## 8 Debriefing & Analysis of Results
### Analysis of Information  
Once the classification of all field notes was completed, an analysis of observed data was performed. The objective of this was to obtain a synthesis of the user experience problems encountered on each urban interface studied. To do so, researchers followed the proposal by [PERSON] [70] who said that a'reduction of data' should be performed in order to obtain concise information. In particular, the following activities were performed:  
Analysis of frequency and repetitionReframer was also used for this step as it allowed field notes to be clustered based on the tags and classifications previously applied. Once this had been done, researchers could analyze the following: The guidelines in which there were more problems and areas of opportunity according to the experience of individuals, and the touchpoints where this occurs with the highest frequency. Figure 16 shows this analysis using the automated parking machines in Cali as an example. Figure 16: Screenshot of analysis of the automated parking machines in Cali performed in Reframer showing the frequency of field notes for each guideline (in blue) and touchpoint (in green). Figure 15: Screenshot of a field note logged in Reframer that corresponds to observations made of the automated parking machines in Cali. Guideline tags (in blue) and touchpoint tags (in green). Observations frequency is made is logged in brackets. Analysis by relationshipIn Reframer existing relationships were reviewed according to the field notes recorded. This allowed researchers to cross reference data and answer questions such as: Which touchpoints demonstrated more problems for a given guideline? Were more problems encountered for a given guideline? Which guidelines have a greater impact on a particular interaction with the interface? In the next case, in Figure 17, it is possible to observe by way of example the relationship between the efficiency guideline and the interface touchpoints of the interface for the automated parking machines in Cali. It is possible to observe that there is a strong relationship between efficiency and the payment touchpoint, and also the moment in which users receive change and obtain a receipt. In addition, it is possible to observe that it has an impact to a lesser extent on the touchpoint Get ticket and Leave. To complement this analysis of the relationships, researchers developed customer experience maps [52] to display the emotional journey for each of the interfaces observed. Researchers used the same touchpoints that had been defined for each interface. A customer experience map was created for each audience or group observed to compare whether differences or relationships exist between these. This was also useful for understanding how the information recorded for each field note related to the user experience of each group of individuals observed. In addition, the time individuals spent completing each touchpoint was recorded in the web-based tool developed for this study. The purpose of this was to obtain information that would help understand the efficiency from a qualitative standpoint. Figure 18 displays the emotional journey of the customer experience map for Group 3: Pensioners on the interface for the automated parking machines in Cali. Identify problems and findingsIn Reframer, researchers organized the list of guidelines once again, this time based on the quantity of field notes that were recorded. This was performed for all the interfaces. Once done, researchers reviewed the texts described in all the field notes that had be logged and classified previously. In particular, they analyzed the concept and ideas mentioned most often. As the field notes had already been tagged, it was possible to identify reoccurring problems in all interfaces that affected user experience, and also the guidelines and touchpoints that these problems relate to.