My desk in #Vietnam Mobile Day 2020 about how to grow, gain more maket share and segmentation

1. HOW TO GAIN MORE MARKET SHARE WITH
DEEP SEGMENTATION & OPTIMIZATION
Manh Phan

2. …growth hacking?
…gain more share?

3. Customers just simply pick the
better options in the maket.
More market share? - Just be simply better.

4. “The difference between something good and
something great is attention to detail.”
- Charles R. Swindoll

5. 5
APPSFLYER/ ADJUST/ KOCHAVA
Business view Ques: HOW CAN WE ALLOCATE THE MINIMUM BUDGET
TO ACHIEVE THE MAXIMUM KPIs?
HCM/
HANOI
DATA
WARE
HOUSEAPP/WEB
Facebook/ Google/…
Or organically
AMPLITUDE/ FB ANALYTICS,.. BIG QUERY, DATA STUDIO,..
If the conversion rate is the same, how much money are
we going to spend?
- Organic vs inorganic
- CPI of Facebook & Google
- Cost per submitted order
- …
How can we increase the delivered orders &
the conversion rate of the funnel?
- Taxonomy
- Conversion rate
- Cancelation rate
- Cost per delivered order
How can we boost the
under-performance people?
- RFM
- Personalized coupons
• ORDER
• REVENUE
• PROFIT
Fat people

6. Trigger App Launch Order success Using Reorder
“Everybody has a different
taste of beauty, humor and
interest.”
Challenges:
+ 46 notifications / day
+ fb: 1 ads every 3 posts
+ Balanced between
keeping our brand
characteristics and
following the trends.
“That’s all I can buy dude! I
have the smaller food wallet
size than that girl has.
Hey, but then what is the best
50k food?”
Challenges:
+ Difference in income and
‘Wallet size for shopping’
+ Group order
+ Perceived wait times feel
longer than actual wait times.
+ ‘Reorder’ or ‘try-new-one’
recommendation system.
“Then why should I share? And
actually, what is the thing that I
want to share with others? My
taste? Brands? Or even
coupon?”
Challenges:
+ Peak-End rules
+ Core values – what we are
trying to stand for.
+ They complain online, but
compliment offline.
“I’m a Shopaholic, then what is the
actual thing that give me interest while
surfing? Coupon? New nearby stores?
Trendy stuff?..”
Challenges:
+ Placing an order is boring.
+ Install 60 – 90 apps but spend 77%
time on top 3 apps.*
+ are you a functional app or habitual
app?
+ Returning users have the same view
as new users do.
User Experience view Ques: WHAT IS THE VALUE THAT WE ARE TRYING TO CREATE?
Healthy and balanced
‘Flirting stage’ ‘Dating stage’ ‘In-a-relationship stage’ ‘Marriage stage’
Like, love, hate Window shopping experience Order & Waiting experience Unboxing & sharing experience

7. characteristics performance willing to share
Psychographic segment
(Personas)
+ Treatment searcher
+ Celebration creator
+ Netflix and eat guy
+ …
ÞMyers-Briggs type/ Big
Five personality traits /
The nine Enneagram
type
RFM segment
+ Champions
+ Need our attention
+ Hibernating
+…
=> By our empty hands and
brains or python library
maybe 🤖
‘Net Promoter Score’ segment
+ Detractors
+ Passive
+ Promoter
=> In-app survey or
branding research.
stickiness
Behavioral segment
+ 3 min searching before order
+ Love seeing promotion
+ Make-it-quick person : order in 2
min
=> Machine learning for clustering by
using K means, Neighborhood-based
Collaborative Filtering
Trigger App Launch Order success Using Reorder
Healthy and balanced
‘Flirting stage’ ‘Dating stage’ ‘In-a-relationship stage’ ‘Marriage stage’
Like, love, hate Window shopping experience Order & Waiting experience Unboxing & sharing experience
User Experience view Ques: WHAT IS THE VALUE THAT WE ARE TRYING TO CREATE?

8. Suggested Models & Use cases

9. characteristics performance willing to share
Psychographic segment
(Personas)
+ Treatment searcher
+ Celebration creator
+ Netflix and eat guy
+ …
ÞMyers-Briggs type/ Big
Five personality traits /
The nine Enneagram
type
RFM segment
+ Champions
+ Need our attention
+ Hibernating
+…
=> By our empty hands and
brains or python library
maybe 🤖
‘Net Promoter Score’ segment
+ Detractors
+ Passive
+ Promoter
=> In-app survey or
branding research.
stickiness
Behavioral segment
+ 3 min searching before order
+ Love seeing promotion
+ Make-it-quick person : order in 2
min
=> Machine learning for clustering by
using K means, Neighborhood-based
Collaborative Filtering
Trigger App Launch Order success Using Reorder
Healthy and balanced
‘Flirting stage’ ‘Dating stage’ ‘In-a-relationship stage’ ‘Marriage stage’
Like, love, hate Window shopping experience Order & Waiting experience Unboxing & sharing experience
User Experience view Ques: WHAT IS THE VALUE THAT WE ARE TRYING TO CREATE?

