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Session Overview
D 3: GOR Best Practice Award 2020 Competition III
Thursday, 10/Sep/2020:
3:30 - 4:30

Session Chair: Alexandra Wachenfeld-Schell, GIM & DGOF, Germany
Session Chair: Otto Hellwig, respondi AG & DGOF, Germany

The presentations in this session will be in German.

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Beyond the Real Voice of the Customer: Emotion measurement with Artificial Intelligence in advertising research

Malte Freksa1, Sandra Vitt2, Holger Lütters3, Dima Feller4, Kim Rogers1

1GapFish GmbH, Germany; 2RTL Mediengruppe, Germany; 3HTW Berlin, Germany; 4Pangea Labs, Germany

The important role of emotions in advertising is undoubted and researchers are experimenting with different ways to measure emotion. According to linguist scientist Sendlmeier “voice conveys our emotional state of mind in the most differentiated way”. With digital speech assistant technology and artificial intelligence new opportunities for research arise.

In the study voice data collection followed up by a high-end automatized emotion data analytics process was implemented in an online research design. The goal of this approach is a) to examine whether this approach is implementable from a technological point of view (realization)

b) to critically analyze the emotion analytic outcome from a research perspective (validation).

An online-representative sample was recruited: participants were confronted with an experimental setting of online video campaigns, audio ads and Instagram ads. After completing a classic item battery for advertising research, participants had to answer questions with their microphone from the device they were using. The device agnostic approach allows to include Desktop, Laptop, Tablet and Smartphone in the research design. The audio data is analyzed with two API AI approaches:

a) automatic transcription from voice into text (“what”)

b) emotional analysis of the tonality of the voice (“how”).

As results the approach offers the content and the analysis of 21 emotional facettes out of the audiofile for each participant.

This research design was effective from a technical perspective: 859 participants (out of 3760 starters) could be analyzed including emotional profiles from each answer. The voice analytic approach shows interesting divergence from the classic answer patterns. Further research approaches should focus in detail on the validity of the emotional scores from audio interactions.

The study combined for the first time an automatized data collection and analytics API approach of voice data with automation in transcription and emotional impact measurement. The promising results clearly show the power of artificial intelligence driven research approaches which will change the landscape of research very soon.

Monetization of customer value in the rail business: Improving yield, revenues and customer relationship at the same time is possible - the case of WESTbahn in Austria

Andreas Krämer1,2, Gerd Wilger2, Thomas Posch3

1University of Applied Sciences Europe, Germany; 2exeo Strategic Consulting AG, Germany; 3WESTbahn Management GmbH, Austria

Relevance & Research Question:

Since the market entry of the WESTbahn in December 2011, Austrian rail passengers have the choice been between two railway companies on the Western route (Vienna - Salzburg). WESTbahn pursues among others the goal of attracting long-term customers through a very good range of rail services at very low prices (Koroschetz 2014). In this context, the question arises whether further growth in demand is realistic even if WESTbahn better meets customers' willingness to pay thanks to a differentiated ticket structure.

Methods & Data:

In order to ensure a holistic market and customer perspective, different empirical studies were conducted in 2019 and later linked together: First. a representative study focusing on travelers on the Western Line, second a customer survey (offline) during the train journey, and third a survey of ticket buyers on Secondary data and information of sales and revenue management systems were used to validate the survey results.


While the market study supports the hypothesis that the railways as a whole have growth potential on the Western Line, it has become apparent that the price as a determinant plays a central role for future growth. To understand the opportunities for shifts in demand within the rail system, customer segmentation is essential, which describes the affinity of rail customers for WESTbahn and OEBB. In the case of the existing WESTbahn customers, there was a considerable spread in willingness to pay, which could be used to differentiate the ticket structure.

Added Value:

Since the fall of 2018, several changes have been made in WESTbahn's price and revenue management (prices have been partly raised, partly reduced, resulting in a stronger price differentiation). Customer surveys supported the project at all stages (conception, testing, implementation, monitoring). As a result, WESTbahn not only continued to grow through demand gains, but also achieved a change in the ticket mix, price levels and double-digit sales growth. At the same time, WESTbahn achieves top marks in terms of customer satisfaction and the intention to recommend.

How to identify future trends in the automotive industry at an early stage of development by relying on access panel surveys?

Patrick Schlickmann1, Jim Walker1, Heiko Rother2, Hauke Witting2

1SKOPOS GmbH & Co. KG, Germany; 2Asahi Kasei Europe GmbH, Germany

Relevance & Research Question: Due to growing environmental requirements, increasing autonomy and changes in mobility behavior, the automotive industry is facing great challenges. Suppliers are under pressure to identify and implement new developments and customer requirements at an early stage in order to keep up with the highly competitive automotive market.

One of the areas in which Asahi Kasei specializes are surfaces and acoustics for vehicle interiors. SKOPOS supports them in establishing which requirements and wishes customers will have regarding vehicle interiors of the future resulting from the changing role of car sharing and autonomous driving.

Answering these questions confronted us with the challenges of not limiting the participants in their thinking about future developments whilst simultaneously leading them towards products from the Asahi Kasei product range.

Methods & Data: We chose a standard quantitative online approach - but with a twist. We presented car drivers and those open to car sharing with a primarily quantitative questionnaire, assessing their mobility behavior and the evaluation of (future) car features regarding their own and shared cars. The twist: We also implemented open questions based on our experience with online research communities, to maximize involvement and effort leading to better and more creative output.

Results: Cleanliness inside the car, especially in car sharing, is the most important factor when it comes to the interior of a car. The overall usability of features within the interior of a car is more important than premium surfaces. Finally, participants responded to open questions with longer and more extensive answers compared to similar automotive studies.

Added Value: The holistic and individualistic approach we followed with our research has proven to be very useful for Asahi Kasei and their business problem. Beginning with the development of the questionnaire, the analysis of the collected data and finally the consultation based on the results: Despite limited budget and time constraints, we were able to lay the groundwork for Asahi Kasei’s future developments of car interiors, enabling them to present the results to current and future customers. In addition, we successfully introduced them to the wonderful world of market research!

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