Upload
angie-judge
View
286
Download
0
Embed Size (px)
Citation preview
Angie Judge, CEO Dexibit DIGITAL ACADEMY @ AUCKLAND MUSEUM MUSEUMS AUSTRALSIA 2016 #MA16NZ #MUSETECH #AKLTECHWEEK
BIG DATA AND ANALYTICS A new age of data driven insight
What can we learn about musedata from Frank Underwood?
GOOD: Analytics is a 10x return strategy for competitive advantage, when we’re competing for visitor attention
BAD: Don’t lock your data scientist in the basement and ask him to win you the presidency. That’s not how life works.
Let’s start with one question. What’s yours?
DON’T BOIL THE OCEAN
Analytics is a foundation, not just a cherry on top: 1. Beginning digital transformation?
Establish a benchmark, start a data history
2. During change What do the numbers say? Analyse cause and effect.
3. Evaluating project success What was the return on investment? What health checks do we need? How do we continue to improve? What next?
The beginning, middle and end ANALYTICS AND YOUR DIGITAL JOURNEY
Leading by the numbers DON’T GUESS, KNOW.
A quick leader’s checklist: n Data is a strategic imperative n Move hippos to data driven decisions n Understand where data comes from and its integrity n Always base in context – you know your museum n Encourage data as a communication tool n Make life easier with less reporting, not more n Ask questions of analytical enquiry
The process of data YOUR PLAN FOR DATA LEADERSHIP
Ask a question
Talk to the
people
Highlight key data
driven decisions
Establish metrics
and goals
Trace your data sources
Know your
data’s journey
Leverage an
analytics solution
Examples: 1. Why is visitation trending up/down?
What are the most common influences?
2. What impacts visitor retention and how can we increase repeat visitation?
3. What parts of the museum experience drives visitor engagement and activation?
Starting with a question IF YOU DO ONE THING, DO THIS…
Data personas WHO IS DRIVING DATA?
Board members
Director or executive
Marketing and membership
Visitor services
Front line staff
Education and learning
Exhibitions and experience
Curatorial and collections
Finance and operations
Digital and Technology
CHAM
PIO
NS
OTH
ER U
SERS
AMBASSADORS
Data driven decisions WHAT DECISIONS ARE WE MAKING?
Visitor
How are our campaigns working?
How can we increase visitor retention
How can we optimise onsite versus online
balance?
Collection
What should we display next? Where?
What content should we invest in?
What should we acquire next?
Venue
How can we drive up sales?
What should we push, up or cross sell?
How should we manage external influences?
Key metrics THE TOP 30: VISITATION, COLLECTION AND VENUE
Total members
Social followers
Email subscribers
32,497 40,321 64,132
Visitor satisfaction
Average visit (min)
Educational visits
4.9 137 116
Onsite visitation
Digital visitation
Repeat visitation
26,011 27,339 1.3
Content readership (%)
Comment interactions
Positive sentiment (%)
23 122 64
On display (%)
Available online (%)
Total access (%)
13 34 38
Collection objects
Content articles
Content cover (%)
394,617 201,922 32
Average temp (°C)
Average humidity (%)
Average exposure (hr)
18 NO DATA NO DATA
Retail sales ($)
Ecommerce sales ($)
Donations received ($)
310,499 93,144 4,312
Sold tickets
Scheduled events
WiFi connections
19,388 14 322
53,450 TOTAL VISITATION
596,539 TOTAL ITEMS
25,490 TOTAL TURNOVER ($)
VISITORS COLLECTION VENUE
Where does data come from? INTEGRATION, SYNC OR ENTRY
What should we do with it? WHAT HAPPENS WITH YOUR DATA
INTEGRATE
INGEST
STORE
MODEL
VISUALISE
< This bit is important:
Know what assumptions, variables and
treatments are being applied to
your data
Have you got:
§ Integration requirements, (especially in real time)?
§ A need to treat data, or blend multiple data sources?
§ Wide user access and mobility?
§ Lower user confidence?
§ Big data storage needs?
