Edukacja to też E-commerce: 3 tematy na licencjat z marketingu uczelni wyższych (CX, Analityka i Strategia)

Zastanawiasz się nad tematem pracy licencjackiej? Szukasz zagadnienia, które połączy twardą analitykę biznesową, zarządzanie doświadczeniami klienta (CX) i realia rynkowe? Jako wykładowca akademicki i praktyk biznesu, często widzę, jak studenci uciekają w stronę ogólnikowych i wtórnych tematów. Tymczasem tuż pod Waszymi nosami rozgrywa się fascynująca, oparta na danych walka o klienta. Mowa o rynku szkolnictwa wyższego.

Zarządzanie doświadczeniem kandydata, a później studenta, wymaga dogłębnego zrozumienia Customer Experience Management (CXM). Jak pisałem w mojej publikacji “Customer Experience Management in Era of AI”, wygrywają te organizacje, które potrafią personalizować komunikację w czasie rzeczywistym w oparciu o dane. Dotyczy to w równym stopniu sklepów internetowych, jak i uniwersytetów.

Poniżej przygotowałem dla Was 3 propozycje tematów prac licencjackich z digital marketingu. Najlepsze z tych prac chętnie opublikuję tutaj, na łamach mietwood.com.

Dlaczego warto badać marketing instytucji edukacyjnych?

Zanim przejdziemy do konkretów, musimy spojrzeć na uczelnię przez pryzmat wskaźników biznesowych. Wdrożenie takiego myślenia do pracy dyplomowej to gwarancja najwyższej oceny.

• Student to Klient (o wysokim LTV): Wskaźnik Customer Lifetime Value (LTV) w edukacji jest ogromny. Obejmuje nie tylko czesne za studia I i II stopnia, ale także studia podyplomowe i MBA.
• Decyzja zakupowa jest złożona: Cykl decyzyjny (Customer Journey) trwa miesiącami, angażuje emocje, logikę i często osoby trzecie (rodziców). To idealne środowisko do badania wielokanałowych punktów styku (omnichannel touchpoints).
• Łatwy dostęp do danych: Strony uczelni są ogólnodostępne, a narzędzia takie jak SimilarWeb czy Senuto pozwalają na głęboki audyt ich działań digitalowych bez posiadania wewnętrznych dostępów.

Architektura Customer Experience (CX) w procesie rekrutacji online. Analiza porównawcza wybranych warszawskich uczelni wyższych (UW, SGH, Akademia Leona Koźmińskiego)

Opis problemu badawczego

W dobie cyfryzacji, system rekrutacyjny (IRK/ISR) to najważniejszy punkt styku (touchpoint) na ścieżce kandydata. To wirtualny “koszyk zakupowy”. Z perspektywy zarządzania operacyjnego w e-commerce, proces ten powinien być maksymalnie bezbłędny, intuicyjny i wspierający. Praca ta skupia się na audycie użyteczności (UX) oraz całkowitym doświadczeniu kandydata (CX) podczas aplikacji na studia w Warszawie, porównując uczelnię publiczną (Uniwersytet Warszawski), uczelnię publiczną o profilu biznesowym (SGH) oraz lidera prywatnej edukacji biznesowej (Akademia Leona Koźmińskiego).

Jak przeprowadzić analizę (Data-driven approach)?

Nie opieraj się na subiektywnych odczuciach. Zbuduj matrycę punktów styku.

1. Mapowanie Customer Journey: Stwórz szczegółową mapę podróży kandydata od momentu wpisania w Google frazy “studia zarządzanie Warszawa”, aż po kliknięcie “Złóż aplikację”.
2. Ocena lejków konwersji: Policz, ile kroków (kliknięć) dzieli kandydata od znalezienia programu studiów do założenia konta rekrutacyjnego. Gdzie występuje największe ryzyko porzucenia procesu (tzw. drop-off rate)?
3. Audyt użyteczności (Heurystyki Nielsena): Przeanalizuj interfejsy systemów rekrutacyjnych pod kątem responsywności mobilnej, jasności komunikatów i łatwości nawigacji.
4. Badania symulacyjne (NPS / CSAT): Przeprowadź badanie symulacyjne wskaźnika Customer Effort Score (CES) – jak wiele wysiłku kosztowało by kandydatów przejście przez proces na tych uczelniach?

Przykład analityczny do pracy

Hipoteza: Uczelnie niepubliczne (ALK) posiadają krótszy, bardziej zoptymalizowany pod kątem mobile lejek konwersji (M-commerce approach) w porównaniu do rozbudowanych systemów uczelni publicznych (UW), co przekłada się na wyższy wskaźnik satysfakcji z procesu rekrutacji (CSAT) i niższy współczynnik odrzuceń na stronie lądowania.

Strategia Digital Marketing Mix jako narzędzie budowania przewagi konkurencyjnej na regionalnym rynku edukacyjnym. Studium przypadków uczelni lubelskich (KUL, PL, WSPA)

Opis problemu badawczego

Marketing Mix (tradycyjne 4P, czy zmodernizowane 7P) ewoluował. Dziś mówimy o cyfrowym miksie marketingowym, w którym kluczową rolę odgrywa content marketing, SEO oraz social media. Temat ten pozwala na zbadanie, jak uczelnie o różnym profilu pozycjonują się na hermetycznym, lokalnym rynku. Jak Katolicki Uniwersytet Lubelski (KUL) walczy o uwagę z uczelnią techniczną (Politechnika Lubelska) oraz nowoczesną szkołą niepubliczną (WSPA)?

Jak przeprowadzić analizę (Business Analytics)?

W tej pracy powinieneś wykorzystać ogólnodostępne narzędzia analityczne, by zamienić “miękki” marketing w twarde dane.

