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AOI Metrics: what they mean and how they are calculated

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When setting up a Sticky experiment, you are able to define AOI for which you want to generate eye tracking statistics.

The key metrics are available on the Analytics page:

  • Seen by, % (percent_fixating)
    Percentage of how many of the respondents that saw the stimulus actually saw the AOI. Calculation: number of participants fixating on this AOI divided by total number of participants who saw this stimulus.

  • Time viewed, seconds (avg_time_fixating)
    The average amount of time that a respondent spends on an AOI. If the respondent did not see the AOI, they are not included in the statistics. Calculation: The sum of the (end - start) sub-periods of times for each participant where the fixation overlaps the AOI in X and Y and time for a least a sub-period of the fixation for all participants with the result divided by the number of total participants who had at least 1 fixation within the AOI. If a participant did not see the AOI, they are not included in the statistics.

  • Seen first by, % (percent_first_fixating)
    Percentage of how many of the respondents that saw the stimulus saw this AOI first. Calculation: num_first_fixating / total participants who saw this stimulus.

  • Revisited by, % (percent_fixated_revisiting)
    Percentage of how many of the respondents that saw this AOI revisited it. Looked at it, looked away, then back again. Calculation: Participants that visited AOI more than once / total participants who saw this AOI.

  • Time until noticed, seconds (avg_time_to_first_fixation)
    The average amount of time it takes for a respondent to see an AOI. Respondents that does not see the AOI will not be included in the statistics. Calculation: For all participants who have at least 1 fixation which overlaps in time and space for at least a sub-period of this AOI, calculate the elapsed time from the onset of the stimulus to the start time of the first fixation where it overlaps with the AOI. Participants who do not see the AOI are removed from the calculation. If an AOI starts after the beginning of the stimulus, fixations which are located inside the AOI before it starts or after it ends are not counted.

  • Viewable to seen, seconds (avg_time_to_first_fixation_since_viewable)
    The average amount of time from which the AOI was viewable on the screen until respondents saw the AOI. Only for video stimulus.

  • Duration, seconds (duration)
    The average amount of time an AOI were shown on the respondents screen. Only for video stimulus.

  • Clicked by, % (percent_clicking)
    Percentage of participants who clicked on the AOI. Calculation: Number of participants who clicked in the AOI / total participants who saw this stimulus.

  • Number of clicks (num_clicks)
    The number of clicks which happen within the AOI.

  • Time to click, seconds (avg_time_to_first_click)
    The average amount of time it takes for a respondent to click inside the AOI. Calculation: The amount of time between the onset of the stimulus and the first click which is registered / number of participants who clicked at least once.

When you download full statistics, the .xlsx files also include the following metrics:

  • Average fixation duration, seconds (avg_fixation_duration)
    The average amount of time a respondent spends on an AOI per time they look at it. This means that if a respondent looks at the AOI for three seconds, then look away for a short while and then back at the AOI for another 1 second. The average would be 2 seconds. ((1+3)/2)=2. The average length (end - start) of all fixations which overlap at least partially with this AOI. If an AOI partially overlaps in time, only the overlapping time is counted.

  •  Average media exposure, seconds (media_avg_exposure_time)
    The average number of seconds the stimulus where shown on the respondents screen. Calculation: the average length of the stimulus event for all participants who saw it.

  • Maximum media exposure, seconds (media_max_exposure_time)
    The maximum amount of seconds a stimulus were shown on the respondents screen. Calculation: the maximum length of the stimulus event for all participants who saw it.

  • Media exposure, seconds (media_exposure_time)
    The amount of seconds a stimulus were shown on the respondent's screen.

  • Media sample size (media_sample_size)
    The number of participants that saw the stimulus. Calculation: the number of participants in the sample.

  • Number of Fixations (num_fixations)
    The amount of total fixations inside the AOI. Calculation: For all fixations, if the fixation overlaps the AOI in x and y and in time for at least a sub-period of the fixation, increment the number of fixations for this AOI.

  • Number fixating (num_fixating)
    Number of participants who have had at least 1 fixation on the AOI. Calculation: The number of participants with at least 1 fixation which overlaps in time and space at least partially with this AOI.

  • Number of revisiting (num_fixating_revisiting)
    Total number of respondents that revisited an AOI. Looked at it, looked away, then back again. Calculation: The total number of participants who have gaze points within this AOI and then leave for at least 1 gaze point and then return to the same AOI.

  • Number of first fixating (num_first_fixating)
    Number of participants that saw this AOI first in the stimuli. Note that if there are many AOIs overlapping each other these numbers will turn multiple. Calculation: The number of participants who's first time they intersect with any AOI they intersect with this one. Note that they can have multiple that they note 'first' if the AOIs overlap in time and space.

