2018/06/26 You can’t take an algorithm out to dinner · 2018-06-26 · Curation Perfect Mission as New Frontier Separating winners from losers today Perfect Shelf as Entry Point

You can’t take an algorithm out to dinnerNew opportunities for consumer and customer engagement …

and the organisational transformation it requires

2018/06/26

Daniel Hulme

Satalia

Stephan Pretorius

Wunderman

Owen McCabe

Kantar Consulting

Welcome

2

Daniel HulmeChief Executive Officer

Stephan PretoriusGlobal Chief Technology Officer

Owen McCabeGroup Director, E-commerce Consulting

Algorithms over time01Daniel HulmeSatalia

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Director of Applied Artificial Intelligence MSc

PhD in Artificial Intelligence

Senior Lecturer in AI and Innovation

Postdoc in Innovation and Technology Transfer

MBA Electives London Business School

MSci in Artificial Intelligence

Daniel HulmeSatalia

4

Founder & CEO of Satalia

Advisor to UAE AI Strategy

Co-founder of the ASI Data Science

Advisor to NOIA Network and others

Kauffman Global Scholar

Startup mentor and speaker

Artificial Intelligence

Daniel HulmeSatalia

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Data driven decision making

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WISDOM

UNDERSTANDING

KNOWLEDGE

INFORMATION

DATA

Daniel HulmeSatalia

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JOHN READ THE LETTER TO MARY


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WISDOM

UNDERSTANDING

KNOWLEDGE

INFORMATION

DATA = symbols

= contextualized DATA


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WISDOM

UNDERSTANDING

KNOWLEDGE

INFORMATION

DATA = symbols


= organised INFORMATION


Daniel HulmeSatalia

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WISDOM

UNDERSTANDING

KNOWLEDGE

INFORMATION

DATA = symbols



= interpreted KNOWLEDGE


Daniel HulmeSatalia

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WISDOM

UNDERSTANDING

KNOWLEDGE

INFORMATION

DATA = symbols



= interpreted KNOWLEDGE

= utilised UNDERSTANDING

Daniel HulmeSatalia

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Data making

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Resource Allocation

RULES

Flying right of walking

Swimming left of walking

Reptiles 2-away from felines

No same colours touching

Tails prefer next to tails

Males prefer near females

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Resource Allocation

RULES







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120

Resource Allocation

RULES







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Resource Allocation

RULES







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1,307,674,368,000

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500! ≈ 1e+1134

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500! ≈ 1e+1134122013682599111006870123878542304692625357434280319284219241358838584537315388199760549644750220328186301361647714820358416

337872207817720048078520515932928547790757193933060377296085908627042917454788242491272634430567017327076946106280231045264

421887878946575477714986349436778103764427403382736539747138647787849543848959553753799042324106127132698432774571554630997

720278101456108118837370953101635632443298702956389662891165897476957208792692887128178007026517450776841071962439039432253

642260523494585012991857150124870696156814162535905669342381300885624924689156412677565448188650659384795177536089400574523

894033579847636394490531306232374906644504882466507594673586207463792518420045936969298102226397195259719094521782333175693

458150855233282076282002340262690789834245171200620771464097945611612762914595123722991334016955236385094288559201872743379

517301458635757082835578015873543276888868012039988238470215146760544540766353598417443048012893831389688163948746965881750

450692636533817505547812864000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000

0000000000000000000000000000000

Daniel HulmeSatalia

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500! ≈ 1e+1134122013682599111006870123878542304692625357434280319284219241358838584537315388199760549644750220328186301361647714820358416

337872207817720048078520515932928547790757193933060377296085908627042917454788242491272634430567017327076946106280231045264

421887878946575477714986349436778103764427403382736539747138647787849543848959553753799042324106127132698432774571554630997

720278101456108118837370953101635632443298702956389662891165897476957208792692887128178007026517450776841071962439039432253

642260523494585012991857150124870696156814162535905669342381300885624924689156412677565448188650659384795177536089400574523

894033579847636394490531306232374906644504882466507594673586207463792518420045936969298102226397195259719094521782333175693

458150855233282076282002340262690789834245171200620771464097945611612762914595123722991334016955236385094288559201872743379

