Still Day One
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Still Day One

How People find their Perfect Car

Understanding the complete buying journey of (potential) Audi customers

SinnerSchrader has been Audi’s digital lead agency since 2016. Malte Grapentin, Neeraj Verma, and myself, Hanna Rosinski, Strategists and User Researchers at SinnerSchrader, conducted a longitudinal research approach in collaboration with Audi to fully understand the user experience of people searching for a car on Audi’s digital platforms.

Through “simultaneous method triangulation” we were able to truly understand people’s car-buying behavior and grasp their implicit and explicit motives. It’s a beautiful example of how applying a completely different, holistic, and multifaceted research approach leads to striking results about people’s behavior and clear insights on how to shape products that fit these needs.

Within Audi, user research is a fully integrated part of the design and development process enabling product teams to learn and innovate continuously. This guarantees that both strategic and design decisions are based on research findings, therefore minimizing prejudices, opinions, and assumptions about the end user’s behavior.

To maximize the users’ digital experience of buying a car, Audi wanted to deepen their own knowledge of how users currently search for and purchase a new vehicle. What micro-moments do the users undergo? Which touchpoints do they use and how do they switch between information sources? And above all, how open-minded are people to changing their minds about a particular brand, type of vehicle, or engine type during their purchase process?

By applying a so-called method triangulation approach, we were able to shed light on these topics and understand the complete buying journey of premium car buyers in detail.

What is method triangulation and what is it good for?

Method triangulation is the combination of multiple research methods, ideally applied simultaneously. Innovative digital players like Spotify have been making use of interdisciplinary longitudinal mixed-method research for quite some time now, reporting benefits such as richer insights, higher certainty, and fewer discrepancies.

To understand the buying journey of premium car buyers, especially of people interested in purchasing an Audi, we adopted this innovative approach.

For that we examined the topic from multiple perspectives, investing creativity while maintaining validity and reliability. To do so, we collected behavioral and attitudinal as well as qualitative and quantitative data to mitigate potential blind spots that a single research method alone might imply.

In a first quantitative survey across different markets, we gathered initial insights into how users go about searching for a car. We were able to identify different groups of car buyers, understand their specific differences and compare their behavior across markets.

These far-reaching insights formed the basis for a subsequent diary study in which we sought an even more in-depth understanding of people's buying behavior. In this diary study, we followed 10 users over the course of 6 weeks who were looking to buy a new car and were all actively considering buying an Audi.

Writing a love letter to the car search

Through the use of the app “dscout”, participants shared their experiences of looking for a new car at least every two days with us. Every two days, different question parts were activated, covering various topics of the car-buying journey.

By evolving the questions throughout the diary study, based on what we had already learned and the participants’ current search behavior, we were able to gradually gain a better and further understanding of the complete purchase process. One task involved writing a love letter to the car search, which gave us insights into the users’ high points, while a break-up letter showed us the pain points, frustrations, and downsides they were experiencing.

Screencasting exercises helped us to understand how users move between different sources of information and how they compare models from different brands. Each part of the questions consisted of a video recording where users talked about the steps they took to get closer to their goal of finding a suitable car, explained to us what the perfect digital buying journey would look like, or when and how they use which touchpoint on which digital device.

Through these different tasks and question types, and especially by following up on the diary entries, we managed to understand the complete buying journey from the identification of a need to the actual purchase of the car in every detail.

But as we know, what people say and what they do is often very different. So we simultaneously tracked our participants’ search behavior on the audi.de and on the audi-boerse.de. We teamed up with the Data Analytics Team to develop a Plug-in that enabled us to identify our participants and track their behavior over the course of the diary study.

Combining those two quite complementary perspectives, which mutually enhance each other in the analysis, gave us a complete and comprehensive picture of how users search for a car.

What are the major findings from this research?

Taking the findings from the initial quantitative survey and enriching them with the insights from the diary study as well as the behavioral tracking yielded striking discoveries about the search behavior of premium car buyers.

1. Everyone starts without a specific idea of which car they want.

No matter how experienced users are with buying a car everyone starts at the same spot, with a fixed price and size in mind. Thereby, users are completely open towards the brand, the engine type, and whether they are looking for a new or a used car.

2. Everyone is looking at used cars even when they intend to buy a new car.

Even people interested in new cars are looking at used cars to compare or find a car that fits their budget and that comes as close as possible to their dream car. Especially, the loss of value of a new car once it hits the road plays a significant role here and causes users to monitor the used car market closely. It became clear that in the end, the best offer determines the decision, not the fact whether it is a new or a used car.

3. Everyone experiences a messy middle during their buying journey.

Right after users identify the need for a new car and start their search process, the messy middle begins, where no typical step-by-step journey can be defined. Here, an uncontrolled going back and forth, comparing information, and jumping between several browser tabs and apps takes place. It seems to be a constant process of exploring and evaluating. If one source does not directly give the user the desired information, another site is called upon to not waste too much time and energy. Emotions range from excitement and curiosity to frustration and overload. It’s the place where people spend the most amount of time in their car buying journey and it is also the most crucial step as people who come out of the messy middle have a shortlist of cars which they mostly stick to.

Wrapping it all up

Although buying journeys are highly complex and an individual enterprise, there are discernible patterns. Everyone goes through five phases when buying a car: Having identified a clear need for a new car, people start to look for suitable cars that fit their expectations. This search process can be seen as the messy middle. The result from this messy middle is a shortlist of cars that people often stick to, except when a better offer crosses their path. Once a decision point is reached where users decide on one or two suitable cars they start to search for the best deal. The offer that triggers the best feeling is selected. Thereby, it does not matter how far away the respective dealer is. Price differences and delivery times are the crucial deciding factors here.

The richness of the results and the validation of the findings from different perspectives clearly showed us the advantage of mixed-method triangulation and allowed us to achieve results that can be applied to all premium car buyers. In the future, we will continue to apply multiple research methods simultaneously to avoid blind spots or unexplainable contradictions.

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