1. Analiza widoczności (SEO): Wykorzystaj narzędzia takie jak Senuto lub Ahrefs. Sprawdź, na ile słów kluczowych widoczne są w TOP10 poszczególne uczelnie. Jaki generują szacunkowy ruch organiczny (Organic Traffic)? To wskaźnik ich pasywnej siły pozyskiwania leadów.
2. Audyt Content Marketingu: Jak uczelnie prowadzą sekcje blogowe i informacyjne? Czy stosują strategię Inbound Marketingu (np. artykuły typu “Jakie studia po profilu mat-fiz?”), aby przechwytywać użytkowników na wczesnym etapie świadomości (Top of the Funnel – ToFu)?
3. Social Media Engagement Rate: Zamiast liczyć “lajki”, oblicz wskaźnik zaangażowania (ER – Engagement Rate). Kto tworzy lepszą społeczność? Czy WSPA zyskuje przewagę na TikToku pokazując kulisy życia studenckiego, podczas gdy KUL dominuje w formalnej komunikacji na Facebooku?

Przykład analityczny do pracy

Możesz przeprowadzić badanie sentymentu (Sentiment Analysis) komentarzy pod postami rekrutacyjnymi wybranych uczelni. Na tej podstawie udowodnisz, jak konkretny styl komunikacji wizualnej i tekstowej (Tone of Voice) wpływa na percepcję marki. Zwróć uwagę na spójność wielokanałową (Omnichannel) – czy doświadczenie kandydata przeglądającego profil Politechniki Lubelskiej na Instagramie jest spójne z tym, co widzi na oficjalnej stronie www? Wniosek może stanowić rekomendację optymalizacyjną dla działu promocji.

Podsumowanie

Pisanie pracy licencjackiej z marketingu nie musi sprowadzać się do nudnego przypisywania definicji Kotlera. Przemysł edukacyjny w Polsce przechodzi obecnie potężną transformację cyfrową. Instytucje te stały się platformami usługowymi, które muszą zarządzać potężnymi zasobami danych, optymalizować swoje lejki sprzedażowe i nieustannie poprawiać Customer Experience.

Jeśli zdecydujecie się na jeden z powyższych tematów, obiecuję Wam, że proces badawczy będzie nie tylko fascynujący, ale przede wszystkim dostarczy Wam “twardych” umiejętności pożądanych na współczesnym rynku pracy. Analityk, który potrafi przełożyć ruch na stronie www, wskaźniki użyteczności oraz dane z social mediów na realne rekomendacje biznesowe optymalizujące proces konwersji, nigdy nie będzie musiał martwić się o zatrudnienie.

Masz już pomysł na badanie? Zbierasz dane, ale utknąłeś przy ich interpretacji? Zapraszam do zgłębiania artykułów w sekcji Analityka Biznesowa na mietwood.com oraz do przesyłania draftów swoich najlepszych tekstów naukowych – najciekawsze analizy chętnie udostępnię w ramach gościnnych wpisów na blogu.

Powodzenia w badaniach!

Słowa kluczowe (Keywords): marketing edukacyjny, customer experience management (CXM), analityka biznesowa w edukacji, e-commerce, uczelnie wyższe, praca licencjacka marketing, user journey, marketing mix, konwersja (CR), optymalizacja lejka, LTV, churn rate, SGH, UW, KUL, Akademia Leona Koźmińskiego.

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AI Influencers Case Studies

Lil Miquela — The Pioneer
Created by Los Angeles startup Brud in 2016, Lil Miquela (Miquela Sousa) is widely credited with proving that virtual influencers could achieve mainstream commercial success. Before releasing a single sponsored post, Brud invested over a year building her persona — a 19-year-old Brazilian-American musician with strong views on social justice, digital identity and pop culture. This character depth proved critical: by the time brands approached Brud, Miquela had an audience that genuinely cared about her narrative. Her 2019 Calvin Klein campaign — shot alongside Bella Hadid — marked the inflection point for the entire industry, demonstrating that consumers would engage with a virtual personality in a luxury fashion context at the level of an A-list celebrity.

Aitana López — The Agency Model
Aitana López (link) represents the next evolutionary stage: a commercially motivated, generative-AI-built persona created explicitly to solve a business problem. The Clueless agency (Barcelona) built her in late 2023 after client campaigns were disrupted by unreliable human models. She was engineered from the outset with commercial viability in mind — pink hair, tattoos, fitness and gaming niche, Spanish-speaking audience, and a Fanvue subscription tier at €15 per month. Her success led The Clueless to pivot its core offering to an AI influencer-as-a-service model, building bespoke virtual personas for other brands — demonstrating the B2B extension of the concept. AI influencers.

Lu do Magalu — The Corporate Model
Brazilian retail giant Magazine Luiza launched Lu in 2009 as a virtual assistant. Over 15 years she evolved
into the world’s most-followed brand character, amassing over 30 million followers across platforms. Lu
simultaneously handles product reviews and customer service, demonstrating that AI influencers can function
as integrated marketing-plus-operations assets. Her ROI extends beyond marketing KPIs to include
measurable reductions in customer service load — a dual-function model increasingly adopted by retailers
globally.

Authenticity in Influencer Marketing: Why It Matters and How to Achieve It

Influencer marketing has become one of the most powerful tools in digital advertising, driving billions in brand collaborations worldwide. Yet, as the industry matures, a critical challenge has emerged: authenticity. Consumers increasingly demand genuine connections, while brands often prioritize reach and engagement metrics. This tension creates a paradox—how can influencers remain authentic while monetizing their content?

Recent research published in the Journal of Marketing (Duffek et al., 2025) explores this issue in depth, offering actionable insights for influencers, brands, and agencies. This blog post breaks down the theoretical foundations, key findings, and practical strategies from the study, helping you understand why authenticity is central to influencer marketing success. AI influencers.

The post AI influencers appeared first on Customer Experience Management.

Zarządzanie operacyjne w e‑commerce to zbiór działań, które pozwalają firmom internetowym sprawnie dostarczać wartość klientowi na każdym etapie jego kontaktu z marką. Obszar ten obejmuje planowanie, organizowanie i kontrolowanie procesów, które – w przeciwieństwie do tradycyjnych modeli biznesowych – są w dużej mierze zautomatyzowane, oparte na danych i wymagają natychmiastowej reakcji. W handlu online operacje zaczynają się już w momencie wejścia klienta na stronę i trwają aż do obsługi posprzedażowej, gdzie satysfakcja, czas reakcji i niezawodność systemów stają się bezpośrednim źródłem przewagi konkurencyjnej -obejrzyj fragment kursu tutaj.