517301458635757082835578015873543276888868012039988238470215146760544540766353598417443048012893831389688163948746965881750

450692636533817505547812864000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000

0000000000000000000000000000000

atoms ≈ 1e+80

TransportationProblems

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TransportationProblems

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# ROUTES 1,000,000

PER SECOND

10 3,628,800 4 seconds

11 39,916,800 1 minute

13 6,227,020,800 2 hours

14 87,178,291,200 1 day

16 20,922,789,888,000 1 year

20 2,432,902,008,176,640,000 77,000 years

22 1,124,000,727,777,610,000,000 36 millennia

24 620,448,401,733,239,000,000,000 20B years


Daniel HulmeSatalia

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WISDOM

UNDERSTANDING

KNOWLEDGE

INFORMATION

DATA

Prescriptive analytics

• Optimisation

• Decision-science

Predictive analytics

• Data-science

• Machine learning

Descriptive analytics

• Contextualisation

• Data visualisation

Data Engineering

• Infrastructure

• Data assimilation

ACTION

INSIGHT

DATA

ArtificialIntelligence

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ACTION

INSIGHT

DATA

ADAPT

Intelligence:

Goal-directed Adaptive BehaviourSternberg & Salter

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Symbolic AI

Sub-symbolic AI

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ArtificialIntelligences

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Artificial

Intelligence

Artificial

General Intelligence

Super

Intelligence

bounds of

human ability

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Simulation Theory

Ethical decision making

Daniel HulmeSatalia

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Ethical AI,Explainable Algorithms and GDPR

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New opportunities for consumer engagement02

Stephan PretoriusWunderman

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39

WTF!?

AI

“The field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem solving, and pattern recognition.”

• Natural Language Understanding

• Automatic Speech Recognition

• Text-to-speech

• Visual Search and Image recognition

• Machine Learning

• Deep Learning


40


41

&Improves the OLD Enables the NEW


42


43

Cortana, Alexa, Google Assistant, DialogFlow, Clova, Siri

Voice Assistants Bing Speech API, Lex, Polly, Google Voice

AI

Devices


44

Command line GUI Touch Swipe Voice


45

WTB!?* Where’s the brand!?


46


47

If your brand could speak, what would it sound like?


48

WDIS!?* Where do I start?

What matters most to you?


49

• How do I develop larger volumes of

personalised content at a lower cost?

• How do I encourage digital self-service

and reduce customer service frustrations?

• How do I look ahead instead of looking in

the rear-view mirror?

• How do I become more adaptive in how I

respond to consumer needs?


50

Creative

intelligence &

augmentation

Language

intelligence &

automation


51

Customer

service

automation


52

Smarter

analytics &

predictions


53

Improving

segmentation &

targeting


54


55

AI marketing

maturity curve

for enterprise

INCUBATION+ Retrospective: Ability to

see what happened

+ Diagnostic: Find out why /

causes

+ Segmentation possible

based on what is known

+ Evaluate vendors

+ Explore build versus buy

+ Data science as individual

contributors in each

function

+ Propensity to look-alike

models, behavious scores,

etc.

+ Channel-based KPI’s

13% of orgs*

ITERATION+ Predictive: Ability to

predict what will happen

+ Requires human

intervention for decision

making

+ ML models often applied in

single channels or use

cases

+ Data science matrixed

across org

+ Next-best action systems,

AI/ML recommendation

engines

+ Team-based KPI’s

32% of orgs*

INTEGRATION+ Proactive: Ability to make

something happen

+ Data models unified and

shared across org

+ Enables 1:1 optimization at

scale

+ AI applied across customer

experience to enhance

every interaction

regardless of channel

+ Humans focus on strategy

and let AI handle execution

on data, decisions and

orchestration

+ Data science as a core

competency

+ Company-based KPI’s

19% of orgs*

INITIATION+ Disconnected and/or

siloed data sources.

