A new segmentation based on traveler needs

The study consisted of three parts:

1. Understanding current traveler needs.
2. Creating a segmentation based on those needs.
3. For each segment, map traveler satisfaction throughout the customer journey.

A key criterion in the study was being able to quantify the segments found and being able to target the segments (i.e.: provide insight into how travelers can be identified as members of a segment).

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Different areas of expertise and research methodologies

In order to best assist GVB, Blauw assembled a project team with experts. Several research methodologies were used. This is the phased approach:

Community research

A qualitative survey was designed to gather the breadth of traveler needs. Qualitative research is the best method for needs assessment because it offers the opportunity to ask thorough questions on given answers and gather in-depth insights through various assignments and questioning techniques. In this case: what travelers find important when traveling in Amsterdam.

During one week, different target groups were asked about their experiences traveling in Amsterdam. These were residents of Amsterdam, commuters who travel to Amsterdam regularly and people who have visited Amsterdam recently. They kept an online diary, shared their experiences and responded to statements. The community research provided insight into:

• needs regarding planning and preparing a trip;
• considerations when choosing car, public transport, shared bike, cab or other means of transportation.
• current perceptions when traveling in Amsterdam and (partially) unmet needs, until arrival at the destination.

But qualitative research you want to be able to validate. Quantitative research was needed to quantify the findings. An online survey was set up for this part.

Online survey

The online survey not only had to validate the findings from the initial research project. It also needed to perform statistical analysis to arrive at segments. In addition, the survey served to identify the customer journey for each segment (from place of departure to destination).

The online questionnaire consisted of questions about profile characteristics such as age, education, postal code and possible limitations to travel. Attitudes about travelling by car and public transport and travel behavior in Amsterdam were also asked. The 25 needs that emerged during the community survey were validated in this phase.

For each need we were able to determine the extent to which travelers recognize themselves in that need. Mirroring this, we asked how satisfied people are with the way in which their needs are met. Additional statistical analyses revealed which needs per segment are most promising. That is, if those needs are better met, traveler satisfaction will increase significantly.

After this fieldwork, we started working on segmentation based on the survey. What is unique about this process is that the profiles were segmented based on needs. Often profiles are based purely on demographic characteristics.

Using a needs segmentation to look at your target audience

We used statistical analysis to examine which needs are unique within groups and to see how many groups you can get at all if you cluster by needs. Needs formed the basis of the segments and these were then dressed up with profile characteristics that were strikingly common to that profile. To give the target group a face, characters were designed.

To avoid delivering the results as bare tables, posters were chosen as deliverables. On these, the characters are represented and provided with characteristics that typify the segment.

An important condition from GVB was that the results had to be targetable. Therefore, we mapped what the absolute numbers of the segments are, what the share of a segment is within the traveler population, how many trips that segment makes, etc. This helps data analysts and/or marketing analysts to make calculations: if GVB succeeds in serving a segment better, what could that yield in terms of number of trips?

But this data also helps make choices: which segments can GVB best respond to first when looking at volumes?

In addition to this comprehensive analysis of the segments, golden questions were formulated. These are questions on the basis of which you can quickly determine to which profile someone belongs. GVB itself already has insight into passenger flows via chip data, but that is completely anonymous. Using these golden questions and the data from the segmentation research, GVB can enrich this data. This gives them a lot of valuable traveler information: entirely with the goal of increasing traveler satisfaction.

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