W centrum zarządzania operacyjnego w e‑commerce znajduje się proces zakupowy klienta – od wyszukiwarki, przez kartę produktu i koszyk, aż po finalizację zamówienia. Każdy etap musi być zoptymalizowany pod kątem UX, szybkości działania i minimalizacji barier, które mogą prowadzić do porzucania koszyka. Kluczową rolę odgrywają tu także zaawansowane narzędzia wyszukiwania (autouzupełnianie, AI, optymalizacja wyników), personalizacja treści oraz segmentacja klientów, pozwalająca lepiej dopasować ofertę i komunikację do ich zachowań i potrzeb (obejrzyj fragment).

Równie ważnym filarem zarządzania operacyjnego w e‑commerce jest logistyka – zarówno jej część wewnętrzna (magazynowanie, zarządzanie zapasami, integracja z WMS/ERP), jak i zewnętrzna (kurierzy, automaty paczkowe, fulfillment, dropshipping). W dynamicznym środowisku zakupowym klienci oczekują wielu opcji dostawy i płatności, a błyskawiczna realizacja zamówień staje się nie tylko przewagą, ale standardem rynkowym. Coraz częściej sklepy sięgają po outsourcing logistyki, by skalować operacje bez konieczności rozbudowy infrastruktury.

Zarządzanie operacyjne w e‑commerce to również umiejętność radzenia sobie ze zwrotami i reklamacjami – obszarem, który bezpośrednio wpływa na doświadczenie klienta. Jasne procedury, przejrzyste formularze i szybkie działanie minimalizują koszty, a jednocześnie wzmacniają zaufanie do marki. Dopełnieniem całości jest analityka operacyjna: monitoring KPI, analiza porzuconych koszyków, dane z GA4, raporty ERP oraz narzędzia marketing automation. To dzięki nim firmy mogą stale usprawniać procesy, eliminować wąskie gardła i zwiększać konwersję (obejrzyj fragment).

Ostatecznie zarządzanie operacyjne w e‑commerce to nie tylko technologia, ale przede wszystkim sprawne zarządzanie procesami, zespołem i doświadczeniem klienta. W świecie szybkich zakupów online liczy się równowaga między efektywnością kosztową, jakością obsługi a elastycznością reagowania. Firmy, które potrafią połączyć te elementy, budują przewagę konkurencyjną opartą na szybkości, niezawodności i realnym zrozumieniu potrzeb użytkowników. To właśnie one definiują przyszłość e‑commerce – wspieraną przez AI, inteligentną logistykę i coraz bardziej zaawansowane modele biznesowe.

The post Zarządzanie operacyjne w e‑commerce – kluczowe fundamenty skutecznego handlu online appeared first on Customer Experience Management.

Author: Ahasbi Fatima Ezzahra (PhD Student UMCS & Researcher)

Customer Experience as a Lived Process

In much of the CXM literature, customer experience is framed as something that can be designed, mapped, and optimized. Innovation in tourism is often perceived through the lens of “Creative Destruction” (a nod to Schumpeterian theory), yet my doctoral research suggests a more nuanced reality. In tourism entrepreneurship, CX is rarely the result of a predefined strategy. Instead, it is shaped through trial, adjustment, and learning mirroring the entrepreneur’s own professional trajectory.

Tourism as a Living Laboratory for CXM

Entrepreneurs do not merely “design” an experience, they live it. Tourism offers a unique empirical ground for CXM analysis because experiences are not confined to isolated touchpoints. They unfold across time, space, and social interaction. In regions such as Marrakech–Safi, innovative tourism entrepreneurs reconstruct customer experience around meaning, authenticity, and human connection rather than standardized service scripts.

Innovation and CX: A Circular Relationship

One of the central findings of my research is the circular relationship between innovation and customer experience (CX). Innovation does not always precede experience; very often, it is the result of experiential friction moments where expectations, emotions, or values are misaligned. CXM, in this sense, becomes a diagnostic lens rather than a performance metric. Tourism Innovation.

My findings indicate that innovation is frequently born from “Customer Dissonance”. When a traveler’s expectations clash with reality, the agile entrepreneur doesn’t just fix a problem but they innovate a new process. This is the heart of CXM: transforming a friction point into a “Moment of Truth”. In the Marrakech-Safi region, this has led to the rise of slow tourism and micro-experiences innovations triggered from customers’ desire to live an authentic and spontaneous experience.

What CXM Should Learn from Entrepreneurial Trajectories?

If CXM is to remain relevant in entrepreneurial contexts, it must move beyond standardized models. Based on my research, three shifts are essential: prioritizing narratives over scores, understanding entrepreneurial trajectories rather than static personas, and accepting imperfection as a source of memorability and innovation. Standard CXM often relies on static personas. However, the complexity of tourism entrepreneurship requires a more dynamic approach. We must move toward “Life-Path Mapping.”

By understanding the entrepreneur’s trajectory, we can predict the quality of the customer experience. A “resilient” trajectory (one that has overcome local systemic challenges) almost always translates into a high-empathy customer experience. The lesson for CXM students is clear: behind-the-scenes aspects of the company or business (the entrepreneur’s struggle) play a key role in shaping brand image (customer satisfaction). Tourism Innovation.

Conclusion

The Marrakech-Safi region is more than a destination, it is a laboratory for the future of CXM. Viewing customer experience as an evolving trajectory allows us to rethink both CX and innovation. For students, researchers, and practitioners, tourism entrepreneurship demonstrates that experience, innovation, and identity are continuously co-constructed. The challenge lies in no longer viewing ‘experience’ as a mere marketing product, but rather as an outcome of entrepreneurship.

“CX is not what is delivered it is what is lived”

About tourism Innovation in hotel industry you can read here: Akceptacja robotów w usługach hotelowych – Henn-na Hotel, Japan

The post Customer Experience as an Entrepreneurial Trajectory: What Tourism Innovation Really Reveals? appeared first on Customer Experience Management.

based on: A review of AI (artificial intelligence) tools and customer experience in online fashion retail – R Pillarisetty, P Mishra – International Journal of E-Business Research (IJEBR), 2022•igi-global.com https://www.igi-global.com/viewtitle.aspx?titleid=294111

How Artificial Intelligence Is Transforming the Customer Experience

Artificial intelligence isn’t new, but its impact has grown dramatically with the rise of the internet and digital commerce. While AI research traditionally focused on technical and engineering challenges, much less attention has been given to how these technologies shape customer experience—especially in marketing.

At its core, AI refers to machines that can perform tasks intelligently and improve through learning. This ability to adapt makes AI an ideal tool for solving complex problems and enhancing digital interactions.

In e‑commerce, AI already powers a wide range of features designed to make shopping easier, more personalized, and more immersive. Examples include:

• Virtual try‑on tools like those offered by LensCrafters, which allow customers to “see” how products look without visiting a store.
• Fit‑prediction systems such as NIKE FIT, which use machine learning to recommend the right size for each customer.

These innovations reduce uncertainty, increase confidence, and ultimately elevate the overall online shopping experience.

As AI continues to evolve, its influence on customer experience will only grow—shaping how products are discovered, evaluated, and purchased in the digital world.

Customer Experience in the Digital Era: More Than Just Products

Modern customers aren’t simply buying products—they’re seeking memorable experiences. This idea, introduced decades ago, holds even more relevance today as much of our shopping takes place online. In digital environments, customers can’t touch or try products, so their entire experience depends on the verbal and visual cues presented on the website. Artificial intelligence in retail

Customer experience spans the entire journey—not just a single transaction. Research shows that people want to feel naturally drawn to a product, not pushed into a purchase. They prefer subtle, engaging interactions that convince them through value and quality rather than pressure.

Online customer experience is often described through four key dimensions:

1. Informativeness (Cognitive): How well the site helps customers understand products and make decisions.
2. Entertainment (Affective): The emotional appeal—whether the site feels enjoyable or stimulating.
3. Social Presence (Social): How interactive or “human” the online environment feels.
4. Sensory Appeal (Sensory): The visual and, increasingly, immersive elements that bring products to life.

These dimensions directly shape how satisfied customers feel during their online shopping journey.

Artificial intelligence now plays a major role in elevating these digital experiences. AI-driven recommendations, chatbots, personalized content, and interactive features help create meaningful engagement throughout the customer journey. Artificial intelligence in retail

A term gaining traction in recent years is “Cyber Atmospherics”—the virtual equivalent of in‑store ambience. It refers to how website design, layout, visuals, and interactive elements come together to influence the online customer experience. Just as lighting, music, and decor shape the mood in physical stores, cyber atmospherics shape the emotional and cognitive responses of online shoppers.

Defining E-satisfaction

What Really Drives E‑Satisfaction in Online Shopping?

E‑satisfaction essentially reflects how customers evaluate their online shopping experience compared to traditional in‑store shopping. Early research highlighted that the quality and clarity of information provided on a website—what some call customer information satisfaction (CIS)—plays a central role in shaping how satisfied customers feel. Artificial intelligence in retail

Because online shoppers rely entirely on digital cues, informativeness becomes the core of their experience. Helpful, accurate, and easy‑to‑find information supports customers through every stage of the decision‑making process.

Studies show that e‑satisfaction is shaped by three major elements:

1. Convenience – How easily customers can navigate, search, and complete purchases.
2. Merchandising – The depth and quality of product descriptions, images, and variety.
3. Site design – Visual appeal, user experience, and overall usability.

Customer satisfaction builds in two layers: the immediate satisfaction from the most recent purchase and the cumulative satisfaction formed over multiple interactions with a specific e‑commerce site. A key driver of both is a website’s usefulness—how effectively it offers helpful information and simplifies transactions.

In the last decade, AI has become a major force behind these improvements. Recommendation systems, chatbots, personalized product feeds, and even virtual try‑on experiences all contribute to higher perceived usefulness and, ultimately, greater satisfaction. Artificial intelligence in retail

Researchers often measure these trends using tools like the American Customer Satisfaction Index (ACSI), which tracks how customer perceptions evolve over time. When customers compare their online experiences with offline ones, they evaluate factors such as convenience, product quality, value for money, and product selection—elements consistently shown to influence satisfaction in the digital environment.

AI in Online Apparel Retailing: Driving the Future of Fashion E‑Commerce

India’s e‑commerce sector—especially online fashion—is experiencing explosive growth. This rapid rise is fueled largely by the widespread adoption of smartphones and a surge in online shopping, accelerated further during the pandemic. As more consumers shift to digital platforms, fashion e‑retailers are investing heavily in technology to stay competitive.

According to data from the India Brand Equity Foundation, online apparel accounts for 29% of India’s e‑commerce market, second only to electronics at 45%. With such a significant share, retailers are increasingly turning to advanced technologies—recommendation engines, natural language processing, AI‑powered chatbots, neural networks, and genetic algorithms—to enhance customer experience and boost e‑satisfaction. Artificial intelligence in retail

Researchers like Wang (2014) have analyzed how AI is shaping the online apparel industry, showing that innovative technologies often lead to major market disruptions. AI enables better product availability, more accurate deliveries, and overall smoother shopping experiences (Kati, 2018).

Importantly, AI doesn’t just transform retail operations—it also changes how customers shop. Smart tools can guide shoppers through personalized product suggestions, virtual fit recommendations, and real‑time assistance. As Johnson (2019) notes, AI has become a core technology in today’s online fashion ecosystem.

From mix‑and‑match styling tools to 24/7 support through intelligent chatbots, AI enhances efficiency, reduces return rates, and ultimately increases repeat purchases. For modern fashion retailers, mapping the right AI tools to the customer journey isn’t optional—it’s essential for staying ahead in an increasingly competitive digital marketplace.

Recommendation Engines: Personalizing the Online Shopping Journey

Recommendation engines use machine learning to suggest products that match a shopper’s preferences, based on their browsing behavior and past purchases. One of the most widely used methods is collaborative filtering, which predicts what a customer might like by analyzing patterns from similar users.

