Privacy and Personalisation

A Private Sector Perspective

Clive Humby October 2014

THE LOYALTY MYTH

1955

A brief timeline of customer insights

1965 1975 1985 1995 2005

Social Class

AB C1 C2 DE

You are the job you do

2015

Geodemo graphics

ACORN MOSAIC

You are where You live

Lifestyles Lists

NDL Guarantee Cards

You are what you say

“ Claimed & demographic data ”

Customer Data

TESCO Amex Visa Amazon

You are what you buy

“

Big Data

Social Media Digital Media Mobile Behaviours Browsing Behaviour

You are what you are passionate about

Actual & behavioural data ”

Who wins… the retailer data model Benefits for the retailer, manufacturers and customers • • • • RETAILERS higher footfall increased share of wallet better retail offer new service development • • • • MANUFACTURERS improved Marketing ROI better NPD effective promotions Increased brand loyalty • • • products I want better prices Relevant offers CUSTOMERS • • • promotions better shopping trip new meal solutions

insight enables action that drives behaviour

customer data enables...

customer insight to inform...

customer experience to drive...

desired customer experience Data sources •EPoS data •Credit & debit card data •Loyalty cards •3 rd party data Basket segmentation •Basket size/value •Affluence •Shopping missions Customer segmentations •Value & Loyalty •Lifestyles •Attitudes •Lifestage / Lifestyle Enabling Better Business Decisions •Great Shopping Experience •Meaningful innovation • Relevant Marketing Building relationships with customers •Retention •Growth • Win back / prospecting Increased Customer Lifetime Value •Same-store sales growth •Same-store Margin growth •Market share growth Personal data is only need in small parts of this process

So what do you have to understand?

MOTIVATIONS

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

SEGMENTATIONS

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

value of insight

v value of customer contact

Well put together insight models… solve real problems create new co-operative business models need education are global for global brands 7

value of insight v

value of customer contact

Effective customer contact… allows you to build

trust

through relevance, content and consent creates win-win-win clears a

direct path

to the customer by dis-intermediating marketing agencies 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 transactions for 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

When do we need

private data

in this process

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 tribes we are not interested in the outliers and exceptions we 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

Red & Blue Data

Blue data is analysed

ETL Process

PIDs Hashed Geocodes Red/Blue Split Red Data is hidden Personalsied Fulfilment When needed

Predictive v Descriptive Analytics v Fact Confirmation

Credit Scoring Insurance Risk Behavioural Scoring Motivations Entitlement (eg Over 18) Membership

Other processes we employ

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

Emerging Trends

Personal Data Stores & Cloud Verification

I 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 transaction car insurance, proof of entitlement MONETISE MY OWN DATA.. What will you give me to share my purchase history with you?

Longer Term Benefits

I 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 Risk

Car 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

Spend patterns are evolving towards digital and social

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

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

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

Source: theCMOsurvey August 2014

Starcount ’s pioneering Fan Science Platform tracks...

You should know your customers better

Through Fan Science we created our core product offering…

Social DNA

Social DNA Insights Internal Insight Product Discover the communities, influencers and content that matters most to your customers Defines Content Returns Data Vibe External Consumer product Create intelligent, curated content streams for you customers.

Conclusions

 Have a clear customer charter  Red / Blue split can protect against most risks, except criminality  Commercial organisations only care about tribes not individuals  Relevance is the key; personalised fulfilment can be driven from anonymised analytics  Be cool not creepy; most commercial organisation are looking at ways of not storing personal data  Big data is not a panacea; to be useful it needs to become actionable  Social Media is rewriting the rules for getting your message to land  Personal data stores will give the consumer control  The future for Brands is engaging with customers via their passions