I am looking for an internship

Stage VodafoneZiggo (Stage market & customer insights) (MM/MADS)

Wat zijn de behoeften van de klanten vandaag én de toekomst? Voor VodafoneZiggo staat deze vraag centraal voor de verdere groei van ons bedrijf. Market & Customer Insights voert marktanalyses uit op basis van onderzoek data en externe bronnen. 

Als stagiair in het Market & Customer Insights team help jij ons bij deze vraag en houd je je bezig bij het vinden van de juiste en meest actuele insights! Een stagiair(e) draait mee in ons team, maar er ook ruimte om aan een afstudeeropdracht te werken. Je kunt bij ons werken aan verschillende vraagstukken en je verder ontwikkelen. Hierbij coachen wij je gedurende jouw gehele stage. Tegelijkertijd gaan we ervan uit dat je ook tot een bepaalde hoogte zelfredzaam bent. We zoeken een stagiair(e) die graag wil leren en verantwoordelijkheid pakt. Een stagiair(e) die nieuwsgierig is en pro-actief meedenkt over oplossingen. Daarnaast vind je het leuk om mee te werken aan de opzet van onderzoeken (bijvoorbeeld via Qualtrics) en de resultaten hiervan te analyseren en rapporteren.

Een stagiair krijgt bij ons een standaardvergoeding en een teamlid als persoonlijke begeleider.

Wat verwachten wij van jou:

Meedraaien in het team en ondertussen werken aan eigen planning en stage-opdracht/scriptie.

• Minimaal twee dagen op locatie (Hoog Catharijne in Utrecht) werken.
• In deze stage werk je mee in het team, maar is er ook ruimte om aan je afstudeerscriptie te werken
• Er is sprake van een reis- & stagevergoeding
• Je volgt de master Marketing Management of Marketing Analytics and Data Science
• Je mag zelf met een vraagstuk komen

Wat je van VodafoneZiggo kan verwachten

Een uitdagende omgeving in een leuk team!

WRITING YOUR THESIS AT DVJ INSIGHTS (MM/MADS)

Do you like combining writing your thesis with working at the most successful marketing research company of the Netherlands? We offer the opportunity to work at the DVJ office in Utrecht either for some days a week or also for a whole week and ‘work along’. There is the option to work from home, which is the default if you only write your thesis based on our data. In case of working along, you would work partly on your thesis and partly on other projects, unrelated to your thesis. You will also follow different courses from our onboarding program for new researchers that teaches you among others how we work at DVJ Insights, how to develop a questionnaire, and how to program the survey in our survey software.

WHO ARE WE?

DVJ Insights is an ambitious, innovative, and fast-growing marketing research agency located in the Netherlands, the UK, Germany, Spain, Denmark, Sweden and Norway, with the ambition to be the best global agency for brand growth. DVJ works closely with the academic world and therefore it is easy to work on your thesis and understand better what it would be like to work in a real agency. The connection with science is always there and that is why many people before you joined DVJ and in some cases also started working at DVJ. We add value by helping our clients to understand consumer behaviour better, improve their brand positioning, realise more successful product introductions, and increase the effectiveness of their media campaigns. At DVJ Insights, more than 100 passionate colleagues from 7 different locations work for clients such as Philips, Samsung, Beiersdorf, Heineken, Cloetta, Domino’s, Nestlé, ING, and Rituals. We are a dynamic and informal place to work with people from different cultures and backgrounds.

WHAT CAN WE OFFER?

The opportunity to write your thesis at DVJ and be able to work with our data. We are conducting internal meta-analyses regularly but want to learn even more from all the data we gather. By conducting research on our databases, we can gather a lot of general learnings on why some innovations are successful, how advertising becomes more effective, why brands grow and why they don’t, and the way media deployment can be optimised. Therefore, you get the opportunity to work with data that is interesting, very rich and practically relevant. Furthermore, you will be able to use sophisticated econometric modelling to find interesting insights, both from an academic as well as a practical perspective. The internship allowance is €400 per month if you are solely writing your thesis at DVJ. If you are also working alongside your thesis, the monthly allowance will be €1.000 based on a 40-hour work week.

