Personalisation is a fundamental tool to providing the optimal customer experience, generating more sales, and increasing customer retention. We all heard about the value of personalisation before, yet how many of us are actually doing it optimally and really serving the customer needs?
Nadia will talk about Moonpig’s approach to making user experience personal and will share the challenges that came across Moonpig’s way.
6. 17% of respondents were mad at
at the person who gave them
their worst gift ever.
16% of respondents said that receiving
their worst gift ever worsened their
relationship with the gift-giver.
Responders relationship to the Worst Gift-Giver
Relative 48,3%
29,3%
Friend
13,9%
Partner
8,6%
Other
Parets were most
likely than
siblings to give a
bad gift.
The average estimated price
of respondent’s worst gifts
was $20.
45% of respondents said the person who
gave them their “worst” gift ever did so on
more than one occasion.
7. Behavioral Segmentation of Customers I like shopping
online.
I need help
planning my
present.
I dont like
spending time &
money on gifts
I want my
present to be
impressive!
1
Moonpig’s mission
8. Personalization is fundamental
to providing the optimal
customer experience,
generating more sales, and
increasing customer retention.
2
Personalisation - help or illusion?
9. There is a problem...
2
Personalisation - help or illusion?
19. Cold-Start problem
even worse on
Moonpig
It takes us a long
time to learn about
user
It's about the users
relationships, more than
the users themselves
We are not a typical
e-commerce
business
Our challenges
3
Moonpig’s approach
20. 3
Moonpig’s approach
Primary Job to Be Done
Related Jobs to Be Done
Give a card to
celebrate an occasion
Find a suitable card in the first shop I visi
I want to be thought of positively by the
recipient and others because I've sent a
car
Find the right words to say in the car
Get the recipient's correct addres
I want a card to arrive with the recipient
exactly when it's supposed t
Make the recipient will feel like I know them
well
+ 55 other jobs
21. Moonpig’s journey
16 same
cross-sell gift
recommenda-
tions
Beginning
3,5 years ago
3
Moonpig’s approach
only biggest wins & lessons presented in the timeline
23. 16 same cross-
sell gift
recommenda-
tions
Gifts paired with
uniquely bought
cards
Beginning Lift algorithm
BIG WIN -
10% uplift
3,5 years ago
only biggest wins & lessons presented in the timeline
3
Moonpig’s approach
Moonpig’s journey
24. 16 same
cross-sell gift
recommenda-
tions
Gifts paired with
uniquely bought
cards
Recommendations
with a new card:
mechanism to
group cards and
missions together
16 gift -> 160 gifts
Beginning Lift algorithm Cold-start fix
No big win
BIG WIN -
10% uplift
3,5 years ago
3
Moonpig’s approach
Moonpig’s journey
only biggest wins & lessons presented in the timeline
25. 16 same
cross-sell gift
recommenda-
tions
Gifts paired with
uniquely bought
cards
Recommendations
with a new card:
mechanism to
group cards and
missions together
16 gift -> 160 gifts
From 16 products in
a random list ->
few product
category groups
Beginning Lift algorithm Cold-start fix Carousels
No big win
BIG WIN -
10% uplift
BIG WIN -
10% uplift
3,5 years ago
3
Moonpig’s approach
Moonpig’s journey
only biggest wins & lessons presented in the timeline
27. 16 same cross-
sell gift
recommenda-
tions
Gifts paired with
uniquely bought
cards
Recommendations
with a new card:
mechanism to
group cards and
missions together
16 gift -> 160 gifts
From 16 products in
a random list ->
few product
category groups
The future
Beginning Lift algorithm Cold-start fix Carousels Card & mission pairing
No big win
BIG WIN -
10% uplift
BIG WIN -
10% uplift
3,5 years ago
3
Moonpig’s approach
Moonpig’s journey
only biggest wins & lessons presented in the timeline
38. 1. Start small and iterate to improve
2. Focus on what users find the biggest struggle
3. Use the wisdom of crowds to surface the right item
4. Relevance to users over everything else
5. Dont be afraid to fail - learn from it!
Summary
4
Lessons learned