These systems continuously learn and adapt, refining suggestions as customers interact with the site. By understanding buying behavior through data mining and behavioral analytics, retailers can deliver more personalized experiences—boosting loyalty, reducing search effort, and improving overall customer satisfaction.

For e‑commerce brands of all sizes, intelligent recommendation tools open the door to global markets by offering shoppers a tailored, engaging experience. Artificial intelligence in retail

Product Reviews: The Powerhouse of Online Shopping Decisions. Artificial intelligence in retail.

Product reviews are one of the most influential elements of e‑commerce. They let customers compare features, assess quality, and evaluate alternatives—all without visiting a physical store. Positive, detailed reviews drive engagement and build trust, while a wide variety of products and opinions strengthens a retailer’s competitive edge.

Artificial intelligence in retail. https://mietwood.com/akceptacja-robotow-w-uslugach-hotelowych

User‑generated reviews are especially credible, providing explicit feedback through ratings and comments, and implicit signals through search and purchase behavior. The broad product variety available online, paired with easy price comparison, enhances customer satisfaction by helping shoppers feel confident they’re getting the best deal.

Modern sites also use digital nudging—subtle design cues that guide faster, more informed decision‑making—further shaping the online shopping experience.

Virtual Try‑Ons: Bringing the Fitting Room to Your Screen

Virtual try‑on technology has become a major innovation in online fashion retail, helping shoppers visualize how products will look and fit—without ever visiting a store. Using 3D modeling and augmented reality, these tools let customers assess size, style, and overall appearance more accurately, which greatly reduces return rates. Artificial intelligence in retail

By turning online product attributes into experience attributes, virtual try‑ons lower the perceived risk of buying apparel or cosmetics online. Whether it’s previewing how a lipstick shade matches your skin tone or seeing how a pair of glasses fits your face, the technology offers an experience close to an in‑store trial.

In India, brands like Lenskart have popularized this feature, allowing users to try on eyewear through realistic 3D models simply by taking a selfie. Research also shows that these immersive tools encourage online purchases by increasing confidence and engagement. Artificial intelligence in retail

Image Interactivity Technology: Making Online Shopping More Immersive

Image Interactivity Technology (IIT) enhances online shopping by allowing customers to interact with products—zooming in, rotating, or mixing and matching items. Rooted in the Stimulus‑Organism‑Response (S‑O‑R) model, IIT explains how website cues influence both a shopper’s emotions (like enjoyment) and thoughts (such as perceived risk), ultimately shaping their behavior on the site. Artificial intelligence in retail

IIT provides two types of cues:

• Utilitarian: tools that support the task of shopping, such as zoom and detailed views.
• Hedonic: elements that make the experience enjoyable, like 3D models and mix‑and‑match features.

These interactive visuals help recreate aspects of the in‑store experience, reducing uncertainty and increasing entertainment value. This has led to a trend called “experiencing the experience”—customers trying out new looks or outfits digitally before buying. Artificial intelligence in retail

Major brands like Nike, Levi’s, H&M, and Speedo now use 3D virtual models and interactive product tools to capture attention, boost engagement, and help shoppers feel more confident in their choices.

Chatbots: The New Face of Customer Service

With the rise of “conversational commerce,” chatbots have become a central part of online customer service. Powered by natural language processing (NLP) and AI, these virtual assistants—similar to Alexa or Siri—can simulate human conversations through websites, apps, and messaging platforms.

Research shows chatbots improve customer experience by answering questions, guiding shoppers, and offering polite, patient assistance based on past customer behavior. Because they use machine learning, they continually improve their responses over time.

However, the experience isn’t always perfect. Customers often report frustration when chatbots misunderstand queries, give irrelevant answers, or get stuck repeating the same response. This highlights the ongoing challenge of balancing automation with accuracy and empathy in digital customer service.

Summary: How AI Is Transforming Online Customer Experience and E‑Satisfaction

The rapid growth of e‑commerce—especially in fashion—has pushed retailers to prioritize not just products, but memorable digital experiences. Online customer experience is shaped by key factors such as informativeness, entertainment, social presence, and sensory appeal. These elements help customers make confident decisions without visiting a physical store and strongly influence overall e‑satisfaction.

Artificial intelligence now plays a central role in enhancing these digital journeys. AI‑powered tools such as recommendation engines, chatbots, virtual try‑ons, and image interactivity technologies personalize the shopping process, reduce uncertainty, and increase engagement. They help customers discover products, visualize fit and style, receive instant assistance, and interact with items more meaningfully.

Product reviews and broad online product variety further boost satisfaction by offering credible feedback, transparent comparisons, and access to the best prices. Combined with digital nudging and smart personalization, these technologies recreate elements of the in‑store experience while adding new forms of convenience and confidence. Artificial intelligence in retail

Overall, AI is reshaping how customers browse, evaluate, and buy—making online shopping more intuitive, immersive, and emotionally satisfying. As these innovations evolve, they will continue to redefine customer expectations and retail competitiveness across global e‑commerce markets.

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The Scenario: In a modern office, there are two employees with the same title and salary.

• Employee A (Manual): Completes tasks purely through manual effort and personal knowledge in 8 hours.
• Employee B (AI-Assisted): Completes the same tasks in 1 hour using tools like ChatGPT or Claude but hides this fact from management (“Shadow AI” usage).

Author: Aykut Akbulut, Erasmus students 2025

The Management Issue: Traditional management focuses on “time spent” (Input), whereas the AI era forces a focus on “value created” (Output). This discrepancy creates a perception of “Unfair Competition” and “Wage Inequity” within the office. Should the manager reward the 1-hour worker, or punish them with more workload? Managerial Dilemma.

Research Findings & Risk Analysis

Our literature review and industry analysis highlight three critical risks:

1. Shadow AI Risk: Approximately 68% of employees (referencing industry trends) use AI without their manager’s knowledge. This poses a significant risk of Data Privacy Leakage.
2. Skill Atrophy: Employee B, who constantly relies on AI, risks losing fundamental problem-solving skills and failing to detect AI-generated errors (Hallucinations).
3. Burnout: Employee A may lose motivation, feeling that “I am working hard while they are taking it easy,” leading to a toxic work environment.