+ Identify KPI’s, resources

and hire your first data

scientist

+ Basic analysis, attribution,

and A/B testing

36% of orgs*

VA

LU

E

CAPABILITY / APPLICATION* MIT Sloan Reshaping Business with AI

New opportunities for customer engagement03

Owen McCabeKantar Consulting

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A New Retail Reality…

is being shaped by Algorithm-led Retail Models


57

KR 2013

1. Walmart $489B

2. Carrefour $116B

3. Costco $108B

4. Tesco $106B

5. Kroger $98B

6. Schwarz Grp $93B

7. Seven & I $86B

8. Metro Group $85B

9. Amazon $78B

54. Alibaba $6B

KR Forecast 2018E

1. Walmart $605B

2. Alibaba $246B

3. Amazon $179B

4. Costco $162B

5. Kroger $137B

6. Tesco $129B

7. Carrefour $129

8. Seven & I $114B

9. Schwarz Grp $110B

10. Metro Group $95B

Algorithm-led Retail Models require New Capabilities for Brand Owners

Algorithms are deciding your brand presence on the world’s Fastest Growing Retailers


58

Source: Seller Labs

Seeing Amazon & Alibaba as partners, not platforms

…but most Brands don’t seem to have noticed…

Common Client Brand “Blind Spots”


59

Attaching little value to on-site Media/PlatformsYour Competition are not who you think they are

Tackling a B&C world with B&M Structures, Tools & Skillsets

Bringing a Knife to a Gunfight

60

If embraced, Algorithms enable you to be in the driver seat, see around corners and navigate a

more effective Route to Consumer

61

Not on any Brand Tracking Radar…

• Ranked #1 on Amazon.com but only 6% prompted awareness

Diagnostics on Search Terms Female anti-hair loss

Predictive modelling

• #1 ranked product for key benefit terms on Google Search

• High conversion on Amazon

• X% share within 12 months

Your Competition aren’t who you think they are…

Pura d’or example

62

You can’t take an Algorithm to Dinner, but you can still be Best Friends with them!

3 ways Algorithms are changing our B2B2C Marketing and Sales Strategies

1. Buyer Supplier Relationships From Pitch to Portal

2. Optimisation Focus From “Perfect Shelf” to “Perfect Mission”

3. Marketing Activity From Promotion to Platform

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1. FROM PITCH TO PORTAL “RELATIONSHIPS”

e.g., for Amazon: Most Brand owners still trying to apply a B&M retailer model to a technology company

Buyer-Supplier Relationship Brand GuidanceManagement by Portal/Algorithm

From: Buy-in, Conceptual Selling To: Sell-through, Programmatic

64

You can’t explain to an algorithm what happened or what went wrong.

Nobody to call: For example, if you go out of stock, the algorithm will punish you, your explanations won’t matter

Amazon operates a cost effective self-service vendor model.

AMZ views direct human contact with vendors as ERRORS

Amazon Looking for Automation: Algorithmically driven emails

Vendor managers overloaded and hard to reach

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Living in an automated world: Pricing against an algorithm

Amazon’s mapping tool dynamically matches lowest price in the marketplace, even if it’s below cost

AUTOMATED PRICE MAPPING IS OUT OF HUMAN CONTROL

MAP/MSRPMax Margin/

Assessments of ASIN

Checks 3P sellersCMT Crawling

AMAZON’S COMPETITIVE MAPPING TOOL (CMT) REQUIRES MAPPING

TO: RETAILER + PRODUCT URL + PRICE + UNIT COUNT

SELLING PRICE

RETAIL PRICING SYSTEM

Reality Check –Death of Category Captaincy?

Partnership or Partnerschaft?


66

Opportunity = Learning to Clap with one Hand!

Become Self-sufficient in

- data analytics- journey understanding- content management- on-site search optimisation- compliance tracking- touchpoint modeling- on-site media effectiveness

to drive smart investment


67

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2. FROM PERFECT SHELF TO PERFECT MISSION

Use of Automation, Analytics and AI to optimise for Shopper Experience and not Supplier advantage

Supplier-led “Perfect Shelf” Brand GuidanceShopper-led Perfect Mission

From: Periodic Range Reviews and

Battle for Brand Advantage

To: “Live” Shopper-defined Categories

and Personalised Experience

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Welcome to the new… Point of Purchase

From Limited Choice to Limitless Choice to Curated Choice

Perfect Screen..

