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Business Goals Vs User Experience: What are good ways to prove or disprove a feature that improves a specific KPI, but will result in lower satisfaction and eventual attrition?

  • Lets say a Product Manager wants to trigger a 'sign-up' modal on every single page the user visits until they have signed up. This will almost certainly improve the sign up KPI, but it will be highly annoying to users. Since there is no way to tell specifically if one user stopped using the site because of all the popups, as there may be other factors, how would you prove/disprove that this feature might improve a specific KPI but will result in lower satisfaction and eventual attrition?

  • Answer:

    You can try and infer certain things purely from data, but data doesn't always give you the full picture. It may seem simple, but just asking users how their experience was can go a long way in helping you understand all that data you've got. We built http://temper.io specifically to help you quickly and easily measure customer satisfaction on a micro level (for example, as part of something like a sign up experience) so you can find out just how happy/frustrated users are with a given interaction.

Josh Pigford at Quora Visit the source

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Brian, Thanks for elaborating on the comment. I'm continuing the conversation here as an answer. For  this specific scenario - an other way could be through usability  studies (a more expensive alternative than a/b testing), however, you  wouldn't have "burned" a potential customer due to the potentially  negative UX.  It depends on how sensitive your target audience might be  to such a UX. From  a cost benefit stand-point however, setting up A-B testing is likely  your best bet both for the short term and the longer term as well (I'm  sure you want to test a number of other things too. http://Optimize.ly is a good solution. PS - I am not associated with this company, other than as a past user) Coming to your question specifically to prove or disprove -- what I believe you are implicitly implying is how to collect data on a specific hypothesis with regards to attributes and their value ala the http://en.wikipedia.org/wiki/Kano_model.  Looking at comparable products and usage rates or testing/customer research IMO are the most straight forward ways to get this data, unless you have some other concept in mind.  If so I would love to know the same too.

Suneetha Malkani

Nobody know this answer except your users! For this you must "ask" them into an indirect way. Because if you'll ask them directly, probably all off them will give you as answer their believes, but not exactly what they really do. For your particular case, the right question is an A/B testing "question". Something like: A - 50% of users will be redirected to pages that show the popup 5 times at 10 visited pages and B - 50% of users will be redirected to pages that show the popup 9 times at 10 visited. after 500-2000 views you can evaluate in which case A/B you have bigger rate of signup. if difference of signup between A and B is greater than 10-15% that mean A is better or B is better. Otherwise, this does not affect to much signup decision. After this A/B testing you can play with different values shown popup/visited pages and you will choose best option. Also as hint is recommended for first 1-3 pages to don't show the popup, because fist of all you must create value in the user mind and then to ask him for signup. An other hint, you can give them some bonuses, according with specific of the website: discount, free ebooks, etc.

Ovidiu Rudi

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