  • Number of Visits (num_visits)
    Total number of times respondents visited an AOI. Calculation: The total number of times where a participant had a fixation which was in this AOI and then had at least 1 fixation which was not within the AOI. If they had 2 fixations within the AOI then 3 out then 1 back in, they would have 2 visits to this AOI.

  • Percent of total revisiting, % (percent_total_revisiting)
    Percentage of how many of the respondents that saw the stimulus revisited this AOI. Looked at it, looked away, then back again. Calculation: Participants that visited AOI more than once / total participants who saw this stimulus.

  • Average number of visits before this one (avg_num_aoi_visits_before_this_one)
    The average amount of other AOIs the participants who have seen this AOI looked at before they saw this one. Calculation: The number of AOIs each participant sees before this one / total participants who saw this AOI.

  • Number clicking (num_clicking)
    Calculation: The number of participants with at least 1 click which happens within the AOI. 

  • Percent of total clicks, % (percent_of_total_clicks)
    Calculation: num_clicks / total clicks on stimulus across all participants.

  • Total fixation duration, seconds (total_fixation_duration)
    Length of time participant looked at the AOI. Calculation: Sum the (end - start) times for all fixations which overlap this AOI in x and y and time for at least a sub-period of the fixation and the time the AOI was present. If there are 2 AOIs with the same name which are viewed at the same time, the union of their viewing times is added. They are not double counted for time.

  • Average time in viewport, seconds (avg_time_in_viewport)
    Amount of time an AOI was visible in the screen. For scrollable webpages, portions of the stimulus can be hidden during participant interaction.

  • Average fixation rank, seconds (avg_first_fixation_rank)
    The number of AOIs which were looked at before this one on average. Calculation: The rank of avg_time_to_first_fixation across all AOIs starting at 1 and sorted from the shortest to the longest avg_time_to_first_fixation. If multiple AOIs have the same value, they are all given the lowest rank and then the next AOI starts at the rate which is the total number of AOIS before it. If an AOI received no fixations, its value is the total number of AOIs that exist.

  • Seen Order
    The typical seen path through the design. It is based on the average time it took for people to first see the areas of interest.  Our algorithm to group the order in which the AOIs were observed on average. When multiple times are very close together we assume part of the population looked into different paths and we show a split into attention. If less than 25% of people have seen an AOI, it will be excluded from the seen order. This calculation is extrapolated from the avg_first_fixation_rank and avg_time_to_first_fixation calculations.

  • Standard deviation of time fixation, seconds (stdev_time_fixating)
    The standard deviation of the avg_time_fixating metric. All standard deviations on the platform use Zero Delta Degrees of Freedom.

  • Standard deviation of time to first fixation, seconds (stdev_time_to_first_fixation)
    The standard deviation of the avg_time_to_first_fixation metric. All standard deviations on the platform use Zero Delta Degrees of Freedom.

  • Word Count
    A number of words written in the AOI as set up by the user. Used for readability metrics: Read Percentage and Read Guidance.

  • Read Percentage, %
    Calculated as the average percentage of text read in the AOI. RP = (Time viewed × words per second / word_count) × 100. If word_count is not set, the value is 0.

  • Points
    The X and Y positions of the points that define the AOI within the stimulus. Positions are defined in percentage of the stimulus dimensions ranging from 0 to 1.

  • Read Guidance
    It is how Read Percentage (RP) results are interpreted. Read (RP ≥ 70%), Glanced (50% ≤ RP < 70%), Skimmed (0 ≤ RP < 50%). If word_count is not set, the value is N/A.

 Important notes:

  • Sticky's hardware eye tracking does apply the Tobii Pro I-VT fixation filter in order to resolve gaze data. To learn more about the Tobii Pro I-VT fixation filter please read about eye movement classification.

  • Sticky's webcam eye tracking does not apply any fixation filter in order to resolve gaze data. This means that the fixation metrics above are based on raw gaze data. The reasoning behind this is that web cameras provide too few data points (15 to 30 Hz). However, the use of a relevant sample size (approx. 30 usable) has shown that the technology does give normalized data distribution where the error can be decided by an average deviation (a deviation normally measured in degrees but also as percentage of the screen or as pixels).

  • The data provided by the platform is founded on sessions with a higher quality, i.e. all sessions have passed a data validation check1 where significant outliers are identified and removed (classified as “unusable”).   

  • Participants with bad data, or who did not see this stimulus are removed from the sample before statistics are calculated and are not included in the final data.

Overlap between a fixation and an AOI is always considered to be that:

  • The quality for the fixation is 'good'.

  • The x and y location of the fixation fall within the bounds of the AOI.

  • If end time for the fixation happened before the start time of the fixation, it is not an overlap.

  • If start time for the fixation happened after the end time of the fixation, it is not an overlap.

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