The Solution – The “Middle Ground” Strategy

Banning AI is not the solution; leveling the playing field is. The proposed management model is:

1. Disclosure Policy: The company should allow AI usage but mandate “disclosure.” Employee B must be able to say, “I drafted this with AI support and verified the data.”
2. Upskilling (Equalization): Employee A (the slower worker) should not be penalized but trained in AI usage. The goal is to bring Employee A down to 1 hour as well.
3. Shift in Performance Metrics: Evaluation should shift from “hours sat at the desk” to “value added on top of AI.” The efficient worker should not be punished with busy work but encouraged to use the remaining time for strategic thinking. Managerial Dilemma.

Managerial Dilemma. https://study.com/academy/lesson/dilemma-management-definition-example.html

Management Style: How Managers Really Manage

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It continues through the purchase stage where the need is fulfilled, and concludes with the post-purchase stage that encompasses feedback and evaluation of the experience (Fuller et al., 2023).

As the first two stages (pre-purchase and purchase) are often difficult to be distinguished from each other due to their overlapping nature, the transaction typically serves as the point of separation (Lemon & Verhoef, 2016).

Throughout the customer journey, customers encounter various touchpoints, which are the points of interaction between a customer and a brand (Følstad, & Kvale, 2018). These touchpoints along the customer journey can be both customer-driven or brand-driven (Barann et al., 2022; Payne et al., 2017).

Source: Kaleton, T., Holkkola, M., Kemppainen, T., & Frank, L. (2026). What Makes or Breaks an Immersive Online Customer Journey? Digital Native Generation Z Customers’ Experiences: Link.

Customer journeys may be enhanced by immersion both directly and indirectly (Flavían et al.,
2024). During their customer journeys, customers are seeking highly customizable experiences, where they
can efficiently view products from various angles and engage interactively with a brand (Neves et al., 2022).

For example, high-quality product photos on online stores allow customers to visualize the products and
imagine them in different situations. If customers are provided with sufficient information, they can make
informed purchasing decisions (Flavián et al., 2019).

Thus, immersivity has great possibilities for retailing companies in digital environments. However, VR and
AR solutions related to clothing retail are yet in their early stages and, thus, not largely available in online
stores or applications (Solís-Sánchez et al., 2022).

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Influencer marketing has become one of the most powerful tools in digital advertising, driving billions in brand collaborations worldwide. Yet, as the industry matures, a critical challenge has emerged: authenticity. Consumers increasingly demand genuine connections, while brands often prioritize reach and engagement metrics. This tension creates a paradox—how can influencers remain authentic while monetizing their content?

Recent research published in the Journal of Marketing (Duffek et al., 2025) explores this issue in depth, offering actionable insights for influencers, brands, and agencies. This blog post breaks down the theoretical foundations, key findings, and practical strategies from the study, helping you understand why authenticity is central to influencer marketing success.

What Does Authenticity Mean?

Authenticity in influencer marketing is not a simple trait—it’s a multidimensional construct shaped by relationships among influencers, brands, and audiences. The study draws on assemblage theory, which views influencer-brand-consumer interactions as dynamic systems rather than static roles. Authenticity emerges from these interactions, not just from an influencer’s personality. See also: What drives people purchase online

The English term “assemblage” captures the result of combining parts. The original French term “agencement”, refers both to the act of arranging and its outcome.

The simplest definition describes an assemblage as a heterogeneous multiplicity that creates relations among its parts. These relations are not genealogical but alliances, emphasizing external connections rather than identity-defining ones. This distinction introduces the notions of intrinsic vs. extrinsic relations.

Intrinsic relations define identity, e.g., family roles, while extrinsic relations connect heterogeneous elements without fusing them into a homogeneous whole, e.g., symbiosis in ecology. Intrinsic relations are coded and arbitrary, whereas extrinsic relations allow diversity and contingency.

In this context, contingency means that the relations are not necessary or predetermined—they happen by circumstance rather than by fixed rules or codes. So, when we say extrinsic relations allow diversity and contingency, we mean:

• They connect heterogeneous elements in ways that are open-ended and flexible,
• The connection is context-dependent and could have been otherwise,
• There is no rigid structure or essential identity forcing the relation
• It’s optional, situational, and variable.

Ultimately, assemblages operate through alliances and exteriority.

Core Dimensions of Authenticity

According to the research and supporting literature, authenticity in influencer marketing involves five key properties:

1. Expertise – Demonstrating knowledge and experience in a niche.
2. Connectedness – Building emotional bonds through genuine engagement.
3. Originality – Crafting unique, creative content that reflects personal style.
4. Transparency – Disclosing partnerships and being open about content creation processes.
5. Integrity – Showing passion-driven motivation rather than purely financial incentives. [provost.gsu.edu]

These dimensions align with broader theories like Source Credibility Model and Uses and Gratification Theory, which emphasize trustworthiness and audience satisfaction as drivers of persuasive communication. [lup.lub.lu.se]

Why Authenticity Matters in Influencer Marketing

The demand for authenticity is not just anecdotal—it’s backed by data. Studies show that 88% of consumers want influencers to be authentic, yet nearly 50% perceive influencers as inauthentic. This gap erodes trust and reduces campaign effectiveness. [journals.sagepub.com]

Authenticity impacts:

• Consumer trust → Higher engagement and conversion rates.
• Brand equity → Authentic partnerships enhance brand credibility.
• Influencer longevity → Authentic influencers maintain loyal communities.

Key Findings from the Research

The Journal of Marketing study conducted 185 in-depth interviews with consumers, influencers, brand managers, and agency leaders. Here are the most relevant insights:

1. Authenticity Is Relational, Not Static

Authenticity is co-created through ongoing interactions. It’s not enough for influencers to “appear real”; brands must allow creative freedom and avoid rigid scripting. When influencers can express their unique voice, engagement and perceived authenticity rise significantly. [provost.gsu.edu]

2. Transparency and Trust

Transparency about technology fosters credibility and aligns with consumer expectations for honesty. [phys.org]

3. Misalignment Among Stakeholders

Consumers, influencers, and brands often prioritize different aspects of authenticity. For example:

• Consumers value emotional connection and honesty.
• Brands focus on professionalism and brand safety.
• Agencies seek scalable processes and compliance.

