2. THE PSYCHOLOGICAL PROCESS – Signal detection theory
Signal detection theory describes the trade-off that happens as we decide to attend to or ignore incoming
information. What Psychologists David Green and John Swets called “signal” and “noise” we’ll call good and
bad memes, but the point is the same: information is either useful and relevant to our goals of the moment
or a distraction.
When we shift our threshold to (a) catch more legitimate emails, the cost is to read more spam. When we
shift to (b) ignore more spam, the cost is to miss more legitimate emails. The more legitimate emails and
spam look alike (c) in their graphical treatment, the more errors we make.
We actively adjust our thresholds depending on whether we want to catch more signals or ignore more
noise. But both adjustments have a cost. To catch more signals, we must attend to more noise. To ignore
more noise, we will miss more signals.
For example, Google had been advertising above, below, to the side of, and all around our inboxes, not
unlike the same practice in Microsoft’s Hotmail and Yahoo! Mail. Google had been advertising above, below,
to the side of, and all around our inboxes, not unlike the same. The answer was a smart application of signal
detection theory. They implemented a mix of elements that simultaneously camouflaged their ads among
our emails , but also set the ads apart so no one could accuse them of spamming us. 1.
3. Explanation of how the psychological process is at play in users experience.
1. Instagram:
User Posts Instagram App: Instagram sponsored
vs. organic posts to illustrate the
signal vs. noise example
Analysis: Currently it is quite hard to
distinguish between the good memes
(i.e. users’ organic posts) and the bad
memes (i.e. sponsored ad posts).
Visually – both look similar and users
think of the ads as genuine organic
posts. The users attentional focus is
wasted and they spend more time /
energy distinguishing between posts.
Over time – it will hamper the brand
as users will stop trusting the content.
2.
Instagram:
Advertised
Posts
These are
genuine
Instagram posts
(signals / good
memes)
These are
advertisements
/ sponsored
posts (Noise /
Bad Memes)
4. Recommendation: what changes would better align it with the psychology of the users.
Changes Proposed: Adding more visual context and
clear indicators that the post is an advertisement will
help the users distinguish signals from noise more easily
(signal: organic non-advertised post / noise: ads). This
will ease attentional focus and reduce time and energy
to interpret content.
Visual changes proposed:
1. Have vertical ad banners specifically for
advertisements
2. Re-iterate that this is an advertisement on the
vertical banner
3. Have dark horizontal spacers before the ad posts
Adding Brand
color related
horizontal
spacers before
the ad post
Clarify /re-iterate
it is ad content
Have vertical
ad banners
specifically
for ads
5. Identifying business outcome metrics: how can it be measured before and after the
changes are implemented.
1. Percentage of likes of organic vs. non-organic posts: The percentage of likes for organic posts should
increase as users will be able to focus on original content (good memes)
2. Original content publishers should increase as original content publishers will be more incentivized given
the increase in likes
3. Net promoter score (NPS) should increase as users will feel that Instagram is a more trusted platform
4. The search/explore section of Instagram (which features top content) should see better quality – this will
be potentially measured using interaction rate with posts on that section (i.e. the search/explore)
5. Overall app rating would increase over time (in the app store or play store)
6. Advertising revenue will probably decrease over time – however this should be viewed in light of long-
term engagement rate and increased app downloads by virtue of the platform becoming more trusted
Sources: Evans, D.C., 2017. Bottlenecks : Aligning UX Design with User Psychology, Place of publication not identified]: Apress.
