CSV file: AOI Metrics per participant
CSV file containing all metrics from the Heatmap Analyzer. TTFF, Time spent and more. Both for metrics based on fixations and gazes.
#What does the "AOI Metrics per participant" CSV file contain?
"AOI Metrics per participant" CSV contains all metrics from Heatmap Analyzer (stimuli heatmap).
Eye-tracking and attention metrics are described in the "What is AOI?" article.
#How to download the "AOI Metrics per participant" CSV file?
"AOI Metrics per participant" CSV file, for all study stimuli, is available on the Study -> Results tab.
"AOI Metrics per participant" CSV file, for a single study stimulus, is available on stimulus Heatmap page.
When exporting data from the Heatmap page, it's possible to export it for filtered panelists.
NOTE: Exported CSV file will be empty if there are no saved AOIs.
#What is the "AOI Metrics per participant" CSV file format?
"AOI Metrics per participant" CSV file contains the following columns:
- string study_id - UUID,
- string item_id - UUID,
- string item_filename - the name of your file, as it was named while adding to the study,
- string item_cdn_url - URL to the tested item saved on our servers,
- string item_test_id - UUID (id for a given item for a given participant),
- string participant_id - UUID,
- string participant_external_id - UUID (in case you provide one by connecting your study with an external tool, i.e., a survey),
- string participant_display_name - a name that a participant gives while asked about a name, gender, and age at the end of the study (if you have chosen that option), i.e., "Anna, Female, 27",
- string participant_tags - tags assigned to a participant (added by the study owner),
- string participant_device - type of device a participant used during the study (desktop / smartphone / tablet),
- int participant_quality_grade - participant's overall data quality grade. From 1 to 6, where 1 means "very low", up to 6 meaning "perfect".
- int participant_quality_grade_item - participant's data quality grade for this stimulus. From 1 to 6, where 1 means "very low", up to 6 meaning "perfect".
- int test_item_display_order - a number indicating the order in which the items were displayed,
- int exposure_number - (useful for Live Website and Website Mockup type of studies) indicates the time the participant saw an item, i.e., 1 means that the participant saw this item for the first time,
- string aoi_id - UUID,
- string aoi_name - name of the AOI,
- float fixation_point_x - the x coordinate of fixation expressed as a percentage of the displayed item size,
- float fixation_point_y - the y coordinate of fixation expressed as a percentage of the displayed item size,
- int fixation_starts_at_ms - when the fixation appeared (counting from the beginning of displaying the item),
- int fixation_ends_at_ms - when the fixation disappeared (counting from the beginning of displaying the item),
- int fixation_duration_ms - for how long lasted the fixation,
- int aoi_gaze_total_count
- int aoi_gaze_time_to_first_gaze_at_ms
- int aoi_gaze_total_time_spent_ms
- float aoi_gaze_participant_ratio_percents
- int aoi_visit_total_count
- int aoi_revisit_total_count
- int aoi_revisit_average_count
- int aoi_click_total_count
- int aoi_click_time_to_first_click_ms
- float aoi_k_coefficient
- string external_data_*- all the external variables assigned to the participant (if applicable),
- notes: RealEye version, fixation filter settings [gazepoint interpolation (Hz) - to improve calculations we interpolate the data to 60 Hz; gazepoint interpolation max gap (ms) - we interpolate data if the timestamp gap between two input values is not bigger than this value (50 ms); gaze velocity threshold; min. fixation duration (Ms); max. fixation duration (Ms); moving median range (Ms); saccade max duration (Ms)]; TestCriteria - data was downloaded for participants [age=min:max, isGenderMale={true/false}, isGenderFemale={true/false}, isGenderOther={true/false}, isGenderNotSpecified={true/false}, qualityMin={from1 to 6}, qualityMax={from 1 to 6}, tags={tag1},{tag2},..., keys=KEY{anykey}, isParticipantTypeRealEye={true/false}, isParticipantTypeNonRealEye={true/false}], timestamp of when the file was downloaded.
See the CSV file for the sample study: