Privacy and Personalisation

A Private Sector Perspective

Clive Humby

October 2014

THE LOYALTY MYTH

A brief timeline of customer insights1955 19851965 1975 20151995 2005

Social ClassABC1C2DE

You are the job you do

Social ClassABC1C2DE

You are the job you do

Geodemo-graphics

ACORNMOSAIC

You are whereYou live

Geodemo-graphics

ACORNMOSAIC

You are whereYou live

LifestylesListsNDL

GuaranteeCards

You are what you say

LifestylesListsNDL

GuaranteeCards

You are what you say

Customer DataTESCOAmexVisa

Amazon

You are what you buy

Customer DataTESCOAmexVisa

Amazon

You are what you buy

Big DataSocial MediaDigital Media

Mobile BehavioursBrowsing Behaviour

You are what you are

passionate about

Big DataSocial MediaDigital Media

Mobile BehavioursBrowsing Behaviour

You are what you are

passionate about

“Claimed & demographic data”“Claimed & demographic data” “Actual & behavioural data”“Actual & behavioural data”

Who wins… the retailer data modelBenefits for the retailer, manufacturers and customers

MANUFACTURERS•improved Marketing ROI•better NPD•effective promotions•Increased brand loyalty

RETAILERS•higher footfall•increased share of wallet•better retail offer•new service development

• promotions• better shopping trip• new meal solutions

• products I want• better prices• Relevant offers

CUSTOMERS

insight enables action that drives behaviour

customer data

enables...

Data sources•EPoS data•Credit & debit card data•Loyalty cards•3rd party data

Increased Customer Lifetime Value•Same-store sales growth•Same-store Margin growth•Market share growth

desired customer experience

to drive...

Enabling Better Business Decisions•Great Shopping Experience•Meaningful innovation•Relevant MarketingBuilding relationships with customers•Retention•Growth•Win back / prospecting

customer experience

customer insight to inform...

Basket segmentation•Basket size/value•Affluence•Shopping missions

Customer segmentations•Value & Loyalty•Lifestyles•Attitudes•Lifestage / Lifestyle

Personal data is only need in small parts of this process

So what do you have to understand?

MOTIVATIONSDescribe customers by attitudes, influence and circumstances. Based on granular behavioural data. All customers measured on each motivation.

SEGMENTATIONSDescribe customers by demographics, usage behaviour and profit. Each customer has one segment.

value of insight v value of customer contact

create new co-operative business

models

solve real problems need education

Well put together insight models…

are global for global

brands

7

value of insight v value of customer contact

creates win-win-win

allows you to build

trust through

relevance, content

and consent

clears a direct path to

the customer by dis-

intermediating

marketing agencies

Effective customer contact…

8

Big data… shopping, mobile, entertainment, payment cards

9

the data myth: it’s all about big data

What is big? What is useful?

1 Terabyte Solid State Disk

Store c 1,000 transactionsfor 10,000,000 people

Or

4 transaction per second for every day of your life

Read & process the entire dataset in about 30 minutes

What do we want from it?

Patterns & Decisions

useful data is not big, it’s tiny

PERSONALISATION & PRIVACY ARE DIFFERENT CONSTRUCTS

Finding patterns, assortment planning, product associations, price optimisation can all be done with “anonymised” data

Claimed attributes (age, children, car ownership) are all better MODELLED than actual; you are what you do NOT what you say

Commerce is fundamentally different to government and research objectives:-

we want to understand the behaviour of groups and tribeswe are not interested in the outliers and exceptionswe are concerned with efficient process, optimising mix

we are data rich; matching data sources less of an imperative

social log-on gives access to a rich public persona of the customer

much personalisation is about what you browse and click not YOU

managing “your data” is often a customer service benefit

Personalisation can be achieved without breaching privacy; only addressable communication needs to carry this risk

When do we need private data in this process

Red & Blue Data

ETL Process

PIDsHashed

Geocodes

Red/Blue Split

Blue data is analysed

Red Data is hidden

PersonalsiedFulfilment

When needed

Predictive v Descriptive Analytics v Fact Confirmation

Credit ScoringInsurance Risk

Behavioural ScoringMotivations

Entitlement (eg Over 18)Membership

Back to “postcode” or small areas•proving very powerful for passions, like theatre going

•allows merging of multiple venues without personal disclosure•perturb the data or use “barnardisation” methods

Recognise we have Consent•develop a customer charter spelling out what you will and will not do•Always work in the common good•Example: no switch messages on repertoire

Be cool not creepy•Apply commonsense rules•Someone will always take exception.. What is the “Daily Mail” test

It’s only junk when it’s not relevant•Customers understand the common standards and expect them•Using data badly or failing to use it carries as much reputational risk as highly targeted and relevant applications

Other processes we employ

Emerging Trends

Personal Data Stores & Cloud VerificationI don’t need your DOB, just proof & photo to show you are over 18 to buy alcohol

User controlled consent & data access

Share just the facts needed to fulfil the transactioncar insurance, proof of entitlement

MONETISE MY OWN DATA.. What will you give me to share my purchase history with you?

Longer Term BenefitsI know my family has a pre-disposition to this genetic disease, I will share my data with you as an act of philanthropy / self interest

Organisations are avoiding unnecessary data

Moral Dilemma… Consumer fears Company Reputational RiskCar telematics… shows me you speed when you drive

Shopping data…you buy more than 50 units of alcohol a week

Smart Meters… you leave your lights on all the time

Mobile phone… movement, location and social circles

ISP… what and where you visit

BUT I can change any of these suppliers at any time

Government is not trusted with data; no consent process

RIPA has damaged consumer trust in government use of data

Social Media spending is expected to be 21.4% of marketing budgets in five years

Source: theCMOsurvey August 2014

Spend patterns are evolving towards digital and social

US ad spending on the internet surpassed ad spending on broadcast television for the first time last year, increasing 17 per cent in 2013 to a record $42.8bn

Source: IAB April 2014

2014 is set to be the first year that consumers spend more time with digital media than they do with traditional media

Source: eMarketer March 2014

You should know your customers better

Starcount’s pioneering Fan Science Platform tracks...

VibeSocial DNAInsights

Defines Content

Returns Data

Social DNA

Through Fan Science we created our core product offering…

Create intelligent, curated content streams for you

customers.

Internal Insight Product

External Consumer product

Discover the communities,

influencers and content that matters

most to your customers

Conclusions

Have a clear customer charterRed / Blue split can protect against most risks, except criminalityCommercial organisations only care about tribes not individualsRelevance is the key; personalised fulfilment can be driven from anonymised

analyticsBe cool not creepy; most commercial organisation are looking at ways of not

storing personal dataBig data is not a panacea; to be useful it needs to become actionableSocial Media is rewriting the rules for getting your message to landPersonal data stores will give the consumer controlThe future for Brands is engaging with customers via their passions