Resolving these misalignments requires clear communication and shared guidelines. [journals.sagepub.com]

4. Generational Differences

Gen Z views influencers as “educated friends,” while Millennials see them as professionals who must act ethically. This affects how authenticity is perceived and should inform campaign strategies. [degruyterbrill.com]

Practical Strategies for Building Authenticity

Based on the findings, here are actionable steps for influencers and brands:

For Influencers

• Stay true to your niche: Consistency in topic and tone builds expertise.
• Engage meaningfully: Respond to comments, share personal stories.
• Disclose partnerships: Transparency is non-negotiable.
• Balance creativity and brand guidelines: Negotiate freedom in collaborations.

For Brands

• Choose values-aligned influencers: Beyond follower count, look for shared mission.
• Avoid over-scripted campaigns: Authenticity thrives on creative autonomy.
• Support long-term partnerships: Sustained relationships feel more genuine to audiences.

Authenticity Dimensions Chart

Here’s a simple chart illustrating the five dimensions of authenticity:

Authenticity Is the Future of Influencer Marketing

Authenticity is not a buzzword—it’s the foundation of sustainable influencer marketing. As consumers demand transparency and genuine engagement, brands and influencers must collaborate to create content that resonates on a human level. By embracing the principles outlined in this research, you can build campaigns that not only perform but also foster trust and loyalty.

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Based on the typical content of a Customer Experience Management (CEM) lecture (Strategy, Journey Mapping, Metrics, and Culture), here are 5 proposed SERVQUAL-style questions for students. The scale should be a 5-point Likert scale, with options like: 1 = Strongly Disagree, 5 = Strongly Agree

5 SERVQUAL Questions for Your CEM Lecture

The questions are organized to cover the core dimensions students would likely expect from a course titled “Customer Experience Management.” For each item, the student will answer two questions: what they Expected and what they Perceived (Got).

Calculating the Gap Score

Once students complete the survey, you can calculate your Gap Score for each of the 5 items:

A Negative Score indicates a gap where the lecture failed to meet student expectations (e.g., 3 – 5 = -2).

• A Zero Score indicates the lecture met expectations (e.g., 4 – 4 = 0).
• A Positive Score indicates the lecture exceeded expectations (e.g., 5 – 4 = +1).

You can read more here: ServQual methodology for assessing the usability of automated sales in grocery

This is a much better way to tailor the survey! Based on the specific themes found on your blog (mietwood.com), which emphasize digital business models, data science, competitive advantage, and sustainability within Customer Experience Management (CEM), I have adapted the 5 SERVQUAL dimensions to reflect your unique lecture content.

Students will rate their Expectation (E) (based on the title) and their Perception (P) (what they got) on a 5-point Likert scale, where 1 = Strongly Disagree and 5 = Strongly Agree.

5 SERVQUAL Questions Tailored to mietwood.com

How to Use the Scores

After the students complete the survey, you can calculate the Gap Score for each question by subtracting the expected score (E) from the perceived score (P)

Reliability – servqual

That’s an excellent way to focus your immediate survey efforts—by zooming in on the Reliability dimension.

In the context of a CEM lecture, Reliability measures the ability of your course to perform the promised service dependably and accurately. It asks: Did the lecture deliver on its core promises and core functions?

Here are 5 SERVQUAL questions, all focused on the Reliability of your CEM lecture (based on the themes from mietwood.com), where students will rate both Expectation (E) and Perception (P) on a Likert scale (1-5).

This set of five questions will give you a detailed view of how well you delivered on the fundamental promises of your CEM lecture.

The most significant scientific paper related to the SERVQUAL scale is the original publication that introduced the instrument:

Title: SERVQUAL: A Multiple-Item Scale for Measuring Consumer Perceptions of Service Quality1 Authors: A. Parasuraman, Valarie A.2 Zeithaml, and Leonard L. Berry3 Journal: Journal of Retailing4 Volume/Issue/Pages: Vol. 64, No. 1, pp. 12-405, Publication Year: 19886

Why This Paper is the Most Significant

This paper is considered seminal for several reasons:

1. Introduction of the 5 Dimensions (RATER): It refined the ten initial determinants of service quality (proposed in their earlier 1985 paper) into the five established dimensions used today: Reliability, Assurance, Tangibles, Empathy, and Responsiveness.
2. The Instrument: It describes the development, refinement, and validation of the 22-item SERVQUAL questionnaire itself, which is designed to measure the gap between customer Expectations (E) and Perceptions (P).⁷
3. Foundation of the Field: It provided the first widely accepted, psychometrically rigorous, and empirically tested scale for measuring the abstract concept of service quality, establishing the fundamental model for nearly all subsequent research in the field.

It’s important to note that the conceptual framework, known as the Gaps Model of Service Quality, was initially introduced by the same authors in an earlier 1985 paper:⁸

• 1985 Paper: A Conceptual Model of Service Quality and its Implications for Future Research, published in the Journal of Marketing.⁹ This paper introduced the five service quality gaps. link
• 1988 Paper: SERVQUAL: A Multiple-Item Scale…, published in the Journal of Retailing.¹⁰ This paper introduced the actual 22-item measurement scale based on the 1985 framework.¹¹

For anyone specifically looking for the measurement tool (the 22-item scale), the 1988 Journal of Retailing paper is the most significant one.

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This blog post explores the key concepts, strategies, and tools involved in managing Customer Experience CX in the digital age, drawing insights from the presentation by Mieczysław Pawłowski, PhD. You can download it from here below.

Customer Experience Management in the Digital Age – Navigating the New Frontier.

The Evolution from CRM to CXM

Customer Relationship Management (CRM) has long been a cornerstone of business strategy, focusing on understanding and influencing customer behavior to drive acquisition, retention, loyalty, and profitability.

Digital technologies have advanced, the scope of Customer Relationship Management CRM has expanded to Customer Experience Management CXM. CXM goes beyond traditional CRM by integrating digital tools and strategies to enhance every touchpoint a customer has with a business.

