Why Is It So Hard To Get Explicit User Feedback Online?
How many times have you seen websites that you visit everyday with messages like: what is your favorite color, brand, size, thumbs up, thumbs down and more seemingly annoying stuff. We all have the same reaction when asked to provide an opinion or assessment. Whats in it for me or GET ME THE HELL OUT OF HERE!
In most instances, sites do not incentivize users enough or provide a true purpose to how the time and information provided by the customer will help. The result is typical users just move on.
Why is this you may ask? generally it seems that the recommendations and their mechanisms are a secret, but an open secret. The user is not conscious of the fact that the site they are visiting has a recommendation system and does not bother to interact with it. If the website adds feedback mechanisms, where they are asked to make a review, or votes by stars, hands, and an endless list, the user loses interest, without realizing that they are loosing a good opportunity to get something back.
One site that breaks the mold is Amazon. The question is why do people bother to vote in Amazon and no where else? Because they know how it works and know the results they will receive. They know that the recommendations help them make educated purchases.
The figure below shows sites where users felt recommendations were a beneficial element, and almost required part of the user experience. It is interesting that customers know that recommendations are useful in e-commerce, but they don´t know about the benefits of recommendations in web searches, entertainment and media, or even social networks.
By:UX Expert Afshan Kirmani
Published: March 23, 2009
Every day we want more things fitted to ourselves, customized to suit our needs, but we are generally lazy as humans and don´t feel like doing anything to get it. Why don’t sites follow the Amazon model and openly say or infer that they need to know your tastes?
Implicit behavior on a site is very useful, and surprisingly it can be tracked and understood. Some recommendation systems such as Strands Recommender are able to learn a customer’s brand preferences, colors, sizes and context automatically as they interact with the site. The goal is making a customer’s life much easier and the experience seamless. Explicit feedback such as ratings, reviews, etc are very powerful and can direct you toward what you want faster. But users need to know how to use explicit feedback to obtain better result from it. A combination of implicit or learned feedback, when paired with implicit feedback can significantly improve the speed of their experience and ease of finding what they want.
Customer’s general stubbornness is hard to beat because their time is valuable, but with good motivation and explanations, even the most stubborn will provide feedback.
What do you think do websites do a good enough job of explaining why their feedback mechanisms are important? Or are we as consumer’s just averse to providing feedback without some incentive? Or both? Send us your comments below and tweet at us @strandsrecs.
xlvector said,
January 23, 2010 @ 3:04 am
Some times, even users themselves do not know what they like or dislike. So, I think mining users’ implicit behavior is important.
When we watch a movie, we can not show our feeling simply by a score, we have complex feelings. So, it is hard to provide explicit feedback.
Explicit feedback may also harmful to recommender systems because a system will neglect implicit feedback if they have enough explicit feedback. Explicit feedback is also very easy to cheating, this is harmful to e-commerce site.
This is why I think study from log data is more important than rating data.
Luz said,
January 24, 2010 @ 1:35 am
Sure, explicit feedback is easy to cheat, but, who really wants to cheat on that? We have to motivate the user to use correctly this kind of service, just for their own profit.
Other thing is, what kind of feedback should have more weight in the recommendation process? Explicit feedback will drive you to the right recommendation, however, implicit feedback sometimes make the engine to misunderstand what you really want: Think in the case of searching for a gift: You spend hours searching for the perfect gift for your mother in law, lots of clicks, views, searches…after your purchase, this buy is going to be taken into account for your next visit. With some kind of explicit opinion you could to avoid this situation, at least: “do not recommend me this again”
Bart Knijnenburg said,
January 25, 2010 @ 1:33 am
I’ve submitted a CHI work-in-progress paper on this issue. As soon as it’s accepted, I’ll post a link here
xlvector said,
January 26, 2010 @ 5:29 pm
I do not mean explicit feedback is not important, I just want to say it has some disadvantage.
Youtube has post a blog and says most of people in youtube only give five stars to video. This may because of UI designment, but it also reflect that explicit feedback only reflect a little part of user preference. In youtube, how long a user watch a video, what related video they click is very important. I admit that implicit feedback has many noise, but I think this is because we have not choose proper features.
However, your example is also right, I think, explicit feedback and implicit feedback have different importance in different field.
I do not mean implicit feedback is more important to explicit feedback, I mean too much researchers are study on explicit feedback and we need to pay more attention on implicit feedback.
Luz said,
January 27, 2010 @ 1:24 am
I agree, the feedback in some sites is not very “serious”.
Should they take into account in a different way explicit and implicit feedback depending on the site? I mean, different type of input for e-commerce than for social media, or social networks, and so on… I think that the “universal recommender” does not exists, and that we
should PERSONALIZE the type or recommeder for each type of site….
(hmmmm, let me think about it for another post!)
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