The landscape of the Internet is continually evolving. This creates huge opportunities for different industries to optimize vital channels online, resulting in various-forms of new Internet services. As a result, digital users are interacting with many digital systems and they are exhibiting dynamic behaviors. Their shopping behaviors are drastically different today than it used to be, with offline and online shopping interacting with each other. They have many channels to access online media but their consumption patterns on different channels are quite different. They do philanthropy online to help others but their heterogeneous motivations and different fundraising campaigns leads to distinct path-to-contribution. Understanding the digital user’s decision making process behind their dynamic behaviors is critical as they interact with various digital systems for the firms to improve user experience and improve their bottom line. In this thesis, I study digital users’ decision journeys and the corresponding digital technology firms’ strategies using inter-disciplinary approaches that combine econometrics, economic structural modeling and machine learning. The uncovered decision journey not only offer empirical managerial insights but also provide guideline for introducing intervention to better serve digital users.

The travel distribution industry is growing. While traditional distribution channels such as online travel agencies and physical stores are decreasing in revenues, metasearch companies are receiving greater attention from consumers. However, metasearch companies face challenges even with an increasing market. Offering a proposition with a business model that revolves around pay per click and advertisements, you are in need of large amount of traffic. To understand the consumer behaviour has never been more critical. It is about increasing the ability to create a rich customer experience. In order to do so, companies are in need of understanding how to interact with consumers. The interaction is mainly occurring through touchpoints. Accordingly, the aim of this study is to investigate how the current identified most relevant digital touchpoints are having impact on the consumers opinion of metasearch websites in the travel distribution industry. By doing so, we contribute to marketing theory, method and practices. The importance of certain touchpoints and to find out if they have the same relevance when the purchase itself is excluded. Focus is being towards factors that metasearch companies see as undiscovered. A quantitative study was conducted with a sample of 148 respondents. The result not only gave new insight in terms of touchpoints relevance in metasearch industries but also a theoretical ground for future research.

In today's dynamic marketplace, understanding consumer behavior has become increasingly complex, especially regarding high-involvement purchases. Nevertheless, it is just as important for both theorists and practitioners to understand. It is known that word-of-mouth (WOM) is one of the most influential factors in consumer behavior during the consumer decision journey (CDJ). Despite this, there is currently a lack of understanding regarding how consumers use WOM during the CDJ and whether different types of WOM are used in different ways. Researchers have asked for more research in the field for over a decade. The research gaps in the literature and the demand for an increased understanding within the literature laid the foundation for this study and the research question: How and why do consumers make use of different types of word-of-mouth during the consumer decision journey within high-involvement purchases? In addition to the research question, the study also aims to expand the understanding of why consumers use WOM during the CDJ. To further investigate the research question and purpose, we performed a qualitative study where we conducted semi-structured interviews with six consumers. The collected data was analyzed through an inductive content analysis which resulted in a data structure consisting of 18 first order concepts, seven second order themes, and four aggregate dimensions. The study's data structure formed the basis for the inductive bottom-up theorizing, which culminated in a theoretical model where consumer's use of WOM is integrated into the CDJ. The model visualizes how it can be assumed a typical consumer uses different types of WOM throughout the different phases of the CDJ, as well as the consumer's motives behind their use of WOM. The empirical findings emphasize that consumers seek different attributes in the type of WOM during various phases of the CDJ, whereupon they use different types of WOM based on various motives. We managed to identify six different motives for consumers' use of WOM, and these motives relate to the different phases in the CDJ. These findings, among others, are included in the model. The study's theoretical model contains several new unique findings that extend today's existing understanding of consumers' use of WOM which has resulted in theoretical, practical and societal contributions. The study contributes to closing the research gaps and enabling further research in the field of literature.