POSSIBLE TOPICS TO WORK ON

For a thesis topic, we can develop a topic together, and you would be able to use our panel for data collection. Or, since we conduct so many different studies and we have a lot of data, you have the option to work on one of the following topics:

1. Shopper missions (Marketing Analytics topic). For our clients, we sometimes conduct customer journey or shopper mission studies. In those studies we examine what needs are triggers to go to the store and buy. Based on those studies we can identify different shopper missions, such as the shopper on the go, or doing the large groceries Additionally, we have access to individual-level purchase data from Danish, Swedish, and Norwegian supermarkets, collected over a period of approximately two years through an app-based registration system. Thus, it includes all purchase receipts including product information for different supermarkets in different regions. There is also information on the users, f.i. age and region where they live. This enables you to examine whether the shopper missions as identified, can also be distinguished in the data. Combining this again with background information of the users, leads to rich insights on shopper missions and consumers. More specifically, one can think of the following research questions: Are certain categories bought more/less often for certain shopper missions? Are certain types of products (i.e., A-brands, private label, different pack sizes) more/less popular for certain shopper missions? Are certain consumers more/less price sensitive for certain shopper missions? Do we observe brand loyalty versus variety seeking? Etc. etc.

2. Packaging (Marketing Analytics & Management topic). In today’s market, brands whose products are sold in retail face several challenges. As shelf space increasingly comes at a premium, each product will have to compete with many others for the consumer’s attention. And, especially for fast-moving consumer goods, where consumer involvement is relatively low and decision-making is primarily based on heuristic cues, it becomes vital that, within a fraction of seconds, a product’s package is able to capture the consumer’s attention and is identified as belonging to the brand (so that the product’s main features will also be linked to the brand). Therefore, DVJ’s vision is that a proper pack test should not only force consumers to pay attention to a package in evaluating it, but should also measure whether the package is able to immediately attract (positive) attention and link its key features to the brand. This database contains evaluation, associations and attention metrics for approximately 150 packs from about 10 countries and different categories. A few example research questions can be: what determines the success of packaging? Which elements are crucial for standing out on the shelf and what determines brand recall?

3. Cross-country differences in advertising response (Marketing Analytics & Management topic). Many brands nowadays operate at least at a somewhat global scale, i.e. they sell their products, and advertise them, across multiple countries. However, we still quite often observe the exact same advertisements being used across different countries, either because of the desire to save costs, or because one assumes that the advertisement will be perceived in a similar way across different markets. However, is this actually the case? Do typical "style elements" in ads invoke the same response across countries, or are there profound differences? And if so, can these differences be conceptually linked to the attributes of these countries (e.g. their national culture, socio-economic position, et cetera)? This project would require the coding of different ads in terms of several "style elements" they may or may not be using. We have different datasets available with different types of ads, namely for TV, TikTok, Online video, or OOH. We also have one specific dataset containing only Christmas TV commercials.

4. Valuable open ended feedback (Marketing Analytics & Management topic). In marketing research, we aim to collect respondents opinions and attitudes around a plethora of topics. Much market research relies only on quantitative measures such as pre-defined statements and questions. However, the danger is that important things are missed. And therefore, it is important to start with letting respondents share their stories and associations around a certain topic, without limiting them to pre-defined statements. However, the added value of this approach all lies within the richness of the open answers. We already did some internal tests to see how we can enhance richness of the open answers, for example by using a social nudge and through AI-SmartProbing technology (using AI to ask follow-up questions). What are more ways to ensure qualitatively rich open answers in online survey research? Are there any new ways known in academic research and if so, how effective are these? And related to this: what are cost and time efficient ways to filter out AI-generated answers?

5. Measuring emotions (Marketing Analytics & Management topic). Emotional responses are playing an increasingly vital role in brand strategy and research. Emotions are not only powerful drivers of consumer behaviour but are also remembered more vividly than neutral experiences. But how can we accurately measure them? Over the past few years, DVJ Insights has explored various approaches to incorporate emotional measurement into large scale quantitative research. These initiatives have included methods such as combining storytelling with MaxDiff, conducting Implicit Association Tests (IAT), and utilizing reaction time measurements. Visual stimuli, such as images, also offer a compelling way to capture emotional reactions. This raises an important question: what is the most effective method for measuring emotions? Additionally, to what extent do cultural or regional differences affect emotional interpretation and how should these variations be addressed, especially in the context of global clients?