11. characteristics performance willing to share
Psychographic segment
(Personas)
+ Treatment searcher
+ Celebration creator
+ Netflix and eat guy
+ …
ÞMyers-Briggs type/ Big
Five personality traits /
The nine Enneagram
type
RFM segment
+ Champions
+ Need our attention
+ Hibernating
+…
=> By our empty hands and
brains or python library
maybe 🤖
‘Net Promoter Score’ segment
+ Detractors
+ Passive
+ Promoter
=> In-app survey or
branding research.
stickiness
Behavioral segment
+ 3 min searching before order
+ Love seeing promotion
+ Make-it-quick person : order in 2
min
=> Machine learning for clustering by
using K means, Neighborhood-based
Collaborative Filtering
Trigger App Launch Order success Using Reorder
Healthy and balanced
‘Flirting stage’ ‘Dating stage’ ‘In-a-relationship stage’ ‘Marriage stage’
Like, love, hate Window shopping experience Order & Waiting experience Unboxing & sharing experience
User Experience view Ques: WHAT IS THE VALUE THAT WE ARE TRYING TO CREATE?

12. Cash vouchers?

13. characteristics performance willing to share
Psychographic segment
(Personas)
+ Treatment searcher
+ Celebration creator
+ Netflix and eat guy
+ …
ÞMyers-Briggs type/ Big
Five personality traits /
The nine Enneagram
type
RFM segment
+ Champions
+ Need our attention
+ Hibernating
+…
=> By our empty hands and
brains or python library
maybe 🤖
‘Net Promoter Score’ segment
+ Detractors
+ Passive
+ Promoter
=> In-app survey or
branding research.
stickiness
Behavioral segment
+ 3 min searching before order
+ Love seeing promotion
+ Make-it-quick person : order in 2
min
=> Machine learning for clustering by
using K means, Neighborhood-based
Collaborative Filtering
Trigger App Launch Order success Using Reorder
Healthy and balanced
‘Flirting stage’ ‘Dating stage’ ‘In-a-relationship stage’ ‘Marriage stage’
Like, love, hate Window shopping experience Order & Waiting experience Unboxing & sharing experience
User Experience view Ques: WHAT IS THE VALUE THAT WE ARE TRYING TO CREATE?

14. Does your app work as a
functional app or habitual app?

15. Neighborhood-based
Collaborative Filtering
Linear Discriminant Analysis (LDA)

16. characteristics performance willing to share
Psychographic segment
(Personas)
+ Treatment searcher
+ Celebration creator
+ Netflix and eat guy
+ …
ÞMyers-Briggs type/ Big
Five personality traits /
The nine Enneagram
type
RFM segment
+ Champions
+ Need our attention
+ Hibernating
+…
=> By our empty hands and
brains or python library
maybe 🤖
‘Net Promoter Score’ segment
+ Detractors
+ Passive
+ Promoter
=> In-app survey or
branding research.
stickiness
Behavioral segment
+ 3 min searching before order
+ Love seeing promotion
+ Make-it-quick person : order in 2
min
=> Machine learning for clustering by
using K means, Neighborhood-based
Collaborative Filtering
Trigger App Launch Order success Using Reorder
Healthy and balanced
‘Flirting stage’ ‘Dating stage’ ‘In-a-relationship stage’ ‘Marriage stage’
Like, love, hate Window shopping experience Order & Waiting experience Unboxing & sharing experience
User Experience view Ques: WHAT IS THE VALUE THAT WE ARE TRYING TO CREATE?

17. Myers-Briggs type Big Five personality traits

18. The nine Enneagram type

19. Psychographic
+ Demographic
= Persona(s)

20. Limited resources!

21. 21
“The Peak-end Rule says that people judge an experience
based on how they felt at its peak and its end, not the
average of every moment of the experience.
And that’s true whether the experience was good or bad.”

22. characteristics performance willing to share
Psychographic segment
(Personas)
+ Treatment searcher
+ Celebration creator
+ Netflix and eat guy
+ …
RFM segment
+ Champions
+ Need our attention
+ Hibernating
+…
‘Net Promoter Score’ segment
+ Detractors
+ Passive
+ Promoter
stickiness
Behavioral segment
+ 3 min searching before order
+ Love seeing promotion
+ Make-it-quick person : order in 2
min
Trigger App Launch Order success Using Reorder
Healthy and balanced
‘Flirting stage’ ‘Dating stage’ ‘In-a-relationship stage’ ‘Marriage stage’
Like, love, hate Window shopping experience Order & Waiting experience Unboxing & sharing experience
User Experience view THEN, WHERE SHOULD WE START FIRST?

23. Thanks
Manhphan.xiii@gmail.com