PHYSICAL SHELF LAPTOP/DESKTOP

Base 2-3 x vs Base

SMARTPHONE/TABLET

^2-3 vs Base

70

Will Voice kill Choice? Curation in action

Amazon’s “Aide Intelligente” launched this month in France

71

Choice and Availability

Navigation & Visibility

Convenience

Service and Experience

CurationPerfect Mission

as New Frontier

Separating winners

from losers today

Perfect Shelf

as Entry Point

• Optimised Assortment

• Distribution

• Availability/Service Levels

• Merchandising

• Planogram & Digital Shelves

• Price and promotion

• Smaller, closer formats

• Omni-channel fulfilment

• Purpose

• Content

• Non-product space

• Personalization

• Omni-modal service

• Conversation/ voice

So where’s the growth? In aligning to the Perfect Mission.

Perfect Shelf (digital or otherwise) is only the Entry Point – adding utility to the journey is the New Frontier


72

Reality Check –Death of Categories?

Defined by Shopper –Curated by Actual Data, not the Supplier or Location in Store

Redefining Sweet Snack aisle


73

Reality Check –Death of Categories?

Defined by Shopper –Curated by Actual Data, not the Supplier or Location in Store

Redefining Sweet Snack aisle

Categorydecision tree

Retailerdemand structure

• At market/channel level• Layout, Adjacencies• Per (static) category, • often manufacturer-centric• Updated every couple of years

• Specific to retailer (or format)• Redefining boundary of categories • in line with retailer strategies• Updated by shoppers in real time

Opportunity = Automate for Alignment & Speed!

Automate Perfect Category based on Perfect Data to

- remove bias, increase trust, - gain alignment faster- drive consistent CX across device- shift to “what if” growth mindset- Maximise Return on Assets


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3. FROM PROMOTIONS TO PLATFORMS

Analytics and AI enable perfectly targeted propositions

Brand Plans Brand GuidanceAudience Plans

From: Participating in Retail Media and

Generic Price-led Promotions

To: Integrating with Retailer Platforms

and ecosystems to deliver Targeted

Content-led Selling

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Integrating with eRetailers and their ecosystems shifts the focus and the investment to Campaigns and Platforms

Think Campaigns & Platforms over Promotions & Activities

Collaborative Platforms

Campaigns

Activities

PromotionKPI = Engagement

& Efficiency

KPI = Shopper

Behaviour Change

KPI = Value Sales &

Post-event RoSKPI = Volume Sales

77

Alibaba Uni Marketing Strategy

UniID = Omni-ConsumerDigitizing the core components of retail operation

• Connect each account and provide three-dimensional and authoritative

shoppers image by UniID

• Integrate and analyze separated brands data through data bank

• Visualize relatively separate shopper journey and optimize operation

e-Supply Chain Management• Digitalize the whole process ( shoppers, logistics, and payment)

• Real time

• Help brands realize flexible product design and manufacturing based on product planning and R&D

OmnichannelIntegrate online and offline channels, and

reconstruct retail economic structure

Multi-Platform Brand Building & MarketingHelp brands operate and understand shopper behavior during the whole purchasing journey at all time

(big data, intelligent algorithm, construct communities of shopper media content)

e-Sales & e-Distribution

2 BN Consumers

2020E

USD 547 BN GMV USD 1 TN GMV

2017E 2020E

78Source: JD Public Release

JD unbounded marketing: Integrated media platform to achieve digital efficiency with brands

Jing fans

plan

Social Marketing PlatformIntelligent business

platforms

JD X Plan

Joint advertisement display

Create traffic cooperation model

Dong Lian Plan

（brand）

Dong Lian Plan

（content）Brands involve JD elements and products links in content

marketing while JD share same traffic

Jing Meng Plan

IP marketingChannel

marketingNational brand

marketing

Campus

marketing

Joint

promotion

JD User

Ecosystem

Brand fans club

PLUS Jing Value Category

badge

Brand

membership……

Goods

finding

Purchase

Albums

JD Lives JD Express

JD User

Ecosystem

• Buy-out model

• Guiding model

• E-commerce

involvement

model

• Jing Store

• Light Store

• ……

Operation empowerment

out of station (Kepler)

JD seckill3 Super

Activities

FindingsBrands

……

Marketing Operation

in Station

Traffic Import Traffic Conversion

79

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

Beer Example @ JD.com – Opportunity to create/participate in various festivals over the year