When does a spreadsheet not cut it? ANALYTICS KICKS IN
X
WAIT! What is big data?
That’s not big data, this is big data UMMM… WHAT IS BIG DATA?
Big data has: 1. Volume And not just created by people 2. Variety Multiple sources, structured and
unstructured 3. Velocity A massive and continuous flow in real time 4. Volatility Data has a use by date 5. Veracity The risk of noise and dirty data 6. Value Drives business insight 7. Validity The right data for the right decision
Dashboards as a quick win HOW ARE YOU COMMUNICATING DATA?
Opportunities for numbers:
n Formal reports
n Board room and department meetings
n Administration areas
n Atrium
n On staff devices
Recommendations POWERED BY BIG DATA: FROM NETFLIX TO THE MUSEUM?
Understanding identity means we can provide: 1. Offers
Events, exhibitions, souvenirs, hospitality…
2. Recommendations Others who enjoyed X liked Y, something you haven’t seen before…
3. Loyalty Repeat visitor rewards, VIP treatment, points, utility marketing…
What else?
WAIT! So what?
Telling a story with data HOW ARE YOU COMMUNICATING DATA?
n Keep it raw: be objective and uncensored n Don’t jump in: use a narrative
n What’s going on? Set the scene. n What does it all mean? Discuss cause and effect. n What have we done already? What next?
n Tailor to your audience n Executive level or grass roots? n What is the audience time and patience? n What medium do our audience understand best?
Lean sigma CONTINUOUS IMPROVEMENT USING METRICS
Plan
Do Study
Act 1. Define
What is the business problem? 2. Measure
What are the metrics saying? 3. Analyse
What is the cause and effect? 4. Improve
How do solutions compare? 5. Control
How do we continuously improve?
Continuous improvement Data & Insights presentation at https://goo.gl/eN5nKr
Step by step:
n Goals
n Strategies
n Tactics
n Measure
n Benchmark
What is an A-B test? BONUS POINTS
Making change? Test the comparison to know if it’s a good one.
OK. Where do I start?
Visitor behaviour Using visitor presence
With visitor presence, discover:
n Visitation footfall
n Zone activation
n Dwell time engagement
n Trail route experience
n Repeat visit retention
(with your WiFi network, or a gallery accessory device)
Cultural enrichment Understanding context
Collection:
n Accessioned
n On display
n Available online
n Content activation
n Lifetime engagement
Commercials:
n Ticketing
n Upsell, cross sell
n Souvenir
n Hospitality
n Parking
n Membership
And more:
n Weather feeds
n Events in your town or city
n How your venues compare (if multi site)
Digital analytics Data & Insights presentation at https://goo.gl/eN5nKr
Understanding the funnel:
n Who is visiting online?
n Where are they coming from? (paid or natural search, sites, direct from email, online ads, other)
n What are they visiting?
n How are they converting or engaging?
Google Analytics Data & Insights presentation at https://goo.gl/eN5nKr
What are we trying to do?
n Segment
n Optimise
n Create relationships
n Customise content
n Test, test, test!
Privacy DOS AND DON’TS
Do:
ü Include data governance in leadership structure
ü Have a clearly agreed policy
ü Think about security
ü Be transparent with visitors
ü Explain the value you’re creating
Don’t: ✗ Collect data you don’t need ✗ Assume privacy laws are static ✗ Forget to explain privacy
implications to staff ✗ Have inconsistencies between
onsite and online policies ✗ Get creepy with personalisation
Respectful data use means:
#musedata What next?
Where next? MUSEDATA
DATA AND INSIGHTS SPECIAL INTEREST
GROUP
ARTS ANALYTICS SUPPORT GROUP
goo.gl/D19dBH
#MUSEDATA
TAKEAWAYS DON’T BE LIKE FRANK! 1. Don’t lock data scientists in the basement 2. Don’t tell them to ‘win you the presidency’ 3. Don’t boil the ocean
DATA DRIVEN INSIGHTS FOR CULTURAL INSTITUTIONS