This document discusses strategies for making effective use of customer data when developing digital services. It recommends establishing a common language to discuss data across an organization. It also suggests making data visible so everyone understands what data is available and its value. The document advises designing systems to capture useful customer data from the start of digital projects to provide evidence of what drives customer behavior and engagement.

1. Coping strategies
for making use of data
when developing customer services
Andrew Lewis
Data and Insights Architect
MMEX INTEPRETATION TECHNOLOGY SEMINAR 2015-2017
TEKNOLOGI I FORMIDLING AARHUS, 22. AUGUST 2016

3. Let’s think about…
• What we mean when we say “data”
• What our digital assets are (or could be)
• Integration and complexity
• Evidence-based decision making
• Customers in customer services

5. Taking risks
• Strategies developed during 15 years of
public-facing digital services in leading UK
museums and library services
• Honest truths and tips
• Theoretical information design
• Pragmatic project delivery
• The importance of soft people management

7. Ideas and helpful things to think about
to take back to your workplace and use
Go away with

8. Unpredictable
Unpredictable and
complex
Predictable and
simple
Predictable but
complex
Unpredictable and
simple
Predictable
Simple Complex
We work here
for the rest of
our careers!

9. Digital assets

12. Objects SecurityKnowledge
Digital
assets
Tools +
standards
Storage

13. Objects Knowledge
Tools +
standards
Digital
assets
Storage Connectivity

15. Photos
Preferences
Videos
Records
What are our digital assets?
Data
Object records
Event records
Shop records
Conservation records
HR records
Whatever…
Customer contact records
(any records)
(any data)
Transaction data
Service data

16. Collection
object records
Media assets
Events
Shop products Customer
behaviour data
Staff
knowledge
Learning
resources

17. Re-use is efficient

18. Search the Collections (STC)
Mobile STC
Website auto-display module
Furniture gallery digital label
Digital map
One chair.
One authoritative digital asset.
Used in five
services

19. V&A Digital Map
Collection data
fed via web API

20. Event data
fed via web API
V&A Digital Map

21. One digital asset updates all information

23. Digital assets
From
Web content system
Digital assets
From
Vimeo.com
Digital assets
From
Blog database
Digital assets
From
Shop database
Digital assets
From
Collection records

24. User’s interests get typed here…User’s interests
User data = digital asset

25. maiolica

28. Digital assets
From
Web content system
Digital assets
From
Shop database
Digital assets
From
Collection records
Digital assets
From
Event database
Automated interests
suggestion based on
digital asset classification

29. Are you making them portable?
Do you know all the assets you have?
Do you look after them nicely?
Is strategy informing your data need?
Managing digital assets
Are you prioritising data that supports it?

30. Build in
data-capture to
provide evidence

35. Browsing
Top 10 object pages
viewed, by country
Engaging
Top 10 large images
downloaded, by country

36. Data that makes
sense has
more impact

39. Create evidence

42. Find out the data staff
need to understand
Then design the data
structure to capture it

43. Event Action 1.1
Event Category 1
Event Label 1.1.1
Event Action 1.2
Event Label 1.1.2
Event Label 1.2.1
Event Label 1.2.2Event Category 2
Event Action 2.1
Event Label 2.1.1
Event Label 2.1.2
Categories Actions Labels

44. SearchAudioguides -
Europe 1600-1815
galleries
Search term used
Navigation - Clicked next item in a
tour
Name of audio
Wi-Fi
Web address visitors are trying to
reach URL visited
Audio controls - Started playing an
audio
Name of Tour
Navigation - Selected room tours
option
Name of audio
Audio controls - Paused an audio
Name of Room
Categories Actions Labels

45. Designing data capture
by physical drawing
and team discussion

46. Data this up

50. 11.7%11.1%
10.6%19.4%
0.9%2.0%
3.5%
3.4%
Game results affect impact of calls to action

54. Customer data
and insights

55. Value of insight
• Commercial opportunity
• Increased public engagement
• Impact of science and research activity

56. Risk
• Legal
e.g. data protection, security, GDPR
compliance
• Financial
Inefficiency, loss of income
• Reputational
Creepy use of data is very emotive

57. Establishing a common language

58. Event card Membership teaser
Website footer email sign up
Wi-Fi welcome page
email sign up
Automated capture
Aligned terms
Manual data entry
Ambiguous terms

59. Something simple
• Twitter’s data store is a
single data repository

60. 34 customer touch points (34 NHM Twitter accounts)

61. Overall
customer view

64. • Location of devices
• Language used on devices
• By time of year?
• Compared to news coverage?
Wi-Fi users
= ?
+

65. • Most sessions
• Longest session
• Compare with engagement of email
responses?
• Compare with income generated?
Individual usage patterns

66. Not all data has
the same value

68. Establishing a common language
Value
Quality
Coverage
Risk
Extractability
Terms of use

69. 70+ places we store customer data

70. Making data visible
advances collective
understanding

71. Establishing a common language

73. Where do we get new contacts from?