6. Exploring the perception of AI-Generated Advertising (Marketing Analytics & Management topic). Many brands are currently exploring the use of AI in their advertising efforts. An intriguing question that arises is whether AI-generated advertisements are perceived differently by audiences compared to traditionally created ads by humans. How do people respond to AI-generated ads versus non-AI ads? Do viewers recognize when an advertisement has been created by AI? And if so, does that recognition influence their perception? Key areas of interest include potential differences in attention, recall, and emotional responses (affective reactions). One effective way to research this would be to create AI generated versions of existing ads and compare them with the original versions in testing. By running both versions through our panel, we can examine audience responses across various dimensions and uncover meaningful insights into how AI influences advertising effectiveness.

7. Which stimuli are the best predictors of innovation success? (Marketing Analytics & Management topic). In innovation research, a variety of stimuli are commonly used to assess the potential success of a new product or concept. Best practices typically include evaluating the product name, consumer friction points, the product promise, reasons to believe (RTBs), and the use of visuals. Each of these elements plays a role in shaping consumer perception and influencing purchase intent. Central question is: How should a stimulus be designed to deliver valid results? This has various dimensions like stimuli elements, stimuli styles (f.i. length, language), how do different categories or to be marketed products differ and how should the stimulus be aligned to it?

Besides these topics we also support students that have a strong idea and need a good partner for data collection. This means that you bring in your own topic and we make sure that DVJ collects the data for you.

WHO ARE WE LOOKING FOR?

We are looking for a master's student (M/F/O) with a background in marketing (research), psychology, or consumer behaviour.

Do you recognize yourself in the following profile?

We are looking for someone who:

• Is currently studying econometrics, data science, computer science, marketing management, marketing research, psychology, (technical) business studies, or a related field

• Is passionate about consumer research and uncovering the “why” behind the “what”

• Has a love for (marketing) data and modeling

• Is skilled in handling large datasets from multiple sources

• Can identify interesting research questions based on data patterns

• Has excellent knowledge of statistical software, such as SPSS or R

• Is proficient in MS Office

• Speaks and writes English fluently

• Is motivated and willing to go the extra mile

• Holds themselves to high standards of quality

Noordhoff: the challenge (MADS)

Education is evolving. Digitalization and flexibilization of education have gained momentum in recent years. This means a challenge for schools, but also for Noordhoff. Noordhoff is a publisher of educational materials (including Getal & Ruimte, Nieuw Nederlands, and the Bosatlas) with almost 200 years of experience. Every day, more than 2 million people of all ages work and learn with Noordhoff's educational solutions. Therefore, an important issue is: How can Noordhoff transition from a traditional publisher to a company that creates blended learning solutions? Noordhoff is in the midst of this transformation. Blended learning solutions refer to the optimal combination of digital and folio educational materials that can be used individually and in the classroom. Every day, we discover how learning can be optimized. With smart methods, personal attention, up-to-date teaching materials, and new technology. Always with the knowledge of today and curious about tomorrow's learning. 

We observe that the competitive field is expanding, and the introduction of AI may further amplify this expansion. There are many tech initiatives from startups as well as larger players such as Google and Amazon, which offer user-friendly products. Startups might possess the needed technology but often lack knowledge of didactics, alignment with curricula, and high-quality content. Traditional publishers typically excel at content creation but may lack technological expertise. 

There is a lot of data available at Noordhoff on various topics such as digital use of our educational solutions, contact with customer service, and online marketing activities. Will you help us use this data for the future of education and to help teachers teach more efficiently and effectively?

Various use cases require our attention to be picked up with the help of quantitative research (data science). Previous interns have focused on questions such as "Does increased or decreased contact with customer service increase the likelihood that customers will leave Noordhoff?", "Is there a relationship between digital use and study results?", "Which marketing action is most effective?", "Are there different user profiles for our online teaching materials?", "Which teachers appreciate which teaching methods?". These and other questions remain relevant and we would be happy to explain them further during an interview.

What do you bring?

• You are studying in the field of Marketing Analytics & Data Science.

• You have a passion for and experience with quantitative (big) data analysis.

• You are motivated, independent, and curious.

• Knowledge of R is a requirement, experience with Python is a plus.

• SQL knowledge is a plus.

• You are available full-time (1 day per week working, 4 days researching), with the possibility of taking additional courses at the university.

What do we offer?

• Get to know the practice: get familiar with different functions within a data & analytics team, attend meetings, get to know analytical tools used in practice (such as PowerBI and Mixpanel), and discover business processes.

• Introduction to marketing automation (such as (near) real-time reports in Power BI, real-time product analytics in Mixpanel, and data warehousing in Snowflake).

• Access to big datasets.

• Experienced (internship) supervisors who provide intensive guidance and can provide a bridge between the university and the business world due to their background.

• Generous internship compensation.

• A workplace in our office in Groningen within the Data & Analytics team. Hybrid working is possible on agreement.

• Time and space to complete any additional courses at university.

More information

www.infinitaslearning.com

AI in advertising research to decrypt the DNA of creativity (MADS)

Which marketing intelligence student wants to fill a thesis with insights about all Dutch advertising from the past 18 years?

There is a “creativity crisis” going on: advertising has become increasingly flat, abstract and rational, and therefore less effective. At the same time, it turns out that award-winning creations do not always have as much impact as previously thought, mainly because people decide in a fraction of a second - unconsciously - whether something is so relevant to them that they want/need to pay attention to it.

Wouldn't it be interesting to perform a content analysis on advertising, to see how it has developed over time? Given the convincing evidence that creativity is the way to greater effectiveness, we can learn a lot from such insights. In a PhD trajectory at the University of Groningen, this issue has been worked on in the past few years, in collaboration with publisher DPG Media, research agency DVJ Insights and data company Nielsen.

It was simply impossible to examine all product categories, media types and creations at once (this annually concerns approximately 43,000 print ads, 18,000 radio spots, 13,500 television commercials, 1.4 million online display ads, etc.), so we started with advertisements from newspapers and magazines for cars: 8,806 unique print ads over a period of 18 years.

Various applications were used to determine semantic meanings of the ads: AI models such as ‘Vision Transformer’ (ViT) and ‘YOLO’ (You Only Look Once) but also AI technologies that use AI models such as ‘Automated Image Analysis’ (AIA), ‘Optical Character Recognition’ (OCR) and ‘TextBlob’. The technology enabled an effective and rapid assessment of, among other things, the distinctiveness and consistency of all advertisements.

A large number of content characteristics of the ads were inventoried, including contrast, visual complexity, proportion of warm tones, share of text and people in surface area, text length, subjectivity, polarity, URLs, calls to action, number of brands, price indication, functional value proposition, sentiment and logo size. A Relative Importance Analysis (RIA) was used to reveal the contribution of different elements to the uniqueness of the ads.

We have had to limit ourselves to print ads for car brands so far, but we would like to continue and broaden this project with similar long-term analyses on other product categories and other media propositions. The precise details are yet to be determined, but we would like to start with an extension to online display ads. The analysis tool that was developed for print ads may need to be adapted to also include online ads.

The graduate student can stand on the shoulders of the PhD student who worked on this project so far, but the intended extension will still offer sufficient challenge and opportunities for innovation, also because initiative in this matter is appreciated.

Terms & conditions

• Since it mainly involves analyses using AI tools, the assignment is probably more suitable for marketing intelligence students (interest in media and advertising is a plus)

• The assignment is also open to international students (English speaking)

• The student is supervised by DPG Media, but the university, DVJ Insights and Nielsen are also stakeholders in the project

• Our office (Mediavaert) is located in Amsterdam, but it is no problem to work from home

• There is a small internship allowance

About DPG Media

DPG Media is the largest media house in the Netherlands. For decades, our media has been present in millions of Dutch households every day. With brands that offer our readers, listeners, users and viewers and also our advertisers a wonderful platform.

Our portfolio consists of strong and reliable brands, each with its own identity and signature. Online and offline. Every day we strive to make the best television, newspapers, radio, magazines & online services and thereby touch the minds and hearts of the Dutch. We reach no less than 91% of the Dutch population with our brands. National, regional and local brands. From AD and NU.nl, to Donald Duck, Libelle and vtwonen. From Het Parool and de Volkskrant, to Qmusic and Independer.

