specific documentation to ensure the end-to-end management using workflow engine.
NLP allows to extract information about interesting entities and their relationships in order to derive precise and relevant RDF-Triples (Subject Predicate Object). In this way, the causes of events can be determined – the answer to the question of "why something happens" – in order then to act
targeted and appropriate to the situation.
The new chances
The early discovering of new trends and the correct action towards the changed customer behavior.
Industrialization of processes and benchmarking (Best Practice incl. KPI).
Linking macro-analysis with micro-analyses for improved understanding of natural and human-caused risks.
Macro-analyses: Identification of trends and patterns for the determination of the strategy and methodology (discover new insights about the opportunities, behavior, performance, etc.)
Micro-analyses: Knowledge about single customers or support of single activities, like diagnoses, assessments and consultations.
Ability to discover operational challenges and opportunities in real time and to answer them proactively.
Semantics as a Solution
Semantics are based on relationships between data and are therefore ideal tool for linking and searching for complex structured and unstructured data with the standard query SPARQL.
With semantic solutions, all sources are linked and isolated data silos avoided.