Festivals Big

PromotionCategory

Promotion

11.11

Double

11

12.12

Double

12

Lunar 7.7

Mid-Autumn

Festival

Lunar 8.15

Double Ninth

Festival

Lunar 9.9

Chinese

Valentine

8.8 9.10 10.1 12.24Christmas

EveMen’s Day

4th Thu

12.25

Christmas

The Dragon

Boat Festival

Lunar 5.5

3rd Sun

6.1Children’s

Day

6.18Tmall

JD

10.31 4th FriBlack

Friday

3.8

JD

Category

Promotio

n

3.14White

Valentine

4.1

Spring

Outing

Tmall Super

Gourm

et

Festival

JD

CNY

Gourm

et

Carniva

l

Tmall Super

2.14

5.1

Love

Telling

5.20

5.4

5.17

Suning

2nd Sun

Tmall Super

Early

Summe

r

1.1

New

Year

Lunar 1.1

Valentine’s

Day

Women’s

DayApril Fool’s

Day

International

Labor Day

Youth

Day

Mother’s

Day

Father’s

Day

Teacher’s

Day

National

Day

Thanks

Giving

Halloween

Winter

Carnival

JD

Gatherin

g Day

TmallCategory

Promotio

n

Tmall

JD

Category

Promotio

n

Beer Category relevant festival Snapshot

80

But festivals have transformed from simple price promotion to engagement building

Evolution of Online Big Events

Price Promotion

Engagement Building

2009 2011 2012 2013

2016 2017

Price promotion for Bachelors

'Day

“ Desert Storm" price promotion

50%off, only for today

Will be cheaper in a few days

Buy it cheap, buy itfast

Enjoy your shopping on Tmall double 11

shopping carnival

Take it serious and buy some good

stuff

Wish you a happy double 11

Pick your favorite on JD

Category Upgrade

2014 2015

Buying products from around the world

JD’s Products, must be the best

products

Buying products from around the

world

With the same price, why not buy a genuine one

81

99 Global Alcohol Festival is the biggest Category event on Tmall with importance beyond sales

➢ The largest Wine &Spirit category campaign on

Tmall since 2016

Tmall Wine &Spirits Festival

Position

Serves not as the sales promotion but as complete the

mission of the wine culture spreading and

consumption upgrade through creative digital

campaign, and engaging shopping experiences

Celebrity Favorite List

Digital Marketing

Master Recommended

List

Live broadcasting Poker design by fans

Milestone

99 new product

launched

100 thousand+

products

100 Million

shopper GMV:2 Billion

Reality Check – Are you ready to become One Demand Team?

New Ways of Working based on shared ownership of influencing across the consumer-shopper journey


82

The Future is Vinaigrette !

Ad Exchanges

Self-Righting

Anticipative Ordering

Eco-systems

Self-Service Portals

Deep Learning

Assistants/ Chatbots

Curation

Contextual Search

Apps

Driving Scale and Experience (Content, Search, & Media)

Opportunity = Algorithms are set to play an ever bigger role in B2B2C

REPEATABLE TASKS

PROGRAMMATIC

ADVISORY

Machine-learning to support decision making

PREDICTIVE

PITCH-BASED

Advanced Search

Subscribe & Save

IFTTT

Caching..Shopping

Lists

ac Prescriptive?

Predictive

Advisory

Programmatic

Standardised

Pitch-Based


84

A few questions to consider

Algorithms - and the Automation/AI they enable - can be your new best friend!

What are you doing today to automate and digitize existing

business processes?

Are you integrating with eRetailers to create/leverage collaborative growth

campaigns/platforms, to reach and engage your shoppers and consumers?

Where are you investing in building shopper-centric competitive

intelligence to power advisory, predictive and prescriptive algorithms?

How are you preparing your sales, cat man and marketing

organizations for new relationship models?

Making it real

Daniel HulmeSatalia

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TheraFlu Flu Tracker

At the edge of Innovation

Daniel HulmeSatalia

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Challenge Russian Cold and Flu season was unpredictable in 2017

Daniel HulmeSatalia

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10-day flu forecast with up to 95% accuracy for 82 Russian regions

Complex Big Data solution powered by AI with a small budget

Daniel HulmeSatalia

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▪ 15 milion data points

▪ 82 algorhytms for different regions

▪Budget 2017: production £23k, media £600k

Breakthrough in bridging the digital gap

High engagement, high business impact, high recognition

Daniel HulmeSatalia

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• 12% TheraFlu sales Y-o-Y growth vs.

