Essay Example on Approach to the research into customer satisfaction

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Abstract The paper focuses on approach to the research into customer satisfaction based on a detailed analysis of consumer reviews written in natural languages using Artificial Intelligence methods such as Text Mining Aspect Sentiment Analysis Data Mining and Machine Learning The results proves the efficacy of the proposed approach for decision support in product quality management and argues for using it instead of classical methods of research Introduction Historically the assurance of quality is based on a process approach of a quality management system The methodology focuses on interaction of the company and the customer in the process of product production and consumption To improve the product quality the model incorporates feedback The feedback is expressed in form of customer reviews of the product quality To gauge customer satisfaction International Quality Standard suggests some methods personal interviews phone interviews discussion groups mail surveys online research and survey These methods have extensive drawbacks like generation of humongous amount of manual work which increases the research costs and hinders the continuous monitoring of customer satisfaction which in turn influences the managerial decision making process as it is dependent on the arrival rate of up to date information about customer opinions

These drawbacks made organization to focu on approach such as AI Big data for Analytics Big data refers to approaches tools and methods to handle structured and unstructured data which is humongous diverse and is effective in the conditions of continuous growth The analysis operations needs to be preformed on large amount of data It is based on the concept of four Vs Volume Variety Velocity and Value The transition to new technologies by the organization to work with a large volume of data is an indicator of readiness which is referred to as Bigd If Bigd exceeds 50 then Big Data analysis technologies should be implemented Volume refers to accumulated data parameter Velocity computation is based on two values the first details the capture and processing of data in near real time the second is the rate of data accumulation in the organization Variety collection of data from multiple sources in which may be in multiple formats Value determination is done by experts and it ranges from 0 to 1 to prioritise the source of the data Big Data technologies aren t efficient for evaluation of the quality of services Various organizations has proposed a methodology to evaluate reviews based on Artificial Intelligence AI AI based approach to Quality Management 



The approach is based on four steps Firstly reviews collection cleansing and loading is done Secondly the analysis processing of the stored reviews is done by evaluating them based on emotional response Then qualitative and quantitative research is done which is based on decision trees where the sentiment is covered as a dependent variable Management decisions are carried on basis of this research Steps in AI based approach Applied AI Based Techniques 3 1 Data Collection The reviews are stored in XML structure It includes separate blocks for product name company and review with other blocks for additional information The reviews are stored in a review object which simplifies data collection The two key methods of reviews collection include taking reviews using API which are ready to use tools and another is data collection using web parsing refers to automated analysis using scripts 3 2 Sentiment Analysis After data collection the processing is done using text mining tools Sentiment analysis evaluates emotional value of author s opinion about product satisfaction in relation to the object in the text Three analysis approach are linguistic statistical and combined The linguistic approach focuses on rules and sentiment vocabulary with the drawback of no quantitative evaluation of the sentiment Statistical approach covers supervised and non supervised machine learning

Combined approach is the amalgamation of the first two approaches Currently supervised machine learning based on Bayesian classification and Support Vector Machines is used which is based on Lemmatization which refers to reducing the words to their basic format 3 3 Aspect Sentiment Analysis It allows evaluation of general customer product An aspect refers to characteristics attributes qualities properties of the product There are two stages in analysis aspect identification and determination of the sentiment of the comment An algorithm for the same was made First stage 1 Extraction all nouns S from set of reviews D 2 Count the frequency of words from set of reviews D 3 Count the difference between the counted frequencies 4 Sort set of nouns S in descending order and then division of nouns S into aspect groups Second Stage 1 Divide of set of reviews into sets of sentences 2 Classification of sentiments 3 Check sentence condition if sentence is based on negative or positive sentiment and contains at least a noun from the aspect group then is labelled as an opinion

Representation of the results of Sentiment and Aspect is done in textual form 3 4 Decision Trees It is an algorithm for data processing obtained from Sentiment Analysis and Aspect Sentiment Analysis The key characteristic of the algorithm is data mining to support decisions in product quality management For the realisation an intelligent data analysis tool is used the results of which are easily comprehensible as they are represented by means of Boolean logic The algorithm explains what product aspects influence customer satisfaction and in what way The decision tree model allows us to consider the influence of not only the separate sentiment comments on aspects but also of their mutual presence or absence in the context on customer satisfaction It enables us to detect the most significant product aspects that are essential for the customer It makes it possible to evaluate experimentally customer satisfaction in dependence on satisfaction with different product attributes which allows to distribute the company s budget effectively to maintain a high product quality The significance of aspects group shows how much the sentiment of a review depends on the sentiment of the aspect group


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