Expert app
My Initial hypothesis.
After doing initial research, I discovered that in spite of so many different social networks, there’s no many apps designed to connect users with reliable experts or providing experts' advices. Precisely, there was Quora (website) which provided general answers, and the only similar app was JustAnswer, which was advertised as "A New Answers App Aims to Succeed Where Quora Failed."
I knew that some people use Quora, but for JustAnswer I have never heard, which made me want to do more research. And I came up with list of possible problems with eventual Expert app:
-Lack of experts
-Experts don’t know for the possibility of making $ via app.
-Niches/directories for advices too narrowed or to wide.
-Expert/seeker mismatch
-A confusing user interface, since there’s two types of users of this app: experts and advice seekers
-Pricing/timing.
I crafted my problem statement:
Our advice seekers need adequate match with an expert because they don’t want to overpay for the advice they don’t need, nor to get some overqualified or someone much more expensive that they want.
We will know this to be true when we test the app with a wider range of different intricacies of advices (different levels of expertise and different times needed to resolve.)
... and then crafted possible solution:
“The user needs to be able to intuitively easily and timely reach and accurate match with the expert. Introducing a timeliness as a category, searching experts with keywords and through categories; and perhaps biding for advices [from expert’s side] would help best match between advice seeker and expert.
Testing Process
User interviews were designed to get more precise picture of volume and possible types of advices the users might need. Also, I believed there was a whole new territory of ideas that I could get for this app, perhaps the whole range of user needs. So that's why I interviewed 4 demographically totally different people: different by country they live in, age, social status, type of career, goals, etc...
The questions were:
1. How often do you need advices from experts?
2. And what type of advices? Private, studies, professional?
3. What type of expert advice do you need most often?
4. What’s the volume of advice do you need most often?
5. What do you do in situation when you need an expert advice? What’s your
first source of information?
6. What would be the best solution for getting advices for you?
first source of information?
6. What would be the best solution for getting advices for you?
7. How do you imagine an ideal omniscient tool?
8. Would there be something that could hook you on seeking advices?
9. When you need some service or information or solution for recurring problem, what needs to happen so that you take your telephone and seek application that might be helpful?
10. For what kind of advice would you pay and in what kind of circumstances?
11. On what terms would you agree to pay the advice?
Results.
I learned that although all testers were different, they shared a lot of similar views, proved also in card sorting.
- They needed experts’ advice at least once per week.
- Each person would first try to google an answer before reaching expert.
- In order to try Expert app they wanted to be sure that the advice comes from reliable and verified experts
- Also they wanted the app to have reasonable, negotiable and competitive pricing.
Some testers needed to talk to expert, and get back from expert
some others to have a video conversation, and some to email a problem and get back from the expert with the resolution. Translated into language of UX, some needed short chat, some video call. And they all wanted to pay the price that was reciprocal with the volume of advice.
For diversity of needed advices/resolutions with an expert I created two user personas. One was Jeanette, student and mother, that often needed to skip long queues at the hospitals and reach expert for advices in regard her baby. Jean, an expert that sometimes needed advices from IT's and he was buying a house so he also needed expert advice about housing and real estate.
User journeys.
The typical user journeys were constructed upon personas of Jean & Jeanette. Jean would usually need succinct advice on how to move on with the coding, while Jeanette would typically need doctor to take a quick look at her child. (To typically give first opinion, should she wait long line-ups at the hospitals or not.)
Task flows.
So, since reliability of experts was main concern of all testers, I wanted that the user to be able to visit expert's page and chat with him/her first before he/she actually gets an advice. Especially since to all users it was important to be able to negotiate and thus that way avoid paying high price if the volume of advice would be small.
Card sorting and iterating the sitemap.
In order to make sure that I am on the right track of making good sitemap, I iterated the initial sitemap by conducting card sorting test with several testers. Actually cards were clustered in several categories indicating that home page is associated with search page. Also clusters were that page with free answers.
Foundational design.
Since the structure of this app should be very simple I have decided for tab bar with carousel of categories. The idea was to make a landing page with a carousel of expert categories that take the user to another carousel with subcategories and then finally a list with experts sorted by proximity and user rating.
Early sketches, Expert app.
Early prototypes.
I sketched some low-fi prototypes based on task flows such as:
1. finding an expert (via carousel)
2. searching an expert (via typing on homepage)
3. video conferencing with an expert
In early low-fi prototypes expert categories were presented in a carousel while experts themselves were presented in a scrollable list.