MSc Thesis Internship opportunity for MADS students at Data Inside

Problem statement

Charities and NGOs in the Netherlands face increasing challenges in recruiting new donors, making the reactivation of lapsed donors a growing priority. A donor is typically considered ‘inactive’ after a period of 24 or more months without contributing a donation. Reactivation strategies, primarily executed through direct mail (DM), telemarketing (TM), or email (EM) campaigns, aim to re-engage these lapsed donors, but their success rates remain variable and often unpredictable.

To address this challenge, there is a need for a data-driven approach that can identify key factors influencing the likelihood of donor reactivation. This research aims to define which variables—such as donation history, communication preferences, demographics, or fundraising channel—correlate with higher reactivation success rates. Additionally, it seeks to develop and implement a predictive model to optimize donor selection for reactivation campaigns.

The insights and tools developed from this research will empower non-profits to make more targeted and cost-effective reactivation efforts, ultimately improving their fundraising outcomes. This complements previous research conducted at Data Inside, which focused on donor retention and churn, by providing actionable strategies for re-engaging donors who have lapsed.

Data

The benchmark dataset from Data Inside consists of data from around 47 different non-profit organizations. It is impressive in size and provides a rich source of data for a thorough and engaging thesis research. With more than 2.8 million active donors, 13.3 million recorded donations per fiscal year, and a total donation value exceeding €167 million, this dataset offers extensive opportunities for detailed analysis and insights into private donor reactivation and the factors influencing it. The size and diversity of the dataset form a robust foundation for meaningful and impactful thesis research.

Company

Data Inside is an organization that resulted from the merger of Mailtraffic, a direct mail company specializing in charities, and Christal, a telemarketing company for charities. Data Inside provides valuable insights and analysis to the non-profit sector, advising charities to help them make effective decisions and develop fundraising strategies. The company is based in Zwolle, the Netherlands, and currently has a team of 15 employees, serving a diverse client base that includes organizations such as Amref Health Africa, Dierenbescherming, Milieudefensie, Terre des Hommes, Aidsfonds, Care, and Wakker Dier.

Form of cooperation

Data Inside is looking for a motivated student with an affinity for the non-profit sector and (some) experience or interest in data visualization and analysis. As part of the thesis project, the student is expected to work on location at Data Inside at least once a week.

Data Inside provides a laptop for the student to work with the available data. Due to the sensitive nature of the data, the student is expected to sign a non-disclosure agreement (NDA). As a token of appreciation for the work, Data Inside will offer a monthly internship fee of €400.- and will cover travel expenses.

This project provides a unique opportunity for the student to contribute significantly to the advancement of the non-profit sector and related research. It may also serve as a stepping stone for a fulfilling career in supporting charitable organizations and making a positive impact on society.

Suggested reading

Marketing research in the charity domain is an active and growing subfield. It fits in new philosophy of Better Marketing for a Better World (see the special issue in Journal of Marketing (Volume 85, Issue 3; and specifically Kim et al. 2021). Two other relevant marketing papers that focus somewhat more on retention are Thomas et al. (2015) and Esterzon et al. (2022). Another good source of inspiration for this research is the Bekkers and Wiepking (2011) review paper.

References:

Bekkers, R., & Wiepking, P. (2011). A literature review of empirical studies of philanthropy: Eight mechanisms that drive charitable giving. Nonprofit and Voluntary Sector Quarterly, 40(5), 924–973.

Esterzon, E., Lemmens, A., & Van den Bergh, B. (2022). EXPRESS: Enhancing Donor Agency to Improve Charitable Giving: Strategies and Heterogeneity. Journal of Marketing, 00222429221148969. https://doi.org/10.1177/00222429221148969

Kim Sungjin, Gupta Sachin, Lee Clarence (2021), “Managing Members, Donors, and Member-Donors for Effective Nonprofit Fundraising,” Journal of Marketing, 85 (3), 220–39.

Thomas, S. A., Feng, S., & Krishnan, T. V. (2015). To retain? To upgrade? The effects of direct mail on regular donation behavior. International Journal of Research in Marketing, 32(1), 48–63. https://doi.org/10.1016/j.ijresmar.2014.09.001