Design Better Products and Services with Data

The work of a UX Designer is to optimize the experience for users. But how can we determine if our designs are truly better? Unless we measure data, we can’t. In this talk, Jenny will share how she uses data to design products and services around the world.

She will discuss:
* Why designers should embrace data
* Qualitative v.s. quantitative data
* Why A/B tests alone is not enough
* How to use data in design
* Case study: building a UX community with data

This talk was presented at UXDA Chiang Mai, sponsored by Punspace

Transcript

1. D E S I G N B E T T E R P R O D U C T S A N D S E R V I C E S W I T H D ATA Jenny Shen • UXDA Chiang Mai • December 1, 2016
2. UX/UI Consultant J E N N Y S H E N Founder of Ladies that UX Amsterdam Digital Nomad since 2013 ✈ " ✏ @jennyshen jennyshen.com
3. @JennyShen B R A N D S I ’ V E W O R K E D W I T H
4. @JennyShen A welcoming and collaborative community of women, that aim to push the boundaries and promote women in UX. W I N N E R O F . N E T G R A S S R O O T S E V E N T O F T H E Y E A R 2 0 1 5
5. A N D Y O U ? @jennyshen D E V E L O P E R U X / D E S I G N E R M A R K E T I N G / P R O D U C T B U S I N E S S / F O U N D E R
6. A N D Y O U ? @jennyshen D E V E L O P E R U X / D E S I G N E R M A R K E T I N G / P R O D U C T B U S I N E S S / F O U N D E R
7. A N D Y O U ? @jennyshen D E V E L O P E R U X / D E S I G N E R M A R K E T I N G / P R O D U C T B U S I N E S S / F O U N D E R
8. A N D Y O U ? @jennyshen D E V E L O P E R U X / D E S I G N E R M A R K E T I N G / P R O D U C T B U S I N E S S / F O U N D E R
9. O N C E U P O N A T I M E … @jennyshen
10. • Why designers should embrace data • Quantitative v.s. qualitative data • Why A/B tests alone is not enough • How to use data in design • Case study: Building a UX community with data TA L K O U T L I N E @jennyshen
11. W H Y D E S I G N E R S S H O U L D E M B R A C E D ATA @jennyshen
12. • You are not the user • Personal opinions don’t matter • Gut feelings can be wrong • Convince stakeholders • Know how your designs perform W H Y D E S I G N E R S S H O U L D E M B R A C E D ATA @jennyshen
13. Q U A N T I TAT I V E V. S . Q U A L I TAT I V E @jennyshen
14. Q U A N T I TAT I V E D ATA • Numerical • Who, when, what, where @jennyshen
15. Q U A N T I TAT I V E D ATA • Conversion rate • Session duration • Bounce rate • Exit rate • Page views @jennyshen
16. @jennyshen
17. Q U A L I TAT I V E D ATA • Non-numerical • How, why = the user experience @jennyshen
18. Q U A L I TAT I V E D ATA • The pains your product/service solve • The ease of use of your product/service • How likely users will recommend your product/service to others • Why users chose your product/service over competitors’ and vice versa @jennyshen
19. @jennyshen
20. • Usability tests • Customer service tools • Focus groups • Recordings • Interviews • Contextual inquiry @jennyshen
21. A method to compare two versions of a web page to see which one performs better A / B T E S T I N G @jennyshen
22. @jennyshen
23. D I S A D VA N TA G E S O F A / B T E S T S • GA: Can’t set who sees version 1 v.s. who sees version 2, or even how long the test is • Expensive to build • Doesn’t tell you why @jennyshen
24. A/B testing can’t tell you if you’re solving the correct problem. “ —Kevin Stone, Senior Product Designer at JUST EAT @jennyshen
25. W H E N T O A / B T E S T • Before you roll out a change • When you have a strategic hypothesis of why the alternate version can perform better @jennyshen
26. N O T A G O O D H Y P O T H E S I S Let’s use blue for CTA because company ABC uses blue. G O O D H Y P O T H E S I S Based on recorded sessions, users seem to have trouble proceeding with purchase. By moving up the CTA to above cart items, we can increase the conversion rate. @jennyshen
27. U S I N G D ATA I N D E S I G N @jennyshen
28. • What do you want to find out? • What are your success metrics? S TA RT W I T H A Q U E S T I O N @jennyshen
29. Research Hypothesize Experiment Measure Analyze @jennyshen
30. C A S E S T U D Y: B U I L D I N G LT U X C O M M U N I T Y @jennyshen