2% category sales (DSM, Oct –

Nov’17)

• Record 34% MS in the TheraFlu

history (DSM, Nov’17)

6 awards

• GSK CH CEE Marketing Award

• 1 Gold + 2 Silver EFFIEs

• 2 Silver @ Festival of Media Global

3 nominations

• Connections Awards

• Cannes Lions

• 647 000 unique visitors*

• Av. time spent on site 9:18

vs. Benchmark*: 01:42

• Bounce rate 18%

vs. Benchmark*: 37%

• 8% brand search requests Y-o-Y

growth vs. 0% category search

requests (Yandex.Wordstat)

High consumer engagement Record business results Industry accolades

* Google Analytics, Benchmarks by MailRu Group’s pharmaceutical special projects in 2017

Strategic Vision& Way Forward

Become a digital revenue stream for GSK CH

Daniel HulmeSatalia

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2020 VISION & STRATEGY

BUILD

AWARENESS

WIN

TRUST

2 STEP – 2HY 2018 4 STEP – 2020

USER JOURNEY

& EXPERIENCE

1 2CREATE

A HABIT

3

3 STEP – 20191 STEP – 1HY 2018

ANNOUNCEMENT

& MAX REACH

EXPANDING REACH & BUILDING

CREDIBILITY

KEY FLU FORECAST

SERVER / APLICATION

in Russia generating revenue

STRONG PARTNERSHIPS &

CREDIBILITY

Video AI PR E-commerceTech & scienceExpert

Tell the news Explain Share Sell

The AI Organisation

Daniel HulmeSatalia

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Hidden dynamics in hierarchy

Daniel HulmeSatalia

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Innovation, Motivation and Purpose “ Creativity that ships”

Steve Jobs

“ Motivation is the Energy for Action”Edward Deci

“ Autonomy, Mastery, Purpose”Dan Pink, Drive

“ Time is the new money”Richard Branson

The rise of the purposeful company

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DATA SCIENCE

CLOUD COMPUTING

OPEN (BIG) DATA

ARTIFICIAL INTELLIGENCE

TALENT

Talent Strategy

Daniel HulmeSatalia

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Industry Sexiness

Ch

alle

ng

ing

Pro

ble

ms

Talent Strategy

Daniel HulmeSatalia

95

No

Talent

Industry Sexiness

Ch

alle

ng

ing

Pro

ble

ms

Talent Strategy

Daniel HulmeSatalia

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Sticky

Talent

No

Talent

Industry Sexiness

Ch

alle

ng

ing

Pro

ble

ms

Talent Strategy

Daniel HulmeSatalia

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Talent

Churn

Sticky

Talent

No

Talent

Talent

Churn

Industry Sexiness

Ch

alle

ng

ing

Pro

ble

ms

Talent Strategy

Daniel HulmeSatalia

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Talent

Churn

Sticky

Talent

No

Talent

Talent

Churn

Industry Sexiness

Ch

alle

ng

ing

Pro

ble

ms

Daniel HulmeSatalia

99

Fat

Thin

Lean

(Distributed)

People Networks

Daniel HulmeSatalia

100

Daniel HulmeSatalia

101

Swarm diagrams provide

transparent data on

activity across network

tools.

Interactive network

diagrams show

relationships and the flow

of information from and to

the worker.

Swarm diagrams show the

significance of points and

the weight of opinion

compared to the

suggestions received by

others within the

organisation.

Social Scoring

Daniel HulmeSatalia

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Purpose

Daniel HulmeSatalia

103

Enable everyone

to do what they

love

Q&A

Daniel HulmeSatalia

104

Thank you2018/06/26

Daniel Hulme

Satalia

Stephan Pretorius

Wunderman

Owen McCabe

Kantar Consulting

Documents

2018/06/26 You can’t take an algorithm out to dinner · 2018-06-26 · Curation Perfect Mission as New Frontier Separating winners from losers today Perfect Shelf as Entry Point