This paper aims to investigate whether or not it is possible to identify users who are about change provider of service with machine learning. It is believed that the Consumer Decision Journey is a better model than traditional funnel models when it comes to depicting the processes which consumers go through, leading up to a purchase. Analytical and operational Customer Relationship Management are presented as possible fields where such implementations can be useful. Based on previous studies, Random Forest and XGBoost were chosen as algorithms to be further evaluated because of its general high performance. The final results were produced by an iterative process which began with data processing followed by feature selection, training of model and testing the model. Literature review and unstructured and semi-structured interviews with the employer Growth Hackers Sthlm were also used as methods in a complementary fashion, with the purpose of gaining a wider perspective of the state-of-the-art of ML-implementations. The final results showed that Random Forest could identify the sought-after users (positive) while XGBoost was inferior to Random Forest in terms of distinguishing between positive and negative classes. An implementation of such model could support and benefit an organization’s customer acquisition operations. However, organizational prerequisites regarding the data infrastructure and the level of AI and machine learning integration in the organization’s culture are the most important ones and need to be considered before such implementations. / I det här arbetet undersöks huruvida det är möjligt att identifiera ett beteende bland användare som innebär att användaren snart ska byta tillhandahållare av tjänst med hjälp av maskininlärning. Målet är att kunna bidra till ett maskininlärningsverktyg i kundförvärvningssyfte, såsom analytical och operational Customer Relationship Management. Det sökta beteendet i rapporten utgår från modellen ”the Consumer Decision Journey”. I modellen beskrivs fyra faser där fas två innebär att konsumenten aktivt söker samt är mer mottaglig för information kring köpet. Genom tidigare studier och handledning av uppdragsgivare valdes algoritmerna RandomForest och XGBoost som huvudsakliga algoritmer som skulle testas. Resultaten producerades genom en iterativ process. Det första steget var att städa data. Därefter valdes parametrar och viktades. Sedan testades algoritmerna mot testdata och utvärderades. Detta gjordes i loopar tills förbättringar endast var marginella. De slutliga resultaten visade att framförallt Random Forest kunde identifiera ett beteende som innebär att en användare är i fas 2, medan XGBoost presterade sämre när det kom till att urskilja bland positiva och negativa användare. Dock fångade XGBoost fler positiva användare än vad Random Forest gjorde. I syfte att undersöka de organisatoriska förutsättningarna för att implementera maskininlärning och AI gjordes litteraturstudier och uppdragsgivaren intervjuades kontinuerligt. De viktigaste förutsättningarna fastställdes till två kategorier, datainfrastruktur och hur väl AI och maskininlärning är integrerat i organisationens kultur.

I dagens värld där digital och teknisk utveckling rör sig snabbt tvingas företagen att skapa dynamiska affärsmodeller anpassande efter dynamiska marknadsförutsättningar. Kunderna blir allt mer digitala, förväntar sig realtidstjänster och är mindre öppna för komplikationer. Linjerna mellan olika marknader som IT och telekom blir all mer oklara utvecklingen av ICT och IOT kommer att förändra vardagen för både B2B och B2C kunder. Denna utveckling påverkar olika marknader på olika sätt och i olika takt. Telekombranschen står inför en global utveckling där konkurrerande företag definierar sig som digitala tjänsteleverantörer samt skapar samarbeten och digitala marknadsplatser vilka erbjuder tjänster som sträcker sig utanför sitt klassiska affärsområde. Inför denna utveckling med nya digitala affärsstrategier och nya försäljningsstrategier är nyckeln att vara en del av den tekniska utvecklingen, dessutom vara en del av nästa generations telekomoperatörer. Möjligheten att ompositionera sig som digital tjänsteleverantören kommer med strategiska utmaningar och nuvarande organisationer måste utvärderas för att bilda en strategi angående hur man ska konkurrera och lyckas i den framtida marknad som uppstår. Detta har gjorts i form av en fallstudie som utförts inom en av de största teleoperatörerna i världen. Bolaget valt är en av ledarna erbjuder både mobila och fasta tjänster med en bred produktportfölj. Studien är dock koncentrerad till en division av bredband och digital-TV, men som studien visar blir förmågan att röra sig över gränserna allt viktigare. Den kvalitativa studien innebär empirisk forskning genom att intervjua hela kedjan av beslutstagare inom företaget. Resultaten tyder på att företaget i fråga visar incitament till att bli en digital tjänsteleverantör och att avancera i sin digitala försäljningsstrategi och digitala kommunikation mot både B2B och B2C kunder. Dock måste företaget att avancera i flera områden av betydelse för att bli en dynamisk digital tjänsteleverantör. Skapa digital kommunikation, förlänga värde-propositioner, skapa innovativa samarbeten samt investera mot ny kärnteknologi för att flytta bort från den prispressning som är associerad med dagens telekom marknad. Resultatet av studien har innebörd ur såväl teoretiskt som ett industriellt perspektiv. Ur en teoretisk synvinkel, bidrar resultaten till befintlig forskning inom hur digitaliseringen påverkar traditionella affärsmodeller och hur bolag bör omformas efter alltmer digitala marknader och kunder. Ur industriell synpunkt bidrar studien med interna och externa faktorer i hur man ska hantera den allt mer digitala telekommarknaden samt viktigaste förbättringsområden. / In today’s world the digital and technological development are moving fast forcing companies to create dynamic business models following the new incentives in the market. Customers are becoming increasingly digital, expecting real time services and are less open towards complications. The walls between different markets such as IT and telecom are becoming increasingly unclear. The development of ICT and IOT will change the everyday life for both B2B and B2C customers. This development is affecting different markets in different ways and in different pace. The telecom industry is facing a global development where competing companies are rebranding and repositioning themselves as digital service providers creating collaborations offering services stretching outside of their classical business area. Facing this development, a new digital business strategy and a new sales strategy is key to be part of the technological evolution, furthermore to be part of the next generation telecom operators. The opportunity as moving toward a position becoming a digital service provider is a strategic shift and current organizations need to be evaluated in order to form a strategy regarding how to compete and succeed in the market. This has been done in a shape of a case study performed in one of the biggest telecom operators in the world. The company chosen is one of the leaders providing both reliable and secure services with a broad product portfolio. The study, however, is concentrated towards the division of broadband and digital TV, but as the study proves, the ability to move across boundaries is becoming increasingly important. The qualitative study involves empirical research interviewing the entire chain of decision makers within the company. The results indicate that the company in question shows incentive into become a digital service provider and to advance in their digital sales strategy and digital communication towards both B2B and B2C customers. However, the company needs to advance in several crucial areas of importance to become a dynamic digital service provider. Create digital communication, extend VPs, create innovative collaborations, capex toward new core technology to move away from the price pressing business of providing a commodity. The findings of the study have implication in both theoretical and an industrial perspective. From a theoretical point of view, the findings contribute to existing research on how digitalisation affects traditional business models and how to reshape the company after increasingly digital markets and customers. From an industrial point of view, the study contributes with internal and external factors in how to address the increasingly digital market with the main areas of improvement

