Essential tools for Product managers and marketeers to understand the levers to pull for growing user base and engaging users

1. How to think through
growth and engaging users
By: Manu Rekhi
Managing Director, Inventus Capital
Contribution by: Jen Granito, Kamo, Gaurav

2. Session Flow
➔ Understanding Consumers
➔ Growth & Engagement Rules
➔ Think like an Optimizer
➔ Optimizing on the Web
➔ Birds & Bees - Growing your user base
➔ Measuring Virality
➔ Case Study 1
➔ Case Study 2

3. Understanding Consumers
Multidisciplinary

4. User Life Cycle
Before they buy
Referral
Repeat Purchases
First purchase

5. User Thought Cycle
I hate change
“You should
check this out!”
What is this?
What was the name
of that app again?

6. Business Life Cycle
Conversion
Advertising
Retention
Virality

7. 5 RULES OF GROWTH
Helps optimize hill but doesn’t help with
finding the next mountain

8. 1. LISTEN & LEARN

9. Leave your computer

10. Talk to them

11. Encourage user feedback and implement features and
solutions that increase engagement.
Feedback: I find a fare
on my mobile device, but it
disappears when I try to
book it later on.
Hipmunk solves it beautifully and offers
it at the right time of the user flow.

12. Prices and discounts are the strongest and most engaging features
Reviews are also a strong value in decision making
Prices
Reviews
DiscountsDiscovery
LocationAware Times
Feedback
Non-stop
Interaction

13. 2. EXPERIMENT

14. Test assumptions every day
Organize around small nimble teams
Be results oriented
Define success metrics

15. 3. DELIVER

16. Focus on quality
Research shows that users are more likely
to invite friends to apps with high
production values.

17. 4. TRACK

18. We are in the Age of Big Data
Data is plentiful
Asking the right question is hard

19. Data Driven

20. Gmail - Inducing growth
More invitations you receive, more likely you are to join – up to a saturation point
Current saturation occurs between 2 and 3 invites.
Sending more invitations helps, even if it is to the same email address

21. 5. ADAPT
Rinse, Repeat, Recycle

22. Atomic Use Case “Aha moment”
…refers to flow or flow of products/feature
that predictably “gets” your target user
Aha moment: https://medium.com/parsa-vc/how-to-discover-your-apps-aha-moment-5f75dd7b6536

23. Examples
10 friends in
7 days
4 invites in 45 days
30 connections
within 30 days
2000 messages
sent within a team

24. Atomic Use Case Loop
Activated
See
Retained
Referring

25. … and remember. None of this
matters if your product sucks

26. THINKING LIKE AN OPTIMIZER

27. DINING OUT
An Example I hope all of
us can relate to.

28. Which section
of the menu
do people
look at first?

29. Which section
of the menu
do people
look at first?1
2
3
4

30. Placement…
4

31. Which way do a
users eyes flow
when reading a
menu?1
2
3
4

32. What items to people pay
attention to within a list?
Entrees Entrees

33. Pricing?
1. $11.99
2. 12
3. twelve Increases the
spending by 8.15%
per person

34. Avoid Embarrassment
Market Price

35. What’s the lowest margin
wine on the menu?
2nd
cheapest bottle of wine has
a high margin.

36. TRY THIS
TONIGHT

37. Optimizing on the Web

38. Design, Estimate, and Measure in FUNNELS

39. Design in
FUNNELS

40. Estimate, and
Measure in
FUNNELS
Energy pinch was an unnecessary gate on virals

41. Birds and the Bees
Growing your user base

42. User Acquisition: Where does traffic come from?
Social Feeds
Facebook, LinkedIn, Twitter, Pinterest
Email
Mainly invitations from friends, or users sharing content
Organic
The best kind! User’s coming directly to your site
SEO
25% of LinkedIn’s new users came from search
Ads/Partnerships

43. User Acquisition: Where does traffic come from?
Wherever possible,
use user generated content
as messaging to increase the response
to your outreach.
What feature within your site prompt
generating user generated content?
It’s likely those have your highest
conversions and are a place you could
start to double down.

44. Measuring Virality
Z-Factor (Mixpanel/Dave McClure)
x = % of users who invite
y = avg number of people they invited
z = % of users who accepted an invitation
Z-Factor = x*y*z
Virality
Every 1 new >= 1 new user
K-Factor (wikipedia)
i = number of invites sent by each customer
c = percent conversion of each invite
K-Factor = i * c

45. Measuring Virality
Cycle Time
“Given that I get a new customer today, how many new customers will they bring in over the
next N days?”
Let’s assume a viral factor of 0.5, and an N of 7. User Acquisition will look like the below
which can be used for projections:
1 + 0.5 + 0.25 + 0.125 ….

46. CASE STUDY
ORKUT - SOCIAL NETWORK
Manu Rekhi
Prof. Raquel Recuero, Prof. Ricardo Araujo, Prof. Lada
Adamic, Sergio Marti, Jen Silverstein and Danah Boyd

47. Orkut (Social Network) Background
● In 2005 fb was less than 1M users
● Strong virality and network effects
● US team but exponential growth in Brasil (>12M users)
● Growing inspite of no clue
● Opportunity: Learn and repeat success in new countries

48. Multidisciplinary approach
● CDC and virus research (Article: Strength in weak ties)
○ My experience and background as a BioChemist
● Sociologist
● Anthropologist
● Physicist
● Data Scientist (before this word was coined)
I framed the hypothesis and the team set up a scientific
approach to come up with results

49. Network effect
Quantitative
Log Data
Cluster Analysis Visualization
Research Completed in Oct 2005
Qualitative
Focus Groups
Interviews
Long and short term system usage

50. Multidisciplinary approach
● CDC and virus research (Article: Strength in weak ties)
○ My experience and background as a BioChemist
● Sociologist
● Anthropologist
● Physicist
● Data Scientist (before this word was coined)
I framed the hypothesis and the team set up a scientific
approach to come up with results

51. CASE STUDY - RECIPROCITY
- FIANCEE / HALLMARK / LOLAPPS
- LOLAPPS & EASTERN EU
- HARE - KRISHNA’S

52. THANK YOU