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M&S Digital Labs
Lean product development, fast feedback
(& leopard print dresses)

@hemalkuntawala
•

About M&S Digital Labs

•

One of our products

5 minutes

15 minutes
About M&S Digital Labs

Lean startup techniques…	

…kick-start products and experiences…	

…our customers wouldn't expect to see from M&S
About M&S Digital Labs
*
Online
Desktop, tablet, mobile

Ops

Marketing
Digital

Trading, fulfilment

Marketing

Ops

Branding,	

campaigns

Supply chain

Stores

Marketing

Ops

High Street, Simply Food, Outlet

Offline

Stock, forecasting

* Not to scale, or very accurate
Lean startup (& product management)
Value
proposition

Customer
segments

Business
model canvas

Marketing
channels

Customer
development

Validate
assumptions

Design thinking

Insight &
assumptions

Learn

UX

Build

Autonomy
User testing

Activation

Data

Product

Revenue

Extreme
programming

Retention
Behaviour
Split tests

Developers
Designers

Vision, instinct &
obsession…

Acquisition

IA

Referral
Product/market fit?

Measure

Continuous
deployment
MVP
Insight &
assumptions

Our brands
confuse

Would our
customers create
and view outfits?

What happens to
conversion if we
remove models?

What happens
if we remove
our brands?

Data

Can’t outfit

Our models
alienate

Product

One of our products
Product

The product: Style Board
Would our
customers create
and view outfits?

What happens to
conversion if we
remove models?

What happens
if we remove
our brands?
Product

Would our
customers create
and view outfits?

Data

The data

Let’s have a
look…

What happens to
conversion if we
remove models?

What happens
if we remove
our brands?
5000

Traffic
3750

Sign ups	

52% conv.

2500

Boards	


39% conv.

1250

Month

October

November

December

January

February
The data

Data

Product

Would our
customers create
and view outfits?

•
•

52% visitors signed up	

39% users created a
board

What happens to
conversion if we
remove models?

•

Traffic from Style Board
converts 36% higher

What happens
if we remove
our brands?
The data

Data

Product

Would our
customers create
and view outfits?

•
•

52% visitors signed up	

39% users created a
board

What happens to
conversion if we
remove models?

•

What happens
if we remove
our brands?

Traffic from Style Board
converts 36% higher

Let’s have a
look…
Brand mix
The data

Data

Product

Would our
customers create
and view outfits?

•
•

52% visitors signed up	

39% users created a
board

What happens
if we remove
our brands?

What happens to
conversion if we
remove models?

•

Traffic from Style Board
converts 36% higher

•

Brands are mixed and
matched

More data!
Category mix

Product relationships
Category mix
The data

Data

Product

Would our
customers create
and view outfits?

•
•

52% visitors signed up	

39% users created a
board

What happens
if we remove
our brands?

What happens to
conversion if we
remove models?

•

Traffic from Style Board
converts 36% higher

•

Brands are mixed and
matched

More data!
Category mix	

•

Some popular categories could
be better sold

Product relationships
Product relationships
Behaviour

Opinion
The data

Data

Product

Would our
customers create
and view outfits?

•
•

52% visitors signed up	

39% users created a
board

What happens
if we remove
our brands?

What happens to
conversion if we
remove models?

•

Traffic from Style Board
converts 36% higher

•

Brands are mixed and
matched

More data!
Product category mix	

•

Popular categories could be
better sold

Product relationships	

•

Relationship data could produce
better product suggestions
What’s next?

Version 1	

• Isolated app (mandsstyleboard.com)	

• Login via Facebook	

• (Minimal) engagement mechanics	

• Deep links	

• Responsive	

• Shipped in 4 weeks	

• Traffic from M&S Facebook

Version 2	

• Increase engagement	

• Increase quality	

• Increase conversion	

• Lick of paint	

• Use as a marketing channel	

• Wherever else the data takes us…
What else you can expect from us

Online
Desktop, tablet, mobile

Stores
High Street, Simply Food, Outlet
Food

High

Online aided by offline

Mainly online

Frequency

Tops
Lingerie

Shoes
Bottoms

Women’s wear

Shirts
Underwear

Handbags

Dresses

Men’s wear
Flowers
Suits

Low

Sofas

Slow

Homeware

Kitchen ware

Purchase-cycle speed

Fast
Thanks!
@mnslabs

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M&S Digital Labs: Lean product development, fast feedback & leopard print dresses

  • 1. M&S Digital Labs Lean product development, fast feedback (& leopard print dresses) @hemalkuntawala
  • 2. • About M&S Digital Labs • One of our products 5 minutes 15 minutes
  • 3. About M&S Digital Labs Lean startup techniques… …kick-start products and experiences… …our customers wouldn't expect to see from M&S
  • 4. About M&S Digital Labs * Online Desktop, tablet, mobile Ops Marketing Digital Trading, fulfilment Marketing Ops Branding, campaigns Supply chain Stores Marketing Ops High Street, Simply Food, Outlet Offline Stock, forecasting * Not to scale, or very accurate
  • 5. Lean startup (& product management) Value proposition Customer segments Business model canvas Marketing channels Customer development Validate assumptions Design thinking Insight & assumptions Learn UX Build Autonomy User testing Activation Data Product Revenue Extreme programming Retention Behaviour Split tests Developers Designers Vision, instinct & obsession… Acquisition IA Referral Product/market fit? Measure Continuous deployment MVP
  • 6. Insight & assumptions Our brands confuse Would our customers create and view outfits? What happens to conversion if we remove models? What happens if we remove our brands? Data Can’t outfit Our models alienate Product One of our products
  • 7. Product The product: Style Board Would our customers create and view outfits? What happens to conversion if we remove models? What happens if we remove our brands?
  • 8. Product Would our customers create and view outfits? Data The data Let’s have a look… What happens to conversion if we remove models? What happens if we remove our brands?
  • 9. 5000 Traffic 3750 Sign ups 52% conv. 2500 Boards 39% conv. 1250 Month October November December January February
  • 10. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens to conversion if we remove models? • Traffic from Style Board converts 36% higher What happens if we remove our brands?
  • 11. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens to conversion if we remove models? • What happens if we remove our brands? Traffic from Style Board converts 36% higher Let’s have a look…
  • 13. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens if we remove our brands? What happens to conversion if we remove models? • Traffic from Style Board converts 36% higher • Brands are mixed and matched More data! Category mix Product relationships
  • 15. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens if we remove our brands? What happens to conversion if we remove models? • Traffic from Style Board converts 36% higher • Brands are mixed and matched More data! Category mix • Some popular categories could be better sold Product relationships
  • 18. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens if we remove our brands? What happens to conversion if we remove models? • Traffic from Style Board converts 36% higher • Brands are mixed and matched More data! Product category mix • Popular categories could be better sold Product relationships • Relationship data could produce better product suggestions
  • 19. What’s next? Version 1 • Isolated app (mandsstyleboard.com) • Login via Facebook • (Minimal) engagement mechanics • Deep links • Responsive • Shipped in 4 weeks • Traffic from M&S Facebook Version 2 • Increase engagement • Increase quality • Increase conversion • Lick of paint • Use as a marketing channel • Wherever else the data takes us…
  • 20. What else you can expect from us Online Desktop, tablet, mobile Stores High Street, Simply Food, Outlet
  • 21. Food High Online aided by offline Mainly online Frequency Tops Lingerie Shoes Bottoms Women’s wear Shirts Underwear Handbags Dresses Men’s wear Flowers Suits Low Sofas Slow Homeware Kitchen ware Purchase-cycle speed Fast