Low fidelity prototypes. Expert app.
Mid-fidelity prototypes. Expert app.
First mid-fi prototypes. Task of finding an adequate expert seemed easy - at first sight.
Mid-fidelity prototypes. Expert app. Contacting expert and initiating communication that can lead to video calls.
Mid-fidelity prototypes. Expert app. Contacting expert and initiating communication that can lead to video calls.
Testing high-fi prototypes.
The early prototypes were tested on new testers as well as on the testers from the first round of testing.
Among many questions, the testers were asked to perform two tasks:
● Your baby looks like she has some kind of rash, that looks regular baby rash, but you want to make sure what is it. There’s a long line in the clinic. You would like to find pediatrician that could help you. Try Expert app and check what it offers. Find the pediatrician with best reviews and most stars.
● You found some pediatrician with good reviews. Now you would like to get in touch with him, check how much he costs, and show him the baby over the video phone.
They liked how easy it is to find the needed expert, but didn’t clearly get the process of negotiating the price, which some of them they initially asked for.
Test results.
3 major and 2 medium level issues were found.
Issue 1: Need to know the price before stepping into communication. (high)
Suggested Change: Put price on expert’s webpage.
Evidence 4/6 testers frowned at the idea of asking the expert how much he costs in person and not seeing it first
Issue 2: Got stuck with prefab chat dialogue (high)
Suggested Change: Users should be able to video call Expert from his/her page (not to go through chat first).
Evidence: 6/6 testers got confused with prefab chat.
Issue 3: Didn’t know where is the video call (didn’t know they should go through chat) (high)
Suggested Change: Offer possibility of video/calling directly from the experts page.
Evidence: 2/6 of testers directly saw it as flaw and 3.6 of them suggested to add that possibility directly on a webpage.
Issue 4: Users don’t see where the experts are from (medium)
Suggested Change: add experts’ location
Evidence: 2/4 users complained
Issue 5: they don’t see ratings/stars (medium)
Suggested Change: add stars
Evidence: 4/6 users complained
Conclusion:
Getting to the desired expert’s page was not a problem. However, learning about him/her was and getting in contact. The solution is to put all these features upfront (prices and means of communication).So I decided to offer them pricing and choice of communication means on Expert’s page and do the:
Preference test 1.
Preference test has shown that testers generally still preferred the old page (Dr Proctor) over the redesigned one (proka3) mainly for the visual design and its simplicity, in 20:13 or 62% : 38%.
Perhaps to that result contributed the fact that the new page was de facto cluttered with information/options and the question did not clearly accentuate usability over visual design: “Which page makes more sense, (for paid app that connects users and experts)?”.
From comments of those that preferred the new page I concluded that they emphasized practical side and usability (Pricing visible, gives all info, more informative) while those who prefered the old page, liked it for design.
Preference test 2.
So, after these results I have asked myself how can testing results be so contradictory with what the usability test showed, which is mainly problem to get in touch with Expert, learn about it’s price, proximity and everything that I thought that I have fixed.
Then I took the second look onto the new design and realized that there’s too many information including CTA, and the slightly different color of the field with four icons of different means of communication.
I decided to make CTA more intuitive and to delete words such as “How can I help you?” and “Choose means of communication” and delete blank field behind. I decided to leave only icons of means of communication, believing that they’re intuitive enough.
Also, I reformulated the test question into: Which page do you prefer - for paid app which should connect you with the expert?
Finally, repeated test with visual design touch-ups has resulted positive in favor for the new one: 59% to 41%.
Refining the design
For final mockups I decided to use light-yellow (FDF8BD) that suggests serenity (related to reliability of experts the users were looking for) and blue (185091) that suggests amazement.
Playful animated cartoons represent expert categories (which testers liked), while the experts themselves are ten-seconds looped headshots of the experts against the white background.
Further iterations.
Furthermore I did some iterations in order to order every element on a page to fit to a grid. Also, I had to adjust blue color of letters into slightly different color in order to comply with accessibility demands.
Also, the buttons and interface was redesigned in order to comply with iOS standards.
Also new prototype was tested again, and this time the testers were peers-UXers. No one had any remark on navigation and usability. Most remarks were centered around details related to User Interface improvements.
Below you can take a look at further improvements of each designed pages.
New prototype link:
