MBA Thesis Explores Why EV Companies Need More Than Data

09.10.2026

Thesis Finds EV Firms Must Turn Data Into Action

The electric vehicle sector is no longer only about putting more EVs on the road. In mature markets such as the Netherlands, the next challenge is what companies do with the data those vehicles and charging networks produce.

For Wittenborg student Poorandokht Aliabadi from Iran, that challenge became the focus of her MBA thesis in International Management. Her dissertation, From Telemetry to Strategy: Bridging the Gap Between Data Analytics Capabilities and Marketing Performance in the Dutch e-Mobility Sector, explored how Dutch e-mobility companies use data to improve marketing performance, product decisions and customer experience.

“This topic is relevant because the Dutch e-mobility sector is growing quickly and becoming increasingly competitive,” Poorandokht explains. “EV charging companies collect large amounts of valuable data, such as charging behaviour, location data, payment information, customer feedback and app usage data. However, having access to data does not automatically mean that companies can turn it into better marketing decisions, customer experience, pricing strategies or product improvements.”

The Netherlands offered a strong setting for the study. The country has a mature EV market, a dense charging network and a competitive group of companies working across charging infrastructure, mobility services and digital platforms.

Poorandokht focused on two key types of organisations in this ecosystem. Charge Point Operators manage the physical charging infrastructure, while e-mobility service providers handle customer-facing services such as apps, charging cards, billing and user accounts. Together with partners such as payment providers, roaming platforms and vehicle manufacturers, they form a complex data web.

But the study found that having this data web does not automatically create business value.

“I noticed that one of the biggest challenges is not only collecting data, but translating it into clear, actionable insights that different teams can actually use,” she says.

Poorandokht chose the topic because of her interest in the connection between data analytics, product management and marketing strategy. Her studies and internship experience in the e-mobility sector helped her see how technical data and commercial decisions often sit close together, but do not always connect smoothly.

Her research used a qualitative method. She first conducted a literature review on data analytics capabilities, marketing performance and the e-mobility sector. She then carried out 20 semi-structured interviews with professionals working in the Dutch EV industry.

The participants worked in data analytics, marketing, product management, customer experience and business strategy roles. They included professionals from EV charging companies, including charge point operators and e-mobility service providers, with direct experience of how data is collected, interpreted and used in business decisions.

Poorandokht reached participants through her professional network, LinkedIn and email. The interviews explored how data is used, shared, understood and translated into marketing decisions. She then analysed the material using thematic analysis, identifying seven final themes.

The main finding was clear: Dutch EV companies are not data-poor. They are often data-rich, but commercially under-activated.

“The main challenge in the Dutch e-mobility sector is not the lack of data, but the difficulty of turning available data into clear and actionable marketing insights,” Poorandokht says.

The study found that companies collect many types of useful information, including charging session data, customer behaviour data, location data, payment data, operational data and app usage data. However, this information is not always used consistently in marketing decisions.

One of the strongest issues was what Poorandokht describes as the translation gap. Raw technical data often needs to be cleaned, explained and converted into commercial recommendations before marketing teams can act on it. In other words, data has to move from numbers to meaning.

The research also found that collaboration between data and marketing teams can be too informal or request-based. Instead of working together from the beginning of a campaign or product decision, teams may interact through tickets, dashboards or individual relationships. This means data specialists can become report providers rather than strategic partners.

Another barrier was data literacy. The study found that access to dashboards does not automatically make teams data-driven. Marketing and commercial teams may have tools such as Power BI or internal dashboards, but still need training, confidence and support to interpret results correctly.

Trust also played an important role. Participants indicated that people are more likely to use data when they understand how it was produced, when the outputs are reliable and when they have repeated experience working with the teams behind the data.

Fragmented systems created another challenge. Companies may have data lakes, cloud platforms, dashboards and marketing tools, but these systems are not always connected in a way that supports real-time marketing action. This can slow down segmentation, campaign planning and customer experience improvements.

External pressures also shaped the picture. General data protection regulation acted as a boundary around personalisation, especially where companies wanted to use location behaviour, payment information or identifiable customer journeys. Competition, however, pushed companies to become faster and more data-driven.

Poorandokht’s research used the Technology-Organisation-Environment framework to interpret these findings. In simple terms, the framework helped her examine not only the technology companies have, but also the internal structures and external pressures that determine whether that technology is useful.

Her conclusion was that data analytics should not be seen only as a technical function. It needs to become part of cross-functional decision-making between data, marketing and product teams.

The thesis makes several practical recommendations. Dutch EV companies should embed data analysts within marketing and product teams, create analytics translator roles, improve data literacy training, simplify dashboards, integrate systems more effectively and establish formal cross-functional routines.

For Poorandokht, the key question is not simply whether a company has data. It is whether the right people can understand it, trust it, access it and act on it at the right moment.

“The aspect I enjoyed the most was connecting academic theory with real industry practice,” she says. “Through the interviews, I had the chance to hear directly from professionals in the Dutch e-mobility sector and understand how data, marketing and product decisions are connected in real business situations.”

She especially enjoyed analysing the interview findings and identifying patterns across participants’ experiences.

“It was exciting to see how the ideas from the literature became visible in practice, and how my research could lead to practical recommendations for EV companies,” she says. “This made the thesis feel meaningful, not only as an academic project but also as something connected to my future career in product management and sustainable mobility.”

Poorandokht is now looking ahead to continuing her career in the e-mobility sector. After completing her studies and internship, she plans to join the same company as a Junior Product Manager, working on a mobility service provider application.

She sees the role as a chance to apply what she learned during her MBA and thesis research in a real professional environment.

“My goal is to play a more meaningful role in developing digital products that improve the EV charging experience for customers,” she says.

In the long term, she hopes to contribute to the growth of the EV sector and support the transition towards more sustainable mobility. She wants her work to help make electric travelling easier, more accessible and more connected to renewable energy.

Poorandokht says her overall experience at Wittenborg was positive and meaningful. She gained academic knowledge, but also the confidence to use that knowledge in professional settings.

“While doing my internship, I often realised how much the lessons, projects and discussions from my classes helped me contribute more effectively in real business situations,” she says.

Writing her first thesis was stressful at the beginning, but she says the support of her supervisor, Dr Robert Muster, helped her become calmer and more confident throughout the process.

“I truly appreciated the availability, patience and encouragement I received, which helped me complete a piece of work I am proud of,” she says.

Her advice to other students is to choose a topic they genuinely care about.

“When you are curious about finding the answer, every step of the research process becomes more meaningful,” she says. “You are more likely to feel motivated, enthusiastic and connected to your work instead of bored or burnt out.”

She also encourages students to listen carefully to their supervisor, trust the process and stay open to feedback.

“The final research assignment can feel stressful at times, but if you choose your topic with passion, follow the process step by step and do the work with love and commitment, you will definitely be able to succeed.”