This study investigates the effects of the digital marketing channels Search engine optimization (SEO) and SEM, focusing on Google Ads, in the context of the consumer decision funnel in the Swedish market. This was done through a single-case study with a medium-sized digital marketing bureau in Sweden. Our research was summarized in a conceptual framework that aims to create a foundational understanding of best practices and strategies for companies to establish a robust and profitable online presence. The research shows that SEO and SEM has different main focuses within the digital marketing landscape where SEO has a more holistic approach and covers areas further up in the consumer funnel, and SEM operated more targeted with a high focus on measurable conversions. However, our research also finds how the respective channels both have the capacity to be used in all parts of the funnel. Concepts such as budget, strategy, timeline, and consumer behavior are key concepts within our research. The research highlights the importance of tailoring a digital marketing strategy to a company’s specific goals and circumstances. This research takes such aspects into consideration, and strategies depending on budget constraints and company size are explored separately. This paper thus provides marketers with a foundational understanding of how to approach digital marketing, and how to best tailor a digital marketing strategy to align with company goals. Effectively combining SEO and SEM creates a great opportunity for companies to establish a good online presence, which in today's society serves as a very effective media to reach out to consumers.

Title:  The effects of online third-party opinions toward Consumer Purchasing Decision on cosmetics products in Thai market Seminar date: June 4th , 2012 Course: Master thesis in International marketing, 15 credits Purpose: The overall purpose of this research is to explain the understanding of the effects of online third-party opinions toward consumer purchasing decision process on cosmetics products in Thai market. This includes the investigation of effective used of online third-party opinions with regards to source credibility and product involvement, specifically toward cosmetics products. Theoretical framework: The theoretical framework of this research is based on literature concerning online third party opinion, consumer decision journey (CDJ), product involvement and source credibility. Methodology: Both quantitative and qualitative method was applied. And thus a questionnaire with 147 respondents on Thai market and two interviews of expert marketers were conducted. The respondents for questionnaire are Thai women with specific age range and criteria. Conclusion: The online third-party opinion plays the important role in nowadays in the marketing perspective. And it does affect the consumer purchasing decision process both pre-purchase and post-purchase stage. However, it mostly affects in Consider and Evaluation Stage. With regards to the product involvement and source credibility applying to cosmetics products, these two variables affect to the use of online third-party opinion. Online third-party opinion works best with high involvement product. However, low involvement product also be considered as suitable to use with online third-party opinion. For source credibility, both online expert and consumer reviews perform better when using with high involvement product comparing with low involvement one.