There are no absolute values for the key metrics that define success, but the general rule of thumb is that the more people that see a "must see" area of interest (AOI), the more likely you are to achieve higher sales conversion, lead generation and/or brand lift, and vice versa.
A useful way to interpret the results is to do A/B-comparisons and see which iteration of a stimuli that scores best for the identified "must see" areas of interest. This article will give a pointer for what to expect from different results in Sticky.
An area of interest (AOI) is a specific area on your stimulus that you want to know the Sticky metrics for. Sticky allows you to create AOIs on your stimulus in the shape of a rectangle or a polygon.
Seen by (%)
Percentage of how many of the respondents that saw the stimulus actually saw the AOI. This can be interpreted as the stimuli ability to catch attention and get seen. Since being seen is a prerequisite to getting purchased, this is a key metric setting limits for potential sales. The ranges below can be used as a rule of thumb to interpret your results:
90–100% Optimal impact with all/most users being able to see it.
70–90% High impact. Consider the surrounding messaging/imagery of the element to see if there can be improvements in visual balance.
50–70% Medium impact. Try engaging more users by ensuring your visuals/messaging is clear.
10–50% Low impact. Reconsider positioning and/or visual design.
0–10% No impact. If it's not seen it can't influence the user to take action. Reconsider the messaging/visual design.
Time viewed (s)
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. This can be interpreted as the stimuli ability to hold attention. Time spent is demonstrated to have high correlation with real world metrics like "likeability" and recall.
There is a strong correlation between the time we spend looking at something and our perception of and ability to remember that object. What defines a "good number" depends on the amount of information in the AOI. For instance, ads are usually made up of several parts: image, logo, text, etc. These elements require more attention and a longer time for viewers to fully process them.
Seen first by (%)
Percentage of how many of the respondents that saw the stimulus saw this AOI first.
Revisited by (%)
Percentage of how many of the respondents that saw this AOI revisited it. (Looked at it, looked away, then back again)
Time until noticed (s)
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. The time intervals below can be used as a rule of thumb when interpreting your results:
Optimal: Seen in less than 3 seconds.
Average: Seen between 3 and 7 seconds.
Ineffective: Seen after 7 seconds.
Viewable to Seen (s)
The average amount of time from which the AOI was viewable on the screen until respondents saw the AOI. If the respondent did not see the AOI, they are not included in the statistics. Only for video stimulus.
The average amount of time an AOI were shown on the respondents screen. Only for
Clicked by (%)
Percentage of participants who clicked on the AOI.
Number of clicks
The number of clicks within the AOI.
Time to click
The average amount of time it takes for a respondent to click inside the AOI.
The Data Maps are graphical representations that, based on the gaze/click points collected, show the relative visual interest that respondents have given different parts in a media. These are used to understand the overall attention from a large number of people:
Heat Map is blue, green yellow and red; the redder an area is the more it has been seen.
Opacity Map Opposite of a heat map, areas that are not seen will have a dark grey overlay while areas with higher attention will become more visible with a clear overlay
Seen Map is a visualization based on grey, blue and white; a light color concentration means that area was seen by more people compared to an area with a darker color concentration.
Gaze Plot is a visualization showing all individual data points connected with lines per participant. It is most useful to follow the gaze pattern of a smaller set of respondents as it easily gets cluttered with increasing number of participants.
Click Map is a visualization of where the participants decided to click during an experiment. Each green arrow pointer represents an individual click, so there is a possibility of multiple clicks per respondent. Click maps are used in experiments where users are asked to select one of the elements presented on the media e.g. click on the button to sign-up.
Media only is a visualization showing the raw media file.
There is also a corresponding video version (without overlays) for of all the Data Maps. Clicking "Play Video" icon on the image will play a video showing the aggregated participant attention.
In the bottom toolbar you can add overlays such as AOIs, AOI names and Seen order when creating your report.
Seen order shows the typical seen path through the design. It is an eye tracking metric based on the average time it took for people to first see the areas of interest. If less than 25% of people have seen an area of interest, it will be excluded from the seen order.
In the bottom toolbar you can create your custom segmentation group by selecting custom group and inputting all relevant participant IDs for that group into the field that appears.
You can easily share a snapshot of Analytics with your client or other stakeholders who don’t have access to the Sticky application. To share click on “Share” in the bottom toolbar, copy the link and distribute it. The snapshot is not a link to the actual Analytics page, but rather a copy of a state of Analytics at a particular point in time. The snapshot will not be updated automatically when you do overlay changes, in order to update the snapshot click “Update Link”. The URL will be unchanged after updating. Furthermore, you can easily revoke the snapshot by clicking on “Revoke Link.”
Sticky Emotion Analysis works by using opt-in participants to watch your media and tracking their facial expressions through their webcams to pinpoint emotional activity in response to frames and elements in your media. Read more about Sticky Emotion Analysis here.