Data Driven Decision Making: Making Data Useful

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Data Driven Decision-Making: Making Big Data Useful Cimeon Ellerton – The Audience Agency

Transcript of Data Driven Decision Making: Making Data Useful

Page 1: Data Driven Decision Making: Making Data Useful

Data Driven Decision-Making:

Making Big Data Useful

Cimeon Ellerton – The Audience Agency

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Big Spenders

• Norwegians spend more per head on music than any other country*

*International Federation of the Phonographic Industry

206.37 NOK (23.58 USD)

per person

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Data is everywhere

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Big Data =

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1984, Headlong Theatre Co

A sinister instrument of the state?

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Hans Rosling, building awareness of world poverty with data

A force for change?

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• Happy Shiny people

Audience, Greenwich & Docklands International Festival

A recipe for inclusion?

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The Audience Agency

leading insight-driven audience policy and practice

Research, Data, Software, Facilitation, Consultancy

• Not-for-profit, mission-led

• Sustainability + access

• 800+ arts, museums & heritage

• Broker collaboration

• Audience intelligence & strategy

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The Audience Agency:co-operative, give-and-gain model

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Big Data?

Volume

Variety

Velocity

Veracity

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700+ cultural organisations sharing data to build

audiences

40 x co-operative groups

Open and free to all

Condition of funding

Behaviour + attitudes + demographics

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Booker Data

Venue Z

Venue Y

Venue X

Census & Consumer Data

Data Warehouse

Audience Survey

Audience Survey

Audience Survey

Quantitative Survey Data

Web Data

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Audience Finder

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Demographics

Consumer profiles

Dashboard analytics

Group reports

Shared insight

Profiling

Benchmarks

Mapping

Segmentation

CRM, Ticket-buyer data

National survey data

Transaction data

Facilitation

Data warehouse

Website-dashboard

Analytics team

Web, social media

Inventory data

Mapping data

Bespoke

Self-service tools

Infrastructure

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A Case Study: English National Opera

Understanding First-time Attenders

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Meet “Maria”

Maria’s night at the English National Opera – what the data tells us

• Her first booking at the London Coliseum

• Out for an evening with her guest at La Bohème

• It’s likely to be a special night:

• She planned it 6 months in advance

• She chose the best seats in the house

• She treated them to champagne in the interval

• Lives in Islington, North London

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What else does Maria do?

• What other venues does she attend

• What other arts and culture does she like?

• What are her booking patterns?

• How much does she pay?

• How frequently does she attend?

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Maria’s Culture Habits

8 Concerts

14 Plays

6 Operas

• Maria attended 6 other venues in 3 years

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Books 156 days

in advance

Pays £63 per

ticket

Books 139 days

in advance

Pays £43 per

ticket

Books 76 days

in advance

Pays £17 per

ticket

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MetroculturalsCommuterland

Culturebuffs

Experience

Seekers

Dormitory

Dependables

Trips &

Treats

Home &

Heritage

Up Our

Street

Facebook

Families

Kaleidoscope

CreativityHeydays

A segmentation of the UK population based

on people’s cultural habits and preferences.

10 distinct profiles, linked to every household

in England and located by postcode.

Helps us understand spectrum of audiences

and non-attenders plan to meet needs,

and find new ones.

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Using Data for Prediction

What if we could predict what

sort of an audience we might

get for a gig, before we’ve even

booked the musicians?

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Audience Predictor

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How does it work?

• The maths:

𝑐 𝑝1, 𝑝2 = 𝑖𝑤𝑖𝛿𝑖 𝑖𝑤𝑖

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Exploring predictive power…

leveraged £80m + £15m per year from government

by predicting the size, location, profile and

appetites of potential audiences

Recently opened: Home in Manchester, leading the repositioning of the city through culture

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Over to you…

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Thank You

Cimeon Ellerton – The Audience Agency

[email protected]