This document discusses how to design products using data in a startup. It recommends combining different types of user research like surveys, interviews and activity logging to understand user needs and problems. It advocates an agile product development process that incorporates findings from data at each stage of the design cycle. The document provides a case study of how a delivery startup called Ninja Van used data to identify issues, optimize their product and increase signups and order volume. It emphasizes that data should guide but not determine product decisions and more data does not always mean better insights if not analyzed properly.

1. How to design products with data in a startup
6 July 2017
Antoni Lewa Lucian Tan
Product Manager User Experience Designer
by
Data-driven design

3. ★ Established in 2014 as a Last-
Mile Delivery Provider for e-
commerce
★ Proprietary tech on scalable,
cloud-based microservices
platform
○ Web, iOS, Android
★ Now in 7 countries - 80+
cities, after securing
US$32.5M+ Funding till date
(Series B)
Ninja Van
About

4. Employees
➔ Operations
➔ Customer Service
➔ Sales
➔ Drivers
Partners
➔ Ninja Points
Our users
Clients
➔ E-commerce
companies
➔ Traditional
Enterprises
Consumers
➔ Small-scale
shippers
➔ End users

5. Our team
UX DesignerProduct Managers
3 1

6. Data is in fashion.
Source: techrepublic.com
Source: cnbc.com

7. Data comes in all forms
User Surveys
Opinions Behavioural
Market Trends Activity LoggingInterviews

8. “User Research”
User Surveys
Opinions
Interviews
To find the reasons, the ‘why’ behind decisions
(helps to drive the design/concept)

9. Behavioural
Market Reports Activity Logging
To discover real user patterns
(helps to identify the problem that users might not be aware of)

10. Source: checkmarket.com/sample-size-
calculator/
Regardless of market
size,
Sample sizes are similar.

11. Design Cycle
Identifying
Problem
User discovery
Context discovery
Extracting
Insight
Validating
Design
Understanding context
Recognising needs
User Testing
Stakeholder Negotiations

12. Design Cycle
Extracting
Insight
Understanding context
Recognising needs
Identifying
Problem
User discovery
Context discovery
From
Focus group discussion
User Interviews
From
Heuristic evaluation
Data analytics
From (New)
User & Market Research
From (Existing)
Customer feedback
Data analytics
Validating
Design
User Testing
Stakeholder Negotiations

13. What to look for
Drop-off
points
User Types
& Behaviour
Screen
correlation
& real user flows

14. But they can’t tell you
why they exist
Data can inform you about problems
that users can’t identify

15. Product Development Process
How to incorporate findings from data into the
Waterfall
Traditional
Agile (Scrum & Kanban)
Modern

16. Our way: “Triple”
Agile
-track
Validate
Stakeholder buy-in
That’s short
for “Business
As Usual”
Uncovering
Opportunities

17. - Ninja Van’s CTO, who re-quoted it from someone else.
Most decisions should be made around 70% of information.
If you wait for 90%, you’re probably being slow.
Pro Tip 1
never buy time
But you can
You can always
get more
money

18. Case Study
Ninja Early Collect

19. “Click & Collect”
on the rise

20. Shippers
want
Delivery
promises
to be met
Customers
want
Cheaper, Faster
deliveries

21. Identifying
Patterns
&
Capabilities

22. MVP deployed in <1 week

23. 100%Utilisation rate >500Parcels
collected
per day
Positive customer feedback
+

24. Pro Tip 2
not a guarantee
Data is aguide,

25. Case Study
Ninja Easy

26. Rising middle class in S.E.A
Source: economist.com

27. More people shop online
Source: bain.com

28. Link. Send. Get Paid

29. Poor Take-up Rate

30. - Daniel Keys Moran
You can have data without information, but you cannot
have information without data.
Pro Tip 3
You can nevercollect too much
data

31. Observe users for trends

32. Finding the Drop-off
Tapped on button to start providing details
Tapped on button to request rider (after details are
provided)

33. Observe operations for trends

34. Identifying the core issues
On-site
Research
Thailand + Indonesia
Online Primary
Research

35. - Carly Fiorina
The goal is to transform data into
information
and information into insight.
Pro Tip 4
It’s not how big your data
is,It’s how you wield
it

36. Knowing the product
Optimisatio
n
Additional
Features
New ValueKey
Unique
Feature
Ninja Easy

37. If we waited

38. Link. Send. Get Paid

39. Send & Get Paid

40. 200%Daily Sign Up rate
10x
Weekly Order Volume

41. Antoni Lewa Lucian Tan
antoni@ninjavan.co lucian@ninjavan.co
Presented by
fin