31. • Men v.s. women ratio in UX/tech meetups • Diversity research • Other women in tech groups Research Hypothesize Experiment Measure Analyze @jennyshen
32. “Other female UXers in Amsterdam also want to meet other female UXers and a safe place to discuss our daily struggles.” Research Hypothesize Experiment Measure Analyze @jennyshen
33. • Started LTUX Amsterdam Meetup group • Invited female UXers • Announced in other UX meetups • Hosted 1 meetup per month Research Hypothesize Experiment Measure Analyze @jennyshen
34. Research Hypothesize Experiment Measure Analyze • Growth rate • Attendance • Active members • Feedback • Reviews @jennyshen
35. Research Hypothesize Experiment Measure Analyze • +2 co-organizers, 2 volunteers • 778 members • 19 group reviews • +60 members per month on Meet-up • +20 members per month on Facebook • +1 city in The Netherlands— LTUX Utrecht @jennyshen
36. Research Hypothesize Experiment Measure Analyze • Avg 58 members in talk events • Avg 22 members in workshops • Avg 22 members in social events • Avg 200 active members per month @jennyshen
37. Research Hypothesize Experiment Measure Analyze “Always great and relevant topics with speakers from across the UX sector. This group is enthusiastic and very welcoming! Join us! ” —Carmen “A great mix of people from all over the world while also being from different fields. The atmosphere encourages creativity and learning.” —Sherin @jennyshen
38. Research Hypothesize Experiment Measure Analyze “Very nice atmosphere, friendly and well organized, these ladies know how to do it, super recommended.” —Mirko “A very nice group of UX professionals who are open to sharing their knowledge in a friendly environment. Great experiences until now. Keep up the good work!” —Anca @jennyshen
39. Research Hypothesize Experiment Measure Analyze How much do you agree with: “LTUX Amsterdam is a welcoming community that promotes women in UX” From 1 to 7, we scored 5.94 @jennyshen
40. Research Hypothesize Experiment Measure Analyze How much do you agree with: “LTUX Amsterdam is offering a good variety of meetups” From 1 to 7, we scored 5.30 @jennyshen
41. Research Hypothesize Experiment Measure Analyze How much do you agree with: “I am a part of the LTUX Amsterdam community” From 1 to 7, we scored 4.32 @jennyshen
42. Research Hypothesize Experiment Measure Analyze • Low attendance on Wednesdays • Few speakers attend meetups • How members feel about being a part of the community (4.32/7) can do better • Harder to acquire sponsorships @jennyshen
43. “People are busier with work on Wednesdays compared to Thursdays, so they will prioritize other things over a social event, especially when the location is outside of the city centre.” Research Hypothesize Experiment Measure Analyze @jennyshen
44. “If we engage members and speakers more and build relationships, they will feel that they are a part of the community. Then they will want to be involved and contribute more.” Research Hypothesize Experiment Measure Analyze @jennyshen
45. • Talk with active members in-person • Ask other LTUX cities how they do this Research Hypothesize Experiment Measure Analyze @jennyshen
46. “Members who have no speaking experience want to speak, but are intimidated by long presentations on the stage. If we introduce low- barrier speaking opportunities, they are more likely to participate.” Research Hypothesize Experiment Measure Analyze @jennyshen
47. • More interactive talks like PechaKucha • Involve members to be speakers • Train members to be speakers • Mentorship program Research Hypothesize Experiment Measure Analyze @jennyshen
48. 5 TA K E AWAY S @jennyshen
49. • Use data in your design process • Measure qualitative and quantitative data • Base A/B tests on strategic hypothesis • When looking at data, have a question in mind • Research, Hypothesize, Experiment, Measure, Analyze 5 TA K E AWAY S @jennyshen
50. @JennyShen Chiang Mai? ladiesthatux.com/start-your-own Bangkok? Your city?
51. S AY H E L L O @jennyshen jenny@jennyshen.com jennyshen.com
52. F E E D B A C K F O R M @jennyshen bit.ly/UXfeedback
53. T H A N K S Y ’ A L L ! @jennyshen