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Coping strategies for using data when developing customer services


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Keynote at MMEx, Aarhus, Denmark 22 August 2016

Shared experience and tips about digital asset management, data and information design, pragmatic project delivery, the importance of soft people management skills and more.

MMEx is an independent organisation that assists museums and cultural institutions across Denmark, with all aspects of digital interpretation

Published in: Data & Analytics
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Coping strategies for using data when developing customer services

  1. 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
  2. 2. 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
  3. 3. 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
  4. 4. Ideas and helpful things to think about to take back to your workplace and use Go away with
  5. 5. 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!
  6. 6. Digital assets
  7. 7. Objects SecurityKnowledge Digital assets Tools + standards Storage
  8. 8. Objects Knowledge Tools + standards Digital assets Storage Connectivity
  9. 9. 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
  10. 10. Collection object records Media assets Events Shop products Customer behaviour data Staff knowledge Learning resources
  11. 11. Re-use is efficient
  12. 12. 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
  13. 13. V&A Digital Map Collection data fed via web API
  14. 14. Event data fed via web API V&A Digital Map
  15. 15. One digital asset updates all information
  16. 16. Digital assets From Web content system Digital assets From Digital assets From Blog database Digital assets From Shop database Digital assets From Collection records
  17. 17. User’s interests get typed here…User’s interests User data = digital asset
  18. 18. maiolica
  19. 19. 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
  20. 20. 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?
  21. 21. Build in data-capture to provide evidence
  22. 22. Browsing Top 10 object pages viewed, by country Engaging Top 10 large images downloaded, by country
  23. 23. Data that makes sense has more impact
  24. 24. Create evidence
  25. 25. Find out the data staff need to understand Then design the data structure to capture it
  26. 26. 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
  27. 27. 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
  28. 28. Designing data capture by physical drawing and team discussion
  29. 29. Data this up
  30. 30. 11.7%11.1% 10.6%19.4% 0.9%2.0% 3.5% 3.4% Game results affect impact of calls to action
  31. 31. Customer data and insights
  32. 32. Value of insight • Commercial opportunity • Increased public engagement • Impact of science and research activity
  33. 33. Risk • Legal e.g. data protection, security, GDPR compliance • Financial Inefficiency, loss of income • Reputational Creepy use of data is very emotive
  34. 34. Establishing a common language
  35. 35. 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
  36. 36. Something simple • Twitter’s data store is a single data repository
  37. 37. 34 customer touch points (34 NHM Twitter accounts)
  38. 38. Overall customer view
  39. 39. • Location of devices • Language used on devices • By time of year? • Compared to news coverage? Wi-Fi users = ? +
  40. 40. • Most sessions • Longest session • Compare with engagement of email responses? • Compare with income generated? Individual usage patterns
  41. 41. Not all data has the same value
  42. 42. Establishing a common language Value Quality Coverage Risk Extractability Terms of use
  43. 43. 70+ places we store customer data
  44. 44. Making data visible advances collective understanding
  45. 45. Establishing a common language
  46. 46. Where do we get new contacts from?