Thank you to Tanzania’s students for listening to me with attention and all activity I experienced from YOU.

The Role of CXM in Business Growth

Effective CXM is crucial for business growth, as it directly impacts customer satisfaction, loyalty, and overall profitability. Companies that excel in CXM can differentiate themselves in the market, build stronger relationships with their customers, and drive sustainable growth. The process involves several key components:

1. Customer Knowledge: Collecting and analyzing customer data to understand their characteristics, needs, and preferences.
2. Value Creation: Linking organizational strategy with customer management processes to create value for both the company and the customer.
3. Competitiveness: Combining business processes and technologies to differentiate products and services in the market.

CXM in the Digital Age

The digital age has brought significant changes to CXM, with e-commerce, digital marketing, and omnichannel sales becoming integral parts of the customer journey. Businesses must now operate and interact with customers differently, utilizing digital interfaces and tools to enhance the customer experience. Key trends in CXM include:

• Digital Transformation: Companies must adapt to digital technologies to stay competitive and meet customer expectations.
• Digitization of Customer Interactions: The integration of digital technologies into customer interactions has evolved from basic processes like online ordering to a complete digitization of the customer journey.
• Customer-Centric Approach: Businesses are shifting from a product-centric to a customer-centric approach, placing customer experience at the forefront of their interactions.

About digital age you can read here: What is digital age?

The Profession of Customer Experience Management

As CXM becomes increasingly important, the role of the Customer Experience Manager has emerged as a critical profession. These professionals are responsible for optimizing every touchpoint a customer has with a business to build brand loyalty and enhance customer relationships. Common responsibilities of a Customer Experience Manager include:

• Championing opportunities to improve the customer experience.
• Driving customer retention and satisfaction.
• Mapping the customer journey and identifying opportunities for proactive intervention.
• Guiding teams in effective client issue resolution.
• Developing strategies for continuous improvement.

Strategies for Effective CXM

To succeed in CXM, businesses must adopt strategies that align with their goals and market position. Some effective strategies include:

• Market Leader: Treating customers as regular resources and focusing on customer satisfaction.
• Pretender: Using customer feedback to improve and innovate.
• Niche: Differentiating through quality and specialized offerings.
• Price Leader: Focusing on product value and competitive pricing.

The Impact of Technology on Customer Experience

Technology plays a pivotal role in shaping customer experience in the digital age. From self-service kiosks that boost consumer spending to digital interfaces that streamline customer interactions, technology enhances the overall customer experience by providing convenience, personalization, and efficiency. Key technological impacts include:

• Enhanced User Experience: Visual displays and photography help entice customers and upsell options.
• Data Collection: Detailed data on customer preferences allows for precise targeting and improved service.
• Automation: Automating processes like checkout frees up staff time and enhances customer satisfaction.

Customer Experience vs. Service Quality

The search results strongly suggest that while “Service Quality” is the foundational academic concept, “Customer Experience” (CX) is the current industry and high-level curriculum trend.

1. CX is the Dominant Industry and Advanced Curriculum Term 🚀

The term “Customer Experience” (or “CX”) is now the preferred term in executive education and advanced programs:

• Masters Programs: Top business schools (like IE Business School, MSU Broad College of Business, Rutgers, HBS Online) offer entire programs or executive courses dedicated to “Customer Experience Management” or “Transforming Customer Experiences.” (Source 3.1, 3.3, 3.4, 3.6). This demonstrates that, for students interested in advanced studies, CX is a recognized, specialized field.
• CX is Strategic: CX is consistently described as a “leading strategy companies harness to grow their market share” and a source of “long-term competitive advantage.” (Source 3.2, 2.5). Business leaders are recognizing that CX is crucial.
• CX is a Modern Evolution: Scholars note that services are undergoing a transformation from the traditional concept of a service transaction to one of an “experience” (Source 1.1). CX is seen as the latest evolution that surpasses simple products and services.

2. Service Quality is the Academic Foundation (The “Known” Term) 🎓

Students are likely more familiar with “Service Quality” because it is the cornerstone of early marketing and management theory:

• Service Quality is the Antecedent: The research confirms that Service Quality (SQ) is viewed as the fundamental antecedent or predictor of Customer Experience (CX) (Source 1.3). In academic models, improving Service Quality is a way to achieve positive Customer Experiences.
• Student Experience Studies: Studies assessing student satisfaction in higher education often use Service Quality models (like SERVQUAL) as the primary framework, although they are now explicitly linking SQ results to overall Customer Experience (Source 1.1, 1.6).

Service Quality – The gap between customer expectations and perceptions of service delivery. Academic, Tactical. It focuses on a transactional evaluation of reliability, responsiveness, etc. It signals a foundational, measurement-focused course.

Customer Experience – The customer’s overall perception and internal, subjective reaction to every direct or indirect contact over a period of time. Strategic, Holistic. It focuses on the full journey and emotional connection, making it a more complex, managerial, and future-oriented topic.

The term “Client” vs. “Customer” is a minor issue. In modern business and academic literature (including the high-level Master’s programs cited), “Customer” is the standard term used in the context of CX, as it refers to a broader B2C or B2B user, not just a high-value client.

Customer Experience Management is the title most aligned with advanced, strategic business education, which attracts the type of student who wants to be on the cutting edge and those seeking high-value skills.

Customer Experience can be combined with the analytical, digital, or process-oriented keywords suggested previously to make its content clear and appealing to the strongest cohorts

Conclusion

Customer Experience Management is not only essential for business growth but also a strategic priority for companies aiming to differentiate themselves in the market. By investing in CXM, businesses can drive increased profitability, customer loyalty, and brand strength while reducing costs and enabling continuous improvement. As the digital age continues to evolve, the importance of CXM will only grow, making it a critical area of focus for businesses looking to thrive in the modern economy.

In conclusion, the role of CXM in the digital age is multifaceted and ever-evolving. By continuously developing strategies, leveraging technology, and prioritizing customer satisfaction, businesses can ensure they remain competitive and successful. The future of CXM is bright, and with the right approach, companies can create unforgettable experiences that drive long-term growth and loyalty.

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